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Li H, Marin M, Farhat MR. Exploring gene content with pangene graphs. ARXIV 2024:arXiv:2402.16185v3. [PMID: 38463499 PMCID: PMC10925376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Motivation The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome. Results We developed pangene, a computational tool to identify gene orientation, gene order and gene copy-number changes in a collection of genomes. Pangene aligns a set of input protein sequences to the genomes, resolves redundancies between protein sequences and constructs a gene graph with each genome represented as a walk in the graph. It additionally finds subgraphs, which we call bibubbles, that capture gene content changes. Applied to the human pangenome, pangene identifies known gene-level variations and reveals complex haplotypes that are not well studied before. Pangene also works with high-quality bacterial pangenome and reports similar numbers of core and accessory genes in comparison to existing tools. Availability and implementation Source code at https://github.com/lh3/pangene; pre-built pangene graphs can be downloaded from https://zenodo.org/records/8118576 and visualized at https://pangene.bioinweb.org.
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Affiliation(s)
- Heng Li
- Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215, USA
- Harvard Medical School, 10 Shattuck St, Boston, MA 02215, USA
- Broad Insitute of Harvard and MIT, 415 Main St, Cambridge, MA 02142, USA
| | | | - Maha Reda Farhat
- Harvard Medical School, 10 Shattuck St, Boston, MA 02215, USA
- Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, USA
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Hirayasu K, Khor SS, Kawai Y, Shimada M, Omae Y, Hasegawa G, Hashikawa Y, Tanimoto H, Ohashi J, Hosomichi K, Tajima A, Nakamura H, Nakamura M, Tokunaga K, Hanayama R, Nagasaki M. Identification of the hybrid gene LILRB5-3 by long-read sequencing and implication of its novel signaling function. Front Immunol 2024; 15:1398935. [PMID: 38807600 PMCID: PMC11130398 DOI: 10.3389/fimmu.2024.1398935] [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: 03/11/2024] [Accepted: 04/10/2024] [Indexed: 05/30/2024] Open
Abstract
Leukocyte immunoglobulin (Ig)-like receptors (LILRs) on human chromosome 19q13.4 encode 11 immunoglobulin superfamily receptors, exhibiting genetic diversity within and between human populations. Among the LILR genes, the genomic region surrounding LILRB3 and LILRA6 has yet to be fully characterized due to their significant sequence homology, which makes it difficult to differentiate between them. To examine the LILRB3 and LILRA6 genomic region, a tool named JoGo-LILR CN Caller, which can call copy number from short-read whole genome sequencing (srWGS) data, was applied to an extensive international srWGS dataset comprising 2,504 samples. During this process, a previously unreported loss of both LILRB3 and LILRA6 was detected in three samples. Using long-read sequencing of these samples, we have discovered a novel large deletion (33,692 bp) in the LILRB3 and LILRA6 genomic regions in the Japanese population. This deletion spanned three genes, LILRB3, LILRA6, and LILRB5, resulting in LILRB3 exons 12-13 being located immediately downstream of LILRB5 exons 1-12 with the loss of LILRA6, suggesting the potential expression of a hybrid gene between LILRB5 and LILRB3 (LILRB5-3). Transcription and subsequent translation of the LILRB5-3 hybrid gene were also verified. The hybrid junction was located within the intracellular domain, resulting in an LILRB5 extracellular domain fused to a partial LILRB3 intracellular domain with three immunoreceptor tyrosine-based inhibitory motifs (ITIMs), suggesting that LILRB5-3 acquired a novel signaling function. Further application of the JoGo-LILR tool to srWGS samples suggested the presence of the LILRB5-3 hybrid gene in the CEU population. Our findings provide insight into the genetic and functional diversity of the LILR family.
