1
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Chan YF, Lu CW, Kuo HC, Hung CM. A chromosome-level genome assembly of the Asian house martin implies potential genes associated with the feathered-foot trait. G3 (BETHESDA, MD.) 2024; 14:jkae077. [PMID: 38607414 DOI: 10.1093/g3journal/jkae077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 03/04/2024] [Accepted: 03/27/2024] [Indexed: 04/13/2024]
Abstract
The presence of feathers is a vital characteristic among birds, yet most modern birds had no feather on their feet. The discoveries of feathers on the hind limbs of basal birds and dinosaurs have sparked an interest in the evolutionary origin and genetic mechanism of feathered feet. However, the majority of studies investigating the genes associated with this trait focused on domestic populations. Understanding the genetic mechanism underpinned feathered-foot development in wild birds is still in its infancy. Here, we assembled a chromosome-level genome of the Asian house martin (Delichon dasypus) using the long-read High Fidelity sequencing approach to initiate the search for genes associated with its feathered feet. We employed the whole-genome alignment of D. dasypus with other swallow species to identify high-SNP regions and chromosomal inversions in the D. dasypus genome. After filtering out variations unrelated to D. dasypus evolution, we found six genes related to feather development near the high-SNP regions. We also detected three feather development genes in chromosomal inversions between the Asian house martin and the barn swallow genomes. We discussed their association with the wingless/integrated (WNT), bone morphogenetic protein, and fibroblast growth factor pathways and their potential roles in feathered-foot development. Future studies are encouraged to utilize the D. dasypus genome to explore the evolutionary process of the feathered-foot trait in avian species. This endeavor will shed light on the evolutionary path of feathers in birds.
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Affiliation(s)
- Yuan-Fu Chan
- Biodiversity Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Chia-Wei Lu
- Biodiversity Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Hao-Chih Kuo
- Biodiversity Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Chih-Ming Hung
- Biodiversity Research Center, Academia Sinica, Taipei 11529, Taiwan
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2
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Wang S, Lin J, Jia P, Xu T, Li X, Liu Y, Xu D, Bush SJ, Meng D, Ye K. De novo and somatic structural variant discovery with SVision-pro. Nat Biotechnol 2024:10.1038/s41587-024-02190-7. [PMID: 38519720 DOI: 10.1038/s41587-024-02190-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 02/27/2024] [Indexed: 03/25/2024]
Abstract
Long-read-based de novo and somatic structural variant (SV) discovery remains challenging, necessitating genomic comparison between samples. We developed SVision-pro, a neural-network-based instance segmentation framework that represents genome-to-genome-level sequencing differences visually and discovers SV comparatively between genomes without any prerequisite for inference models. SVision-pro outperforms state-of-the-art approaches, in particular, the resolving of complex SVs is improved, with low Mendelian error rates, high sensitivity of low-frequency SVs and reduced false-positive rates compared with SV merging approaches.
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Affiliation(s)
- Songbo Wang
- Department of Gynecology and Obstetrics, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Jiadong Lin
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Peng Jia
- Department of Gynecology and Obstetrics, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Tun Xu
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Xiujuan Li
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Yuezhuangnan Liu
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Dan Xu
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Stephen J Bush
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Deyu Meng
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China
- Macau Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau
- Pazhou Laboratory (Huangpu), Guangzhou, Guangdong, China
| | - Kai Ye
- Department of Gynecology and Obstetrics, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
- Faculty of Science, Leiden University, Leiden, The Netherlands.
- Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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3
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Liu YH, Luo C, Golding SG, Ioffe JB, Zhou XM. Tradeoffs in alignment and assembly-based methods for structural variant detection with long-read sequencing data. Nat Commun 2024; 15:2447. [PMID: 38503752 PMCID: PMC10951360 DOI: 10.1038/s41467-024-46614-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 03/04/2024] [Indexed: 03/21/2024] Open
Abstract
Long-read sequencing offers long contiguous DNA fragments, facilitating diploid genome assembly and structural variant (SV) detection. Efficient and robust algorithms for SV identification are crucial with increasing data availability. Alignment-based methods, favored for their computational efficiency and lower coverage requirements, are prominent. Alternative approaches, relying solely on available reads for de novo genome assembly and employing assembly-based tools for SV detection via comparison to a reference genome, demand significantly more computational resources. However, the lack of comprehensive benchmarking constrains our comprehension and hampers further algorithm development. Here we systematically compare 14 read alignment-based SV calling methods (including 4 deep learning-based methods and 1 hybrid method), and 4 assembly-based SV calling methods, alongside 4 upstream aligners and 7 assemblers. Assembly-based tools excel in detecting large SVs, especially insertions, and exhibit robustness to evaluation parameter changes and coverage fluctuations. Conversely, alignment-based tools demonstrate superior genotyping accuracy at low sequencing coverage (5-10×) and excel in detecting complex SVs, like translocations, inversions, and duplications. Our evaluation provides performance insights, highlighting the absence of a universally superior tool. We furnish guidelines across 31 criteria combinations, aiding users in selecting the most suitable tools for diverse scenarios and offering directions for further method development.
