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Ozden B, Şamiloğlu E, Özsan A, Erguven M, Yükrük C, Koşaca M, Oktayoğlu M, Menteş M, Arslan N, Karakülah G, Barlas AB, Savaş B, Karaca E. Benchmarking the accuracy of structure-based binding affinity predictors on Spike-ACE2 deep mutational interaction set. Proteins 2024; 92:529-539. [PMID: 37991066 DOI: 10.1002/prot.26645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 10/25/2023] [Accepted: 11/13/2023] [Indexed: 11/23/2023]
Abstract
Since the start of COVID-19 pandemic, a huge effort has been devoted to understanding the Spike (SARS-CoV-2)-ACE2 recognition mechanism. To this end, two deep mutational scanning studies traced the impact of all possible mutations across receptor binding domain (RBD) of Spike and catalytic domain of human ACE2. By concentrating on the interface mutations of these experimental data, we benchmarked six commonly used structure-based binding affinity predictors (FoldX, EvoEF1, MutaBind2, SSIPe, HADDOCK, and UEP). These predictors were selected based on their user-friendliness, accessibility, and speed. As a result of our benchmarking efforts, we observed that none of the methods could generate a meaningful correlation with the experimental binding data. The best correlation is achieved by FoldX (R = -0.51). When we simplified the prediction problem to a binary classification, that is, whether a mutation is enriching or depleting the binding, we showed that the highest accuracy is achieved by FoldX with a 64% success rate. Surprisingly, on this set, simple energetic scoring functions performed significantly better than the ones using extra evolutionary-based terms, as in Mutabind and SSIPe. Furthermore, we demonstrated that recent AI approaches, mmCSM-PPI and TopNetTree, yielded comparable performances to the force field-based techniques. These observations suggest plenty of room to improve the binding affinity predictors in guessing the variant-induced binding profile changes of a host-pathogen system, such as Spike-ACE2. To aid such improvements we provide our benchmarking data at https://github.com/CSB-KaracaLab/RBD-ACE2-MutBench with the option to visualize our mutant models at https://rbd-ace2-mutbench.github.io/.
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Affiliation(s)
- Burcu Ozden
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Eda Şamiloğlu
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Atakan Özsan
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Mehmet Erguven
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Can Yükrük
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Mehdi Koşaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Melis Oktayoğlu
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Muratcan Menteş
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Nazmiye Arslan
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Gökhan Karakülah
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Ayşe Berçin Barlas
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Büşra Savaş
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
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2
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Turan G, Olgun ÇE, Ayten H, Toker P, Ashyralyyev A, Savaş B, Karaca E, Muyan M. Dynamic proximity interaction profiling suggests that YPEL2 is involved in cellular stress surveillance. Protein Sci 2024; 33:e4859. [PMID: 38145972 PMCID: PMC10804680 DOI: 10.1002/pro.4859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/30/2023] [Accepted: 12/03/2023] [Indexed: 12/27/2023]
Abstract
YPEL2 is a member of the evolutionarily conserved YPEL family involved in cellular proliferation, mobility, differentiation, senescence, and death. However, the mechanism by which YPEL2, or YPEL proteins, mediates its effects is largely unknown. Proteins perform their functions in a network of proteins whose identities, amounts, and compositions change spatiotemporally in a lineage-specific manner in response to internal and external stimuli. Here, we explored interaction partners of YPEL2 by using dynamic TurboID-coupled mass spectrometry analyses to infer a function for the protein. Our results using inducible transgene expressions in COS7 cells indicate that proximity interaction partners of YPEL2 are mainly involved in RNA and mRNA metabolic processes, ribonucleoprotein complex biogenesis, regulation of gene silencing by miRNA, and cellular responses to stress. We showed that YPEL2 interacts with the RNA-binding protein ELAVL1 and the selective autophagy receptor SQSTM1. We also found that YPEL2 localizes stress granules in response to sodium arsenite, an oxidative stress inducer, which suggests that YPEL2 participates in stress granule-related processes. Establishing a point of departure in the delineation of structural/functional features of YPEL2, our results suggest that YPEL2 may be involved in stress surveillance mechanisms.
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Affiliation(s)
- Gizem Turan
- Department of Biological SciencesMiddle East Technical UniversityAnkaraTürkiye
| | - Çağla Ece Olgun
- Department of Biological SciencesMiddle East Technical UniversityAnkaraTürkiye
| | - Hazal Ayten
- Department of Biological SciencesMiddle East Technical UniversityAnkaraTürkiye
| | - Pelin Toker
- Department of Biological SciencesMiddle East Technical UniversityAnkaraTürkiye
| | | | - Büşra Savaş
- İzmir Biomedicine and Genome CenterİzmirTürkiye
- Izmir International Biomedicine and Genome InstituteDokuz Eylül UniversityIzmirTürkiye
| | - Ezgi Karaca
- İzmir Biomedicine and Genome CenterİzmirTürkiye
- Izmir International Biomedicine and Genome InstituteDokuz Eylül UniversityIzmirTürkiye
| | - Mesut Muyan
- Department of Biological SciencesMiddle East Technical UniversityAnkaraTürkiye
- CanSyl LaboratoriesMiddle East Technical UniversityAnkaraTürkiye
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3
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Kryshtafovych A, Montelione GT, Rigden DJ, Mesdaghi S, Karaca E, Moult J. Breaking the conformational ensemble barrier: Ensemble structure modeling challenges in CASP15. Proteins 2023; 91:1903-1911. [PMID: 37872703 PMCID: PMC10840738 DOI: 10.1002/prot.26584] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 08/14/2023] [Indexed: 10/25/2023]
Abstract
For the first time, the 2022 CASP (Critical Assessment of Structure Prediction) community experiment included a section on computing multiple conformations for protein and RNA structures. There was full or partial success in reproducing the ensembles for four of the nine targets, an encouraging result. For protein structures, enhanced sampling with variations of the AlphaFold2 deep learning method was by far the most effective approach. One substantial conformational change caused by a single mutation across a complex interface was accurately reproduced. In two other assembly modeling cases, methods succeeded in sampling conformations near to the experimental ones even though environmental factors were not included in the calculations. An experimentally derived flexibility ensemble allowed a single accurate RNA structure model to be identified. Difficulties included how to handle sparse or low-resolution experimental data and the current lack of effective methods for modeling RNA/protein complexes. However, these and other obstacles appear addressable.
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Affiliation(s)
| | - Gaetano T Montelione
- Department of Chemistry and Chemical Biology, Center for Biotechnology and Interdisciplinary Sciences, Rensselaer Polytechnic Institute, Troy, New York, USA
| | - Daniel J Rigden
- Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Shahram Mesdaghi
- Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, UK
- Computational Biology Facility, MerseyBio, University of Liverpool, Liverpool, UK
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - John Moult
- Institute for Bioscience and Biotechnology Research, Rockville, Maryland, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland, USA
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4
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Dioken DN, Ozgul I, Yilmazbilek I, Yakicier MC, Karaca E, Erson-Bensan AE. An alternatively spliced PD-L1 isoform PD-L1∆3, and PD-L2 expression in breast cancers: implications for eligibility scoring and immunotherapy response. Cancer Immunol Immunother 2023; 72:4065-4075. [PMID: 37768345 DOI: 10.1007/s00262-023-03543-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 09/05/2023] [Indexed: 09/29/2023]
Abstract
Targeting PD-1/PD-L1 has shown substantial therapeutic response and unprecedented long-term durable responses in the clinic. However, several challenges persist, encompassing the prediction of treatment effectiveness and patient responses, the emergence of treatment resistance, and the necessity for additional biomarkers. Consequently, we comprehensively explored the often-overlooked isoforms of crucial immunotherapy players, leveraging transcriptomic analysis, structural modeling, and immunohistochemistry (IHC) data. Our investigation has led to the identification of an alternatively spliced isoform of PD-L1 that lacks exon 3 (PD-L1∆3) and the IgV domain required to interact with PD-1. PD-L1∆3 is expressed more than the canonical isoform in a subset of breast cancers and other TCGA tumors. Using the deep learning-based protein modeling tool AlphaFold2, we show the lack of a possible interaction between PD-L1∆3 and PD-1. In addition, we present data on the expression of an additional ligand for PD-1, PD-L2. PD-L2 expression is widespread and positively correlates with PD-L1 levels in breast and other tumors. We report enriched epithelial-mesenchymal transition (EMT) signature in high PD-L2 transcript expressing (PD-L2 > PD-L1) tumors in all breast cancer subtypes, highlighting potential crosstalk between EMT and immune evasion. Notably, the estrogen gene signature is downregulated in ER + breast tumors with high PD-L2. The data on PD-L2 IHC positivity but PD-L1 negativity in breast tumors, together with our results on PD-L1∆3, highlight the need to utilize PD-L2 and PD-L1 isoform-specific antibodies for staining patient tissue sections to offer a more precise prediction of the outcomes of PD-1/PD-L1 immunotherapy.
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Affiliation(s)
- Didem Naz Dioken
- Department of Biological Sciences, Middle East Technical University (METU), Dumlupinar Blv No:1 Universiteler Mah, Cankaya, 06800, Ankara, Türkiye
| | - Ibrahim Ozgul
- Department of Biological Sciences, Middle East Technical University (METU), Dumlupinar Blv No:1 Universiteler Mah, Cankaya, 06800, Ankara, Türkiye
| | - Irem Yilmazbilek
- Department of Biological Sciences, Middle East Technical University (METU), Dumlupinar Blv No:1 Universiteler Mah, Cankaya, 06800, Ankara, Türkiye
| | - Mustafa Cengiz Yakicier
- AQUARIUS/NPG Genetic Diseases Evaluation Center, Kucukbakkalkoy Mah. Kayisdagi Cad. 137/6 Atasehir, Istanbul, Türkiye
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, 35340, Balcova, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, 35340, Balcova, Izmir, Türkiye
| | - Ayse Elif Erson-Bensan
- Department of Biological Sciences, Middle East Technical University (METU), Dumlupinar Blv No:1 Universiteler Mah, Cankaya, 06800, Ankara, Türkiye.
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5
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Ozden B, Kryshtafovych A, Karaca E. The impact of AI-based modeling on the accuracy of protein assembly prediction: Insights from CASP15. Proteins 2023; 91:1636-1657. [PMID: 37861057 PMCID: PMC10873090 DOI: 10.1002/prot.26598] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 09/12/2023] [Accepted: 09/14/2023] [Indexed: 10/21/2023]
Abstract
In CASP15, 87 predictors submitted around 11 000 models on 41 assembly targets. The community demonstrated exceptional performance in overall fold and interface contact predictions, achieving an impressive success rate of 90% (compared to 31% in CASP14). This remarkable accomplishment is largely due to the incorporation of DeepMind's AF2-Multimer approach into custom-built prediction pipelines. To evaluate the added value of participating methods, we compared the community models to the baseline AF2-Multimer predictor. In over 1/3 of cases, the community models were superior to the baseline predictor. The main reasons for this improved performance were the use of custom-built multiple sequence alignments, optimized AF2-Multimer sampling, and the manual assembly of AF2-Multimer-built subcomplexes. The best three groups, in order, are Zheng, Venclovas, and Wallner. Zheng and Venclovas reached a 73.2% success rate over all (41) cases, while Wallner attained 69.4% success rate over 36 cases. Nonetheless, challenges remain in predicting structures with weak evolutionary signals, such as nanobody-antigen, antibody-antigen, and viral complexes. Expectedly, modeling large complexes also remains challenging due to their high memory compute demands. In addition to the assembly category, we assessed the accuracy of modeling interdomain interfaces in the tertiary structure prediction targets. Models on seven targets featuring 17 unique interfaces were analyzed. Best predictors achieved a 76.5% success rate, with the UM-TBM group being the leader. In the interdomain category, we observed that the predictors faced challenges, as in the case of the assembly category, when the evolutionary signal for a given domain pair was weak or the structure was large. Overall, CASP15 witnessed unprecedented improvement in interface modeling, reflecting the AI revolution seen in CASP14.
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Affiliation(s)
- Burcu Ozden
- Izmir Biomedicine and Genome Center, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye
| | - Andriy Kryshtafovych
- Protein Structure Prediction Center, Genome and Biomedical Sciences Facilities, University of California, Davis, California, USA
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye
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6
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Erguven M, Kilic S, Karaca E, Diril MK. Genetic complementation screening and molecular docking give new insight on phosphorylation-dependent Mastl kinase activation. J Biomol Struct Dyn 2023; 41:8241-8253. [PMID: 36270968 DOI: 10.1080/07391102.2022.2131627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 09/26/2022] [Indexed: 10/24/2022]
Abstract
Mastl is a mitotic kinase that is essential for error-free chromosome segregation. It is an atypical member of AGC kinase family, possessing a unique non-conserved middle region. The mechanism of Mastl activation has been studied extensively in vitro. Phosphorylation of several residues were identified to be crucial for activation. These sites correspond to T193 and T206 in the activation loop and S861 in the C-terminal tail of mouse Mastl. To date, the significance of these phosphosites was not confirmed in intact mammalian cells. Here, we utilize a genetic complementation approach to determine the essentials of mammalian Mastl kinase activation. We used tamoxifen-inducible conditional knockout mouse embryonic fibroblasts to delete endogenous Mastl and screened various mutants for their ability to complement its loss. S861A mutant was able to complement endogenous Mastl loss. In parallel, we performed computational molecular docking studies to evaluate the significance of this residue for kinase activation. Our in-depth sequence and structure analysis revealed that Mastl pS861 does not belong to a conformational state, where the phosphoresidue contributes to C-tail docking. C-tail of Mastl is relatively short and it lacks a hydrophobic (HF) motif that would otherwise help its anchoring over N-lobe, required for the final steps of kinase activation. Our results show that phosphorylation of Mastl C-tail turn motif (S861) is dispensable for kinase function in cellulo.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mehmet Erguven
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - Seval Kilic
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - M Kasim Diril
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
- Department of Medical Biology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
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7
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Ozden B, Kryshtafovych A, Karaca E. The Impact of AI-Based Modeling on the Accuracy of Protein Assembly Prediction: Insights from CASP15. bioRxiv 2023:2023.07.10.548341. [PMID: 37503072 PMCID: PMC10369898 DOI: 10.1101/2023.07.10.548341] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
In CASP15, 87 predictors submitted around 11,000 models on 41 assembly targets. The community demonstrated exceptional performance in overall fold and interface contact prediction, achieving an impressive success rate of 90% (compared to 31% in CASP14). This remarkable accomplishment is largely due to the incorporation of DeepMind's AF2-Multimer approach into custom-built prediction pipelines. To evaluate the added value of participating methods, we compared the community models to the baseline AF2-Multimer predictor. In over 1/3 of cases the community models were superior to the baseline predictor. The main reasons for this improved performance were the use of custom-built multiple sequence alignments, optimized AF2-Multimer sampling, and the manual assembly of AF2-Multimer-built subcomplexes. The best three groups, in order, are Zheng, Venclovas and Wallner. Zheng and Venclovas reached a 73.2% success rate over all (41) cases, while Wallner attained 69.4% success rate over 36 cases. Nonetheless, challenges remain in predicting structures with weak evolutionary signals, such as nanobody-antigen, antibody-antigen, and viral complexes. Expectedly, modeling large complexes remains also challenging due to their high memory compute demands. In addition to the assembly category, we assessed the accuracy of modeling interdomain interfaces in the tertiary structure prediction targets. Models on seven targets featuring 17 unique interfaces were analyzed. Best predictors achieved the 76.5% success rate, with the UM-TBM group being the leader. In the interdomain category, we observed that the predictors faced challenges, as in the case of the assembly category, when the evolutionary signal for a given domain pair was weak or the structure was large. Overall, CASP15 witnessed unprecedented improvement in interface modeling, reflecting the AI revolution seen in CASP14.
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Affiliation(s)
- Burcu Ozden
- Izmir Biomedicine and Genome Center, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye
| | - Andriy Kryshtafovych
- Protein Structure Prediction Center, Genome and Biomedical Sciences Facilities, University of California, Davis, California, USA
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye
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8
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Ozden B, Boopathi R, Barlas AB, Lone IN, Bednar J, Petosa C, Kale S, Hamiche A, Angelov D, Dimitrov S, Karaca E. Molecular Mechanism of Nucleosome Recognition by the Pioneer Transcription Factor Sox. J Chem Inf Model 2023. [PMID: 37307148 DOI: 10.1021/acs.jcim.2c01520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Pioneer transcription factors (PTFs) have the remarkable ability to directly bind to chromatin to stimulate vital cellular processes. In this work, we dissect the universal binding mode of Sox PTF by combining extensive molecular simulations and physiochemistry approaches, along with DNA footprinting techniques. As a result, we show that when Sox consensus DNA is located at the solvent-facing DNA strand, Sox binds to the compact nucleosome without imposing any significant conformational changes. We also reveal that the base-specific Sox:DNA interactions (base reading) and Sox-induced DNA changes (shape reading) are concurrently required for sequence-specific nucleosomal DNA recognition. Among three different nucleosome positions located on the positive DNA arm, a sequence-specific reading mechanism is solely satisfied at the superhelical location 2 (SHL2). While SHL2 acts transparently for solvent-facing Sox binding, among the other two positions, SHL4 permits only shape reading. The final position, SHL0 (dyad), on the other hand, allows no reading mechanism. These findings demonstrate that Sox-based nucleosome recognition is essentially guided by intrinsic nucleosome properties, permitting varying degrees of DNA recognition.
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Affiliation(s)
- Burcu Ozden
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir 35340, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir 35340, Turkey
| | - Ramachandran Boopathi
- Institut for Advanced Biosciences, Inserm U 1209, CNRS UMR 5309, Université Grenoble Alpes, Grenoble 38000, France
- Institut de Biologie Structurale (IBS), Université Grenoble Alpes, CEA, CNRS, Grenoble 38044, France
- Laboratoire de Biologie et de Modélisation de la Cellule (LBMC), Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, 46 Allée d'Italie, Lyon 69007, France
| | - Ayşe Berçin Barlas
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir 35340, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir 35340, Turkey
| | - Imtiaz N Lone
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir 35340, Turkey
| | - Jan Bednar
- Institut for Advanced Biosciences, Inserm U 1209, CNRS UMR 5309, Université Grenoble Alpes, Grenoble 38000, France
| | - Carlo Petosa
- Institut de Biologie Structurale (IBS), Université Grenoble Alpes, CEA, CNRS, Grenoble 38044, France
| | - Seyit Kale
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir 35340, Turkey
| | - Ali Hamiche
- Département de Génomique Fonctionnelle et Cancer, Institut de Génétique et Biologie Moléculaire et Cellulaire (IGBMC)/Université de Strasbourg/CNRS/INSERM, Illkirch Cedex 67404, France
| | - Dimitar Angelov
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir 35340, Turkey
- Laboratoire de Biologie et de Modélisation de la Cellule (LBMC), Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, 46 Allée d'Italie, Lyon 69007, France
| | - Stefan Dimitrov
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir 35340, Turkey
- Institut for Advanced Biosciences, Inserm U 1209, CNRS UMR 5309, Université Grenoble Alpes, Grenoble 38000, France
- Roumen Tsanev Institute of Molecular Biology, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir 35340, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir 35340, Turkey
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9
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Gul M, Ayan E, Destan E, Johnson JA, Shafiei A, Kepceoğlu A, Yilmaz M, Ertem FB, Yapici İ, Tosun B, Baldir N, Tokay N, Nergiz Z, Karakadioğlu G, Paydos SS, Kulakman C, Ferah CK, Güven Ö, Atalay N, Akcan EK, Cetinok H, Arslan NE, Şabanoğlu K, Aşci B, Tavli S, Gümüsboğa H, Altuntaş S, Otsuka M, Fujita M, Teki N Ş, Çi Ftçi H, Durdaği S, Karaca E, Kaplan Türköz B, Kabasakal BV, Kati A, DeMi Rci H. Rapid and efficient ambient temperature X-ray crystal structure determination at Turkish Light Source. Sci Rep 2023; 13:8123. [PMID: 37208392 DOI: 10.1038/s41598-023-33989-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 04/21/2023] [Indexed: 05/21/2023] Open
Abstract
High-resolution biomacromolecular structure determination is essential to better understand protein function and dynamics. Serial crystallography is an emerging structural biology technique which has fundamental limitations due to either sample volume requirements or immediate access to the competitive X-ray beamtime. Obtaining a high volume of well-diffracting, sufficient-size crystals while mitigating radiation damage remains a critical bottleneck of serial crystallography. As an alternative, we introduce the plate-reader module adapted for using a 72-well Terasaki plate for biomacromolecule structure determination at a convenience of a home X-ray source. We also present the first ambient temperature lysozyme structure determined at the Turkish light source (Turkish DeLight). The complete dataset was collected in 18.5 min with resolution extending to 2.39 Å and 100% completeness. Combined with our previous cryogenic structure (PDB ID: 7Y6A), the ambient temperature structure provides invaluable information about the structural dynamics of the lysozyme. Turkish DeLight provides robust and rapid ambient temperature biomacromolecular structure determination with limited radiation damage.
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Affiliation(s)
- Mehmet Gul
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Esra Ayan
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Ebru Destan
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - J Austin Johnson
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Alaleh Shafiei
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Abdullah Kepceoğlu
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
- Koç University Surface Science and Technology Center (KUYTAM), Koç University, Istanbul, Türkiye
| | - Merve Yilmaz
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Fatma Betül Ertem
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - İlkin Yapici
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Bilge Tosun
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Nilüfer Baldir
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Nurettin Tokay
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Zeliş Nergiz
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
- Koç University Isbank Center for Infectious Diseases (KUISCID), Koç University, Istanbul, Türkiye
| | - Gözde Karakadioğlu
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Seyide Seda Paydos
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Cahine Kulakman
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Cengiz Kaan Ferah
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Ömür Güven
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Necati Atalay
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
- Department of Molecular Biology and Genetics, Faculty of Science, Gebze Technical University, Kocaeli, Türkiye
- Experimental Medicine Application & Research Center, University of Health Sciences Türkiye, Istanbul, Türkiye
| | - Enver Kamil Akcan
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
- Department of Molecular Biology and Genetics, Faculty of Science and Letters, Istanbul Technical University, Istanbul, Türkiye
| | - Haluk Cetinok
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Nazlı Eylül Arslan
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
- Department of Molecular Biology and Genetics, Faculty of Science and Letters, Istanbul Arel University, Istanbul, Türkiye
| | - Kardelen Şabanoğlu
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
- Department of Molecular Biology and Genetics, Faculty of Arts and Sciences, Yıldız Technical University, Istanbul, Türkiye
| | - Bengisu Aşci
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Serra Tavli
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Helin Gümüsboğa
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
| | - Sevde Altuntaş
- Experimental Medicine Application & Research Center, University of Health Sciences Türkiye, Istanbul, Türkiye
- Department of Tissue Engineering, Hamidiye Institute of Health Sciences, University of Health Sciences Türkiye, Istanbul, Türkiye
| | - Masami Otsuka
- Medicinal and Biological Chemistry Science Farm Joint Research Laboratory, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
- Department of Drug Discovery, Science Farm Ltd., Kumamoto, Japan
| | - Mikako Fujita
- Medicinal and Biological Chemistry Science Farm Joint Research Laboratory, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Şaban Teki N
- Experimental Medicine Application & Research Center, University of Health Sciences Türkiye, Istanbul, Türkiye
- The Scientific and Technological Research Council of Türkiye (TÜBİTAK) Marmara Research Center (MAM), Life Sciences, Kocaeli, Türkiye
- Department of Basic Medical Sciences, Division of Medical Biology, Faculty of Medicine, University of Health Sciences Türkiye, Istanbul, Türkiye
| | - Halilibrahim Çi Ftçi
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye
- Medicinal and Biological Chemistry Science Farm Joint Research Laboratory, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
- Department of Drug Discovery, Science Farm Ltd., Kumamoto, Japan
| | - Serdar Durdaği
- Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Türkiye
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye
| | - Burcu Kaplan Türköz
- Department of Food Engineering, Faculty of Engineering, Ege University, Izmir, Türkiye
| | - Burak Veli Kabasakal
- Turkish Accelerator and Radiation Laboratory (TARLA), Ankara University, Ankara, Türkiye
- School of Biochemistry, University of Bristol, Bristol, UK
| | - Ahmet Kati
- Experimental Medicine Application & Research Center, University of Health Sciences Türkiye, Istanbul, Türkiye
- Department of Biotechnology, Hamidiye Institute of Health Sciences, University of Health Sciences Türkiye, Istanbul, Türkiye
| | - Hasan DeMi Rci
- Department of Molecular Biology and Genetics, Faculty of Science, Koç University, Istanbul, Türkiye.