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Affiliation(s)
- Kouyuki Hirayasu
- Advanced Preventive Medical Sciences Research Center, Kanazawa University, Kanazawa, Japan
- Department of Evolutionary Immunology, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Kanazawa, Japan
- Department of Immunology, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan
- Department of Immunology, School of Medical and Pharmaceutical Sciences, Kanazawa University, Kanazawa, Japan
| | - Seik-Soon Khor
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Yosuke Kawai
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Mihoko Shimada
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Yosuke Omae
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Gen Hasegawa
- Department of Immunology, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Yuko Hashikawa
- WPI Nano Life Science Institute (NanoLSI), Kanazawa University, Kanazawa, Japan
| | - Hiromu Tanimoto
- Department of Immunology, School of Medical and Pharmaceutical Sciences, Kanazawa University, Kanazawa, Japan
| | - Jun Ohashi
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan
| | - Kazuyoshi Hosomichi
- Laboratory of Computational Genomics, School of Life Science, Tokyo University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Atsushi Tajima
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Kanazawa, Japan
| | - Hiroyuki Nakamura
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | - Minoru Nakamura
- Clinical Research Center, National Hospital Organization (NHO) Nagasaki Medical Center, Omura, Japan
- Department of Hepatology, Nagasaki University Graduate School of Biomedical Sciences, Omura, Japan
- Headquarters of Primary Biliary Cholangitis (PBC) Research in NHO Study Group for Liver Disease in Japan (NHOSLJ), Clinical Research Center, NHO Nagasaki Medical Center, Omura, Japan
- Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Rikinari Hanayama
- Advanced Preventive Medical Sciences Research Center, Kanazawa University, Kanazawa, Japan
- Department of Immunology, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan
- Department of Immunology, School of Medical and Pharmaceutical Sciences, Kanazawa University, Kanazawa, Japan
- WPI Nano Life Science Institute (NanoLSI), Kanazawa University, Kanazawa, Japan
| | - Masao Nagasaki
- Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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3
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Schloissnig S, Pani S, Rodriguez-Martin B, Ebler J, Hain C, Tsapalou V, Söylev A, Hüther P, Ashraf H, Prodanov T, Asparuhova M, Hunt S, Rausch T, Marschall T, Korbel JO. Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590093. [PMID: 38659906 PMCID: PMC11042266 DOI: 10.1101/2024.04.18.590093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Structural variants (SVs) contribute significantly to human genetic diversity and disease 1-4 . Previously, SVs have remained incompletely resolved by population genomics, with short-read sequencing facing limitations in capturing the whole spectrum of SVs at nucleotide resolution 5-7 . Here we leveraged nanopore sequencing 8 to construct an intermediate coverage resource of 1,019 long-read genomes sampled within 26 human populations from the 1000 Genomes Project. By integrating linear and graph-based approaches for SV analysis via pangenome graph-augmentation, we uncover 167,291 sequence-resolved SVs in these samples, considerably advancing SV characterization compared to population-wide short-read sequencing studies 3,4 . Our analysis details diverse SV classes-deletions, duplications, insertions, and inversions-at population-scale. LINE-1 and SVA retrotransposition activities frequently mediate transductions 9,10 of unique sequences, with both mobile element classes transducing sequences at either the 3'- or 5'-end, depending on the source element locus. Furthermore, analyses of SV breakpoint junctions suggest a continuum of homology-mediated rearrangement processes are integral to SV formation, and highlight evidence for SV recurrence involving repeat sequences. Our open-access dataset underscores the transformative impact of long-read sequencing in advancing the characterisation of polymorphic genomic architectures, and provides a resource for guiding variant prioritisation in future long-read sequencing-based disease studies.
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Darian JC, Kundu R, Rajaby R, Sung WK. Constructing telomere-to-telomere diploid genome by polishing haploid nanopore-based assembly. Nat Methods 2024; 21:574-583. [PMID: 38459383 DOI: 10.1038/s41592-023-02141-1] [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: 09/08/2022] [Accepted: 11/30/2023] [Indexed: 03/10/2024]
Abstract
Draft genomes generated from Oxford Nanopore Technologies (ONT) long reads are known to have a higher error rate. Although existing genome polishers can enhance their quality, the error rate (including mismatches, indels and switching errors between paternal and maternal haplotypes) can be significant. Here, we develop two polishers, hypo-short and hypo-hybrid to address this issue. Hypo-short utilizes Illumina short reads to polish an ONT-based draft assembly, resulting in a high-quality assembly with low error rates and switching errors. Expanding on this, hypo-hybrid incorporates ONT long reads to further refine the assembly into a diploid representation. Leveraging on hypo-hybrid, we have created a diploid genome assembly pipeline called hypo-assembler. Hypo-assembler automates the generation of highly accurate, contiguous and nearly complete diploid assemblies using ONT long reads, Illumina short reads and optionally Hi-C reads. Notably, our solution even allows for the production of telomere-to-telomere diploid genomes with additional manual steps. As a proof of concept, we successfully assembled a fully phased telomere-to-telomere diploid genome of HG00733, achieving a quality value exceeding 50.