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Affiliation(s)
- Yichen Henry Liu
- Department of Computer Science, Vanderbilt University, 37235, Nashville, TN, USA
| | - Can Luo
- Department of Biomedical Engineering, Vanderbilt University, 37235, Nashville, TN, USA
| | - Staunton G Golding
- Department of Biomedical Engineering, Vanderbilt University, 37235, Nashville, TN, USA
| | - Jacob B Ioffe
- Department of Computer Science, Vanderbilt University, 37235, Nashville, TN, USA
| | - Xin Maizie Zhou
- Department of Computer Science, Vanderbilt University, 37235, Nashville, TN, USA.
- Department of Biomedical Engineering, Vanderbilt University, 37235, Nashville, TN, USA.
- Data Science Institute, Vanderbilt University, 37235, Nashville, TN, USA.
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4
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Lesack KJ, Wasmuth JD. The impact of FASTQ and alignment read order on structural variant calling from long-read sequencing data. PeerJ 2024; 12:e17101. [PMID: 38500526 PMCID: PMC10946394 DOI: 10.7717/peerj.17101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 02/21/2024] [Indexed: 03/20/2024] Open
Abstract
Background Structural variant (SV) calling from DNA sequencing data has been challenging due to several factors, including the ambiguity of short-read alignments, multiple complex SVs in the same genomic region, and the lack of "truth" datasets for benchmarking. Additionally, caller choice, parameter settings, and alignment method are known to affect SV calling. However, the impact of FASTQ read order on SV calling has not been explored for long-read data. Results Here, we used PacBio DNA sequencing data from 15 Caenorhabditis elegans strains and four Arabidopsis thaliana ecotypes to evaluate the sensitivity of different SV callers on FASTQ read order. Comparisons of variant call format files generated from the original and permutated FASTQ files demonstrated that the order of input data affected the SVs predicted by each caller. In particular, pbsv was highly sensitive to the order of the input data, especially at the highest depths where over 70% of the SV calls generated from pairs of differently ordered FASTQ files were in disagreement. These demonstrate that read order sensitivity is a complex, multifactorial process, as the differences observed both within and between species varied considerably according to the specific combination of aligner, SV caller, and sequencing depth. In addition to the SV callers being sensitive to the input data order, the SAMtools alignment sorting algorithm was identified as a source of variability following read order randomization. Conclusion The results of this study highlight the sensitivity of SV calling on the order of reads encoded in FASTQ files, which has not been recognized in long-read approaches. These findings have implications for the replication of SV studies and the development of consistent SV calling protocols. Our study suggests that researchers should pay attention to the input order sensitivity of read alignment sorting methods when analyzing long-read sequencing data for SV calling, as mitigating a source of variability could facilitate future replication work. These results also raise important questions surrounding the relationship between SV caller read order sensitivity and tool performance. Therefore, tool developers should also consider input order sensitivity as a potential source of variability during the development and benchmarking of new and improved methods for SV calling.
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Affiliation(s)
- Kyle J. Lesack
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
- Host-Parasite Interactions Research Training Network, University of Calgary, Calgary, Alberta, Canada
| | - James D. Wasmuth
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada
- Host-Parasite Interactions Research Training Network, University of Calgary, Calgary, Alberta, Canada
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5
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Zheng Y, Shang X. SVvalidation: A long-read-based validation method for genomic structural variation. PLoS One 2024; 19:e0291741. [PMID: 38181020 PMCID: PMC10769053 DOI: 10.1371/journal.pone.0291741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 09/05/2023] [Indexed: 01/07/2024] Open
Abstract
Although various methods have been developed to detect structural variations (SVs) in genomic sequences, few are used to validate these results. Several commonly used SV callers produce many false positive SVs, and existing validation methods are not accurate enough. Therefore, a highly efficient and accurate validation method is essential. In response, we propose SVvalidation-a new method that uses long-read sequencing data for validating SVs with higher accuracy and efficiency. Compared to existing methods, SVvalidation performs better in validating SVs in repeat regions and can determine the homozygosity or heterozygosity of an SV. Additionally, SVvalidation offers the highest recall, precision, and F1-score (improving by 7-16%) across all datasets. Moreover, SVvalidation is suitable for different types of SVs. The program is available at https://github.com/nwpuzhengyan/SVvalidation.