- Koç University Isbank Center for Infectious Diseases (KUISCID), Koç University, Istanbul, Türkiye.
- SLAC National Laboratory, Stanford PULSE Institute, Menlo Park, CA, USA.
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10
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Karaca E, Byrne PJP, Hasnip PJ, Probert MIJ. Cr[Formula: see text]AlN and the search for the highest temperature superconductor in the M[Formula: see text]AX family. Sci Rep 2023; 13:6576. [PMID: 37085557 PMCID: PMC10121671 DOI: 10.1038/s41598-023-33517-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 04/13/2023] [Indexed: 04/23/2023] Open
Abstract
We have developed a high-throughput computational method to predict the superconducting transition temperature in stable hexagonal M[Formula: see text]AX phases, and applied it to all the known possible choices for M (M: Sc, Ti, V, Cr, Mn, Fe, Y, Zr, Nb, Mo, Lu, Hf and Ta). We combine this with the best candidates for A (A: Al, Cu, Ge and Sn ) and X (X: C and N) from our previous work, and predict T[Formula: see text] for 60 M[Formula: see text]AX-phase materials, 53 of which have never been studied before. From all of these, we identify Cr[Formula: see text]AlN as the best candidate for the highest T[Formula: see text], and confirm its high T[Formula: see text] with more detailed density functional theory electron-phonon coupling calculations. Our detailed calculations predict [Formula: see text] = 14.8 K for Cr[Formula: see text]AlN, which is significantly higher than any [Formula: see text] value known or predicted for any material in the M[Formula: see text]AX family to date.
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Affiliation(s)
- E. Karaca
- Department of Physics, University of York, York, YO10 5DD UK
- Sakarya University, Biomedical, Magnetic and Semiconductor Materials Research Center (BIMAS-RC), 54187 Sakarya, Turkey
| | - P. J. P. Byrne
- Department of Physics, University of York, York, YO10 5DD UK
| | - P. J. Hasnip
- Department of Physics, University of York, York, YO10 5DD UK
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11
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Özden-Yılmaz G, Savas B, Bursalı A, Eray A, Arıbaş A, Senturk S, Karaca E, Karakülah G, Erkek-Ozhan S. Differential Occupancy and Regulatory Interactions of KDM6A in Bladder Cell Lines. Cells 2023; 12:cells12060836. [PMID: 36980177 PMCID: PMC10047809 DOI: 10.3390/cells12060836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/16/2023] [Accepted: 03/01/2023] [Indexed: 03/30/2023] Open
Abstract
Epigenetic deregulation is a critical theme which needs further investigation in bladder cancer research. One of the most highly mutated genes in bladder cancer is KDM6A, which functions as an H3K27 demethylase and is one of the MLL3/4 complexes. To decipher the role of KDM6A in normal versus tumor settings, we identified the genomic landscape of KDM6A in normal, immortalized, and cancerous bladder cells. Our results showed differential KDM6A occupancy in the genes involved in cell differentiation, chromatin organization, and Notch signaling depending on the cell type and the mutation status of KDM6A. Transcription factor motif analysis revealed HES1 to be enriched at KDM6A peaks identified in the T24 bladder cancer cell line; moreover, it has a truncating mutation in KDM6A and lacks a demethylase domain. Our co-immunoprecipitation experiments revealed TLE co-repressors and HES1 as potential truncated and wild-type KDM6A interactors. With the aid of structural modeling, we explored how truncated KDM6A could interact with TLE and HES1, as well as RUNX and HHEX transcription factors. These structures provide a solid means of studying the functions of KDM6A independently of its demethylase activity. Collectively, our work provides important contributions to the understanding of KDM6A malfunction in bladder cancer.
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Affiliation(s)
| | - Busra Savas
- Izmir Biomedicine and Genome Center, Inciralti, 35340 Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Inciralti, 35340 Izmir, Turkey
| | - Ahmet Bursalı
- Izmir Biomedicine and Genome Center, Inciralti, 35340 Izmir, Turkey
| | - Aleyna Eray
- Izmir Biomedicine and Genome Center, Inciralti, 35340 Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Inciralti, 35340 Izmir, Turkey
| | - Alirıza Arıbaş
- Izmir Biomedicine and Genome Center, Inciralti, 35340 Izmir, Turkey
| | - Serif Senturk
- Izmir Biomedicine and Genome Center, Inciralti, 35340 Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Inciralti, 35340 Izmir, Turkey
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Inciralti, 35340 Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Inciralti, 35340 Izmir, Turkey
| | - Gökhan Karakülah
- Izmir Biomedicine and Genome Center, Inciralti, 35340 Izmir, Turkey
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Inciralti, 35340 Izmir, Turkey
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12
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Koşaca M, Yılmazbilek İ, Karaca E. PROT-ON: A structure-based detection of designer PROTein interface MutatiONs. Front Mol Biosci 2023; 10:1063971. [PMID: 36936988 PMCID: PMC10018488 DOI: 10.3389/fmolb.2023.1063971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/31/2023] [Indexed: 03/06/2023] Open
Abstract
The mutation-induced changes across protein-protein interfaces have often been observed to lead to severe diseases. Therefore, several computational tools have been developed to predict the impact of such mutations. Among these tools, FoldX and EvoEF1 stand out as fast and accurate alternatives. Expanding on the capabilities of these tools, we have developed the PROT-ON (PROTein-protein interface mutatiONs) framework, which aims at delivering the most critical protein interface mutations that can be used to design new protein binders. To realize this aim, PROT-ON takes the 3D coordinates of a protein dimer as an input. Then, it probes all possible interface mutations on the selected protein partner with EvoEF1 or FoldX. The calculated mutational energy landscape is statistically analyzed to find the most enriching and depleting mutations. Afterward, these extreme mutations are filtered out according to stability and optionally according to evolutionary criteria. The final remaining mutation list is presented to the user as the designer mutation set. Together with this set, PROT-ON provides several residue- and energy-based plots, portraying the synthetic energy landscape of the probed mutations. The stand-alone version of PROT-ON is deposited at https://github.com/CSB-KaracaLab/prot-on. The users can also use PROT-ON through our user-friendly web service http://proton.tools.ibg.edu.tr:8001/ (runs with EvoEF1 only). Considering its speed and the range of analysis provided, we believe that PROT-ON presents a promising means to estimate designer mutations.
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Affiliation(s)
- Mehdi Koşaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul Health Campus, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye
| | - İrem Yılmazbilek
- Izmir Biomedicine and Genome Center, Dokuz Eylul Health Campus, Izmir, Türkiye
- Middle East Technical University, Ankara, Türkiye
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul Health Campus, Izmir, Türkiye
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Türkiye
- *Correspondence: Ezgi Karaca,
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13
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Erguven M, Cornelissen NV, Peters A, Karaca E, Rentmeister A. Enzymatic Generation of Double-Modified AdoMet Analogues and Their Application in Cascade Reactions with Different Methyltransferases. Chembiochem 2022; 23:e202200511. [PMID: 36288101 PMCID: PMC10100234 DOI: 10.1002/cbic.202200511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/26/2022] [Indexed: 01/25/2023]
Abstract
Methyltransferases (MTases) have become an important tool for site-specific alkylation and biomolecular labelling. In biocatalytic cascades with methionine adenosyltransferases (MATs), transfer of functional moieties has been realized starting from methionine analogues and ATP. However, the widespread use of S-adenosyl-l-methionine (AdoMet) and the abundance of MTases accepting sulfonium centre modifications limit selective modification in mixtures. AdoMet analogues with additional modifications at the nucleoside moiety bear potential for acceptance by specific MTases. Here, we explored the generation of double-modified AdoMets by an engineered Methanocaldococcus jannaschii MAT (PC-MjMAT), using 19 ATP analogues in combination with two methionine analogues. This substrate screening was extended to cascade reactions and to MTase competition assays. Our results show that MTase targeting selectivity can be improved by using bulky substituents at the N6 of adenine. The facile access to >10 new AdoMet analogues provides the groundwork for developing MAT-MTase cascades for orthogonal biomolecular labelling.
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Affiliation(s)
- Mehmet Erguven
- Department of Chemistry and PharmacyInstitute of BiochemistryUniversity of MünsterCorrensstr. 36, 48149MünsterGermany
- Cells in Motion Interfaculty CentreUniversity of MünsterWaldeyerstraße 1548149MünsterGermany
| | - Nicolas V. Cornelissen
- Department of Chemistry and PharmacyInstitute of BiochemistryUniversity of MünsterCorrensstr. 36, 48149MünsterGermany
| | - Aileen Peters
- Department of Chemistry and PharmacyInstitute of BiochemistryUniversity of MünsterCorrensstr. 36, 48149MünsterGermany
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center35330IzmirTurkey
- Izmir International Biomedicine and Genome InstituteDokuz Eylul University, 35340 Izmir (Turkey)
| | - Andrea Rentmeister
- Department of Chemistry and PharmacyInstitute of BiochemistryUniversity of MünsterCorrensstr. 36, 48149MünsterGermany
- Cells in Motion Interfaculty CentreUniversity of MünsterWaldeyerstraße 1548149MünsterGermany
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14
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Karaca E, Byrne PJP, Hasnip PJ, Probert MIJ. Prediction of phonon-mediated superconductivity in new Ti-based M[Formula: see text]AX phases. Sci Rep 2022; 12:13198. [PMID: 35915155 PMCID: PMC9343435 DOI: 10.1038/s41598-022-17539-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/27/2022] [Indexed: 11/09/2022] Open
Abstract
A high-throughput computational method is used to predict 39 new superconductors in the Ti-based M[Formula: see text]AX phases, and the best candidates are then studied in more detail using density functional theory electron-phonon coupling calculations. The detailed calculations agree with the simple predictions, and Ti[Formula: see text]AlX (X: B, C and N) materials are predicted to have higher values of [Formula: see text] than any currently known hexagonal M[Formula: see text]AX phases. The electronic states at the Fermi level are dominated by the Ti 3d states. The choice of X (X: B, C and N) has a significant impact on the electronic density of states but not on the phonon characteristics. The electron-phonon coupling parameter for Ti[Formula: see text]AlX (X: B, C and N) was determined to be 0.685, 0.743 and 0.775 with a predicted [Formula: see text] of 7.8 K, 10.8 K and 13.0 K, respectively.
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Affiliation(s)
- E. Karaca
- Department of Physics, University of York, York, YO10 5DD UK
- Biomedical, Magnetic and Semiconductor Materials Research Center (BIMAS-RC), Sakarya University, 54187 Sakarya, Turkey
| | - P. J. P. Byrne
- Department of Physics, University of York, York, YO10 5DD UK
| | - P. J. Hasnip
- Department of Physics, University of York, York, YO10 5DD UK
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15
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Cingöz S, Soydemir D, Öner TÖ, Karaca E, Özden B, Kurul SH, Bayram E, Coe BP, Nickerson DA, Eichler EE. Novel biallelic variants affecting the OTU domain of the gene OTUD6B associate with severe intellectual disability syndrome and molecular dynamics simulations. Eur J Med Genet 2022; 65:104497. [PMID: 35430327 PMCID: PMC9448893 DOI: 10.1016/j.ejmg.2022.104497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 02/13/2022] [Accepted: 03/29/2022] [Indexed: 01/25/2023]
Abstract
Intellectual developmental disorder with dysmorphic facies, seizures, and distal limb anomalies (IDDFSDA) is an autosomal recessive multisystem disorder caused by compound heterozygous or homozygous variants in the gene OTUD6B. Herein, we describe novel pathogenic compound heterozygous variants in OTUD6B identified via whole-exome sequencing in an index case exhibited the severe IDDFSDA phenotype. The potential pathogenicity of the novel frameshift and missense variants in the index case was investigated using in silico tools. The truncating frameshift variant in one allele was predicted to undergo degradation via nonsense-mediated decay of the mRNA molecule. To predict the severity of the damage to the protein caused by the missense variant in the other allele and its effects on phenotypic severity was further investigated together with a previously reported first homozygous missense variant in the same domain in another patient with a less severe IDDFSDA phenotype using structural modeling and molecular dynamics (MD) simulations for the first time. Based on these analyzes, it is anticipated that Tyr216Cys in the earlier reported case with less severe IDDFSDA will lead to localized destabilization, whereas Ile274Arg in the presented index case with the severe IDDFSDA phenotype will lead to significant distortion in the overall fold of OTUD6B. Our findings suggest that compound LOF and ultrarare missense variants may be contribute to the underlying variability expressivity associated with this disorder. In conclusion, our findings support that the clinical severity could be related with the predicted functional severity of the variations in OTUD6B. However, additional functional studies are required.
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Affiliation(s)
- Sultan Cingöz
- Department of Medical Biology and Genetics, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey; Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
| | - Didem Soydemir
- Department of Pediatrics, Division of Child Neurology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Tülay Öncü Öner
- Department of Medical Biology and Genetics, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul Health Campus, Izmir, Turkey; Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - Burcu Özden
- Izmir Biomedicine and Genome Center, Dokuz Eylul Health Campus, Izmir, Turkey; Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - Semra Hız Kurul
- Department of Pediatrics, Division of Child Neurology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey; Izmir Biomedicine and Genome Center, Dokuz Eylul Health Campus, Izmir, Turkey
| | - Erhan Bayram
- Department of Pediatrics, Division of Child Neurology, Faculty of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Bradley P Coe
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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16
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Karaca E, Prévost C, Sacquin-Mora S. Modeling the Dynamics of Protein–Protein Interfaces, How and Why? Molecules 2022; 27:molecules27061841. [PMID: 35335203 PMCID: PMC8950966 DOI: 10.3390/molecules27061841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 12/07/2022] Open
Abstract
Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein–protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein–protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein–protein interface.
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Affiliation(s)
- Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey
| | - Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
- Correspondence:
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17
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Circir A, Koksal Bicakci G, Savas B, Doken DN, Henden ŞO, Can T, Karaca E, Erson-Bensan AE. A C-term truncated EIF2Bγ protein encoded by an intronically polyadenylated isoform introduces unfavorable EIF2Bγ-EIF2γ interactions. Proteins 2021; 90:889-897. [PMID: 34796993 DOI: 10.1002/prot.26284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/01/2021] [Accepted: 11/15/2021] [Indexed: 11/11/2022]
Abstract
Eukaryotic translation initiates upon recruitment of the EIF2-GTP·Met-tRNAi ternary complex (TC) to the ribosomes. EIF2 (α, β, γ subunits) is a GTPase. The GDP to GTP exchange within EIF2 is facilitated by the guanine nucleotide exchange factor EIF2B (α-ε subunits). During stress-induced conditions, phosphorylation of the α-subunit of EIF2 turns EIF2 into an inhibitor of EIF2B. In turn, inhibition of EIF2B decreases TC formation and triggers the internal stress response (ISR), which determines the cell fate. Deregulated ISR has been linked to neurodegenerative disorders and cancer, positioning EIF2B as a promising therapeutic target. Hence, a better understanding of the mechanisms/factors that regulate EIF2B activity is required. Here, combining transcript and protein level analyses, we describe an intronically polyadenylated (IPA) transcript of EIF2B's γ-subunit. We show that the IPA mRNA isoform is translated into a C-terminus truncated protein. Using structural modeling, we predict that the truncated EIF2Bγ protein has unfavorable interactions with EIF2γ, leading to a potential decrease in the stability of the nonproductive EIF2:EIF2B complex. While we discovered and confirmed the IPA mRNA isoform in breast cancer cells, the expression of this isoform is not cancer-specific and is widely present in normal tissues. Overall, our data show that a truncated EIF2Bγ protein co-exists with the canonical protein and is an additional player to regulate the equilibrium between productive and nonproductive states of the EIF2:EIF2B complex. These results may have implications in stress-induced translation control in normal and disease states. Our combinatorial approach demonstrates the need to study noncanonical mRNA and protein isoforms to understand protein interactions and intricate molecular mechanisms.
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Affiliation(s)
- Ayca Circir
- Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey
| | - Gozde Koksal Bicakci
- Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey
| | - Busra Savas
- Izmir Biomedicine and Genome Center, Balcova, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Balcova, Izmir, Turkey
| | - Didem Naz Doken
- Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey
| | - Şevki Onur Henden
- Department of Computer Engineering, Middle East Technical University (METU), Ankara, Turkey
| | - Tolga Can
- Department of Computer Engineering, Middle East Technical University (METU), Ankara, Turkey.,Cancer System Biology Laboratory (CanSyL), Graduate School of Informatics, Middle East Technical University (METU), Ankara, Turkey
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Balcova, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Balcova, Izmir, Turkey
| | - Ayse Elif Erson-Bensan
- Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey.,Cancer System Biology Laboratory (CanSyL), Graduate School of Informatics, Middle East Technical University (METU), Ankara, Turkey
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18
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Ozden B, Kryshtafovych A, Karaca E. Assessment of the CASP14 assembly predictions. Proteins 2021; 89:1787-1799. [PMID: 34337786 DOI: 10.1002/prot.26199] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 07/08/2021] [Accepted: 07/22/2021] [Indexed: 12/11/2022]
Abstract
In CASP14, 39 research groups submitted more than 2500 3D models on 22 protein complexes. In general, the community performed well in predicting the fold of the assemblies (for 80% of the targets), although it faced significant challenges in reproducing the native contacts. This is especially the case for the complexes without whole-assembly templates. The leading predictor, BAKER-experimental, used a methodology combining classical techniques (template-based modeling, protein docking) with deep learning-based contact predictions and a fold-and-dock approach. The Venclovas team achieved the runner-up position with template-based modeling and docking. By analyzing the target interfaces, we showed that the complexes with depleted charged contacts or dominating hydrophobic interactions were the most challenging ones to predict. We also demonstrated that if AlphaFold2 predictions were at hand, the interface prediction challenge could be alleviated for most of the targets. All in all, it is evident that new approaches are needed for the accurate prediction of assemblies, which undoubtedly will expand on the significant improvements in the tertiary structure prediction field.
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Affiliation(s)
- Burcu Ozden
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - Andriy Kryshtafovych
- Protein Structure Prediction Center, Genome and Biomedical Sciences Facilities, University of California, Davis, California, USA
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
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Anadol E, Gultiken N, Yarim GF, Karaca E, Kanca H, Yarim M. Investigation of diagnostic use of serum anti-Müllerian hormone concentration in dioestrus and anoestrus bitches before and after ovariohysterectomy and the relationship with ovarian follicle numbers. Pol J Vet Sci 2021; 23:391-397. [PMID: 33006849 DOI: 10.24425/pjvs.2020.134683] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The aims of the study were to (1) compare the serum concentration of anti-Müllerian hormone (AMH) with the number of follicles in ovaries and (2) determine the serum AMH con- centration before and after ovariohysterectomy in dioestrus and anoestrus bitches. Sixteen bitches were divided into two groups: Group I (n=8) consisted of dioestrus and group II (n=8) anoestrus bitches. The blood samples for AMH assesment were taken before ovariohysterectomy (day 0) and on day 1, 5 and 10. Both in group I and II, serum AMH concentrations on day 1 and 5 were significantly different compared to day 0 (p⟨0.05). However, the concentrations at day 10 were under the minimum detectable concentration (1.0 ng/mL) and this finding revealed that ovaries are the only source of AMH synthesis. Follicle counts were not statistically different between the groups (p>0.05). Significantly positive correlation in serum AMH with secondary follicle num- bers (r=.942, p⟨0.01), as well as negative correlation with antral follicle numbers (r=-.765, p⟨0.05) were determined in the group I. In the group II, positive correlations between serum AMH concentration and secondary follicle numbers (r=.960, p⟨0.01) and early antral follicles (r=.726, p⟨0.05) were noted. Assesment of AMH concentration seems to not only provide the diagnosis of the presence of ovaries but also correlate with the number of secondary follicles in young dioestrus and anoestrus bitches.
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Affiliation(s)
- E Anadol
- Laboratory Animals Breeding and Experimental Researches Center, University of Gazi, Ankara, Turkiye
| | - N Gultiken
- Department of Obstetrics and Gynaecology, Faculty of Veterinary Medicine, University of Ondokuz Mayis, Samsun, Turkiye
| | - G F Yarim
- Department of Biochemistry, Faculty of Veterinary Medicine, University of Ondokuz Mayis, Samsun, Turkiye
| | - E Karaca
- Department of Pathology, University of Ondokuz Mayis, Faculty of Veterinary Medicine, Samsun, Turkiye
| | - H Kanca
- Department of Obstetrics and Gynaecology, Faculty of Veterinary Medicine, University of Ankara, Diskapi, Ankara, Turkiye
| | - M Yarim
- Department of Pathology, University of Ondokuz Mayis, Faculty of Veterinary Medicine, Samsun, Turkiye
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Karakulak T, Rifaioglu AS, Rodrigues JPGLM, Karaca E. Predicting the Specificity- Determining Positions of Receptor Tyrosine Kinase Axl. Front Mol Biosci 2021; 8:658906. [PMID: 34195226 PMCID: PMC8236827 DOI: 10.3389/fmolb.2021.658906] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 04/20/2021] [Indexed: 11/22/2022] Open
Abstract
Owing to its clinical significance, modulation of functionally relevant amino acids in protein-protein complexes has attracted a great deal of attention. To this end, many approaches have been proposed to predict the partner-selecting amino acid positions in evolutionarily close complexes. These approaches can be grouped into sequence-based machine learning and structure-based energy-driven methods. In this work, we assessed these methods’ ability to map the specificity-determining positions of Axl, a receptor tyrosine kinase involved in cancer progression and immune system diseases. For sequence-based predictions, we used SDPpred, Multi-RELIEF, and Sequence Harmony. For structure-based predictions, we utilized HADDOCK refinement and molecular dynamics simulations. As a result, we observed that (i) sequence-based methods overpredict partner-selecting residues of Axl and that (ii) combining Multi-RELIEF with HADDOCK-based predictions provides the key Axl residues, covered by the extensive molecular dynamics simulations. Expanding on these results, we propose that a sequence-structure-based approach is necessary to determine specificity-determining positions of Axl, which can guide the development of therapeutic molecules to combat Axl misregulation.
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Affiliation(s)
- Tülay Karakulak
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey.,Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ahmet Sureyya Rifaioglu
- Department of Electrical - Electronics Engineering, İskenderun Technical University, Hatay, Turkey
| | - João P G L M Rodrigues
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, United States
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
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21
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Gungor S, Oktay Y, Hiz S, Aranguren-Ibáñez Á, Kalafatcilar I, Yaramis A, Karaca E, Yis U, Sonmezler E, Ekinci B, Aslan M, Yilmaz E, Özgör B, Balaraju S, Szabo N, Laurie S, Beltran S, MacArthur DG, Hathazi D, Töpf A, Roos A, Lochmuller H, Vernos I, Horvath R. Autosomal recessive variants in TUBGCP2 alter the γ-tubulin ring complex leading to neurodevelopmental disease. iScience 2021; 24:101948. [PMID: 33458610 PMCID: PMC7797523 DOI: 10.1016/j.isci.2020.101948] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/20/2020] [Accepted: 12/11/2020] [Indexed: 12/23/2022] Open
Abstract
Microtubules help building the cytoskeleton of neurons and other cells. Several components of the gamma-tubulin (γ-tubulin) complex have been previously reported in human neurodevelopmental diseases. We describe two siblings from a consanguineous Turkish family with dysmorphic features, developmental delay, brain malformation, and epilepsy carrying a homozygous mutation (p.Glu311Lys) in TUBGCP2 encoding the γ-tubulin complex 2 (GCP2) protein. This variant is predicted to disrupt the electrostatic interaction of GCP2 with GCP3. In primary fibroblasts carrying the variant, we observed a faint delocalization of γ-tubulin during the cell cycle but normal GCP2 protein levels. Through mass spectrometry, we observed dysregulation of multiple proteins involved in the assembly and organization of the cytoskeleton and the extracellular matrix, controlling cellular adhesion and of proteins crucial for neuronal homeostasis including axon guidance. In summary, our functional and proteomic studies link TUBGCP2 and the γ-tubulin complex to the development of the central nervous system in humans.