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Affiliation(s)
| | - Ritu Kundu
- School of Computing, National University of Singapore, Singapore, Singapore
| | | | - Wing-Kin Sung
- School of Computing, National University of Singapore, Singapore, Singapore.
- Genome Institute of Singapore, Singapore, Singapore.
- Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong, China.
- JC STEM Laboratory of Computational Genomics, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China.
- Hong Kong Genome Institute, Hong Kong, China.
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5
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Mao Y, Harvey WT, Porubsky D, Munson KM, Hoekzema K, Lewis AP, Audano PA, Rozanski A, Yang X, Zhang S, Yoo D, Gordon DS, Fair T, Wei X, Logsdon GA, Haukness M, Dishuck PC, Jeong H, Del Rosario R, Bauer VL, Fattor WT, Wilkerson GK, Mao Y, Shi Y, Sun Q, Lu Q, Paten B, Bakken TE, Pollen AA, Feng G, Sawyer SL, Warren WC, Carbone L, Eichler EE. Structurally divergent and recurrently mutated regions of primate genomes. Cell 2024; 187:1547-1562.e13. [PMID: 38428424 PMCID: PMC10947866 DOI: 10.1016/j.cell.2024.01.052] [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: 03/28/2023] [Revised: 11/26/2023] [Accepted: 01/31/2024] [Indexed: 03/03/2024]
Abstract
We sequenced and assembled using multiple long-read sequencing technologies the genomes of chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, owl monkey, and marmoset. We identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. We estimate that 819.47 Mbp or ∼27% of the genome has been affected by SVs across primate evolution. We identify 1,607 structurally divergent regions wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (e.g., CARD, C4, and OLAH gene families) and additional lineage-specific genes are generated (e.g., CKAP2, VPS36, ACBD7, and NEK5 paralogs), becoming targets of rapid chromosomal diversification and positive selection (e.g., RGPD gene family). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species.
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Affiliation(s)
- Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China.
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Allison Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xiangyu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Xiaoxi Wei
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ricardo Del Rosario
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vanessa L Bauer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Will T Fattor
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Gregory K Wilkerson
- Department of Veterinary Sciences, Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA; Department of Clinical Sciences, North Carolina State University, Raleigh, NC, USA
| | - Yuxiang Mao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Qiang Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Qing Lu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Guoping Feng
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sara L Sawyer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Wesley C Warren
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA; Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA; Institute of Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Lucia Carbone
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA; Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA; Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, 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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Guitart X, Porubsky D, Yoo D, Dougherty ML, Dishuck PC, Munson KM, Lewis AP, Hoekzema K, Knuth J, Chang S, Pastinen T, Eichler EE. Independent expansion, selection and hypervariability of the TBC1D3 gene family in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.12.584650. [PMID: 38654825 PMCID: PMC11037872 DOI: 10.1101/2024.03.12.584650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
TBC1D3 is a primate-specific gene family that has expanded in the human lineage and has been implicated in neuronal progenitor proliferation and expansion of the frontal cortex. The gene family and its expression have been challenging to investigate because it is embedded in high-identity and highly variable segmental duplications. We sequenced and assembled the gene family using long-read sequencing data from 34 humans and 11 nonhuman primate species. Our analysis shows that this particular gene family has independently duplicated in at least five primate lineages, and the duplicated loci are enriched at sites of large-scale chromosomal rearrangements on chromosome 17. We find that most humans vary along two TBC1D3 clusters where human haplotypes are highly variable in copy number, differing by as many as 20 copies, and structure (structural heterozygosity 90%). We also show evidence of positive selection, as well as a significant change in the predicted human TBC1D3 protein sequence. Lastly, we find that, despite multiple duplications, human TBC1D3 expression is limited to a subset of copies and, most notably, from a single paralog group: TBC1D3-CDKL. These observations may help explain why a gene potentially important in cortical development can be so variable in the human population.