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Affiliation(s)
- Yan Zheng
- School of Computer Science, Northwestern Polytechnical University, Xi’an, China
| | - Xuequn Shang
- School of Computer Science, Northwestern Polytechnical University, Xi’an, China
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6
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Brannan EO, Hartley GA, O’Neill RJ. Mechanisms of Rapid Karyotype Evolution in Mammals. Genes (Basel) 2023; 15:62. [PMID: 38254952 PMCID: PMC10815390 DOI: 10.3390/genes15010062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 12/27/2023] [Accepted: 12/28/2023] [Indexed: 01/24/2024] Open
Abstract
Chromosome reshuffling events are often a foundational mechanism by which speciation can occur, giving rise to highly derivative karyotypes even amongst closely related species. Yet, the features that distinguish lineages prone to such rapid chromosome evolution from those that maintain stable karyotypes across evolutionary time are still to be defined. In this review, we summarize lineages prone to rapid karyotypic evolution in the context of Simpson's rates of evolution-tachytelic, horotelic, and bradytelic-and outline the mechanisms proposed to contribute to chromosome rearrangements, their fixation, and their potential impact on speciation events. Furthermore, we discuss relevant genomic features that underpin chromosome variation, including patterns of fusions/fissions, centromere positioning, and epigenetic marks such as DNA methylation. Finally, in the era of telomere-to-telomere genomics, we discuss the value of gapless genome resources to the future of research focused on the plasticity of highly rearranged karyotypes.
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Affiliation(s)
- Emry O. Brannan
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269, USA; (E.O.B.); (G.A.H.)
| | - Gabrielle A. Hartley
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269, USA; (E.O.B.); (G.A.H.)
| | - Rachel J. O’Neill
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269, USA; (E.O.B.); (G.A.H.)
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA
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7
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Ghielmetti G, Loubser J, Kerr TJ, Stuber T, Thacker T, Martin LC, O'Hare MA, Mhlophe SK, Okunola A, Loxton AG, Warren RM, Moseley MH, Miller MA, Goosen WJ. Advancing animal tuberculosis surveillance using culture-independent long-read whole-genome sequencing. Front Microbiol 2023; 14:1307440. [PMID: 38075895 PMCID: PMC10699144 DOI: 10.3389/fmicb.2023.1307440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 10/23/2023] [Indexed: 02/12/2024] Open
Abstract
Animal tuberculosis is a significant infectious disease affecting both livestock and wildlife populations worldwide. Effective disease surveillance and characterization of Mycobacterium bovis (M. bovis) strains are essential for understanding transmission dynamics and implementing control measures. Currently, sequencing of genomic information has relied on culture-based methods, which are time-consuming, resource-demanding, and concerning in terms of biosafety. This study explores the use of culture-independent long-read whole-genome sequencing (WGS) for a better understanding of M. bovis epidemiology in African buffaloes (Syncerus caffer). By comparing two sequencing approaches, we evaluated the efficacy of Illumina WGS performed on culture extracts and culture-independent Oxford Nanopore adaptive sampling (NAS). Our objective was to assess the potential of NAS to detect genomic variants without sample culture. In addition, culture-independent amplicon sequencing, targeting mycobacterial-specific housekeeping and full-length 16S rRNA genes, was applied to investigate the presence of microorganisms, including nontuberculous mycobacteria. The sequencing quality obtained from DNA extracted directly from tissues using NAS is comparable to the sequencing quality of reads generated from culture-derived DNA using both NAS and Illumina technologies. We present a new approach that provides complete and accurate genome sequence reconstruction, culture independently, and using an economically affordable technique.