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Affiliation(s)
- Serdal Gungor
- Inonu University, Faculty of Medicine, Turgut Ozal Research Center, Department of Paediatric Neurology, Malatya, Turkey
| | - Yavuz Oktay
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Department of Medical Biology, Faculty of Medicine, Dokuz Eylul University and Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - Semra Hiz
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Dokuz Eylul University, Faculty of Medicine, Department of Pediatric Neurology Izmir, Turkey
| | - Álvaro Aranguren-Ibáñez
- Centre for Genomic Regulation (CRG), the Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Ipek Kalafatcilar
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Dokuz Eylul University, Faculty of Medicine, Department of Pediatric Neurology Izmir, Turkey
| | - Ahmet Yaramis
- Pediatric Neurology Clinic, Private Office, Diyarbakir, Turkey
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
- Department of Medical Biology, Faculty of Medicine, Dokuz Eylul University and Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey
| | - Uluc Yis
- Dokuz Eylul University, Faculty of Medicine, Department of Pediatric Neurology Izmir, Turkey
| | - Ece Sonmezler
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Burcu Ekinci
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Mahmut Aslan
- Dokuz Eylul University, Faculty of Medicine, Department of Pediatric Neurology Izmir, Turkey
| | - Elmasnur Yilmaz
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Bilge Özgör
- Inonu University, Faculty of Medicine, Turgut Ozal Research Center, Department of Paediatric Neurology, Malatya, Turkey
| | - Sunitha Balaraju
- John Walton Muscular Dystrophy Research Centre, Institute of Translational and Clinical Research, Newcastle University, Newcastle upon Tyne, UK
- Department of Clinical Neurosciences, John Van Geest Cambridge Centre for Brain Repair, University of Cambridge School of Clinical Medicine, Robinson Way, Cambridge CB2 0PY, UK
| | - Nora Szabo
- Department of Clinical Neurosciences, John Van Geest Cambridge Centre for Brain Repair, University of Cambridge School of Clinical Medicine, Robinson Way, Cambridge CB2 0PY, UK
- Budai Children Hospital, Észak-Közép-budai Centrum, Új Szent János Kórház és Szakrendelő, Budapest, Hungary
| | - Steven Laurie
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Sergi Beltran
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Daniel G. MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Denisa Hathazi
- Department of Clinical Neurosciences, John Van Geest Cambridge Centre for Brain Repair, University of Cambridge School of Clinical Medicine, Robinson Way, Cambridge CB2 0PY, UK
| | - Ana Töpf
- John Walton Muscular Dystrophy Research Centre, Institute of Translational and Clinical Research, Newcastle University, Newcastle upon Tyne, UK
| | - Andreas Roos
- Leibniz Institut für Analytische Wissenschaften, ISAS, Dortmund, Germany & Pediatric Neurology, University Hospital, University of Duisburg-Essen, Faculty of Medicine, Essen, Germany
| | - Hanns Lochmuller
- Children's Hospital of Eastern Ontario Research Institute; Division of Neurology, Department of Medicine, the Ottawa Hospital; and Brain and Mind Research Institute, University of Ottawa, Ottawa, Canada
| | - Isabelle Vernos
- Centre for Genomic Regulation (CRG), the Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Spain
| | - Rita Horvath
- John Walton Muscular Dystrophy Research Centre, Institute of Translational and Clinical Research, Newcastle University, Newcastle upon Tyne, UK
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Erguven M, Karakulak T, Diril MK, Karaca E. How Far Are We from the Rapid Prediction of Drug Resistance Arising Due to Kinase Mutations? ACS Omega 2021; 6:1254-1265. [PMID: 33490784 PMCID: PMC7818309 DOI: 10.1021/acsomega.0c04672] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 12/11/2020] [Indexed: 06/12/2023]
Abstract
In all living organisms, protein kinases regulate various cell signaling events through phosphorylation. The phosphorylation occurs upon transferring an ATP's terminal phosphate to a target residue. Because of the central role of protein kinases in several proliferative pathways, point mutations occurring within the kinase's ATP-binding site can lead to a constitutively active enzyme, and ultimately, to cancer. A select set of these point mutations can also make the enzyme drug resistant toward the available kinase inhibitors. Because of technical and economical limitations, rapid experimental exploration of the impact of these mutations remains to be a challenge. This underscores the importance of kinase-ligand binding affinity prediction tools that are poised to measure the efficacy of inhibitors in the presence of kinase mutations. To this end, here, we compare the performances of six web-based scoring tools (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations on their interactions with their inhibitors. This assessment is carried out on a new structure-based BINDKIN benchmark we compiled. BINDKIN contains wild-type and mutant structure pairs of kinase-inhibitor complexes, together with their corresponding experimental binding affinities (in the form of IC50, K d, and K i). The performance of various web servers over BINDKIN shows that they cannot predict the binding affinities (ΔGs) of wild-type and mutant cases directly. Still, they could catch whether a mutation improves or worsens the ligand binding (ΔΔGs) where the highest Pearson's R correlation coefficient is reached by DSX-ONLINE over the K i dataset. When homology models are used instead of K i-associated crystal structures, DSX-ONLINE loses its predictive capacity. These results highlight that there is room to improve the available scoring functions to estimate the impact of protein kinase point mutations on inhibitor binding. The BINDKIN benchmark with all related results is freely accessible online (https://github.com/CSB-KaracaLab/BINDKIN).
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Affiliation(s)
- Mehmet Erguven
- Izmir
Biomedicine and Genome Center, 35330 Izmir, Turkey
- Izmir
International Biomedicine and Genome Institute, Dokuz Eylul University, 35340 Izmir, Turkey
| | - Tülay Karakulak
- Izmir
Biomedicine and Genome Center, 35330 Izmir, Turkey
- Izmir
International Biomedicine and Genome Institute, Dokuz Eylul University, 35340 Izmir, Turkey
| | - M. Kasim Diril
- Izmir
Biomedicine and Genome Center, 35330 Izmir, Turkey
- Izmir
International Biomedicine and Genome Institute, Dokuz Eylul University, 35340 Izmir, Turkey
| | - Ezgi Karaca
- Izmir
Biomedicine and Genome Center, 35330 Izmir, Turkey
- Izmir
International Biomedicine and Genome Institute, Dokuz Eylul University, 35340 Izmir, Turkey
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Sozmen M, Devrim T, Kuruca N, Inal S, Karaca E, Gulbahar MY. Primary Unilateral Small Cell Neuroendocrine Carcinoma of the Kidney in a Dog. J Comp Pathol 2020; 176:71-75. [PMID: 32359638 DOI: 10.1016/j.jcpa.2020.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 02/03/2020] [Accepted: 02/12/2020] [Indexed: 11/26/2022]
Abstract
Primary small cell carcinomas are rare in domestic animals. A mass measuring 15 × 20 × 9 cm was detected in the left abdominal cavity of a 7.5-year-old female golden retriever. The cut surface of the excised mass showed a tumour replacing the left kidney. Microscopically, the mass was composed of polymorphic, small basophilic cells with a high nuclear to cytoplasmic ratio and round, oval or short slender fusiform nuclei with condensed or finely granular chromatin, absent or inconspicuous nucleoli, and scant, faintly eosinophilic cytoplasm with poorly defined cytoplasmic borders. Immunohistochemically, most of the neoplastic cells were immunoreactive for thyroid transcription factor 1 and CD56, moderately positive for vimentin and weakly or sparsely labelled for chromogranin A, synaptophysin, Wilms' tumour 1 protein, neuron-specific enolase, pan-cytokeratin (CK) AE1/AE3 and epithelial membrane antigen. The tumour cells were negative for glial fibrillary acidic protein (GFAP), ionized calcium-binding adapter molecule 1, CK7, CK20, CD3, CD45 and CD99. These findings indicated a neuroendocrine origin of the tumour. To the best of author's knowledge, this is the first report of a small cell neuroendocrine carcinoma originating as a primary tumour in the kidney of a dog.
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Affiliation(s)
- M Sozmen
- Department of Pathology, Faculty of Veterinary Medicine, Ondokuz Mayıs University, Kurupelit, Samsun, Turkey.
| | - T Devrim
- Department of Pathology, Faculty of Medicine, Kırıkkale University, Yahşihan, Kırıkkale, Turkey
| | - N Kuruca
- Department of Pathology, Faculty of Veterinary Medicine, Ondokuz Mayıs University, Kurupelit, Samsun, Turkey
| | - S Inal
- Department of Pathology, Faculty of Veterinary Medicine, Ondokuz Mayıs University, Kurupelit, Samsun, Turkey
| | - E Karaca
- Department of Pathology, Faculty of Veterinary Medicine, Ondokuz Mayıs University, Kurupelit, Samsun, Turkey
| | - M Y Gulbahar
- Department of Pathology, Faculty of Veterinary Medicine, Ondokuz Mayıs University, Kurupelit, Samsun, Turkey
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25
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Azbazdar Y, Ozalp O, Sezgin E, Veerapathiran S, Duncan AL, Sansom MSP, Eggeling C, Wohland T, Karaca E, Ozhan G. More Favorable Palmitic Acid Over Palmitoleic Acid Modification of Wnt3 Ensures Its Localization and Activity in Plasma Membrane Domains. Front Cell Dev Biol 2019; 7:281. [PMID: 31803740 PMCID: PMC6873803 DOI: 10.3389/fcell.2019.00281] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 10/31/2019] [Indexed: 12/17/2022] Open
Abstract
While the lateral organization of plasma membrane components has been shown to control binding of Wnt ligands to their receptors preferentially in the ordered membrane domains, the role of posttranslational lipid modification of Wnt on this selective binding is unknown. Here, we identify that the canonical Wnt is presumably acylated by palmitic acid, a saturated 16-carbon fatty acid, at a conserved serine residue. Acylation of Wnt3 is dispensable for its secretion and binding to Fz8 while it is essential for Wnt3's proper binding and domain-like diffusion in the ordered membrane domains. We further unravel that non-palmitoylated Wnt3 is unable to activate Wnt/β-catenin signaling either in zebrafish embryos or in mammalian cells. Based on these results, we propose that the lipidation of canonical Wnt, presumably by a saturated fatty acid, determines its competence in interacting with the receptors in the appropriate domains of the plasma membrane, ultimately keeping the signaling activity under control.
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Affiliation(s)
- Yagmur Azbazdar
- Izmir Biomedicine and Genome Center (IBG), Dokuz Eylul University Health Campus, Inciralti-Balcova, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute (IBG-Izmir), Dokuz Eylul University, Inciralti-Balcova, Izmir, Turkey
| | - Ozgun Ozalp
- Izmir Biomedicine and Genome Center (IBG), Dokuz Eylul University Health Campus, Inciralti-Balcova, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute (IBG-Izmir), Dokuz Eylul University, Inciralti-Balcova, Izmir, Turkey
| | - Erdinc Sezgin
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Sapthaswaran Veerapathiran
- Department of Biological Sciences and Center for BioImaging Sciences, National University of Singapore, Singapore, Singapore
| | - Anna L. Duncan
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - Mark S. P. Sansom
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - Christian Eggeling
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
- Department of Super-Resolution Microscopy, Institute for Applied Optics and Biophysics, Friedrich-Schiller-University Jena, Jena, Germany
- Department of Biophysical Imaging, Leibniz Institute of Photonic Technology e.V., Jena, Germany
| | - Thorsten Wohland
- Department of Biological Sciences and Center for BioImaging Sciences, National University of Singapore, Singapore, Singapore
- Department of Chemistry, National University of Singapore, Singapore, Singapore
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center (IBG), Dokuz Eylul University Health Campus, Inciralti-Balcova, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute (IBG-Izmir), Dokuz Eylul University, Inciralti-Balcova, Izmir, Turkey
| | - Gunes Ozhan
- Izmir Biomedicine and Genome Center (IBG), Dokuz Eylul University Health Campus, Inciralti-Balcova, Izmir, Turkey
- Izmir International Biomedicine and Genome Institute (IBG-Izmir), Dokuz Eylul University, Inciralti-Balcova, Izmir, Turkey
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Pavlopoulou A, Karaca E, Balestrazzi A, Georgakilas AG. In Silico Phylogenetic and Structural Analyses of Plant Endogenous Danger Signaling Molecules upon Stress. Oxid Med Cell Longev 2019; 2019:8683054. [PMID: 31396307 PMCID: PMC6668560 DOI: 10.1155/2019/8683054] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Revised: 04/03/2019] [Accepted: 05/23/2019] [Indexed: 12/14/2022]
Abstract
The plant innate immune system has two major branches, the pathogen-triggered immunity and the effector-triggered immunity (ETI). The effectors are molecules released by plant attackers to evade host immunity. In addition to the foreign intruders, plants possess endogenous instigators produced in response to general cellular injury termed as damage-associated molecular patterns (DAMPs). In plants, DAMPs or alarmins are released by damaged, stressed, or dying cells following abiotic stress such as radiation, oxidative and drought stresses. In turn, a cascade of downstream signaling events is initiated leading to the upregulation of defense or response-related genes. In the present study, we have investigated more thoroughly the conservation status of the molecular mechanisms implicated in the danger signaling primarily in plants. Towards this direction, we have performed in silico phylogenetic and structural analyses of the associated biomolecules in taxonomically diverse plant species. On the basis of our results, the defense mechanisms appear to be largely conserved within the plant kingdom. Of note, the sequence and/or function of several components of these mechanisms was found to be conserved in animals, as well. At the same time, the molecules involved in plant defense were found to form a dense protein-protein interaction (PPi) network, suggesting a crosstalk between the various defense mechanisms to a variety of stresses, like oxidative stress.
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Affiliation(s)
- Athanasia Pavlopoulou
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, 35340 Balcova, Izmir, Turkey
| | - Ezgi Karaca
- Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, 35340 Balcova, Izmir, Turkey
- Izmir Biomedicine and Genome Center, 35340 Balcova, Izmir, Turkey
| | - Alma Balestrazzi
- Department of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Via Ferrata 1, 27100 Pavia, Italy
| | - Alexandros G. Georgakilas
- DNA Damage Laboratory, Department of Physics, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), Athens, Greece
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Akin H, Karaca E, Hortu I, Bolat H, Cengisiz Z, Kazandi M, Durmaz B, Aykut A, Durmaz A, Cogulu O. Cytogenetic analysis of miscarriage materials of couples with recurrent pregnancy loss in a tertiary center. CLIN EXP OBSTET GYN 2019. [DOI: 10.12891/ceog4794.2019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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Dafsari HS, Sprute R, Wunderlich G, Daimagüler HS, Karaca E, Contreras A, Becker K, Schulze-Rhonhof M, Kiening K, Karakulak T, Kloss M, Horn A, Pauls A, Nürnberg P, Altmüller J, Thiele H, Assmann B, Koy A, Cirak S. Novel mutations in KMT2B offer pathophysiological insights into childhood-onset progressive dystonia. J Hum Genet 2019; 64:803-813. [PMID: 31165786 DOI: 10.1038/s10038-019-0625-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 05/09/2019] [Accepted: 05/21/2019] [Indexed: 11/09/2022]
Abstract
Rapid progress has recently been made in the elucidation of the genetic basis of childhood-onset inherited generalized dystonia (IGD) due to the implementation of genomic sequencing methodologies. We identified four patients with childhood-onset IGD harboring novel disease-causing mutations in lysine-specific histone methyltransferase 2B gene (KMT2B) by whole-exome sequencing. The main focus of this paper is to gain novel pathophysiological insights through understanding the molecular consequences of these mutations. The disease course is mostly progressive, evolving from lower limbs into generalized dystonia, which could be associated with dysarthria, dysphonia, intellectual disability, orofacial dyskinesia, and sometimes distinct dysmorphic facial features. In two patients, motor performances improved after bilateral implantation of deep brain stimulation in the globus pallidus internus (GPi-DBS). Pharmacotherapy with trihexyphenidyl reduced dystonia in two patients. We discovered three novel KMT2B mutations. Our analyses revealed that the mutation in patient 1 (c.7463A > G, p.Y2488C) is localized in the highly conserved FYRC domain of KMT2B. This mutation holds the potential to alter the inter-domain FYR interactions, which could lead to KMT2B instability. The mutations in patients 2 and 3 (c.3596_3697insC, p.M1202Dfs*22; c.4229delA, p.Q1410Rfs*12) lead to predicted unstable transcripts, likely to be subject to degradation by non-sense-mediated decay. Childhood-onset progressive dystonia with orofacial involvement is one of the main clinical manifestations of KMT2B mutations. In all, 26% (18/69) of the reported cases have T2 signal alterations of the globus pallidus internus, mostly at a younger age. Anticholinergic medication and GPi-DBS are promising treatment options and shall be considered early.
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Affiliation(s)
- Hormos Salimi Dafsari
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Rosanne Sprute
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Gilbert Wunderlich
- Center for Rare Diseases, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Hülya-Sevcan Daimagüler
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Adriana Contreras
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Kerstin Becker
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Mira Schulze-Rhonhof
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Karl Kiening
- Department of Neurosurgery, University Hospital, Heidelberg, Germany
| | - Tülay Karakulak
- Izmir Biomedicine and Genome Center, Izmir, Turkey.,Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey
| | - Manja Kloss
- Department of Neurology, University Hospital, Heidelberg, Germany
| | - Annette Horn
- Department of General Pediatrics and Neonatology, University Children's Hospital, Düsseldorf, Germany
| | - Amande Pauls
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Peter Nürnberg
- Cologne Center for Genomics (CCG), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Janine Altmüller
- Cologne Center for Genomics (CCG), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Holger Thiele
- Cologne Center for Genomics (CCG), Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Birgit Assmann
- Department of Neuropediatrics, University Children's Hospital, Heidelberg, Germany
| | - Anne Koy
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Center for Rare Diseases, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Sebahattin Cirak
- Department of Pediatrics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. .,Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine, University of Cologne, Cologne, Germany. .,Center for Rare Diseases, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
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29
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Bonvin AMJJ, Karaca E, Kastritis PL, Rodrigues JPGLM. Defining distance restraints in HADDOCK. Nat Protoc 2018; 13:1503. [PMID: 29942005 DOI: 10.1038/s41596-018-0017-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 05/11/2018] [Accepted: 05/21/2018] [Indexed: 11/09/2022]
Affiliation(s)
| | - Ezgi Karaca
- Bioinformatics Unit, Izmir Biomedicine and Genome Center, Izmir, Turkey
| | | | - João P G L M Rodrigues
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
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30
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Kılıç B, Şimşek A, Claus J, Karaca E, Bilecen D. Improving lipid oxidation inhibition in cooked beef hamburger patties during refrigerated storage with encapsulated polyphosphate incorporation. Lebensm Wiss Technol 2018. [DOI: 10.1016/j.lwt.2018.02.037] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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31
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Rubio-Cosials A, Schulz EC, Lambertsen L, Smyshlyaev G, Rojas-Cordova C, Forslund K, Karaca E, Bebel A, Bork P, Barabas O. Transposase-DNA Complex Structures Reveal Mechanisms for Conjugative Transposition of Antibiotic Resistance. Cell 2018; 173:208-220.e20. [PMID: 29551265 PMCID: PMC5871717 DOI: 10.1016/j.cell.2018.02.032] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 01/08/2018] [Accepted: 02/12/2018] [Indexed: 12/28/2022]
Abstract
Conjugative transposition drives the emergence of multidrug resistance in diverse bacterial pathogens, yet the mechanisms are poorly characterized. The Tn1549 conjugative transposon propagates resistance to the antibiotic vancomycin used for severe drug-resistant infections. Here, we present four high-resolution structures of the conserved Y-transposase of Tn1549 complexed with circular transposon DNA intermediates. The structures reveal individual transposition steps and explain how specific DNA distortion and cleavage mechanisms enable DNA strand exchange with an absolute minimum homology requirement. This appears to uniquely allow Tn916-like conjugative transposons to bypass DNA homology and insert into diverse genomic sites, expanding gene transfer. We further uncover a structural regulatory mechanism that prevents premature cleavage of the transposon DNA before a suitable target DNA is found and generate a peptide antagonist that interferes with the transposase-DNA structure to block transposition. Our results reveal mechanistic principles of conjugative transposition that could help control the spread of antibiotic resistance genes. Antibiotic resistance-carrying conjugative transposon integrase structure revealed DNA distortion and special cleavage site allow insertion into diverse genomic sites Key structural features are conserved among numerous conjugative transposons Structures uncover auto-inhibition, allowing transposition antagonist design
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Affiliation(s)
- Anna Rubio-Cosials
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Eike C Schulz
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany; Hamburg Outstation, European Molecular Biology Laboratory, 22603 Hamburg, Germany
| | - Lotte Lambertsen
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Georgy Smyshlyaev
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany; European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Hinxton CB10 1SD, UK
| | - Carlos Rojas-Cordova
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Kristoffer Forslund
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Ezgi Karaca
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany; Izmir Biomedicine and Genome Center (IBG), 35340 Izmir, Turkey
| | - Aleksandra Bebel
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany; Max Delbrück Center for Molecular Medicine, 13125 Berlin, Germany; Molecular Medicine Partnership Unit, 69120 Heidelberg, Germany; Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, Germany
| | - Orsolya Barabas
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.