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Affiliation(s)
- Xavi Guitart
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Max L. Dougherty
- Tisch Cancer Institute, Division of Hematology and Medical Oncology, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jordan Knuth
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Stephen Chang
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA
| | - Tomi Pastinen
- Department of Pediatrics, Genomic Medicine Center, Children’s Mercy Kansas City, Kansas City, MO, USA
- Department of Pediatrics, School of Medicine, University of Missouri Kansas City, Kansas City, MO, 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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Zhou Q, Ghezelji M, Hari A, Ford MKB, Holley C, Mirabello L, Chanock S, Sahinalp SC, Numanagić I. Geny: A Genotyping Tool for Allelic Decomposition of Killer Cell Immunoglobulin-Like Receptor Genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.27.582413. [PMID: 38529502 PMCID: PMC10962708 DOI: 10.1101/2024.02.27.582413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Accurate genotyping of Killer cell Immunoglobulin-like Receptor (KIR) genes plays a pivotal role in enhancing our understanding of innate immune responses, disease correlations, and the advancement of personalized medicine. However, due to the high variability of the KIR region and high level of sequence similarity among different KIR genes, the currently available genotyping methods are unable to accurately infer copy numbers, genotypes and haplotypes of individual KIR genes from next-generation sequencing data. Here we introduce Geny, a new computational tool for precise genotyping of KIR genes. Geny utilizes available KIR haplotype databases and proposes a novel combination of expectation-maximization filtering schemes and integer linear programming-based combinatorial optimization models to resolve ambiguous reads, provide accurate copy number estimation and estimate the haplotype of each copy for the genes within the KIR region. We evaluated Geny on a large set of simulated short-read datasets covering the known validated KIR region assemblies and a set of Illumina short-read samples sequenced from 25 validated samples from the Human Pangenome Reference Consortium collection and showed that it outperforms the existing genotyping tools in terms of accuracy, precision and recall. We envision Geny becoming a valuable resource for understanding immune system response and consequently advancing the field of patient-centric medicine.
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8
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Wang H, Chang TS, Dombroski BA, Cheng PL, Si YQ, Tucci A, Patil V, Valiente-Banuet L, Farrell K, Mclean C, Molina-Porcel L, Alex R, Paul De Deyn P, Le Bastard N, Gearing M, Donker Kaat L, Van Swieten JC, Dopper E, Ghetti BF, Newell KL, Troakes C, G de Yébenes J, Rábano-Gutierrez A, Meller T, Oertel WH, Respondek G, Stamelou M, Arzberger T, Roeber S, Müller U, Hopfner F, Pastor P, Brice A, Durr A, Ber IL, Beach TG, Serrano GE, Hazrati LN, Litvan I, Rademakers R, Ross OA, Galasko D, Boxer AL, Miller BL, Seeley WW, Van Deerlin VM, Lee EB, White CL, Morris HR, de Silva R, Crary JF, Goate AM, Friedman JS, Leung YY, Coppola G, Naj AC, Wang LS, Dickson DW, Höglinger GU, Tzeng JY, Geschwind DH, Schellenberg GD, Lee WP. Association of Structural Forms of 17q21.31 with the Risk of Progressive Supranuclear Palsy and MAPT Sub-haplotypes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.26.24303379. [PMID: 38464214 PMCID: PMC10925353 DOI: 10.1101/2024.02.26.24303379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Importance The chromosome 17q21.31 region, containing a 900 Kb inversion that defines H1 and H2 haplotypes, represents the strongest genetic risk locus in progressive supranuclear palsy (PSP). In addition to H1 and H2, various structural forms of 17q21.31, characterized by the copy number of α, β, and γ duplications, have been identified. However, the specific effect of each structural form on the risk of PSP has never been evaluated in a large cohort study. Objective To assess the association of different structural forms of 17q.21.31, defined by the copy numbers of α, β, and γ duplications, with the risk of PSP and MAPT sub-haplotypes. Design setting and participants Utilizing whole genome sequencing data of 1,684 (1,386 autopsy confirmed) individuals with PSP and 2,392 control subjects, a case-control study was conducted to investigate the association of copy numbers of α, β, and γ duplications and structural forms of 17q21.31 with the risk of PSP. All study subjects were selected from the Alzheimer's Disease Sequencing Project (ADSP) Umbrella NG00067.v7. Data were analyzed between March 2022 and November 2023. Main outcomes and measures The main outcomes were the risk (odds ratios [ORs]) for PSP with 95% CIs. Risks for PSP were evaluated by logistic regression models. Results The copy numbers of α and β were associated with the risk of PSP only due to their correlation with H1 and H2, while the copy number of γ was independently associated with the increased risk of PSP. Each additional duplication of γ was associated with 1.10 (95% CI, 1.04-1.17; P = 0.0018) fold of increased risk of PSP when conditioning H1 and H2. For the H1 haplotype, addition γ duplications displayed a higher odds ratio for PSP: the odds ratio increases from 1.21 (95%CI 1.10-1.33, P = 5.47 × 10-5) for H1β1γ1 to 1.29 (95%CI 1.16-1.43, P = 1.35 × 10-6) for H1β1γ2, 1.45 (95%CI 1.27-1.65, P = 3.94 × 10-8) for H1β1γ3, and 1.57 (95%CI 1.10-2.26, P = 1.35 × 10-2) for H1β1γ4. Moreover, H1β1γ3 is in linkage disequilibrium with H1c (R2 = 0.31), a widely recognized MAPT sub-haplotype associated with increased risk of PSP. The proportion of MAPT sub-haplotypes associated with increased risk of PSP (i.e., H1c, H1d, H1g, H1o, and H1h) increased from 34% in H1β1γ1 to 77% in H1β1γ4. Conclusions and relevance This study revealed that the copy number of γ was associated with the risk of PSP independently from H1 and H2. The H1 haplotype with more γ duplications showed a higher odds ratio for PSP and were associated with MAPT sub-haplotypes with increased risk of PSP. These findings expand our understanding of how the complex structure at 17q21.31 affect the risk of PSP.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy S Chang