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Affiliation(s)
- Giovanni Ghielmetti
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Section of Veterinary Bacteriology, Institute for Food Safety and Hygiene, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
| | - Johannes Loubser
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tanya J. Kerr
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Tod Stuber
- National Veterinary Services Laboratories, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Ames, IA, United States
| | - Tyler Thacker
- National Veterinary Services Laboratories, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Ames, IA, United States
| | - Lauren C. Martin
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Michaela A. O'Hare
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Sinegugu K. Mhlophe
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Abisola Okunola
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Andre G. Loxton
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Robin M. Warren
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Mark H. Moseley
- School of Biological Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Michele A. Miller
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Wynand J. Goosen
- Division of Molecular Biology and Human Genetics, South African Medical Research Council Centre for Tuberculosis Research, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
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8
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Ahsan MU, Liu Q, Perdomo JE, Fang L, Wang K. A survey of algorithms for the detection of genomic structural variants from long-read sequencing data. Nat Methods 2023; 20:1143-1158. [PMID: 37386186 DOI: 10.1038/s41592-023-01932-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 05/31/2023] [Indexed: 07/01/2023]
Abstract
As long-read sequencing technologies are becoming increasingly popular, a number of methods have been developed for the discovery and analysis of structural variants (SVs) from long reads. Long reads enable detection of SVs that could not be previously detected from short-read sequencing, but computational methods must adapt to the unique challenges and opportunities presented by long-read sequencing. Here, we summarize over 50 long-read-based methods for SV detection, genotyping and visualization, and discuss how new telomere-to-telomere genome assemblies and pangenome efforts can improve the accuracy and drive the development of SV callers in the future.
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Affiliation(s)
- Mian Umair Ahsan
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Qian Liu
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jonathan Elliot Perdomo
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA
| | - Li Fang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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9
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Ren J, Gu B, Chaisson MJP. vamos: variable-number tandem repeats annotation using efficient motif sets. Genome Biol 2023; 24:175. [PMID: 37501141 PMCID: PMC10373352 DOI: 10.1186/s13059-023-03010-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 07/06/2023] [Indexed: 07/29/2023] Open
Abstract
Roughly 3% of the human genome is composed of variable-number tandem repeats (VNTRs): arrays of motifs at least six bases. These loci are highly polymorphic, yet current approaches that define and merge variants based on alignment breakpoints do not capture their full diversity. Here we present a method vamos: VNTR Annotation using efficient Motif Sets that instead annotates VNTR using repeat composition under different levels of motif diversity. Using vamos we estimate 7.4-16.7 alleles per locus when applied to 74 haplotype-resolved human assemblies, compared to breakpoint-based approaches that estimate 4.0-5.5 alleles per locus.
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Affiliation(s)
- Jingwen Ren
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, US
| | - Bida Gu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, US
| | - Mark J. P. Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, US
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10
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Drazdauskienė U, Kapustina Ž, Medžiūnė J, Dubovskaja V, Sabaliauskaitė R, Jarmalaitė S, Lubys A. Fusion sequencing via terminator-assisted synthesis (FTAS-seq) identifies TMPRSS2 fusion partners in prostate cancer. Mol Oncol 2023; 17:993-1006. [PMID: 37300660 DOI: 10.1002/1878-0261.13428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 02/26/2023] [Accepted: 04/03/2023] [Indexed: 06/12/2023] Open
Abstract
Genetic rearrangements that fuse an androgen-regulated promoter area with a protein-coding portion of an originally androgen-unaffected gene are frequent in prostate cancer, with the fusion between transmembrane serine protease 2 (TMPRSS2) and ETS transcription factor ERG (ERG) (TMPRSS2-ERG fusion) being the most prevalent. Conventional hybridization- or amplification-based methods can test for the presence of expected gene fusions, but the exploratory analysis of currently unknown fusion partners is often cost-prohibitive. Here, we developed an innovative next-generation sequencing (NGS)-based approach for gene fusion analysis termed fusion sequencing via terminator-assisted synthesis (FTAS-seq). FTAS-seq can be used to enrich the gene of interest while simultaneously profiling the whole spectrum of its 3'-terminal fusion partners. Using this novel semi-targeted RNA-sequencing technique, we were able to identify 11 previously uncharacterized TMPRSS2 fusion partners and capture a range of TMPRSS2-ERG isoforms. We tested the performance of FTAS-seq with well-characterized prostate cancer cell lines and utilized the technique for the analysis of patient RNA samples. FTAS-seq chemistry combined with appropriate primer panels holds great potential as a tool for biomarker discovery that can support the development of personalized cancer therapies.
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Affiliation(s)
| | | | | | | | | | - Sonata Jarmalaitė
- National Cancer Institute, Vilnius, Lithuania
- Institute of Biosciences, Life Sciences Center, Vilnius University, Lithuania
| | - Arvydas Lubys
- Thermo Fisher Scientific Baltics, Vilnius, Lithuania
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