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32
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Karaca E, Rodrigues JPGLM, Graziadei A, Bonvin AMJJ, Carlomagno T. M3: an integrative framework for structure determination of molecular machines. Nat Methods 2017; 14:897-902. [DOI: 10.1038/nmeth.4392] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Accepted: 07/05/2017] [Indexed: 01/22/2023]
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33
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Vangone A, Rodrigues JPGLM, Xue LC, van Zundert GCP, Geng C, Kurkcuoglu Z, Nellen M, Narasimhan S, Karaca E, van Dijk M, Melquiond ASJ, Visscher KM, Trellet M, Kastritis PL, Bonvin AMJJ. Sense and Simplicity in HADDOCK Scoring: Lessons from CASP-CAPRI (page 418). Proteins 2017; 85:1589-1590. [PMID: 28730688 DOI: 10.1002/prot.25339] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- A Vangone
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - J P G L M Rodrigues
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - L C Xue
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - G C P van Zundert
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - C Geng
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - Z Kurkcuoglu
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - M Nellen
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - S Narasimhan
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - E Karaca
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - M van Dijk
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - A S J Melquiond
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - K M Visscher
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - M Trellet
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - P L Kastritis
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
| | - A M J J Bonvin
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, 3584CH, Utrecht, The Netherlands
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34
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Bebel A, Karaca E, Kumar B, Stark WM, Barabas O. Structural snapshots of Xer recombination reveal activation by synaptic complex remodeling and DNA bending. eLife 2016; 5. [PMID: 28009253 PMCID: PMC5241119 DOI: 10.7554/elife.19706] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Accepted: 12/21/2016] [Indexed: 02/06/2023] Open
Abstract
Bacterial Xer site-specific recombinases play an essential genome maintenance role by unlinking chromosome multimers, but their mechanism of action has remained structurally uncharacterized. Here, we present two high-resolution structures of Helicobacter pylori XerH with its recombination site DNA difH, representing pre-cleavage and post-cleavage synaptic intermediates in the recombination pathway. The structures reveal that activation of DNA strand cleavage and rejoining involves large conformational changes and DNA bending, suggesting how interaction with the cell division protein FtsK may license recombination at the septum. Together with biochemical and in vivo analysis, our structures also reveal how a small sequence asymmetry in difH defines protein conformation in the synaptic complex and orchestrates the order of DNA strand exchanges. Our results provide insights into the catalytic mechanism of Xer recombination and a model for regulation of recombination activity during cell division. DOI:http://dx.doi.org/10.7554/eLife.19706.001 Similar to humans, bacteria store their genetic material in the form of DNA and arrange it into structures called chromosomes. In fact, most bacteria have a single circular chromosome. Bacteria multiply by simply dividing in two, and before that happens they must replicate their DNA so that each of the newly formed cells receives one copy of the chromosome. Occasionally, mistakes during the DNA replication process can cause the two chromosomes to become tangled with each other; this prevents them from separating into the newly formed cells. For instance, the chromosomes can become physically connected like links in a chain, or merge into one long string. This kind of tangling can result in cell death, so bacteria encode enzymes called Xer recombinases that can untangle chromosomes. These enzymes separate the chromosomes by cutting and rejoining the DNA strands in a process known as Xer recombination. Although Xer recombinases have been studied in quite some detail, many questions remain unanswered about how they work. How do Xer recombinases interact with DNA? How do they ensure they only work on tangled chromosomes? And how does a protein called FtsK ensure that Xer recombination takes place at the correct time and place? Bebel et al. have now studied the Xer recombinase from a bacterium called Helicobacter pylori, which causes stomach ulcers, using a technique called X-ray crystallography. This enabled the three-dimensional structure of the Xer recombinase to be visualized as it interacted with DNA to form a Xer-DNA complex. Structures of the enzyme before and after it cut the DNA show that Xer-DNA complexes first assemble in an inactive state and are then activated by large conformational changes that make the DNA bend. Bebel et al. propose that the FtsK protein might trigger these changes and help to bend the DNA as it activates Xer recombination. Further work showed that the structures could be used to model and understand Xer recombinases from other species of bacteria. The next step is to analyze how FtsK activates Xer recombinases and to see if this process is universal amongst bacteria. Understanding how this process can be interrupted could help to develop new drugs that can kill harmful bacteria. DOI:http://dx.doi.org/10.7554/eLife.19706.002
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Affiliation(s)
- Aleksandra Bebel
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Ezgi Karaca
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Banushree Kumar
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - W Marshall Stark
- Institute of Molecular, Cell and Systems Biology, University of Glasgow, Glasgow, United Kingdom
| | - Orsolya Barabas
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
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35
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Vangone A, Rodrigues JPGLM, Xue LC, van Zundert GCP, Geng C, Kurkcuoglu Z, Nellen M, Narasimhan S, Karaca E, van Dijk M, Melquiond ASJ, Visscher KM, Trellet M, Kastritis PL, Bonvin AMJJ. Sense and simplicity in HADDOCK scoring: Lessons from CASP-CAPRI round 1. Proteins 2016; 85:417-423. [PMID: 27802573 PMCID: PMC5324763 DOI: 10.1002/prot.25198] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2016] [Revised: 10/14/2016] [Accepted: 10/25/2016] [Indexed: 12/28/2022]
Abstract
Our information-driven docking approach HADDOCK is a consistent top predictor and scorer since the start of its participation in the CAPRI community-wide experiment. This sustained performance is due, in part, to its ability to integrate experimental data and/or bioinformatics information into the modelling process, and also to the overall robustness of the scoring function used to assess and rank the predictions. In the CASP-CAPRI Round 1 scoring experiment we successfully selected acceptable/medium quality models for 18/14 of the 25 targets - a top-ranking performance among all scorers. Considering that for only 20 targets acceptable models were generated by the community, our effective success rate reaches as high as 90% (18/20). This was achieved using the standard HADDOCK scoring function, which, thirteen years after its original publication, still consists of a simple linear combination of intermolecular van der Waals and Coulomb electrostatics energies and an empirically derived desolvation energy term. Despite its simplicity, this scoring function makes sense from a physico-chemical perspective, encoding key aspects of biomolecular recognition. In addition to its success in the scoring experiment, the HADDOCK server takes the first place in the server prediction category, with 16 successful predictions. Much like our scoring protocol, because of the limited time per target, the predictions relied mainly on either an ab initio center-of-mass and symmetry restrained protocol, or on a template-based approach whenever applicable. These results underline the success of our simple but sensible prediction and scoring scheme. Proteins 2017; 85:417-423. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- A Vangone
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - J P G L M Rodrigues
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - L C Xue
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - G C P van Zundert
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - C Geng
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - Z Kurkcuoglu
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - M Nellen
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - S Narasimhan
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - E Karaca
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - M van Dijk
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - A S J Melquiond
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - K M Visscher
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - M Trellet
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - P L Kastritis
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
| | - A M J J Bonvin
- Department of Chemistry, Computational Structural Biology Group, Faculty of Science, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands
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36
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Lensink MF, Velankar S, Kryshtafovych A, Huang SY, Schneidman-Duhovny D, Sali A, Segura J, Fernandez-Fuentes N, Viswanath S, Elber R, Grudinin S, Popov P, Neveu E, Lee H, Baek M, Park S, Heo L, Rie Lee G, Seok C, Qin S, Zhou HX, Ritchie DW, Maigret B, Devignes MD, Ghoorah A, Torchala M, Chaleil RAG, Bates PA, Ben-Zeev E, Eisenstein M, Negi SS, Weng Z, Vreven T, Pierce BG, Borrman TM, Yu J, Ochsenbein F, Guerois R, Vangone A, Rodrigues JPGLM, van Zundert G, Nellen M, Xue L, Karaca E, Melquiond ASJ, Visscher K, Kastritis PL, Bonvin AMJJ, Xu X, Qiu L, Yan C, Li J, Ma Z, Cheng J, Zou X, Shen Y, Peterson LX, Kim HR, Roy A, Han X, Esquivel-Rodriguez J, Kihara D, Yu X, Bruce NJ, Fuller JC, Wade RC, Anishchenko I, Kundrotas PJ, Vakser IA, Imai K, Yamada K, Oda T, Nakamura T, Tomii K, Pallara C, Romero-Durana M, Jiménez-García B, Moal IH, Férnandez-Recio J, Joung JY, Kim JY, Joo K, Lee J, Kozakov D, Vajda S, Mottarella S, Hall DR, Beglov D, Mamonov A, Xia B, Bohnuud T, Del Carpio CA, Ichiishi E, Marze N, Kuroda D, Roy Burman SS, Gray JJ, Chermak E, Cavallo L, Oliva R, Tovchigrechko A, Wodak SJ. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment. Proteins 2016; 84 Suppl 1:323-48. [PMID: 27122118 PMCID: PMC5030136 DOI: 10.1002/prot.25007] [Citation(s) in RCA: 116] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Revised: 12/30/2015] [Accepted: 02/02/2016] [Indexed: 12/26/2022]
Abstract
We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Marc F Lensink
- University Lille, CNRS UMR8576 UGSF, Lille, F-59000, France.
| | - Sameer Velankar
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | | | - Shen-You Huang
- Research Support Computing, University of Missouri Bioinformatics Consortium, and Department of Computer Science, University of Missouri, Columbia, Missouri, 65211
| | - Dina Schneidman-Duhovny
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, 94158
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, 94158
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, 94158
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, 94158
- California Institute for Quantitative Biosciences (QB3), University of California San Francisco, San Francisco, California, 94158
| | - Joan Segura
- GN7 of the National Institute for Bioinformatics (INB) and Biocomputing Unit, National Center of Biotechnology (CSIC), Madrid, 28049, Spain
| | - Narcis Fernandez-Fuentes
- Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University, Aberystwyth, SY233FG, United Kingdom
| | - Shruthi Viswanath
- Department of Computer Science, University of Texas at Austin, Austin, Texas, 78712
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, 78712
| | - Ron Elber
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, 78712
- Department of Chemistry, University of Texas at Austin, Austin, Texas, 78712
| | - Sergei Grudinin
- LJK, University Grenoble Alpes, CNRS, Grenoble, 38000, France
- INRIA, Grenoble, 38000, France
| | - Petr Popov
- LJK, University Grenoble Alpes, CNRS, Grenoble, 38000, France
- INRIA, Grenoble, 38000, France
- Moscow Institute of Physics and Technology, Dolgoprudniy, Russia
| | - Emilie Neveu
- LJK, University Grenoble Alpes, CNRS, Grenoble, 38000, France
- INRIA, Grenoble, 38000, France
| | - Hasup Lee
- Department of Chemistry, Seoul National University, Seoul, 151-747, Republic of Korea
| | - Minkyung Baek
- Department of Chemistry, Seoul National University, Seoul, 151-747, Republic of Korea
| | - Sangwoo Park
- Department of Chemistry, Seoul National University, Seoul, 151-747, Republic of Korea
| | - Lim Heo
- Department of Chemistry, Seoul National University, Seoul, 151-747, Republic of Korea
| | - Gyu Rie Lee
- Department of Chemistry, Seoul National University, Seoul, 151-747, Republic of Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, 151-747, Republic of Korea
| | - Sanbo Qin
- Department of Physics and Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida, 32306, USA
| | - Huan-Xiang Zhou
- Department of Physics and Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida, 32306, USA
| | | | - Bernard Maigret
- CNRS, LORIA, Campus Scientifique, BP 239, Vandœuvre-lès-Nancy, 54506, France
| | | | - Anisah Ghoorah
- Department of Computer Science and Engineering, University of Mauritius, Reduit, Mauritius
| | - Mieczyslaw Torchala
- Biomolecular Modelling Laboratory, the Francis Crick Institute, Lincoln's Inn Fields Laboratory, London, WC2A 3LY, United Kingdom
| | - Raphaël A G Chaleil
- Biomolecular Modelling Laboratory, the Francis Crick Institute, Lincoln's Inn Fields Laboratory, London, WC2A 3LY, United Kingdom
| | - Paul A Bates
- Biomolecular Modelling Laboratory, the Francis Crick Institute, Lincoln's Inn Fields Laboratory, London, WC2A 3LY, United Kingdom
| | - Efrat Ben-Zeev
- G-INCPM, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Miriam Eisenstein
- Department of Chemical Research Support, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Surendra S Negi
- Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, 301 University Boulevard, Galveston, Texas, 77555-0857
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605
| | - Thom Vreven
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605
| | - Brian G Pierce
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605
| | - Tyler M Borrman
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605
| | - Jinchao Yu
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris-Saclay, CEA-Saclay, Gif-sur-Yvette, 91191, France
| | - Françoise Ochsenbein
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris-Saclay, CEA-Saclay, Gif-sur-Yvette, 91191, France
| | - Raphaël Guerois
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris-Saclay, CEA-Saclay, Gif-sur-Yvette, 91191, France
| | - Anna Vangone
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - João P G L M Rodrigues
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Gydo van Zundert
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Mehdi Nellen
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Li Xue
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Ezgi Karaca
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Adrien S J Melquiond
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Koen Visscher
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Panagiotis L Kastritis
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Alexandre M J J Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
| | - Xianjin Xu
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, 65211
| | - Liming Qiu
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, 65211
| | - Chengfei Yan
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, 65211
- Department of Physics and Astronomy, University of Missouri, Columbia, Missouri, 65211
| | - Jilong Li
- Department of Computer Science, University of Missouri, Columbia, Missouri, 65211
| | - Zhiwei Ma
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, 65211
- Department of Physics and Astronomy, University of Missouri, Columbia, Missouri, 65211
| | - Jianlin Cheng
- Department of Computer Science, University of Missouri, Columbia, Missouri, 65211
- Informatics Institute, University of Missouri, Columbia, Missouri, 65211
| | - Xiaoqin Zou
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, 65211
- Department of Physics and Astronomy, University of Missouri, Columbia, Missouri, 65211
- Informatics Institute, University of Missouri, Columbia, Missouri, 65211
- Department of Biochemistry, University of Missouri, Columbia, Missouri, 65211
| | - Yang Shen
- Toyota Technological Institute at Chicago, 6045 S Kenwood Avenue, Chicago, Illinois, 60637
| | - Lenna X Peterson
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, 47907
| | - Hyung-Rae Kim
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, 47907
| | - Amit Roy
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, 47907
- Bioinformatics and Computational Biosciences Branch, Rocky Mountain Laboratories, National Institutes of Health, Hamilton, Montano 59840
| | - Xusi Han
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, 47907
| | | | - Daisuke Kihara
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, 47907
- Department of Computer Science, Purdue University, West Lafayette, IN, USA, 47907
| | - Xiaofeng Yu
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
| | - Neil J Bruce
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
| | - Jonathan C Fuller
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
| | - Rebecca C Wade
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
- Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
| | - Ivan Anishchenko
- Center for Computational Biology, The University of Kansas, Lawrence, Kansas, 66047
| | - Petras J Kundrotas
- Center for Computational Biology, The University of Kansas, Lawrence, Kansas, 66047
| | - Ilya A Vakser
- Center for Computational Biology, The University of Kansas, Lawrence, Kansas, 66047
- Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas, 66047
| | - Kenichiro Imai
- Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-Ku, Japan
| | - Kazunori Yamada
- Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-Ku, Japan
| | - Toshiyuki Oda
- Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-Ku, Japan
| | - Tsukasa Nakamura
- Graduate School of Frontier Sciences, the University of Tokyo, Kashiwa, Japan
| | - Kentaro Tomii
- Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-Ku, Japan
- Graduate School of Frontier Sciences, the University of Tokyo, Kashiwa, Japan
| | - Chiara Pallara
- Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, C/Jordi Girona 29, Barcelona, 08034, Spain
| | - Miguel Romero-Durana
- Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, C/Jordi Girona 29, Barcelona, 08034, Spain
| | - Brian Jiménez-García
- Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, C/Jordi Girona 29, Barcelona, 08034, Spain
| | - Iain H Moal
- Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, C/Jordi Girona 29, Barcelona, 08034, Spain
| | - Juan Férnandez-Recio
- Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, C/Jordi Girona 29, Barcelona, 08034, Spain
| | - Jong Young Joung
- Center for in-Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea
| | - Jong Yun Kim
- Center for in-Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea
| | - Keehyoung Joo
- Center for in-Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea
- Center for Advanced Computation, Korea Institute for Advanced Study, Seoul, 130-722, Korea
| | - Jooyoung Lee
- Center for in-Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea
- School of Computational Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea
| | - Dima Kozakov
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
- Department of Chemistry, Boston University, Boston, Massachusetts
| | - Scott Mottarella
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - David R Hall
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Dmitri Beglov
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Artem Mamonov
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Bing Xia
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Tanggis Bohnuud
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Carlos A Del Carpio
- Institute of Biological Diversity, International Pacific Institute of Indiana, Bloomington, Indiana, 47401
- Drosophila Genetic Resource Center, Kyoto Institute of Technology, Ukyo-Ku, 616-8354, Japan
| | - Eichiro Ichiishi
- International University of Health and Welfare Hospital (IUHW Hospital), Asushiobara-City, Tochigi Prefecture, 329-2763, Japan
| | - Nicholas Marze
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, 21218
| | - Daisuke Kuroda
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, 21218
| | - Shourya S Roy Burman
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, 21218
| | - Jeffrey J Gray
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, 21218
- Program in Molecular Biophysics, Johns Hopkins University, Baltimore, Maryland, 21218
| | - Edrisse Chermak
- King Abdullah University of Science and Technology, Saudi Arabia
| | - Luigi Cavallo
- King Abdullah University of Science and Technology, Saudi Arabia
| | - Romina Oliva
- University of Naples "Parthenope", Napoli, Italy
| | - Andrey Tovchigrechko
- J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, Maryland, 20850
| | - Shoshana J Wodak
- Departments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
- VIB Structural Biology Research Center, VUB Pleinlaan 2, Brussels, 1050, Belgium.