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Beth A Dombroski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Po-Liang Cheng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ya-Qin Si
- Bioinformatics Research Center, North Carolina State University, NC, USA
| | - Albert Tucci
- Bioinformatics Research Center, North Carolina State University, NC, USA
| | - Vishakha Patil
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Leopoldo Valiente-Banuet
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kurt Farrell
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer’s Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Catriona Mclean
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Laura Molina-Porcel
- Alzheimer’s disease and other cognitive disorders unit. Neurology Service, Hospital Clínic, Fundació Recerca Clínic Barcelona (FRCB). Institut d’Investigacions Biomediques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Neurological Tissue Bank of the Biobanc-Hospital Clínic-IDIBAPS, Barcelona, Spain
| | - Rajput Alex
- Movement Disorders Program, Division of Neurology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Peter Paul De Deyn
- Laboratory of Neurochemistry and Behavior, Experimental Neurobiology Unit, University of Antwerp, Wilrijk (Antwerp), Belgium
- Department of Neurology, University Medical Center Groningen, NL-9713 AV Groningen, Netherlands
| | | | - Marla Gearing
- Department of Pathology and Laboratory Medicine and Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | - Elise Dopper
- Netherlands Brain Bank and Erasmus University, Netherlands
| | - Bernardino F Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathy L Newell
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Claire Troakes
- London Neurodegenerative Diseases Brain Bank, King’s College London, London, UK
| | | | - Alberto Rábano-Gutierrez
- Fundación CIEN (Centro de Investigación de Enfermedades Neurológicas) - Centro Alzheimer Fundación Reina Sofía, Madrid, Spain
| | - Tina Meller
- Department of Neurology, Philipps-Universität, Marburg, Germany
| | | | - Gesine Respondek
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Maria Stamelou
- Parkinson’s disease and Movement Disorders Department, HYGEIA Hospital, Athens, Greece
- European University of Cyprus, Nicosia, Cyprus
| | - Thomas Arzberger
- Department of Psychiatry and Psychotherapy, University Hospital Munich, Ludwig-Maximilians-University Munich, Germany
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Germany
| | | | | | - Franziska Hopfner
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität (LMU) München; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Pau Pastor
- Unit of Neurodegenerative diseases, Department of Neurology, University Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain
- Neurosciences, The Germans Trias i Pujol Research Institute (IGTP) Badalona, Badalona, Spain
| | - Alexis Brice
- Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | | | | | | | - Irene Litvan
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Rosa Rademakers
- VIB Center for Molecular Neurology, University of Antwerp, Belgium
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA
| | - Douglas Galasko
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Adam L Boxer
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Willian W Seeley
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Vivianna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Charles L White
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Huw R Morris
- Departmento of Clinical and Movement Neuroscience, University College of London, London, UK
| | - Rohan de Silva
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, UK
| | - John F Crary
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer’s Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison M Goate
- Department of Genetics and Genomic Sciences, New York, NY, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jeffrey S Friedman
- Friedman Bioventure, Inc., Del Mar, CA, USA: Department of Genetics and Genomic Sciences, New York, NY, USA
| | - Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Giovanni Coppola
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Adam C Naj
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Günter U Höglinger
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität (LMU) München; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Jung-Ying Tzeng
- Bioinformatics Research Center, North Carolina State University, NC, USA
- Department of Statistics, North Carolina State University, NC, USA
| | - Daniel H Geschwind
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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9