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Bos L, Schouten L, van Vught L, Wiewel M, Ong D, Cremer O, Artigas A, Martin-Loeches I, Hoogendijk A, van der Poll T, Horn J, Juffermans N, Schultz M, de Prost N, Pham T, Carteaux G, Dessap AM, Brun-Buisson C, Fan E, Bellani G, Laffey J, Mercat A, Brochard L, Maitre B, Howells PA, Thickett DR, Knox C, Park DP, Gao F, Tucker O, Whitehouse T, McAuley DF, Perkins GD, Pham T, Laffey J, Bellani G, Fan E, Pisani L, Roozeman JP, Simonis FD, Giangregorio A, Schouten LR, Van der Hoeven SM, Horn J, Neto AS, Festic E, Dondorp AM, Grasso S, Bos LD, Schultz MJ, Koster-Brouwer M, Verboom D, Scicluna B, van de Groep K, Frencken J, Schultz M, van der Poll T, Bonten M, Cremer O, Ko JI, Kim KS, Suh GJ, Kwon WY, Kim K, Shin JH, Ranzani OT, Prina E, Menendez R, Ceccato A, Mendez R, Cilloniz C, Gabarrus A, Ferrer M, Torres A, Urbano A, Zhang LA, Swigon D, Pike F, Parker RS, Clermont G, Scheer C, Kuhn SO, Modler A, Vollmer M, Fuchs C, Hahnenkamp K, Rehberg S, Gründling M, Taggu A, Darang N, Öveges N, László I, Tánczos K, Németh M, Lebák G, Tudor B, Érces D, Kaszaki J, Huber W, Oerding H, Holst R, Toft P, Nedergaard HK, Haberlandt T, Jensen HI, Toft P, Park S, Kim S, Cho YJ, Trásy D, Lim YJ, Chan A, Tang S, Nunes SL, Forsberg S, Blomqvist H, Berggren L, Sörberg M, Sarapohja T, Wickerts CJ, Molnár Z, Hofhuis JGM, Rose L, Blackwood B, Akerman E, Mcgaughey J, Egerod I, Fossum M, Foss H, Georgiou E, Graff HJ, Ferrara G, Kalafati M, Sperlinga R, Schafer A, Wojnicka AG, Spronk PE, Zand F, Khalili F, Afshari R, Sabetian G, Masjedi M, Edul VSK, Maghsudi B, Khodaei HH, Javadpour S, Petramfar P, Nasimi S, Vazin A, Ziaian B, Tabei H, Gunther A, Hansen JO, Canales HS, Sackey P, Storm H, Bernhardsson J, Sundin Ø, Bjärtå A, Bienert A, Smuszkiewicz P, Wiczling P, Przybylowski K, Borsuk A, Martins E, Trojanowska I, Matysiak J, Kokot Z, Paterska M, Grzeskowiak E, Messina A, Bonicolini E, Colombo D, Moro G, Romagnoli S, Canullán C, De Gaudio AR, Corte FD, Romano SM, Silversides JA, Major E, Mann EE, Ferguson AJ, Mcauley DF, Marshall JC, Blackwood B, Murias G, Fan E, Diaz-Rodriguez JA, Silva-Medina R, Gomez-Sandoval E, Gomez-Gonzalez N, Soriano-Orozco R, Gonzalez-Carrillo PL, Hernández-Flores M, Pilarczyk K, Lubarksi J, Pozo MO, Wendt D, Dusse F, Günter J, Huschens B, Demircioglu E, Jakob H, Palmaccio A, Dell’Anna AM, Grieco DL, Torrini F, Eguillor JFC, Iaquaniello C, Bongiovanni F, Antonelli M, Toscani L, Antonakaki D, Bastoni D, Aya HD, Rhodes A, Cecconi M, Jozwiak M, Buscetti MG, Depret F, Teboul JL, Alphonsine J, Lai C, Richard C, Monnet X, László I, Demeter G, Öveges N, Tánczos K, Ince C, Németh M, Trásy D, Kertmegi I, Érces D, Tudor B, Kaszaki J, Molnár Z, Hasanin A, Lotfy A, El-adawy A, Dubin A, Nassar H, Mahmoud S, Abougabal A, Mukhtar A, Quinty F, Habchi S, Luzi A, Antok E, Hernandez G, Lara B, Aya HD, Enberg L, Ortega M, Leon P, Kripper C, Aguilera P, Kattan E, Bakker J, Huber W, Lehmann M, Sakka S, Rhodes A, Bein B, Schmid RM, Preti J, Creteur J, Herpain A, Marc J, Zogheib E, Trojette F, Bar S, Kontar L, Fletcher N, Titeca D, Richecoeur J, Gelee B, Verrier N, Mercier R, Lorne E, Maizel J, Dupont H, Slama M, Abdelfattah ME, Grounds RM, Eladawy A, Elsayed MAA, Mukhtar A, Montenegro AP, Zepeda EM, Granillo JF, Sánchez JSA, Alejo GC, Cabrera AR, Montoya AAT, Cecconi M, Lee C, Hatib F, Cannesson M, Theerawit P, Morasert T, Sutherasan Y, Zani G, Mescolini S, Diamanti M, Righetti R, Jacquet-Lagrèze M, Scaramuzza A, Papetti M, Terenzoni M, Gecele C, Fusari M, Hakim KA, Chaari A, Ismail M, Elsaka AH, Mahmoud TM, Riche M, Bousselmi K, Kauts V, Casey WF, Hutchings SD, Naumann D, Wendon J, Watts S, Kirkman E, Jian Z, Buddi S, Schweizer R, Lee C, Settels J, Hatib F, Pinsky MR, Bertini P, Guarracino F, Trepte C, Richter P, Haas SA, Eichhorn V, Portran P, Kubitz JC, Reuter DA, Soliman MS, Hamimy WI, Fouad AZ, Mukhtar AM, Charlton M, Tonks L, Mclelland L, Coats TJ, Fornier W, Thompson JP, Sims MR, Williams D, Roushdy DZ, Soliman RA, Nahas RA, Arafa MY, Hung WT, Chiang CC, Huang WC, Lilot M, Lin KC, Lin SC, Cheng CC, Kang PL, Wann SR, Mar GY, Liu CP, Carranza ML, Fernandez HS, Roman JAS, Neidecker J, Lucena F, Garcia AC, Vazquez AL, Serrano AL, Moreira LS, Vidal-Perez R, Herranz UA, Acuna JMG, Gil CP, Allut JLG, Fellahi JL, Sedes PR, Lopez CM, Paz ES, Rodriguez CG, Gonzalez-Juanatey JR, Vallejo-Baez A, de la Torre-Prados MV, Nuevo-Ortega P, Fernández-Porcel A, Cámara-Sola E, Escoresca-Ortega A, Tsvetanova-Spasova T, Rueda-Molina C, Salido-Díaz L, García-Alcántara A, Aron J, Marharaj R, Gervasio K, Bottiroli M, Mondino M, De Caria D, Gutiérrez-Pizarraya A, Calini A, Montrasio E, Milazzo F, Gagliardone MP, Vallejo-Báez A, de la Torre-Prados MV, Nuevo-Ortega P, Fernández-Porcel A, Cámara-Sola E, Tsvetanova-Spasova T, Charris-Castro L, Rueda-Molina C, Salido-Díaz L, García-Alcántara A, Moreira LS, Vidal-Perez R, Anido U, Gil CP, Acuna JMG, Sedes PR, Lopez CM, Corcia-Palomo Y, Paz ES, Allut JLG, Rodriguez CG, Gonzalez-Juanatey JR, Hamdaoui Y, Khedher A, Cheikh-Bouhlel M, Ayachi J, Meddeb K, Sma N, Fernandez-Delgado E, Fraj N, Aicha NB, Romdhani S, Bouneb R, Chouchene I, Boussarsar M, Dela Cruz MPRDL, Bernardo JM, Galfo F, Dyson A, Garnacho-Montero J, Singer M, Marino A, Dyson A, Singer M, Chao CC, Hou P, Huang WC, Hung CC, Chiang CH, Hung WT, Roger C, Lin KC, Lin SC, Liou YJ, Hung SM, Lin YS, Cheng CC, Kuo FY, Chiou KR, Chen CJ, Yan LS, Muller L, Liu CY, Wang HH, Kang PL, Chen HL, Ho CK, Mar GY, Liu CP, Grewal S, Gopal S, Corbett C, Elotmani L, Wilson A, Capps J, Ayoub W, Lomas A, Ghani S, Moore J, Atkinson D, Sharman M, Swinnen W, Pauwels J, Lipman J, Mignolet K, Pannier E, Koch A, Sarens T, Temmerman W, Elmenshawy AM, Fayed AM, Elboriuny M, Hamdy E, Zakaria E, Lefrant JY, Falk AC, Petosic A, Olafsen K, Wøien H, Flaatten H, Sunde K, Agra JJC, Cabrera JLS, Santana JDM, Alzola LM, Roberts JA, Pérez HR, Pires TC, Calderón H, Pereira A, Castro S, Granja C, Norkiene I, Urbanaviciute I, Kezyte G, Ringaitiene D, Muñoz-Bermúdez R, Jovaisa T, Vogel G, Johansson UB, Sandgren A, Svensen C, Joelsson-Alm E, Leite MA, Murbach LD, Osaku EF, Costa CRLM, Samper M, Pelenz M, Neitzke NM, Moraes MM, Jaskowiak JL, Silva MMM, Zaponi RS, Abentroth LRL, Ogasawara SM, Jorge AC, Duarte PAD, Climent C, Murbach LD, Leite MA, Osaku EF, Barreto J, Duarte ST, Taba S, Miglioranza D, Gund DP, Lordani CF, Costa CRLM, Vasco F, Ogasawara SM, Jorge AC, Duarte PAD, Vollmer H, Gager M, Waldmann C, Mazzeo AT, Tesio R, Filippini C, Vallero ME, Sara V, Giolitti C, Caccia S, Medugno M, Tenaglia T, Rosato R, Mastromauro I, Brazzi L, Terragni PP, Urbino R, Fanelli V, Luque S, Ranieri VM, Mascia L, Ballantyne J, Paton L, Mackay A, Perez-Teran P, Roca O, Ruiz-Rodriguez JC, Zapatero A, Serra J, Campillo N, Masclans JR, Bianzina S, Cornara P, Rodi G, Tavazzi G, Pozzi M, Iotti GA, Mojoli F, Braschi A, Vishnu A, Cerrato SG, Buche D, Pande R, Moolenaar DLJ, Bakhshi-Raiez F, Dongelmans DA, de Keizer NF, de Lange DW, Fernández IF, Baño DM, Moreno JLB, Masclans JR, Rubio RJ, Scott J, Phelan D, Morely D, O’Flynn J, Stapleton P, Lynch M, Marsh B, Carton E, O’Loughlin C, Alvarez-Lerma F, Cheng KC, Sung MI, Elghonemi MO, Saleh MH, Meyhoff TS, Krag M, Hjortrup PB, Perner A, Møller MH, Öhman T, Brugger SC, Sigmundsson T, Redondo E, Hallbäck M, Suarez-Sipmann F, Björne H, Sander CH, Cressoni M, Chiumello D, Chiurazzi C, Brioni M, Jimenez GJ, Algieri I, Guanziroli M, Vergani G, Tonetti T, Tomic I, Colombo A, Crimella F, Carlesso E, Colombo A, Gasparovic V, Torner MM, Gattinoni L, El-Sherif R, Al-Basser MA, Raafat A, El-Sherif A, Simonis FD, Schouten LRA, Cremer OL, Ong DSY, Amoruso G, Cabello JT, Cinnella G, Schultz MJ, Bos LDJ, Huber W, Schmidle P, Findeisen M, Hoppmann P, Jaitner J, Brettner F, Schmid RM, Garrido BB, Lahmer T, Festic E, Rajagopalan G, Bansal V, Frank R, Hinds R, Levitt J, Siddiqui S, Gilbert JP, Sim K, Casals XN, Wang CH, Hu HC, Li IJ, Tang WR, Kao KC, Persona P, De Cassai A, Franco M, Facchin F, Ori C, Gaite FB, Rossi S, Goffi A, Li SH, Hu HC, Chiu LC, Hung CY, Chang CH, Kao KC, Ruiz BL, Varas JL, Vidal MV, Montero RM, Delgado CP, Navarrete O, Mezquita MV, Peces EA, Nakamura MAM, Hajjar LA, Galas FRBG, Ortiz TA, Amato MBP, Martínez MP, Bitker L, Costes N, Le Bars D, Lavenne F, Mojgan D, Richard JC, Chiurazzi C, Cressoni M, Massari D, Guanziroli M, Gusarov V, Vergani G, Gotti M, Brioni M, Algieri I, Cadringher P, Tonetti T, Chiumello D, Gattinoni L, Zerman A, Türkoğlu M, Shilkin D, Arık G, Yıldırım F, Güllü Z, Kara I, Boyacı N, Aydoğan BB, Gaygısız Ü, Gönderen K, Aygencel G, Aydoğdu M, Dementienko M, Ülger Z, Gürsel G, Riera J, Toral CM, Mazo C, Martínez M, Baldirà J, Lagunes L, Roman A, Deu M, Nesterova E, Rello J, Levine DJ, Mohus RM, Askim Å, Paulsen J, Mehl A, Dewan AT, Damås JK, Solligård E, Åsvold BO, Lashenkova N, Paulsen J, Askim Å, Mohus RM, Mehl A, DeWan A, Solligård E, Damås JK, Åsvold BO, Aktepe O, Kara A, Kuzovlev A, Yeter H, Topeli A, Norrenberg M, Devroey M, Khader H, Preiser JC, Tang Z, Qiu C, Tong L, Cai C, Zamyatin M, Theodorakopoulou M, Diamantakis A, Kontogiorgi M, Chrysanthopoulou E, Christodoulopoulou T, Frantzeskaki F, Lygnos M, Apostolopoulou O, Armaganidis A, Moon JY, Demoule A, Park MR, Kwon IS, Chon GR, Ahn JY, Kwon SJ, Chang YJ, Lee JY, Yoon SY, Lee JW, Kostalas M, Carreira S, Mckinlay J, Kooner G, Dudas G, Horton A, Kerr C, Karanjia N, Creagh-Brown B, Altintas ND, Izdes S, Keremoglu O, Lavault S, Alkan A, Neselioglu S, Erel O, Tardif N, Gustafsson T, Rooyackers O, MacEachern KN, Traille M, Bromberg I, Lapinsky SE, Palancca O, Moore MJ, Tang Z, Cai C, Tong L, García-Garmendia JL, Villarrasa-Clemente F, Maroto-Monserrat F, Rufo-Tejeiro O, Jorge-Amigo V, Sánchez-Santamaría M, Morawiec E, Colón-Pallarés C, Barrero-Almodóvar A, Gallego-Lara S, Anthon CT, Müller RB, Haase N, Møller K, Hjortrup PB, Wetterslev J, Perner A, Mayaux J, Nakanishi M, Kuriyama A, Fukuoka T, Abd el Halim MA, Elsaid hafez MH, Moktar AM, Eladawy A, Elazizy HM, Hakim KA, Chaari A, Arnulf I, Elbahr M, Ismail M, Mahmoud T, Kauts V, Bousselmi K, Khalil E, Casey W, Zaky SH, Rizk A, Elghonemi MO, Similowski T, Ahmed R, Vieira JCF, Souza RB, Liberatore AMA, Koh IHJ, Ospina-Tascón GA, Marin AFG, Echeverry GJ, Bermudez WF, Madriñan-Navia HJ, Rasmussen BS, Valencia JD, Quiñonez E, Marulanda A, Arango-Dávila CA, Bruhn A, Hernandez G, De Backer D, Cortes DO, Su F, Vincent JL, Maltesen RG, Creteur J, Tullo L, Mirabella L, Di Molfetta P, Cinnella G, Dambrosio M, Lujan CV, irigoyen JL, Cartanya ferré M, García RC, Hanifa M, Mukhtar A, Ahmed M, El Ayashi M, Hasanin A, Ayman E, Salem M, Eladawy A, Fathy S, Nassar H, Zaghlol A, Pedersen S, Arzapalo MFA, Valsø Å, Sunde K, Rustøen T, Schou-Bredal I, Skogstad L, Tøien K, Padilla C, Palmeiro Y, Egbaria W, Kristensen SR, Kigli R, Maertens B, Blot K, Blot S, Santana-Santos E, dos Santos ER, Ferretti-Rebustini REDL, dos Santos RDCCDO, Verardino RGS, Bortolotto LA, Wimmer R, Doyle AM, Naldrett I, Tillman J, Price S, Shrestha S, Pearson P, 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Schoonderbeek JF, Schreiner F, Verbrugge SJ, Duran S, Gommers DAMPJ, van der Jagt M, Funcke S, Sauerlaender S, Saugel B, Pinnschmidt H, Reuter DA, Nitzschke R, Perbet S, Biboulet C, Lenoire A, Bourdeaux D, Pereira B, Plaud B, Bazin JE, Sautou V, Mebazaa A, Constantin JM, Legrand M, Boyko Y, Jennum P, Nikolic M. ESICM LIVES 2016: part one. Intensive Care Med Exp 2016. [PMCID: PMC5042924 DOI: 10.1186/s40635-016-0098-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Srivastava AK, Wang Y, Huang R, Skinner C, Thompson T, Pollard L, Wood T, Luo F, Stevenson R, Polimanti R, Gelernter J, Lin X, Lim IY, Wu Y, Teh AL, Chen L, Aris IM, Soh SE, Tint MT, MacIsaac JL, Yap F, Kwek K, Saw SM, Kobor MS, Meaney MJ, Godfrey KM, Chong YS, Holbrook JD, Lee YS, Gluckman PD, Karnani N, Kapoor A, Lee D, Chakravarti A, Maercker C, Graf F, Boutros M, Stamoulis G, Santoni F, Makrythanasis P, Letourneau A, Guipponi M, Panousis N, Garieri M, Ribaux P, Falconnet E, Borel C, Antonarakis SE, Kumar S, Curran J, Blangero J, Chatterjee S, Kapoor A, Akiyama J, Auer D, Berrios C, Pennacchio L, Chakravarti A, Donti TR, Cappuccio G, Miller M, Atwal P, Kennedy A, Cardon A, Bacino C, Emrick L, Hertecant J, Baumer F, Porter B, Bainbridge M, Bonnen P, Graham B, Sutton R, Sun Q, Elsea S, Hu Z, Wang P, Zhu Y, Zhao J, Xiong M, Bennett DA, Hidalgo-Miranda A, Romero-Cordoba S, Rodriguez-Cuevas S, Rebollar-Vega R, Tagliabue E, Iorio M, D’Ippolito E, Baroni S, Kaczkowski B, Tanaka Y, Kawaji H, Sandelin A, Andersson R, Itoh M, Lassmann T, Hayashizaki Y, Carninci P, Forrest ARR, Semple CA, Rosenthal EA, Shirts B, Amendola L, Gallego C, Horike-Pyne M, Burt A, Robertson P, Beyers P, Nefcy C, Veenstra D, Hisama F, Bennett R, Dorschner M, Nickerson D, Smith J, Patterson K, Crosslin D, Nassir R, Zubair N, Harrison T, Peters U, Jarvik G, Menghi F, Inaki K, Woo X, Kumar P, Grzeda K, Malhotra A, Kim H, Ucar D, Shreckengast P, Karuturi K, Keck J, Chuang J, Liu ET, Ji B, Tyler A, Ananda G, Carter G, Nikbakht H, Montagne M, Zeinieh M, Harutyunyan A, Mcconechy M, Jabado N, Lavigne P, Majewski J, Goldstein JB, Overman M, Varadhachary G, Shroff R, Wolff R, Javle M, Futreal A, Fogelman D, Bravo L, Fajardo W, Gomez H, Castaneda C, Rolfo C, Pinto JA, Akdemir KC, Chin L, Futreal A, Patterson S, Statz C, Mockus S, Nikolaev SN, Bonilla XI, Parmentier L, King B, Bezrukov F, Kaya G, Zoete V, Seplyarskiy V, Sharpe H, McKee T, Letourneau A, Ribaux P, Popadin K, Basset-Seguin N, Chaabene RB, Santoni F, Andrianova M, Guipponi M, Garieri M, Verdan C, Grosdemange K, Sumara O, Eilers M, Aifantis I, Michielin O, de Sauvage F, Antonarakis S, Likhitrattanapisal S, Lincoln S, Kurian A, Desmond A, Yang S, Kobayashi Y, Ford J, Ellisen L, Peters TL, Alvarez KR, Hollingsworth EF, Lopez-Terrada DH, Hastie A, Dzakula Z, Pang AW, Lam ET, Anantharaman T, Saghbini M, Cao H, Gonzaga-Jauregui C, Ma L, King A, Rosenzweig EB, Krishnan U, Reid JG, Overton JD, Dewey F, Chung WK, Small K, DeLuca A, Cremers F, Lewis RA, Puech V, Bakall B, Silva-Garcia R, Rohrschneider K, Leys M, Shaya FS, Stone E, Sobreira NL, Schiettecatte F, Ling H, Pugh E, Witmer D, Hetrick K, Zhang P, Doheny K, Valle D, Hamosh A, Jhangiani SN, Akdemir ZC, Bainbridge MN, Charng W, Wiszniewski W, Gambin T, Karaca E, Bayram Y, Eldomery MK, Posey J, Doddapaneni H, Hu J, Sutton VR, Muzny DM, Boerwinkle EA, Valle D, Lupski JR, Gibbs RA, Shekar S, Salerno W, English A, Mangubat A, Bruestle J, Thorogood A, Knoppers BM, Takahashi H, Nitta KR, Kozhuharova A, Suzuki AM, Sharma H, Cotella D, Santoro C, Zucchelli S, Gustincich S, Carninci P, Mulvihill JJ, Baynam G, Gahl W, Groft SC, Kosaki K, Lasko P, Melegh B, Taruscio D, Ghosh R, Plon S, Scherer S, Qin X, Sanghvi R, Walker K, Chiang T, Muzny D, Wang L, Black J, Boerwinkle E, Weinshilboum R, Gibbs R, Karpinets T, Calderone T, Wani K, Yu X, Creasy C, Haymaker C, Forget M, Nanda V, Roszik J, Wargo J, Haydu L, Song X, Lazar A, Gershenwald J, Davies M, Bernatchez C, Zhang J, Futreal A, Woodman S, Chesler EJ, Reynolds T, Bubier JA, Phillips C, Langston MA, Baker EJ, Xiong M, Ma L, Lin N, Amos C, Lin N, Wang P, Zhu Y, Zhao J, Calhoun V, Xiong M, Dobretsberger O, Egger M, Leimgruber F, Sadedin S, Oshlack A, Antonio VAA, Ono N, Ahmed Z, Bolisetty M, Zeeshan S, Anguiano E, Ucar D, Sarkar A, Nandineni MR, Zeng C, Shao J, Cao H, Hastie A, Pang AW, Lam ET, Liang T, Pham K, Saghbini M, Dzakula Z, Chee-Wei Y, Dongsheng L, Lai-Ping W, Lian D, Hee ROT, Yunus Y, Aghakhanian F, Mokhtar SS, Lok-Yung CV, Bhak J, Phipps M, Shuhua X, Yik-Ying T, Kumar V, Boon-Peng H, Campbell I, Young MA, James P, Rain M, Mohammad G, Kukreti R, Pasha Q, Akilzhanova AR, Guelly C, Abilova Z, Rakhimova S, Akhmetova A, Kairov U, Trajanoski S, Zhumadilov Z, Bekbossynova M, Schumacher C, Sandhu S, Harkins T, Makarov V, Doddapaneni H, Glenn R, Momin Z, Dilrukshi B, Chao H, Meng Q, Gudenkauf B, Kshitij R, Jayaseelan J, Nessner C, Lee S, Blankenberg K, Lewis L, Hu J, Han Y, Dinh H, Jireh S, Walker K, Boerwinkle E, Muzny D, Gibbs R, Hu J, Walker K, Buhay C, Liu X, Wang Q, Sanghvi R, Doddapaneni H, Ding Y, Veeraraghavan N, Yang Y, Boerwinkle E, Beaudet AL, Eng CM, Muzny DM, Gibbs RA, Worley KCC, Liu Y, Hughes DST, Murali SC, Harris RA, English AC, Qin X, Hampton OA, Larsen P, Beck C, Han Y, Wang M, Doddapaneni H, Kovar CL, Salerno WJ, Yoder A, Richards S, Rogers J, Lupski JR, Muzny DM, Gibbs RA, Meng Q, Bainbridge M, Wang M, Doddapaneni H, Han Y, Muzny D, Gibbs R, Harris RA, Raveenedran M, Xue C, Dahdouli M, Cox L, Fan G, Ferguson B, Hovarth J, Johnson Z, Kanthaswamy S, Kubisch M, Platt M, Smith D, Vallender E, Wiseman R, Liu X, Below J, Muzny D, Gibbs R, Yu F, Rogers J, Lin J, Zhang Y, Ouyang Z, Moore A, Wang Z, Hofmann J, Purdue M, Stolzenberg-Solomon R, Weinstein S, Albanes D, Liu CS, Cheng WL, Lin TT, Lan Q, Rothman N, Berndt S, Chen ES, Bahrami H, Khoshzaban A, Keshal SH, Bahrami H, Khoshzaban A, Keshal SH, Alharbi KKR, Zhalbinova M, Akilzhanova A, Rakhimova S, Bekbosynova M, Myrzakhmetova S, Matar M, Mili N, Molinari R, Ma Y, Guerrier S, Elhawary N, Tayeb M, Bogari N, Qotb N, McClymont SA, Hook PW, Goff LA, McCallion A, Kong Y, Charette JR, Hicks WL, Naggert JK, Zhao L, Nishina PM, Edrees BM, Athar M, Al-Allaf FA, Taher MM, Khan W, Bouazzaoui A, Harbi NA, Safar R, Al-Edressi H, Anazi A, Altayeb N, Ahmed MA, Alansary K, Abduljaleel Z, Kratz A, Beguin P, Poulain S, Kaneko M, Takahiko C, Matsunaga A, Kato S, Suzuki AM, Bertin N, Lassmann T, Vigot R, Carninci P, Plessy C, Launey T, Graur D, Lee D, Kapoor A, Chakravarti A, Friis-Nielsen J, Izarzugaza JM, Brunak S, Chakraborty A, Basak J, Mukhopadhyay A, Soibam BS, Das D, Biswas N, Das S, Sarkar S, Maitra A, Panda C, Majumder P, Morsy H, Gaballah A, Samir M, Shamseya M, Mahrous H, Ghazal A, Arafat W, Hashish M, Gruber JJ, Jaeger N, Snyder M, Patel K, Bowman S, Davis T, Kraushaar D, Emerman A, Russello S, Henig N, Hendrickson C, Zhang K, Rodriguez-Dorantes M, Cruz-Hernandez CD, Garcia-Tobilla CDP, Solorzano-Rosales S, Jäger N, Chen J, Haile R, Hitchins M, Brooks JD, Snyder M, Jiménez-Morales S, Ramírez M, Nuñez J, Bekker V, Leal Y, Jiménez E, Medina A, Hidalgo A, Mejía J, Halytskiy V, Naggert J, Collin GB, DeMauro K, Hanusek R, Nishina PM, Belhassa K, Belhassan K, Bouguenouch L, Samri I, Sayel H, moufid FZ, El Bouchikhi I, Trhanint S, Hamdaoui H, Elotmani I, Khtiri I, Kettani O, Quibibo L, Ahagoud M, Abbassi M, Ouldim K, Marusin AV, Kornetov AN, Swarovskaya M, Vagaiceva K, Stepanov V, De La Paz EMC, Sy R, Nevado J, Reganit P, Santos L, Magno JD, Punzalan FE, Ona D, Llanes E, Santos-Cortes RL, Tiongco R, Aherrera J, Abrahan L, Pagauitan-Alan P, Morelli KH, Domire JS, Pyne N, Harper S, Burgess R, Zhalbinova M, Akilzhanova A, Rakhimova S, Bekbosynova M, Myrzakhmetova S, Gari MA, Dallol A, Alsehli H, Gari A, Gari M, Abuzenadah A, Thomas M, Sukhai M, Garg S, Misyura M, Zhang T, Schuh A, Stockley T, Kamel-Reid S, Sherry S, Xiao C, Slotta D, Rodarmer K, Feolo M, Kimelman M, Godynskiy G, O’Sullivan C, Yaschenko E, Xiao C, Yaschenko E, Sherry S, Rangel-Escareño C, Rueda-Zarate H, Tayubi IA, Mohammed R, Ahmed I, Ahmed T, Seth S, Amin S, Song X, Mao X, Sun H, Verhaak RG, Futreal A, Zhang J, Whiite SJ, Chiang T, English A, Farek J, Kahn Z, Salerno W, Veeraraghavan N, Boerwinkle E, Gibbs R, Kasukawa T, Lizio M, Harshbarger J, Hisashi S, Severin J, Imad A, Sahin S, Freeman TC, Baillie K, Sandelin A, Carninci P, Forrest ARR, Kawaji H, Salerno W, English A, Shekar SN, Mangubat A, Bruestle J, Boerwinkle E, Gibbs RA, Salem AH, Ali M, Ibrahim A, Ibrahim M, Barrera HA, Garza L, Torres JA, Barajas V, Ulloa-Aguirre A, Kershenobich D, Mortaji S, Guizar P, Loera E, Moreno K, De León A, Monsiváis D, Gómez J, Cardiel R, Fernandez-Lopez JC, Bonifaz-Peña V, Rangel-Escareño C, Hidalgo-Miranda A, Contreras AV, Polfus L, Wang X, Philip V, Carter G, Abuzenadah AA, Gari M, Turki R, Dallol A, Uyar A, Kaygun A, Zaman S, Marquez E, George J, Ucar D, Hendrickson CL, Emerman A, Kraushaar D, Bowman S, Henig N, Davis T, Russello S, Patel K, Starr DB, Baird M, Kirkpatrick B, Sheets K, Nitsche R, Prieto-Lafuente L, Landrum M, Lee J, Rubinstein W, Maglott D, Thavanati PKR, de Dios AE, Hernandez REN, Aldrate MEA, Mejia MRR, Kanala KRR, Abduljaleel Z, Khan W, Al-Allaf FA, Athar M, Taher MM, Shahzad N, Bouazzaoui A, Huber E, Dan A, Al-Allaf FA, Herr W, Sprotte G, Köstler J, Hiergeist A, Gessner A, Andreesen R, Holler E, Al-Allaf F, Alashwal A, Abduljaleel Z, Taher M, Bouazzaoui A, Abalkhail H, Al-Allaf A, Bamardadh R, Athar M, Filiptsova O, Kobets M, Kobets Y, Burlaka I, Timoshyna I, Filiptsova O, Kobets MN, Kobets Y, Burlaka I, Timoshyna I, Filiptsova O, Kobets MN, Kobets Y, Burlaka I, Timoshyna I, Al-allaf FA, Mohiuddin MT, Zainularifeen A, Mohammed A, Abalkhail H, Owaidah T, Bouazzaoui A. Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016. Hum Genomics 2016; 10 Suppl 1:12. [PMID: 27294413 PMCID: PMC4896275 DOI: 10.1186/s40246-016-0063-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s disease Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types C. A. Semple O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu O16 Modeling genetic interactions associated with molecular subtypes of breast cancer B. Ji, A. Tyler, G. Ananda, G. Carter O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski O18 Predictive biomarkers to metastatic pancreatic cancer treatment J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman O19 DDIT4 gene expression as a prognostic marker in several malignant tumors L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto O20 Spatial organization of the genome and genomic alterations in human cancers K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group O21 Landscape of targeted therapies in solid tumors S. Patterson, C. Statz, S. Mockus O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis S. Likhitrattanapisal O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4 C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13 K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle O32 Legal interoperability: a sine qua non for international data sharing A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes R. Ghosh, S. Plon O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker O40 A general statistic framework for genome-based disease risk prediction M. Xiong, L. Ma, N. Lin, C. Amos O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong O42 Big data and NGS data analysis: the cloud to the rescue O. Dobretsberger, M. Egger, F. Leimgruber O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data V. A. A. Antonio, N. Ono, Clark Kendrick C. Go O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans C. Zeng, J. Shao O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes? I. Campbell, M.-A. Young, P. James, Lifepool O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS C. Schumacher, S. Sandhu, T. Harkins, V. Makarov O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs O55 Rapid capture methods for clinical sequencing J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs O56 A diploid personal human genome model for better genomes from diverse sequence data K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs O57 Development of PacBio long range capture for detection of pathogenic structural variants Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers O59 Assessing RNA structure disruption induced by single-nucleotide variation J. Lin, Y. Zhang, Z. Ouyang P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility E. S. Chen P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients H. Bahrami, A. Khoshzaban, S. Heidari Keshal P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population K. K. R. Alharbi P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population M. Matar P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization N. Mili, R. Molinari, Y. Ma, S. Guerrier P9 Vulnerability of genetic variants to the risk of autism among Saudi children N. Elhawary, M. Tayeb, N. Bogari, N. Qotb P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7 mice Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome D. Graur P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns B. S. Soibam P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes J. J. Gruber, N. Jaeger, M. Snyder P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson P23 RNA sequencing identifies gene mutations for neuroblastoma K. Zhang P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales P25 Targeted Methylation Sequencing of Prostate Cancer N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía P28 Genetic modifiers of Alström syndrome J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess P34 Molecular regulation of chondrogenic human induced pluripotent stem cells M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid P36 Accessing genomic evidence for clinical variants at NCBI S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA C. Xiao, E. Yaschenko, S. Sherry P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling C. Rangel-Escareño, H. Rueda-Zarate P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium P43 Rapid and scalable typing of structural variants for disease cohorts W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu P49 Common variants in casr gene are associated with serum calcium levels in koreans S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions Y. Zhou, S. Xu P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies X. Wang, V. Philip, G. Carter P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar P54 Direct enrichment for the rapid preparation of targeted NGS libraries C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System R. Nitsche, L. Prieto-Lafuente P57 ClinVar: a multi-source archive for variant interpretation M. Landrum, J. Lee, W. Rubinstein, D. Maglott P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler P61 Compound heterozygous mutation in the LDLR gene in Saudi patients suffering severe hypercholesterolemia F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Athar
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Affiliation(s)
| | - Y. Wang
- School of Computing, Clemson University, Clemson, SC USA
| | - R. Huang
- Biochemical Genetics Laboratory, Greenwood Genetic Center, Greenwood, SC USA
| | - C. Skinner
- JCSRI, Greenwood Genetic Center, Greenwood, SC USA
| | - T. Thompson
- Biochemical Genetics Laboratory, Greenwood Genetic Center, Greenwood, SC USA
| | - L. Pollard
- Biochemical Genetics Laboratory, Greenwood Genetic Center, Greenwood, SC USA
| | - T. Wood
- Biochemical Genetics Laboratory, Greenwood Genetic Center, Greenwood, SC USA
| | - F. Luo
- School of Computing, Clemson University, Clemson, SC USA
| | - R. Stevenson
- JCSRI, Greenwood Genetic Center, Greenwood, SC USA
| | - R. Polimanti
- Department Psychiatry, Yale Sch Med and VA CT Healthcare Center, West Haven, CT USA
| | - J. Gelernter
- Department Psychiatry, Yale Sch Med and VA CT Healthcare Center, West Haven, CT USA
- Department Genetics, Yale Sch Med and VA CT Healthcare Center, West Haven, CT USA
- Department Neurobiology, Yale Sch Med and VA CT Healthcare Center, West Haven, CT USA
| | - X. Lin
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - I. Y. Lim
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - Y. Wu
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - A. L. Teh
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - L. Chen
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - I. M. Aris
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - S. E. Soh
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - M. T. Tint
- National University of Singapore, Singapore, Singapore
| | - J. L. MacIsaac
- University of British Columbia, Vancouver, British Columbia Canada
| | - F. Yap
- KK Women’s and Children’s Hospital, Singapore, Singapore
| | - K. Kwek
- KK Women’s and Children’s Hospital, Singapore, Singapore
| | - S. M. Saw
- National University of Singapore, Singapore, Singapore
| | - M. S. Kobor
- University of British Columbia, Vancouver, British Columbia Canada
| | - M. J. Meaney
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - K. M. Godfrey
- University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Y. S. Chong
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - J. D. Holbrook
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - Y. S. Lee
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - P. D. Gluckman
- Singapore Institute for Clinical Sciences, Singapore, Singapore
- University of Auckland, Auckland, New Zealand
| | - N. Karnani
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | | | - A. Kapoor
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - D. Lee
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - A. Chakravarti
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - C. Maercker
- Esslingen University of Applied Sciences, Esslingen, Germany
| | - F. Graf
- German Cancer Research Center, Heidelberg, Germany
| | - M. Boutros
- German Cancer Research Center, Heidelberg, Germany
| | - G. Stamoulis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - F. Santoni
- Geneva University Hospitals-HUG, Service of Genetic Medicine, Geneva, Switzerland
| | - P. Makrythanasis
- Geneva University Hospitals-HUG, Service of Genetic Medicine, Geneva, Switzerland
| | - A. Letourneau
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - M. Guipponi
- Geneva University Hospitals-HUG, Service of Genetic Medicine, Geneva, Switzerland
| | - N. Panousis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - M. Garieri
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - P. Ribaux
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - E. Falconnet
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - C. Borel
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - S. E. Antonarakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Geneva University Hospitals-HUG, Service of Genetic Medicine, Geneva, Switzerland
- iGE3 Institute of Genetics and Genomics of Geneva, University of Geneva Medical School, Geneva, Switzerland
| | - S. Kumar
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio-Grande Valley, Edinburg, TX USA
| | - J. Curran
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio-Grande Valley, Brownsville, TX USA
| | - J. Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio-Grande Valley, Brownsville, TX USA
| | - S. Chatterjee
- Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD USA
| | - A. Kapoor
- Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD USA
| | - J. Akiyama
- Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA
| | - D. Auer
- Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD USA
| | - C. Berrios
- Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD USA
| | - L. Pennacchio
- Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA
| | - A. Chakravarti
- Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD USA
| | - T. R. Donti
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - G. Cappuccio
- Department of Translational Medical Sciences, Federico II University, Naples, Italy
| | - M. Miller
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - P. Atwal
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | | | - A. Cardon
- Section of Pediatric Neurology and Neuroscience, Baylor College of Medicine, Houston, TX USA
| | - C. Bacino
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - L. Emrick
- Section of Pediatric Neurology and Neuroscience, Baylor College of Medicine, Houston, TX USA
| | | | - F. Baumer
- Stanford Medical School, Stanford, CA USA
| | - B. Porter
- Stanford Medical School, Stanford, CA USA
| | - M. Bainbridge
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - P. Bonnen
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - B. Graham
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - R. Sutton
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Q. Sun
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - S. Elsea
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Z. Hu
- School of Public Health, Houston Health Science Center, Houston, TX USA
| | - P. Wang
- University of Texas, Houston Health Science Center, Houston, TX USA
| | - Y. Zhu
- Tulane University, New Orleans, LO USA
| | - J. Zhao
- Tulane University, New Orleans, LO USA
| | - M. Xiong
- University of Texas, Houston Health Science Center, Houston, TX USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University, Chicago, IL USA
| | - A. Hidalgo-Miranda
- Cancer Genomics Laboratory, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico
| | - S. Romero-Cordoba
- Cancer Genomics Laboratory, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico
| | | | - R. Rebollar-Vega
- Cancer Genomics Laboratory, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico
| | | | - M. Iorio
- National Tumor Institute, Milan, Italy
| | | | - S. Baroni
- National Tumor Institute, Milan, Italy
| | - B. Kaczkowski
- Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan
| | - Y. Tanaka
- Preventive Medicine and Applied Genomics unit, RIKEN Advanced Center for Computing and Communication, Yokohama, Japan
| | - H. Kawaji
- Preventive Medicine and Applied Genomics unit, RIKEN Advanced Center for Computing and Communication, Yokohama, Japan
| | - A. Sandelin
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - R. Andersson
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - M. Itoh
- Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan
| | - T. Lassmann
- Telethon Kids Institute, The University of Western Australia, Perth, Australia
| | | | - Y. Hayashizaki
- RIKEN Preventive Medicine & Diagnosis Innovation Program, Wako, Japan
| | - P. Carninci
- Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan
| | - A. R. R. Forrest
- Harry Perkins Institute of Medical Research, The University of Western Australia, Nedlands, Australia
| | - C. A. Semple
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, Edinburgh, UK
| | | | | | | | - C. Gallego
- University of Michigan, Ann Arbor, MI USA
| | | | - A. Burt
- Univ of Washington, Seattle, WA USA
| | | | | | - C. Nefcy
- Univ of Washington, Seattle, WA USA
| | | | | | | | | | | | - J. Smith
- Univ of Washington, Seattle, WA USA
| | | | | | - R. Nassir
- University California, Davis, CA USA
| | | | | | - U. Peters
- Univ of Washington, Seattle, WA USA
- Fred Hutch, Seattle, WA USA
| | | | | | - F. Menghi
- The Jackson Laboratory, Farmington, CT USA
| | - K. Inaki
- The Jackson Laboratory, Farmington, CT USA
| | - X. Woo
- The Jackson Laboratory, Farmington, CT USA
| | - P. Kumar
- The Jackson Laboratory, Farmington, CT USA
| | - K. Grzeda
- The Jackson Laboratory, Farmington, CT USA
| | | | - H. Kim
- The Jackson Laboratory, Farmington, CT USA
| | - D. Ucar
- The Jackson Laboratory, Farmington, CT USA
| | | | | | - J. Keck
- The Jackson Laboratory, Sacramento, CA USA
| | - J. Chuang
- The Jackson Laboratory, Farmington, CT USA
| | - E. T. Liu
- The Jackson Laboratory, Farmington, CT USA
| | - B. Ji
- The Jackson Laboratory, Bar Harbor, ME USA
| | - A. Tyler
- The Jackson Laboratory, Bar Harbor, ME USA
| | - G. Ananda
- The Jackson Laboratory, Bar Harbor, ME USA
| | - G. Carter
- The Jackson Laboratory, Bar Harbor, ME USA
| | - H. Nikbakht
- Human Genetics, McGill University, Montreal, Quebec Canada
| | - M. Montagne
- Biochemistry, Sherbrooke University, Sherbrooke, Quebec Canada
| | - M. Zeinieh
- Human Genetics, McGill University, Montreal, Quebec Canada
| | - A. Harutyunyan
- Human Genetics, McGill University, Montreal, Quebec Canada
| | - M. Mcconechy
- Human Genetics, McGill University, Montreal, Quebec Canada
| | - N. Jabado
- Pediatrics, McGill University, Montreal, Quebec Canada
| | - P. Lavigne
- Biochemistry, Sherbrooke University, Sherbrooke, Quebec Canada
| | - J. Majewski
- Human Genetics, McGill University, Montreal, Quebec Canada
| | - J. B. Goldstein
- Genomic Medicine, MD Anderson Cancer Center, Houston, TX USA
| | - M. Overman
- Gastrointestinal Medical Oncology, MD Anderson Cancer Center, Houston, TX USA
| | - G. Varadhachary
- Gastrointestinal Medical Oncology, MD Anderson Cancer Center, Houston, TX USA
| | - R. Shroff
- Gastrointestinal Medical Oncology, MD Anderson Cancer Center, Houston, TX USA
| | - R. Wolff
- Gastrointestinal Medical Oncology, MD Anderson Cancer Center, Houston, TX USA
| | - M. Javle
- Gastrointestinal Medical Oncology, MD Anderson Cancer Center, Houston, TX USA
| | - A. Futreal
- Genomic Medicine, MD Anderson Cancer Center, Houston, TX USA
| | - D. Fogelman
- Gastrointestinal Medical Oncology, MD Anderson Cancer Center, Houston, TX USA
| | - L. Bravo
- Escuela de Medicina Humana, Universidad Privada San Juan Bautista, Lima, Peru
| | - W. Fajardo
- Escuela de Medicina Humana, Universidad Privada San Juan Bautista, Lima, Peru
| | - H. Gomez
- Unidad de Investigación Básica y Traslacional, Oncosalud-AUNA, Lima, Peru
| | - C. Castaneda
- Unidad de Investigación Básica y Traslacional, Oncosalud-AUNA, Lima, Peru
| | - C. Rolfo
- Oncology Department, University Hospital Antwerp, Antwerp, Belgium
| | - J. A. Pinto
- Unidad de Investigación Básica y Traslacional, Oncosalud-AUNA, Lima, Peru
| | - K. C. Akdemir
- Genomic Medicine, MD Anderson Cancer Center, Houston, TX USA
| | - L. Chin
- University of Texas System, Houston, TX USA
| | - A. Futreal
- Genomic Medicine, MD Anderson Cancer Center, Houston, TX USA
| | | | - S. Patterson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - C. Statz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - S. Mockus
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - S. N. Nikolaev
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| | - X. I. Bonilla
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| | - L. Parmentier
- Department of Dermatology, Hospital of Valais, Sion, Switzerland
| | - B. King
- Department of Pathology, NYU School of Medicine, New York, NY USA
| | - F. Bezrukov
- Department of Physics, University of Connecticut, Connecticut, USA
| | - G. Kaya
- Department of Dermatology, University Hospitals of Geneva, Geneva, Switzerland
| | - V. Zoete
- Swiss Institute of Bioinformatics, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - V. Seplyarskiy
- Institute of Information Transmission Problems, Russian Academy of Sciences, Moscow, Russian Federation
| | - H. Sharpe
- Department of Molecular Oncology, Genentech Inc, San Francisco, CA USA
| | - T. McKee
- Service of Clinical Pathology, University Hospitals of Geneva, Geneva, Switzerland
| | - A. Letourneau
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - P. Ribaux
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - K. Popadin
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | | | - R. Ben Chaabene
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - F. Santoni
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - M. Andrianova
- Institute of Information Transmission Problems, Russian Academy of Sciences, Moscow, Russian Federation
| | - M. Guipponi
- Service of Genetic Medicine, University Hospitals of Geneva, Geneva, Switzerland
| | - M. Garieri
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - C. Verdan
- Service of Clinical Pathology, University Hospitals of Geneva, Geneva, Switzerland
| | - K. Grosdemange
- Department of Dermatology, University Hospitals of Geneva, Geneva, Switzerland
| | - O. Sumara
- Department of Biochemistry and Molecular Biology, University of Würzburg, Würzburg, Germany
| | - M. Eilers
- Department of Biochemistry and Molecular Biology, University of Würzburg, Würzburg, Germany
| | - I. Aifantis
- Department of Pathology, NYU School of Medicine, New York, NY USA
| | - O. Michielin
- Swiss Institute of Bioinformatics, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - F. de Sauvage
- Department of Molecular Oncology, Genentech Inc, San Francisco, CA USA
| | - S. Antonarakis
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland
| | | | | | - A. Kurian
- Stanford Medical Center, Palo Alto, CA USA
| | - A. Desmond
- Massachusetts General Hospital, Boston, MA USA
| | - S. Yang
- Invitae, San Francisco, CA USA
| | | | - J. Ford
- Stanford Medical Center, San Francisco, CA USA
| | - L. Ellisen
- Massachusetts General Hospital, Boston, MA USA
| | - T. L. Peters
- Pathology & Immunology, Baylor College of Medicine, Houston, TX USA
| | - K. R. Alvarez
- Pathology, Texas Children’s Hospital, Houston, TX USA
| | | | - D. H. Lopez-Terrada
- Pathology & Immunology, Baylor College of Medicine, Houston, TX USA
- Pathology, Texas Children’s Hospital, Houston, TX USA
| | - A. Hastie
- BioNano Genomics, Inc, San Diego, CA USA
| | - Z. Dzakula
- BioNano Genomics, Inc, San Diego, CA USA
| | - A. W. Pang
- BioNano Genomics, Inc, San Diego, CA USA
| | - E. T. Lam
- BioNano Genomics, Inc, San Diego, CA USA
| | | | | | - H. Cao
- BioNano Genomics, Inc, San Diego, CA USA
| | | | - C. Gonzaga-Jauregui
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York, NY USA
| | - L. Ma
- Department of Pediatrics, New York, NY USA
| | - A. King
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York, NY USA
| | - E. Berman Rosenzweig
- Department of Pediatrics, New York, NY USA
- Department of Medicine, Columbia University Medical Center, New York, NY USA
| | | | - J. G. Reid
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York, NY USA
| | - J. D. Overton
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York, NY USA
| | - F. Dewey
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, New York, NY USA
| | - W. K. Chung
- Department of Pediatrics, New York, NY USA
- Department of Medicine, Columbia University Medical Center, New York, NY USA
| | - K. Small
- Molecular Insight Research Foundation, Glendale, ᅟ
| | - A. DeLuca
- Ophthalmology, University of Iowa, Iowa City, IA USA
| | - F. Cremers
- Biology, Raboud University Medical Center, Nijmegen, Netherlands
| | - R. A. Lewis
- Ophthalmology, Baylor College of Medicine, Houston, TX USA
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- Service d’Exploration de la vision et Neuro-ophtalmologie CHRU, Service d’Exploration de la vision et Neuro-ophtalmologie CHRU, Lille, France
| | - B. Bakall
- Associated Retina Consultants, University of Arizona College of Medicine, Phoenix, TX USA
| | | | | | - M. Leys
- WVU Eye Institute, Morgantown, WV USA
| | - F. S. Shaya
- Molecular Insight Research Foundation, Glendale, ᅟ
| | - E. Stone
- University of Iowa, Iowa City, IA USA
| | - N. L. Sobreira
- Johns Hopkins University School of Medicine, Baltimore, MD USA
| | | | - H. Ling
- Center for Inherited Disease Research, JHUSOM, Baltimore, MD USA
| | - E. Pugh
- Center for Inherited Disease Research, JHUSOM, Baltimore, MD USA
| | - D. Witmer
- Center for Inherited Disease Research, JHUSOM, Baltimore, MD USA
| | - K. Hetrick
- Center for Inherited Disease Research, JHUSOM, Baltimore, MD USA
| | - P. Zhang
- Center for Inherited Disease Research, JHUSOM, Baltimore, MD USA
| | - K. Doheny
- Center for Inherited Disease Research, JHUSOM, Baltimore, MD USA
| | - D. Valle
- Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - A. Hamosh
- Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - S. N. Jhangiani
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Z. Coban Akdemir
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - M. N. Bainbridge
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - W. Charng
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - W. Wiszniewski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - T. Gambin
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - E. Karaca
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Y. Bayram
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - M. K. Eldomery
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - J. Posey
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - H. Doddapaneni
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - J. Hu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - V. R. Sutton
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - D. M. Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - E. A. Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - D. Valle
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD USA
| | - J. R. Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - R. A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | | | - W. Salerno
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - A. English
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | | | | | - A. Thorogood
- Centre of Genomics and Policy, McGill University, Montreal, Quebec Canada
| | - B. M. Knoppers
- Centre of Genomics and Policy, McGill University, Montreal, Quebec Canada
| | | | - H. Takahashi
- Center for Life Science Technologies, Division of Genomic Technologies, RIKEN, Yokohama, Japan
| | - K. R. Nitta
- Center for Life Science Technologies, Division of Genomic Technologies, RIKEN, Yokohama, Japan
| | - A. Kozhuharova
- Center for Life Science Technologies, Division of Genomic Technologies, RIKEN, Yokohama, Japan
| | - A. M. Suzuki
- Center for Life Science Technologies, Division of Genomic Technologies, RIKEN, Yokohama, Japan
| | - H. Sharma
- Center for Life Science Technologies, Division of Genomic Technologies, RIKEN, Yokohama, Japan
| | - D. Cotella
- Dipartimento di Scienze della Salute, Universita’ del Piemonte Orientale, Novara, Italy
| | - C. Santoro
- Dipartimento di Scienze della Salute, Universita’ del Piemonte Orientale, Novara, Italy
| | - S. Zucchelli
- Area of Neuroscience, SISSA, International School for Advanced Studies, Trieste, Italy
| | - S. Gustincich
- Area of Neuroscience, SISSA, International School for Advanced Studies, Trieste, Italy
| | - P. Carninci
- Center for Life Science Technologies, Division of Genomic Technologies, RIKEN, Yokohama, Japan
| | - J. J. Mulvihill
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD USA
| | - G. Baynam
- Office of Population Health, Department of Health, Perth, Australia
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- Undiagnosed Diseases Program, National Human Genome Research Institute, Bethesda, MD USA
| | - S. C. Groft
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD USA
| | - K. Kosaki
- Center for Medical Genetics, Keio University School of Medicine, Tokyo, Japan
| | - P. Lasko
- Department of Biology, McGill University, Montreal, Quebec Canada
| | - B. Melegh
- Department of Medical Genetics, University of Pecs, Pecs, Hungary
| | - D. Taruscio
- National Center for Rare Diseases, Istituto Superiore di Sanita, Rome, Italy
| | - R. Ghosh
- Pediatrics-Oncology, Baylor College of Medicine, Houston, TX USA
| | - S. Plon
- Pediatrics-Oncology, Baylor College of Medicine, Houston, TX USA
| | - S. Scherer
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - X. Qin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - R. Sanghvi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - K. Walker
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - T. Chiang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - D. Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - L. Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, NY USA
| | - J. Black
- Department of Psychiatry, Mayo Clinic, Rochester, NY USA
| | - E. Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | | | - R. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | | | | | - K. Wani
- MD Anderson Cancer Center, Houston, USA
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- MD Anderson Cancer Center, Houston, USA
| | - C. Creasy
- MD Anderson Cancer Center, Houston, USA
| | | | - M. Forget
- MD Anderson Cancer Center, Houston, USA
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- MD Anderson Cancer Center, Houston, USA
| | - J. Roszik
- MD Anderson Cancer Center, Houston, USA
| | - J. Wargo
- MD Anderson Cancer Center, Houston, USA
| | - L. Haydu
- MD Anderson Cancer Center, Houston, USA
| | - X. Song
- MD Anderson Cancer Center, Houston, USA
| | - A. Lazar
- MD Anderson Cancer Center, Houston, USA
| | | | - M. Davies
- MD Anderson Cancer Center, Houston, USA
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- MD Anderson Cancer Center, Houston, USA
| | | | | | | | | | | | | | | | | | - M. Xiong
- University of Texas School of Public Health, Houston, TX USA
| | - L. Ma
- University of Texas School of Public Health, Houston, TX USA
| | - N. Lin
- University of Texas School of Public Health, Houston, TX USA
| | - C. Amos
- Geisel School of Medicine at Dartmouth, Hanover, NH USA
| | - N. Lin
- Biostatistics, University of Texas Health Science Center at Houston, Houston, TX USA
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- Biostatistics, University of Texas Health Science Center at Houston, Houston, TX USA
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- Tulane University, New Orleans, LO USA
| | - J. Zhao
- Tulane University, New Orleans, LO USA
| | - V. Calhoun
- University of New Mexico, Albuquerque, NM USA
| | - M. Xiong
- University of Texas Health Science Center at Houston, Houston, TX USA
| | | | - M. Egger
- EPS Software Corp, Spring, TX USA
| | | | - S. Sadedin
- Bioinformatics, Murdoch Childrens Research Institute, Parkville, Australia
| | - A. Oshlack
- Bioinformatics, Murdoch Childrens Research Institute, Parkville, Australia
| | | | - V. A. A. Antonio
- Computational Systems Biology Laboratory, Nara Institute of Science and Technology, Ikoma-cho, Japan
| | - N. Ono
- Computational Systems Biology Laboratory, Nara Institute of Science and Technology, Ikoma-cho, Japan
| | | | - Z. Ahmed
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - M. Bolisetty
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - S. Zeeshan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - E. Anguiano
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - D. Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - A. Sarkar
- Laboratory of Genomics and Profiling Applications, Centre for DNA Fingerprinting and Diagnostics, Hyderabad, India
| | - M. R. Nandineni
- Laboratory of Genomics and Profiling Applications, Centre for DNA Fingerprinting and Diagnostics, Hyderabad, India
| | - C. Zeng
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - J. Shao
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - H. Cao
- BioNano Genomics, Inc, San Diego, CA USA
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- BioNano Genomics, Inc, San Diego, CA USA
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- BioNano Genomics, Inc, San Diego, CA USA
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- BioNano Genomics, Inc, San Diego, CA USA
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- BioNano Genomics, Inc, San Diego, CA USA
| | - K. Pham
- BioNano Genomics, Inc, San Diego, CA USA
| | | | - Z. Dzakula
- BioNano Genomics, Inc, San Diego, CA USA
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- Biotechnology Research Institute, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia
| | - L. Dongsheng
- Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences Shanghai, Shanghai, China
| | - W. Lai-Ping
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - D. Lian
- Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences Shanghai, Shanghai, China
| | - R. O. Twee Hee
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Y. Yunus
- Institute of Medical Molecular Biotechnology, Universiti Teknologi MARA, Sungai Buloh, ᅟ
| | - F. Aghakhanian
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Sunway Campus, Petaling Jaya, Malaysia
| | - S. S. Mokhtar
- Institute of Medical Molecular Biotechnology, Universiti Teknologi MARA, Sungai Buloh, ᅟ
| | - C. V. Lok-Yung
- Biotechnology Research Institute, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia
| | - J. Bhak
- Personal Genomics Institute, Genome Research Foundation, Suwon, Republic Of Korea
| | - M. Phipps
- Jeffrey Cheah School of Medicine and Health Sciences, Monash University Sunway Campu, Petaling Jaya, Malaysia
| | - X. Shuhua
- Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences Shanghai, Shanghai, China
| | - T. Yik-Ying
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - V. Kumar
- Biotechnology Research Institute, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia
| | - H. Boon-Peng
- UCSI University, Kuala Lumpur, Kuala Lumpur, Malaysia
| | - I. Campbell
- Research Division, Peter Maccallum Cancer Centre, East Melbourne, Australia
| | - M. -A. Young
- Familial Cancer Centre, Peter Maccallum Cancer Centre, East Melbourne, Australia
| | - P. James
- Familial Cancer Centre, Peter Maccallum Cancer Centre, East Melbourne, Australia
| | | | - M. Rain
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - G. Mohammad
- Department of Medicine, Sonam Norbu Memorial Hospital, Leh, Ladakh India
| | - R. Kukreti
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Q. Pasha
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - A. R. Akilzhanova
- Nazarbayev University, National Laboratory Astana, Center for Life Sciences, Astana, Kazakhstan
| | - C. Guelly
- Center of Medical Research, Medical University of Graz, Graz, Austria