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Aversano R, Iovene M, Esposito S, L'Abbate A, Villano C, Di Serio E, Cardone MF, Bergamini C, Cigliano RA, D'Amelia V, Frusciante L, Carputo D. Distinct structural variants and repeat landscape shape the genomes of the ancient grapes Aglianico and Falanghina. BMC PLANT BIOLOGY 2024; 24:88. [PMID: 38317087 PMCID: PMC10845522 DOI: 10.1186/s12870-024-04778-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 01/29/2024] [Indexed: 02/07/2024]
Abstract
Mounting evidence recognizes structural variations (SVs) and repetitive DNA sequences as crucial players in shaping the existing grape phenotypic diversity at intra- and inter-species levels. To deepen our understanding on the abundance, diversity, and distribution of SVs and repetitive DNAs, including transposable elements (TEs) and tandemly repeated satellite DNA (satDNAs), we re-sequenced the genomes of the ancient grapes Aglianico and Falanghina. The analysis of large copy number variants (CNVs) detected candidate polymorphic genes that are involved in the enological features of these varieties. In a comparative analysis of Aglianico and Falanghina sequences with 21 publicly available genomes of cultivated grapes, we provided a genome-wide annotation of grape TEs at the lineage level. We disclosed that at least two main clusters of grape cultivars could be identified based on the TEs content. Multiple TEs families appeared either significantly enriched or depleted. In addition, in silico and cytological analyses provided evidence for a diverse chromosomal distribution of several satellite repeats between Aglianico, Falanghina, and other grapes. Overall, our data further improved our understanding of the intricate grape diversity held by two Italian traditional varieties, unveiling a pool of unique candidate genes never so far exploited in breeding for improved fruit quality.
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Affiliation(s)
- Riccardo Aversano
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy.
| | - Marina Iovene
- Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy.
| | - Salvatore Esposito
- Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy
- Research Centre for Cereal and Industrial Crops, Council for Agricultural Research and Economics (CREA-CI), Foggia, Italy
| | - Alberto L'Abbate
- Institute of Biomembranes, Bioenergetics, and Molecular Biotechnologies, National Research Council (IBIOM-CNR), Bari, Italy
| | - Clizia Villano
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
| | - Ermanno Di Serio
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
| | - Maria Francesca Cardone
- Research Centre for Viticulture and Enology, Council for Agricultural Research and Economics (CREA-VE), Turi, Italy
| | - Carlo Bergamini
- Research Centre for Viticulture and Enology, Council for Agricultural Research and Economics (CREA-VE), Turi, Italy
| | | | - Vincenzo D'Amelia
- Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy
| | - Luigi Frusciante
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
| | - Domenico Carputo
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
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10
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Huttner WB, Heide M, Mora-Bermúdez F, Namba T. Neocortical neurogenesis in development and evolution-Human-specific features. J Comp Neurol 2024; 532:e25576. [PMID: 38189676 DOI: 10.1002/cne.25576] [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: 09/06/2023] [Revised: 12/11/2023] [Accepted: 12/17/2023] [Indexed: 01/09/2024]
Abstract
In this review, we focus on human-specific features of neocortical neurogenesis in development and evolution. Two distinct topics will be addressed. In the first section, we discuss the expansion of the neocortex during human evolution and concentrate on the human-specific gene ARHGAP11B. We review the ability of ARHGAP11B to amplify basal progenitors and to expand a primate neocortex. We discuss the contribution of ARHGAP11B to neocortex expansion during human evolution and its potential implications for neurodevelopmental disorders and brain tumors. We then review the action of ARHGAP11B in mitochondria as a regulator of basal progenitor metabolism, and how it promotes glutaminolysis and basal progenitor proliferation. Finally, we discuss the increase in cognitive performance due to the ARHGAP11B-induced neocortical expansion. In the second section, we focus on neocortical development in modern humans versus Neanderthals. Specifically, we discuss two recent findings pointing to differences in neocortical neurogenesis between these two hominins that are due to a small number of amino acid substitutions in certain key proteins. One set of such proteins are the kinetochore-associated proteins KIF18a and KNL1, where three modern human-specific amino acid substitutions underlie the prolongation of metaphase during apical progenitor mitosis. This prolongation in turn is associated with an increased fidelity of chromosome segregation to the apical progenitor progeny during modern human neocortical development, with implications for the proper formation of radial units. Another such key protein is transketolase-like 1 (TKTL1), where a single modern human-specific amino acid substitution endows TKTL1 with the ability to amplify basal radial glia, resulting in an increase in upper-layer neuron generation. TKTL1's ability is based on its action in the pentose phosphate pathway, resulting in increased fatty acid synthesis. The data imply greater neurogenesis during neocortical development in modern humans than Neanderthals due to TKTL1, in particular in the developing frontal lobe.