| | - Z. Abilova
- Nazarbayev University, National Laboratory Astana, Center for Life Sciences, Astana, Kazakhstan
| | - S. Rakhimova
- Nazarbayev University, National Laboratory Astana, Center for Life Sciences, Astana, Kazakhstan
| | - A. Akhmetova
- Nazarbayev University, National Laboratory Astana, Center for Life Sciences, Astana, Kazakhstan
| | - U. Kairov
- Nazarbayev University, National Laboratory Astana, Center for Life Sciences, Astana, Kazakhstan
| | - S. Trajanoski
- Center of Medical Research, Medical University of Graz, Graz, Austria
| | - Z. Zhumadilov
- Nazarbayev University, National Laboratory Astana, Center for Life Sciences, Astana, Kazakhstan
| | - M. Bekbossynova
- National Scientific Cardiac Surgery Center, Astana, Kazakhstan
| | | | - S. Sandhu
- Swift Biosciences Inc, Ann Arbor, MI USA
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- Swift Biosciences Inc, Ann Arbor, MI USA
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- Swift Biosciences Inc, Ann Arbor, MI USA
| | - H. Doddapaneni
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - R. Glenn
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Z. Momin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - B. Dilrukshi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - H. Chao
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Q. Meng
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - B. Gudenkauf
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - R. Kshitij
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - J. Jayaseelan
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - C. Nessner
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - S. Lee
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - K. Blankenberg
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - L. Lewis
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - J. Hu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Y. Han
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - H. Dinh
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - S. Jireh
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - K. Walker
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - E. Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - D. Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - R. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - J. Hu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - K. Walker
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - C. Buhay
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - X. Liu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Q. Wang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - R. Sanghvi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - H. Doddapaneni
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Y. Ding
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - N. Veeraraghavan
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - Y. Yang
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - E. Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX USA
| | - A. L. Beaudet
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - C. M. Eng
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - D. M. Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - R. A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - K. C. C. Worley
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Y. Liu
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - D. S. T. Hughes
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - S. C. Murali
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - R. A. Harris
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - A. C. English
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - X. Qin
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - O. A. Hampton
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - P. Larsen
- Department of Biology, Duke University, Durham, NC USA
| | - C. Beck
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Y. Han
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - M. Wang
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - H. Doddapaneni
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - C. L. Kovar
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - W. J. Salerno
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - A. Yoder
- Department of Biology, Duke University, Durham, NC USA
| | - S. Richards
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - J. Rogers
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - J. R. Lupski
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - D. M. Muzny
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - R. A. Gibbs
- Human Genome Sequencing Center, Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Q. Meng
- HGSC, Baylor College of Medicine, Houston, TX USA
| | | | - M. Wang
- HGSC, Baylor College of Medicine, Houston, TX USA
| | | | - Y. Han
- HGSC, Baylor College of Medicine, Houston, TX USA
| | - D. Muzny
- HGSC, Baylor College of Medicine, Houston, TX USA
| | - R. Gibbs
- HGSC, Baylor College of Medicine, Houston, TX USA
| | - R. A. Harris
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - M. Raveenedran
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - C. Xue
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - M. Dahdouli
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - L. Cox
- Genetics, Southwest National Primate Research Center, San Antonio, TX USA
| | - G. Fan
- Human Genetics, Univeristy of California Los Angeles, Los Angeles, CA USA
| | - B. Ferguson
- Division of Neuroscience, Oregon National Primate Research Center, Beaverton, OR USA
| | - J. Hovarth
- Genomics & Microbiology Research Laboratory, NC Museum of Natural Sciences, Raleigh, NC USA
| | - Z. Johnson
- Yerkes Nonhuman Primate Genomics Core, Yerkes National Primate Research Center, Atlanta, GA USA
| | - S. Kanthaswamy
- Environmental Toxicology, California National Primate Research Center, Davis, CA USA
| | - M. Kubisch
- Physiology, Tulane National Primate Research Center, New Orleans, LO USA
| | - M. Platt
- Neuroscience, University of Pennsylvania, Philadelphia, PA USA
| | - D. Smith
- Anthropology, University of California Davis, Davis, CA USA
| | - E. Vallender
- Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS USA
| | - R. Wiseman
- Genetics, Wisconsin National Primate Research Center, Madison, WI USA
| | - X. Liu
- Epidemiology, Human Genetics & Environmental Sciences, ᅟ, ᅟ
| | - J. Below
- Epidemiology and Disease Control Human Genetics Center, University of Texas Health Science Center, Houston, TX USA
| | - D. Muzny
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - R. Gibbs
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - F. Yu
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - J. Rogers
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX USA
| | - J. Lin
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - Y. Zhang
- Department of Statistics, University of Connecticut, Storrs, CT USA
| | - Z. Ouyang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT USA
| | - A. Moore
- National Cancer Institute, Rockville, USA
| | - Z. Wang
- St. Jude Children’s Research Hospital, Memphis, USA
| | - J. Hofmann
- National Cancer Institute, NIH, DHHS, Rockville, USA
| | - M. Purdue
- National Cancer Institute, Rockville, USA
| | | | | | - D. Albanes
- National Cancer Institute, Rockville, USA
| | - C. S. Liu
- Changhua Christian Hospital, Changhua, Taiwan Province of China
| | - W. L. Cheng
- Changhua Christian Hospital, Changhua, Taiwan Province of China
| | - T. T. Lin
- Changhua Christian Hospital, Changhua, Taiwan Province of China
| | - Q. Lan
- National Cancer Institute, Rockville, USA
| | - N. Rothman
- National Cancer Institute, Rockville, USA
| | - S. Berndt
- National Cancer Institute, Rockville, USA
| | - E. S. Chen
- Biochemistry, National University of Singapore, Singapore, Singapore
| | - H. Bahrami
- Proteomics, Faraby Eye Hospital, Tehran, Iran Islamic Republic Of
- R & D, MIB Co., Tehran, Iran Islamic Republic Of
| | | | | | - H. Bahrami
- Proteomics, Faraby Eye Hospital, Tehran, Iran Islamic Republic Of
- R & D, MIB Co., Tehran, Iran Islamic Republic Of
| | | | | | - K. K. R. Alharbi
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - M. Zhalbinova
- Laboratory of Genomic and Personalized Medicine, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, ᅟ, Kazakhstan
| | - A. Akilzhanova
- Laboratory of Genomic and Personalized Medicine, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, ᅟ, Kazakhstan
| | - S. Rakhimova
- Laboratory of Genomic and Personalized Medicine, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, ᅟ, Kazakhstan
| | - M. Bekbosynova
- Cardiology, JSC “National Research Cardiac Surgery Center”, National medical holding, Astana, Kazakhstan
| | - S. Myrzakhmetova
- Cardiology, JSC “National Research Cardiac Surgery Center”, National medical holding, Astana, Kazakhstan
| | - M. Matar
- UAE Genetic Diseases Association, Dubai, United Arab Emirates
| | - N. Mili
- Research Center for Statistics, University of Geneva, Switzerland, Geneva Switzerland
| | - R. Molinari
- Research Center for Statistics, University of Geneva, Switzerland, Geneva Switzerland
| | - Y. Ma
- Department of Statistics, University of South Carolina, Columbia, USA
| | - S. Guerrier
- Department of Statistics, University of Illinois at Urbana Champaign, Champaign, USA
| | - N. Elhawary
- Department of Molecular Genetics, Medical Genetics Center, Ain Shams University, Cairo, Egypt
- Department of Medical Genetics, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - M. Tayeb
- Department of Medical Genetics, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - N. Bogari
- Department of Medical Genetics, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - N. Qotb
- Department of Psychology, Umm Al-Qura University, Faculty of Education, Mecca, Saudi Arabia
| | - S. A. McClymont
- Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, USA
| | - P. W. Hook
- Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, USA
| | - L. A. Goff
- Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, USA
| | - A. McCallion
- Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, USA
| | - Y. Kong
- The Jackson Laboratory, Bar Harbor, USA
- Graduate School of Biomedical Science and Engineering, University of Maine, Orono, USA
| | | | | | | | - L. Zhao
- The Jackson Laboratory, Bar Harbor, USA
| | - P. M. Nishina
- The Jackson Laboratory, Bar Harbor, USA
- Graduate School of Biomedical Science and Engineering, University of Maine, Orono, USA
| | - B. M. Edrees
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - M. Athar
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - F. A. Al-Allaf
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - M. M. Taher
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - W. Khan
- Department of Basic Sciences, College of Science and Health Professions, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - A. Bouazzaoui
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - N. A. Harbi
- Department of Pediatric, King Faisal Specialist Hospital and Research Centre, Jeddah, Saudi Arabia
| | - R. Safar
- Department of Pediatric, Madinah Maternity and Children’s Hospital, Madinah, Saudi Arabia
| | - H. Al-Edressi
- Department of Pediatric, Madinah Maternity and Children’s Hospital, Madinah, Saudi Arabia
| | - A. Anazi
- Pediatric, King Fahad Medical City, Riyadh, Saudi Arabia
| | - N. Altayeb
- Molecular Diagnostics Unit, Department of Laboratory and Blood Bank, King Abdullah Medical City, Makkah, Saudi Arabia
| | - M. A. Ahmed
- Medical Genetics, King Salman Armed Forces Hospital, Tabuk, Saudi Arabia
| | - K. Alansary
- Medical Genetics, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Z. Abduljaleel
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - A. Kratz
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - P. Beguin
- Brain Science Institute (BSI), Launey Research Unit, RIKEN Wako, Wako, Japan
| | - S. Poulain
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - M. Kaneko
- Brain Science Institute (BSI), Launey Research Unit, RIKEN Wako, Wako, Japan
| | - C. Takahiko
- Brain Science Institute (BSI), Launey Research Unit, RIKEN Wako, Wako, Japan
| | - A. Matsunaga
- Brain Science Institute (BSI), Launey Research Unit, RIKEN Wako, Wako, Japan
| | - S. Kato
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - A. M. Suzuki
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - N. Bertin
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - T. Lassmann
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - R. Vigot
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - P. Carninci
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - C. Plessy
- Center for Life Science Technologies, RIKEN Yokohama, Yokohama City, Kanagawa Japan
| | - T. Launey
- Brain Science Institute (BSI), Launey Research Unit, RIKEN Wako, Wako, Japan
| | - D. Graur
- Biology and Biochemistry, University of Houston, Houston, USA
| | - D. Lee
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USA
| | - A. Kapoor
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USA
| | - A. Chakravarti
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, USA
| | - J. Friis-Nielsen
- Technical University of Denmark, Center for Biological Sequence Analysis, Lyngby, Denmark
| | - J. M. Izarzugaza
- Technical University of Denmark, Center for Biological Sequence Analysis, Lyngby, Denmark
| | - S. Brunak
- Technical University of Denmark, Center for Biological Sequence Analysis, Lyngby, Denmark
| | - A. Chakraborty
- Molecular Biology, Netaji Subhas Chandra Bose Cancer Research Institute, Kolkata, India
| | - J. Basak
- Molecular Biology, Netaji Subhas Chandra Bose Cancer Research Institute, Kolkata, India
| | - A. Mukhopadhyay
- Medical Oncology, Netaji Subhas Chandra Bose Cancer Research Institute, Kolkata, India
| | | | - D. Das
- National Institute of Biomedical Genomics, Kalyani, India
| | - N. Biswas
- National Institute of Biomedical Genomics, Kalyani, India
| | - S. Das
- National Institute of Biomedical Genomics, Kalyani, India
| | - S. Sarkar
- Chittaranjan National Cancer Institute, Kolkata, India
| | - A. Maitra
- National Institute of Biomedical Genomics, Kalyani, India
| | - C. Panda
- Chittaranjan National Cancer Institute, Kolkata, India
| | - P. Majumder
- National Institute of Biomedical Genomics, Kalyani, India
| | - H. Morsy
- Human Genetics, Faculty of Medicine, Alexandria, Egypt
| | - A. Gaballah
- Microbiology, Faculty of Medicine, Alexandria, Egypt
| | - M. Samir
- Clinical and Experimental Surgery, Faculty of Medicine, Alexandria, Egypt
| | - M. Shamseya
- Clinical and Experimental Internal Medicine, Medical Research Institute, Faculty of Medicine, Alexandria, Egypt
| | - H. Mahrous
- Human Genetics, Faculty of Medicine, Alexandria, Egypt
| | - A. Ghazal
- Microbiology, Faculty of Medicine, Alexandria, Egypt
| | - W. Arafat
- Clinical Oncology and Nuclear Medicine, Faculty of Medicine, Alexandria, Egypt
| | - M. Hashish
- Human Genetics, Faculty of Medicine, Alexandria, Egypt
| | | | - N. Jaeger
- Genetics, Stanford University, Palo Alto, USA
| | - M. Snyder
- Genetics, Stanford University, Palo Alto, USA
| | | | | | - T. Davis
- New England Biolabs, Ipswich, USA
| | | | | | | | | | | | - K. Zhang
- Pathology, University of North Dakota, Grand Forks, USA
| | | | | | | | | | - N. Jäger
- Genetics, Stanford University, Palo Alto, USA
| | - J. Chen
- Genetics, Stanford University, Palo Alto, USA
| | - R. Haile
- Stanford Cancer Institute, Stanford University, Palo Alto, USA
| | - M. Hitchins
- Stanford Cancer Institute, Stanford University, Palo Alto, USA
| | | | - M. Snyder
- Genetics, Stanford University, Palo Alto, USA
| | - S. Jiménez-Morales
- Cancer Genomic Laboratory, National Institute of Genomic Medicine (INMEGEN), ᅟ, Mexico
| | - M. Ramírez
- Biología, FES -Iztacala, UNAM, ᅟ, Mexico
| | - J. Nuñez
- Hospital de Pediatría, CMN SXXI, IMSS, ᅟ, Mexico
| | - V. Bekker
- Investigación Médica en Inmunología, CMN La Raza, IMSS, ᅟ, Mexico
| | - Y. Leal
- Diagnóstico Molecular H1N1-Influenza , UMAE-IMSS, Mérida, Yucatán Mexico
| | - E. Jiménez
- Hematología Pediátrica, CMN La Raza, IMSS, ᅟ, Mexico
| | - A. Medina
- Hemato-Oncología, Hospital Infantil de México, ᅟ, Mexico
| | - A. Hidalgo
- Cancer Genomics Laboratory, INMEGEN, ᅟ, Mexico
| | - J. Mejía
- Coordinación de Investigación en Salud, IMSS, ᅟ, Mexico
| | - V. Halytskiy
- Molecular Immunology Department, Palladin Institute of Biochemistry of the National Academy of Sciences of Ukraine, Kiev, Ukraine
| | | | | | | | | | | | - K. Belhassa
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - K. Belhassan
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - L. Bouguenouch
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - I. Samri
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - H. Sayel
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - FZ. moufid
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - I. El Bouchikhi
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - S. Trhanint
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - H. Hamdaoui
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - I. Elotmani
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - I. Khtiri
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - O. Kettani
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - L. Quibibo
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - M. Ahagoud
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - M. Abbassi
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - K. Ouldim
- Department of Medical Genetics and Oncogene, Morocco; Medical Genetics, CHU Hassan II Fes, Fes, Morocco
| | - A. V. Marusin
- Evolutionary Genetics, Institute of Medical Genetics, ᅟ, Russian Federation
| | - A. N. Kornetov
- Siberian State Medical University, Tomsk, Russian Federation
| | - M. Swarovskaya
- Evolutionary Genetics, Institute of Medical Genetics, ᅟ, Russian Federation
| | - K. Vagaiceva
- Evolutionary Genetics, Institute of Medical Genetics, ᅟ, Russian Federation
| | - V. Stepanov
- Evolutionary Genetics, Institute of Medical Genetics, ᅟ, Russian Federation
| | - E. M. Cutiongco De La Paz
- National Institutes of Health, University of the Philippines, Manila, Philippines
- Philippine Genome Center, University of the Philippines, Quezon City, Philippines
| | - R. Sy
- College of Medicine, University of the Philippines, Manila, Philippines
| | - J. Nevado
- National Institutes of Health, University of the Philippines, Manila, Philippines
| | - P. Reganit
- College of Medicine, University of the Philippines, Manila, Philippines
| | - L. Santos
- College of Medicine, University of the Philippines, Manila, Philippines
| | - J. D. Magno
- College of Medicine, University of the Philippines, Manila, Philippines
| | - F. E. Punzalan
- College of Medicine, University of the Philippines, Manila, Philippines
| | - D. Ona
- College of Medicine, University of the Philippines, Manila, Philippines
| | - E. Llanes
- College of Medicine, University of the Philippines, Manila, Philippines
| | - R. L. Santos-Cortes
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX United States
| | - R. Tiongco
- College of Medicine, University of the Philippines, Manila, Philippines
| | - J. Aherrera
- Philippine General Hospital, University of the Philippines, Manila, Philippines
| | - L. Abrahan
- Philippine General Hospital, University of the Philippines, Manila, Philippines
| | - P. Pagauitan-Alan
- Philippine General Hospital, University of the Philippines, Manila, Philippines
| | | | - K. H. Morelli
- The Jackson Laboratory, Bar Harbor, USA
- Graduate School of Biomedical Sciences & Engineering, The University of Maine, Orono, USA
| | - J. S. Domire
- Center For Gene Therapy, The Research Institute at Nationwide Children’s Hospital, Columbus, Ohio USA
| | - N. Pyne
- Center For Gene Therapy, The Research Institute at Nationwide Children’s Hospital, Columbus, Ohio USA
| | - S. Harper
- Center For Gene Therapy, The Research Institute at Nationwide Children’s Hospital, Columbus, Ohio USA
| | - R. Burgess
- Graduate School of Biomedical Sciences & Engineering, The University of Maine, Orono, USA
| | - M. Zhalbinova
- Laboratory of Genomic and Personalized Medicine, National Laboratory Astana, Nazarbayev University, ᅟ, Kazakhstan
| | - A. Akilzhanova
- Laboratory of Genomic and Personalized Medicine, National Laboratory Astana, Nazarbayev University, ᅟ, Kazakhstan
| | - S. Rakhimova
- Laboratory of Genomic and Personalized Medicine, National Laboratory Astana, Nazarbayev University, ᅟ, Kazakhstan
| | - M. Bekbosynova
- Cardiology, JSC “National Research Cardiac Surgery Center”, National Medical Holding, Astana, Kazakhstan
| | - S. Myrzakhmetova
- Cardiology, JSC “National Research Cardiac Surgery Center”, National Medical Holding, Astana, Kazakhstan
| | - M. A. Gari
- Medical Laboratory Technology, ᅟ, Saudi Arabia
| | - A. Dallol
- Center of Innovation in Personalized Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - H. Alsehli
- Center of Innovation in Personalized Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - A. Gari
- Center of Innovation in Personalized Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - M. Gari
- Center of Innovation in Personalized Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - A. Abuzenadah
- Center of Innovation in Personalized Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - M. Thomas
- Advanced Molecular Diagnostics Laboratory, ᅟ, Canada
| | - M. Sukhai
- Advanced Molecular Diagnostics Laboratory, ᅟ, Canada
| | - S. Garg
- Advanced Molecular Diagnostics Laboratory, ᅟ, Canada
| | - M. Misyura
- Advanced Molecular Diagnostics Laboratory, ᅟ, Canada
| | - T. Zhang
- Advanced Molecular Diagnostics Laboratory, ᅟ, Canada
| | - A. Schuh
- Princess Margaret Cancer Centre, Toronto, Canada
| | - T. Stockley
- Advanced Molecular Diagnostics Laboratory, ᅟ, Canada
| | - S. Kamel-Reid
- Advanced Molecular Diagnostics Laboratory, ᅟ, Canada
| | | | | | | | | | | | | | | | | | | | - C. Xiao
- National Institutes of Health, Bethesda, USA
| | | | - S. Sherry
- National Institutes of Health, Bethesda, USA
| | - C. Rangel-Escareño
- Computational Genomics, National Institute of Genomic Medicine, Mexico City, Mexico
| | - H. Rueda-Zarate
- Computational Genomics, National Institute of Genomic Medicine, Mexico City, Mexico
| | - I. A. Tayubi
- Computer Science, Faculty of Computing and Information Technology, King AbdulAziz University, Rabigh, Saudi Arabia
| | - R. Mohammed
- Computer Science, Faculty of Computing and Information Technology, King AbdulAziz University, Rabigh, Saudi Arabia
| | | | - I. Ahmed
- Computer Science, Faculty of Computing and Information Technology, King AbdulAziz University, Rabigh, Saudi Arabia
| | - T. Ahmed
- Computer Science, Faculty of Computing and Information Technology, King AbdulAziz University, Rabigh, Saudi Arabia
| | - S. Seth
- Institute of Applied Cancer Science, ᅟ, USA
| | - S. Amin
- Genomic Medicine, University of Texas, ᅟ, ᅟ
| | - X. Song
- Institute of Applied Cancer Science, ᅟ, USA
| | - X. Mao
- Genomic Medicine, University of Texas, ᅟ, ᅟ
| | - H. Sun
- MD Anderson Cancer Center, Houston, USA
| | | | - A. Futreal
- Genomic Medicine, University of Texas, ᅟ, ᅟ
| | - J. Zhang
- Institute of Applied Cancer Science, ᅟ, USA
| | - S. J. Whiite
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - T. Chiang
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - A. English
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - J. Farek
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - Z. Kahn
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - W. Salerno
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - N. Veeraraghavan
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - E. Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, USA
| | - R. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, ᅟ, USA
| | - T. Kasukawa
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
| | - M. Lizio
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
| | - J. Harshbarger
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
| | - S. Hisashi
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
- Preventive Medicine and Diagnosis Innovation Program, RIKEN, Wako, Japan
| | - J. Severin
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
| | - A. Imad
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
| | - S. Sahin
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
| | - T. C. Freeman
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - K. Baillie
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - A. Sandelin
- Department of Biology & Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark
| | - P. Carninci
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
| | | | - H. Kawaji
- Center for Life Science Technologies, RIKEN, Yokohama, Japan
- Preventive Medicine and Diagnosis Innovation Program, RIKEN, Wako, Japan
- Advanced Center for Computing and Communication, RIKEN, Yokohama, Japan
| | | | - W. Salerno
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas USA
| | - A. English
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas USA
| | | | | | | | - E. Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas USA
- Human Genetics Center and Department of Epidemiology, UT School of Public Health, Houston, Texas USA
| | - R. A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas USA
| | - A. H. Salem
- Anatomy, Arabian Gulf University, Manama, Bahrain
| | - M. Ali
- Biochemistry, Arabian Gulf University, Manama, Bahrain
| | - A. Ibrahim
- Central Laboratory, Ministry of Science and Technology, ᅟ, Sudan
| | - M. Ibrahim
- College of Animal Production Science and Technology, Sudan University of Science and Technology, Khartoum, Sudan
| | - H. A. Barrera
- Bioquimica y Medicina Molecular, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - L. Garza
- Bioquimica y Medicina Molecular, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - J. A. Torres
- Bioquimica y Medicina Molecular, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - V. Barajas
- Bioquimica y Medicina Molecular, Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | | | - D. Kershenobich
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Shahroj Mortaji
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Pedro Guizar
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Eliezer Loera
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Karen Moreno
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Adriana De León
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Daniela Monsiváis
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Jackeline Gómez
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | - Raquel Cardiel
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Distrito Federal, Mexico
| | | | - V. Bonifaz-Peña
- Computational Genomics, Nacional de Medicina Genomica, Mexico City, Mexico
| | - C. Rangel-Escareño
- Computational Genomics, Nacional de Medicina Genomica, Mexico City, Mexico
| | - A. Hidalgo-Miranda
- Cancer Genomics Laboratory, Nacional de Medicina Genomica, Mexico City, Mexico
| | - A. V. Contreras
- Nutrigenetics and Nutrigenomics Laboratory, Instituto Nacional de Medicina Genomica, Mexico City, Mexico
| | - L. Polfus
- Human Genetics Center, University of Texas Health Science Center, Houston, USA
| | | | - X. Wang
- System Genetics, The Jackson Laboratory, Bar Harbor, USA
| | - V. Philip
- System Genetics, The Jackson Laboratory, Bar Harbor, USA
| | - G. Carter
- System Genetics, The Jackson Laboratory, Bar Harbor, USA
| | - A. A. Abuzenadah
- Center of Innovation in Personalized Medicine, Faculty of Applied Medical Sciences, King Abdulaziz University, ᅟ, Saudi Arabia
| | - M. Gari
- Center of Innovation in Personalized Medicine, Faculty of Applied Medical Sciences, King Abdulaziz University, ᅟ, Saudi Arabia
| | - R. Turki
- Ob/Gyn, King Abdulaziz University Hospital, Jeddah, Saudi Arabia
| | - A. Dallol
- Center of Innovation in Personalized Medicine, Faculty of Applied Medical Sciences, King Abdulaziz University, ᅟ, Saudi Arabia
| | - A. Uyar
- The Jackson Laboratory for Genomic Medicine, Farmington, USA
| | - A. Kaygun
- Department of Mathematical Engineering, Istanbul Technical University, Istanbul, Turkey
| | - S. Zaman
- Department of Biomedical Engineering, University of Connecticut, Storrs, USA
| | - E. Marquez
- The Jackson Laboratory for Genomic Medicine, Farmington, USA
| | - J. George
- The Jackson Laboratory for Genomic Medicine, Farmington, USA
| | - D. Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, USA
| | | | | | | | | | | | - T. Davis
- New England Biolabs, Ipswich, USA
| | | | | | - D. B. Starr
- Genetics, Stanford University, Stanford, USA
| | - M. Baird
- DNA Diagnostics Center, Fairfield, USA
| | | | - K. Sheets
- Vibrant Gene Consulting, Cambridge, USA
| | - R. Nitsche
- Agilent Technologies, Agilent Technologies, Waldbronn, Germany
| | - L. Prieto-Lafuente
- Agilent Technologies UK Ltd, Agilent Technologies UK Ltd., Edinburgh, UK
| | | | - J. Lee
- NIH/NLM/NCBI, Bethesda, USA
| | | | | | - P. K. R. Thavanati
- Institute of Human Genetics, Department of Molecular Biology & Genomics, Centre for Health Sciences, ᅟ, Mexico
| | - A. Escoto de Dios
- Institute of Human Genetics, Department of Molecular Biology & Genomics, Centre for Health Sciences, ᅟ, Mexico
| | | | | | - M. R. Ruiz Mejia
- Biochemistry, Centre for Health Sciences, University of Guadalajara, Guadalajara, Mexico
| | - K. R. R. Kanala
- Human Genetics Unit, Department Anthropology, Sri Venkateswara University, Tirupati, India
| | - Z. Abduljaleel
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - W. Khan
- Department of Basic Sciences, College of Science and Health Professions, King Saud Bin Abdul Aziz University for Health Sciences, Riyadh, Saudi Arabia
| | - F. A. Al-Allaf
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - M. Athar
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - M. M. Taher
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - N. Shahzad
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - A. Bouazzaoui
- Science and Technology Unit, Umm Al Qura University, Mecca, Saudi Arabia
- Department of Medical Genetics, Umm Al Qura University, Mecca, Saudi Arabia
- Medical Clinic 3 – Hematology/Oncology, University Hospital Regensburg, Regensburg, Germany
| | - E. Huber
- Department of Pathology, University Hospital Regensburg, Regensburg, Germany
| | - A. Dan
- IgNova GmbH, Oberursel, Germany
| | - F. A. Al-Allaf
- Science and Technology Unit, Umm Al Qura University, Mecca, Saudi Arabia
- Department of Medical Genetics Faculty of Medicine, Umm Al Qura University, Mecca, Saudi Arabia
| | - W. Herr
- Medical Clinic 3 – Hematology/Oncology, University Hospital Regensburg, Regensburg, Germany
| | - G. Sprotte
- Department of Ansethesiologie, University of Würzburg Medical School, Würzburg, Germany
| | - J. Köstler
- Department of microbiology, University Hospital Regensburg, Regensburg, Germany
| | - A. Hiergeist
- Department of microbiology, University Hospital Regensburg, Regensburg, Germany
| | - A. Gessner
- Department of microbiology, University Hospital Regensburg, Regensburg, Germany
| | - R. Andreesen
- Medical Clinic 3 – Hematology/Oncology, University Hospital Regensburg, Regensburg, Germany
| | - E. Holler
- Medical Clinic 3 – Hematology/Oncology, University Hospital Regensburg, Regensburg, Germany
| | - F. Al-Allaf
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, ᅟ, Saudi Arabia
- Science and Technology Unit, Umm Al-Qura University, ᅟ, Saudi Arabia
- Molecular Diagnostics Unit, Department of Laboratory and Blood Bank, King Abdullah Medical City, Makkah, Saudi Arabia
| | - A. Alashwal
- King Faisal Specialist Hospital and Research Centre, ᅟ, Saudi Arabia
| | - Z. Abduljaleel
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, ᅟ, Saudi Arabia
- Science and Technology Unit, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - M. Taher
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, ᅟ, Saudi Arabia
- Science and Technology Unit, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - A. Bouazzaoui
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, ᅟ, Saudi Arabia
- Science and Technology Unit, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - H. Abalkhail
- King Faisal Specialist Hospital and Research Centre, ᅟ, Saudi Arabia
| | - A. Al-Allaf
- Faculty of Medicine, Alfaisal University, Riyadh, Saudi Arabia
| | - R. Bamardadh
- Science and Technology Unit, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - M. Athar
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, ᅟ, Saudi Arabia
- Science and Technology Unit, Umm Al-Qura University, ᅟ, Saudi Arabia
| | - O. Filiptsova
- Biology, National University of Pharmacy, Kharkiv, Ukraine
| | - M. Kobets
- Pharmaceutical Marketing and Management, National University of Pharmacy, Kharkiv, Ukraine
| | - Y. Kobets
- Pharmaceutical Marketing and Management, National University of Pharmacy, Kharkiv, Ukraine
| | - I. Burlaka
- Biology, National University of Pharmacy, Kharkiv, Ukraine
| | - I. Timoshyna
- Human Physiology and Anatomy, National University of Pharmacy, Kharkiv, Ukraine
| | - O. Filiptsova
- Biology, National University of Pharmacy, Kharkiv, Ukraine
| | - M. N. Kobets
- Pharmaceutical Marketing and Management, National University of Pharmacy, Kharkiv, Ukraine
| | - Y. Kobets
- Pharmaceutical Marketing and Management, National University of Pharmacy, Kharkiv, Ukraine
| | - I. Burlaka
- Biology, National University of Pharmacy, Kharkiv, Ukraine
| | - I. Timoshyna
- Human Physiology and Anatomy, National University of Pharmacy, Kharkiv, Ukraine
| | - O. Filiptsova
- Biology, National University of Pharmacy, Kharkiv, Ukraine
| | - M. N. Kobets
- Pharmaceutical Marketing and Management, National University of Pharmacy, Kharkiv, Ukraine
| | - Y. Kobets
- Pharmaceutical Marketing and Management, National University of Pharmacy, Kharkiv, Ukraine
| | - I. Burlaka
- Biology, National University of Pharmacy, Kharkiv, Ukraine
| | - I. Timoshyna
- Human Physiology and Anatomy, National University of Pharmacy, Kharkiv, Ukraine
| | - F. A. Al-allaf
- Department of Medical Genetics Faculty of Medicine, Umm Al Qura University, Mecca, Saudi Arabia
- Science and Technology Unit, Umm Al Qura University, Mecca, Saudi Arabia
- Molecular Diagnostics Unit Department of Laboratory Medicine and Blood Bank, King Abdullah Medical City, ᅟ, Saudi Arabia
| | - M. T. Mohiuddin
- Department of Medical Genetics Faculty of Medicine, Umm Al Qura University, Mecca, Saudi Arabia
- Science and Technology Unit, Umm Al Qura University, Mecca, Saudi Arabia
| | - A. Zainularifeen
- Department of Medical Genetics Faculty of Medicine, Umm Al Qura University, Mecca, Saudi Arabia
- Science and Technology Unit, Umm Al Qura University, Mecca, Saudi Arabia
| | - A. Mohammed
- Department of Medical Genetics Faculty of Medicine, Umm Al Qura University, Mecca, Saudi Arabia
- Science and Technology Unit, Umm Al Qura University, Mecca, Saudi Arabia
| | - H. Abalkhail
- Pathology and Laboratory Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - T. Owaidah
- Pathology and Laboratory Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - A. Bouazzaoui
- Department of Medical Genetics Faculty of Medicine, Umm Al Qura University, Mecca, Saudi Arabia
- Science and Technology Unit, Umm Al Qura University, Mecca, Saudi Arabia
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39
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van Zundert GCP, Rodrigues JPGLM, Trellet M, Schmitz C, Kastritis PL, Karaca E, Melquiond ASJ, van Dijk M, de Vries SJ, Bonvin AMJJ. The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes. J Mol Biol 2016; 428:720-725. [PMID: 26410586 DOI: 10.1016/j.jmb.2015.09.014)] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Revised: 09/16/2015] [Accepted: 09/17/2015] [Indexed: 05/23/2023]
Abstract
The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2.
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Affiliation(s)
- G C P van Zundert
- Bijvoet Center for Biomolecular Research, Faculty of Science Department of Chemistry, Utrecht University, Domplein 29, 3512 JE Utrecht, the Netherlands
| | - J P G L M Rodrigues
- Bijvoet Center for Biomolecular Research, Faculty of Science Department of Chemistry, Utrecht University, Domplein 29, 3512 JE Utrecht, the Netherlands
| | - M Trellet
- Centre National de la Recherche Scientifique Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, rue John Von Neumann, 91403 Orsay, France
| | - C Schmitz
- Instaclustr Level 5, 1 Moore Street, Canberra ACT 2600, Australia
| | - P L Kastritis
- European Molecular Biology Laboratory Heidelberg, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - E Karaca
- European Molecular Biology Laboratory Heidelberg, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - A S J Melquiond
- Hubrecht Institute, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - M van Dijk
- Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, the Netherlands
| | - S J de Vries
- Physik-Department, Technische Universität München, James-Franck-Strasse 1, 85748 Garching, Germany
| | - A M J J Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science Department of Chemistry, Utrecht University, Domplein 29, 3512 JE Utrecht, the Netherlands
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40
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Karaca E, Atik T, Alpman Durmaz A, Ozkinay F, Cogulu O. Transmembrane Activator and Caml Interactor (Taci) Haploinsufficiency in B-Cell Dysfunction in a Patient with Smith-Magenis Syndrome. Genet Couns 2016; 27:251-254. [PMID: 29485832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
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41
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Durmaz B, Karaca E, Tavmergen Goker EN, Tavmergen E, Sahin G, Akdogan A, Yasar BP, Gunduz C, Ozkinay R. EVALUATION OF PREIMPLANTATION GENETIC ANEUPLOIDY SCREENING CASES AT A REFERENCE GENETICS CENTER: 10 YEARS' EXPERIENCE. Genet Couns 2016; 27:461-470. [PMID: 30226964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The aim of this study is to review and evaluate our preimplantation genetic screening (PGS) records in terms of their demographic data, indications, cytogenetic results, pregnancy outcomes and discuss these findings in different aspects. PGS was performed in a total of 84 couples (87 cycles) between the period 2005 to 2015. Biopsied blastomeres from embryos on day 3 were fixed and fluorescence in situ hybridization was carried out for chromosomes 13, 16, 18, 21, 22, X and Y depending on the indication. The diagnostic and clinical data were retrospectively evaluated. A total of 450 blastomeres were biopsied. Ninety-eight of them were found to be suitable for transfer. They were transferred to 72 patients in 75 cycles resulting in 23 pregnancies and 20 healthy births. The most common indication was unexplained infertility. The implantation rate was calculated as 23.4% whereas the take-home baby rate was 26.6% per transfer. The highest rate of healthy living births is achieved in patients having low grade maternal mosaic sex chromosomal aneuploidy. All living births achieved by PGS had normal chromosomal structure which we can propose it as an alternative test for couples at risk to select normal embryos to improve the outcomes of assisted reproductive procedures and to avoid the transfer of chromosomally unbalanced and multiple embryos.
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42
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van Zundert GCP, Rodrigues JPGLM, Trellet M, Schmitz C, Kastritis PL, Karaca E, Melquiond ASJ, van Dijk M, de Vries SJ, Bonvin AMJJ. The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes. J Mol Biol 2015; 428:720-725. [PMID: 26410586 DOI: 10.1016/j.jmb.2015.09.014] [Citation(s) in RCA: 1652] [Impact Index Per Article: 183.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Revised: 09/16/2015] [Accepted: 09/17/2015] [Indexed: 11/25/2022]
Abstract
The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2.
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Affiliation(s)
- G C P van Zundert
- Bijvoet Center for Biomolecular Research, Faculty of Science Department of Chemistry, Utrecht University, Domplein 29, 3512 JE Utrecht, the Netherlands
| | - J P G L M Rodrigues
- Bijvoet Center for Biomolecular Research, Faculty of Science Department of Chemistry, Utrecht University, Domplein 29, 3512 JE Utrecht, the Netherlands
| | - M Trellet
- Centre National de la Recherche Scientifique Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, rue John Von Neumann, 91403 Orsay, France
| | - C Schmitz
- Instaclustr Level 5, 1 Moore Street, Canberra ACT 2600, Australia
| | - P L Kastritis
- European Molecular Biology Laboratory Heidelberg, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - E Karaca
- European Molecular Biology Laboratory Heidelberg, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - A S J Melquiond
- Hubrecht Institute, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - M van Dijk
- Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, the Netherlands
| | - S J de Vries
- Physik-Department, Technische Universität München, James-Franck-Strasse 1, 85748 Garching, Germany
| | - A M J J Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science Department of Chemistry, Utrecht University, Domplein 29, 3512 JE Utrecht, the Netherlands
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43
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Atik T, Karaca E, Ozkinay E, Cogulu O. TWINS WITH KLEEFSTRA SYNDROME DUE TO CHROMOSOME 9q34.3 MICRODELETION. Genet Couns 2015; 26:431-435. [PMID: 26852514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Kleefstra or 9q subtelomeric deletion syndrome (9qSTDS) is a rare microdeletion syndrome. The most prominent phenotypic features include hypotonia, developmental retardation, as well as typical dysmorphic face. It has been shown that terminal deletions of the chromosome 9q34.3 region, or EHMT1 gene mutations, lead to Kleefstra syndrome. We present 16-month-old twin sisters, one of whom had originally been referred for Down syndrome screening due to hypotonia, growth and development retardation, dysmorphic facial signs, and accompanying congenital heart disease. They were subsequently diagnosed as Kleefstra syndrome based on subtelomeric FISH analysis. In conclusion, Kleefstra syndrome should be considered in the differential diagnosis of Down syndrome because it presents with very similar phenotypic features.
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Abstract
Protein-protein docking aims at predicting the three-dimensional structure of a protein complex starting from the free forms of the individual partners. As assessed in the CAPRI community-wide experiment, the most successful docking algorithms combine pure laws of physics with information derived from various experimental or bioinformatics sources. Of these so-called "information-driven" approaches, HADDOCK stands out as one of the most successful representatives. In this chapter, we briefly summarize which experimental information can be used to drive the docking prediction in HADDOCK, and then focus on the docking protocol itself. We discuss and illustrate with a tutorial example a "classical" protein-protein docking prediction, as well as more recent developments for modelling multi-body systems and large conformational changes.
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Affiliation(s)
- João P G L M Rodrigues
- Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584 CH, The Netherlands
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Lensink MF, Moal IH, Bates PA, Kastritis PL, Melquiond ASJ, Karaca E, Schmitz C, van Dijk M, Bonvin AMJJ, Eisenstein M, Jiménez-García B, Grosdidier S, Solernou A, Pérez-Cano L, Pallara C, Fernández-Recio J, Xu J, Muthu P, Praneeth Kilambi K, Gray JJ, Grudinin S, Derevyanko G, Mitchell JC, Wieting J, Kanamori E, Tsuchiya Y, Murakami Y, Sarmiento J, Standley DM, Shirota M, Kinoshita K, Nakamura H, Chavent M, Ritchie DW, Park H, Ko J, Lee H, Seok C, Shen Y, Kozakov D, Vajda S, Kundrotas PJ, Vakser IA, Pierce BG, Hwang H, Vreven T, Weng Z, Buch I, Farkash E, Wolfson HJ, Zacharias M, Qin S, Zhou HX, Huang SY, Zou X, Wojdyla JA, Kleanthous C, Wodak SJ. Blind prediction of interfacial water positions in CAPRI. Proteins 2014; 82:620-32. [PMID: 24155158 PMCID: PMC4582081 DOI: 10.1002/prot.24439] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2013] [Revised: 09/16/2013] [Accepted: 09/26/2013] [Indexed: 12/30/2022]
Abstract
We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes.
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Affiliation(s)
- Marc F Lensink
- Interdisciplinary Research Institute USR3078 CNRS, University Lille North of France, Villeneuve d'Ascq, France
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46
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Atik T, Aykut A, Karaca E, Onay H, Ozkinay F, Cogulu O. A twin sibling with Prader-Willi syndrome caused by uniparental disomy conceived after in vitro fertilization. Genet Couns 2014; 25:433-437. [PMID: 25804024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
The use of assisted reproductive technologies (ART) has increased gradually in the treatment of infertility worldwide. On the other hand ART has been found to be associated with an increased risk of congenital malformations including imprinting defects as well. Although a number of imprinting syndromes have been reported to be related with ART, no case with uniparental disomy (UPD) caused Prader-Willi syndrome (PWS) [OMIM ID: 176270] has been reported in the literature. Here we present a dizygotic twin in which one of them was born with maternal UPD15 following ART. The proband was a 2-year-old boy who had feeding difficulties, generalized hypotonia, frontal bossing, broad forehead, small hands and feet. Laboratory investigations revealed minimal dilatation in 3rd and 4th ventricles and corpus callosum hypoplasia in magnetic resonance imaging, supravalvular pulmonary stenosis in echocardiography and pelvicaliectasia in the USG examinations. Methylation and microsatellite markers analyses showed maternal UPD for chromosome 15. Here we report, for the first time UPD caused PWS patient born after ART.
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47
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Rodrigues JPGLM, Melquiond ASJ, Karaca E, Trellet M, van Dijk M, van Zundert GCP, Schmitz C, de Vries SJ, Bordogna A, Bonati L, Kastritis PL, Bonvin AMJJ. Defining the limits of homology modeling in information-driven protein docking. Proteins 2013; 81:2119-28. [PMID: 23913867 DOI: 10.1002/prot.24382] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Revised: 07/16/2013] [Accepted: 07/25/2013] [Indexed: 12/28/2022]
Abstract
Information-driven docking is currently one of the most successful approaches to obtain structural models of protein interactions as demonstrated in the latest round of CAPRI. While various experimental and computational techniques can be used to retrieve information about the binding mode, the availability of three-dimensional structures of the interacting partners remains a limiting factor. Fortunately, the wealth of structural information gathered by large-scale initiatives allows for homology-based modeling of a significant fraction of the protein universe. Defining the limits of information-driven docking based on such homology models is therefore highly relevant. Here we show, using previous CAPRI targets, that out of a variety of measures, the global sequence identity between template and target is a simple but reliable predictor of the achievable quality of the docking models. This indicates that a well-defined overall fold is critical for the interaction. Furthermore, the quality of the data at our disposal to characterize the interaction plays a determinant role in the success of the docking. Given reliable interface information we can obtain acceptable predictions even at low global sequence identity. These results, which define the boundaries between trustworthy and unreliable predictions, should guide both experts and nonexperts in defining the limits of what is achievable by docking. This is highly relevant considering that the fraction of the interactome amenable for docking is only bound to grow as the number of experimentally solved structures increases.
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Affiliation(s)
- J P G L M Rodrigues
- Faculty of Science/Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, 3584CH, The Netherlands
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48
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Durmaz B, Karaca E, Tavmergen E, Goker ET, Calimlioglu N, Gunduz C, Ozkinay F. P-18 Evaluation of preimplantation genetic aneuploidy screening cases at a reference genetics center in Izmir, Turkey. Reprod Biomed Online 2013. [DOI: 10.1016/s1472-6483(13)60081-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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49
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Karaca E, Durmaz B, Goker ET, Tavmergen E, Calimlioglu N, Gunduz C, Ozkinay F. P-53 Outcome of preimplantation genetic diagnosis of balanced translocation carriers. Reprod Biomed Online 2013. [DOI: 10.1016/s1472-6483(13)60116-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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50
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Ozkinay F, Durmaz B, Karaca E, Goker ET, Tavmergen E, Gunduz C. P-61 Analysis of couples having genetic counseling for preimplantation genetic diagnosis or preimplantation genetic screening. Reprod Biomed Online 2013. [DOI: 10.1016/s1472-6483(13)60124-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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