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Affiliation(s)
- Wieland B Huttner
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Michael Heide
- German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
| | | | - Takashi Namba
- Neuroscience Center, HiLIFE - Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
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11
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Lee S, Clémentine C, Kim H. Exploring the genetic factors behind the discrepancy in resistance to bovine tuberculosis between African zebu cattle and European taurine cattle. Sci Rep 2024; 14:2370. [PMID: 38287127 PMCID: PMC10824790 DOI: 10.1038/s41598-024-52606-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/21/2024] [Indexed: 01/31/2024] Open
Abstract
Caused by the pathogenic agent Mycobacterium bovis, bovine tuberculosis (bTB) is a major concern in cattle breeding due to both its zoonotic potential and economic impact. Greater resistance to this disease has been reported in certain African zebu breeds compared to European taurine breeds. However the genetic basis for the lower susceptibility to bTB infection observed in zebu cattle remains poorly explored. This study was conducted on whole genome sequencing data of three bTB infection-resistant African zebu breeds and two bTB infection-susceptible taurine breeds to decipher the genetic background. A set of four selection signature statistics based on linkage disequilibrium, site frequency spectrum, and population differentiation were used on SNPs whereas between population variance based VST and t-test were used on CNVs. As a complement, genes from previous literature reported as candidate genes for bTB resistance were also inspected to identify genetic variations. Interestingly, the resulting nine candidate genes had deleterious missense variants (SHC3, IFNGR1, TLR2, TLR6, IL1A, LRRK2, EP300 and IRAK4) or a CNV difference (CD48) segregating between the groups. The genes found in the study play a role in immune pathways activated during Mycobacterium infection, contributing to the proliferation of immune cells and the granuloma formation, ultimately modulating the outcome of the infectious event. In particular, a deleterious variant in the LRRK2 gene, whose deficiency has been linked to improved prognosis upon tuberculosis infection, was found in the bTB infection-resistant zebu breeds. Therefore, these genes constitute credible candidates in explaining the discrepancy in Mycobacterium bovis infection susceptibility among different breed.
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Affiliation(s)
- SangJung Lee
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Charton Clémentine
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Heebal Kim
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
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12
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Irving-Pease EK, Refoyo-Martínez A, Barrie W, Ingason A, Pearson A, Fischer A, Sjögren KG, Halgren AS, Macleod R, Demeter F, Henriksen RA, Vimala T, McColl H, Vaughn AH, Speidel L, Stern AJ, Scorrano G, Ramsøe A, Schork AJ, Rosengren A, Zhao L, Kristiansen K, Iversen AKN, Fugger L, Sudmant PH, Lawson DJ, Durbin R, Korneliussen T, Werge T, Allentoft ME, Sikora M, Nielsen R, Racimo F, Willerslev E. The selection landscape and genetic legacy of ancient Eurasians. Nature 2024; 625:312-320. [PMID: 38200293 PMCID: PMC10781624 DOI: 10.1038/s41586-023-06705-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 10/03/2023] [Indexed: 01/12/2024]
Abstract
The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.
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Affiliation(s)
- Evan K Irving-Pease
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Alba Refoyo-Martínez
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - William Barrie
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Andrés Ingason
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
| | - Alice Pearson
- Department of Genetics, University of Cambridge, Cambridge, UK
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Anders Fischer
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
- Sealand Archaeology, Kalundborg, Denmark
| | - Karl-Göran Sjögren
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
| | - Alma S Halgren
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - Ruairidh Macleod
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- UCL Genetics Institute, University College London, London, UK
| | - Fabrice Demeter
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Eco-anthropologie, Muséum national d'Histoire naturelle, CNRS, Université Paris Cité, Musée de l'Homme, Paris, France
| | - Rasmus A Henriksen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Tharsika Vimala
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Hugh McColl
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Andrew H Vaughn
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Leo Speidel
- UCL Genetics Institute, University College London, London, UK
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Aaron J Stern
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Gabriele Scorrano
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Abigail Ramsøe
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
| | - Anders Rosengren
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
| | - Lei Zhao
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Kristian Kristiansen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
| | - Astrid K N Iversen
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
- MRC Human Immunology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Daniel J Lawson
- Institute of Statistical Sciences, School of Mathematics, University of Bristol, Bristol, UK
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
| | - Thorfinn Korneliussen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Werge
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
| | - Morten E Allentoft
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Trace and Environmental DNA (TrEnD) Laboratory, School of Molecular and Life Science, Curtin University, Perth, Western Australia, Australia
| | - Martin Sikora
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rasmus Nielsen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
- Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA, USA.
| | - Fernando Racimo
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Eske Willerslev
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK.
- MARUM Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany.
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13
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Safdar M, Ullah M, Wahab A, Hamayun S, Ur Rehman M, Khan MA, Khan SU, Ullah A, Din FU, Awan UA, Naeem M. Genomic insights into heart health: Exploring the genetic basis of cardiovascular disease. Curr Probl Cardiol 2024; 49:102182. [PMID: 37913933 DOI: 10.1016/j.cpcardiol.2023.102182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 10/28/2023] [Indexed: 11/03/2023]
Abstract
Cardiovascular diseases (CVDs) are considered as the leading cause of death worldwide. CVD continues to be a major cause of death and morbidity despite significant improvements in its detection and treatment. Therefore, it is strategically important to be able to precisely characterize an individual's sensitivity to certain illnesses. The discovery of genes linked to cardiovascular illnesses has benefited from linkage analysis and genome-wide association research. The last 20 years have seen significant advancements in the field of molecular genetics, particularly with the development of new tools like genome-wide association studies. In this article we explore the profound impact of genetic variations on disease development, prognosis, and therapeutic responses. And the significance of genetics in cardiovascular risk assessment and the ever-evolving realm of genetic testing, offering insights into the potential for personalized medicine in this domain. Embracing the future of cardiovascular care, the article explores the implications of pharmacogenomics for tailored treatments, the promise of emerging technologies in cardiovascular genetics and therapies, including the transformative influence of nanotechnology. Furthermore, it delves into the exciting frontiers of gene editing, such as CRISPR/Cas9, as a novel approach to combat cardiovascular diseases. And also explore the potential of stem cell therapy and regenerative medicine, providing a holistic view of the dynamic landscape of cardiovascular genomics and its transformative potential for the field of cardiovascular medicine.
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Affiliation(s)
- Mishal Safdar
- Department of Biological Sciences, National University of Medical Sciences (NUMS) Rawalpindi 46000, Punjab, Pakistan
| | - Muneeb Ullah
- Department of Pharmacy, Kohat University of Science, and technology (KUST), Kohat, 26000, Khyber Pakhtunkhwa, Pakistan
| | - Abdul Wahab
- Department of Pharmacy, Kohat University of Science, and technology (KUST), Kohat, 26000, Khyber Pakhtunkhwa, Pakistan
| | - Shah Hamayun
- Department of Cardiology, Pakistan Institute of Medical Sciences (PIMS), Islamabad, 04485 Punjab, Pakistan
| | - Mahboob Ur Rehman
- Department of Cardiology, Pakistan Institute of Medical Sciences (PIMS), Islamabad, 04485 Punjab, Pakistan
| | - Muhammad Amir Khan
- Department of Foreign Medical education, Fergana Medical institute of Public Health, 2A Yangi Turon street, Fergana 150100, Uzbekistan
| | - Shahid Ullah Khan
- Department of Biochemistry, Women Medical and Dental College, Khyber Medical University, Abbottabad, 22080, Khyber Pakhtunkhwa, Pakistan
| | - Aziz Ullah
- Department of Chemical Engineering, Pukyong National University, Busan 48513, Republic of Korea
| | - Fakhar Ud Din
- Department of Pharmacy, Quaid-i-Azam University, 45320, Islamabad, Pakistan
| | - Uzma Azeem Awan
- Department of Biological Sciences, National University of Medical Sciences (NUMS) Rawalpindi 46000, Punjab, Pakistan
| | - Muhammad Naeem
- Department of Biological Sciences, National University of Medical Sciences (NUMS) Rawalpindi 46000, Punjab, Pakistan.
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14
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Wilfinger WW, Eghbalnia HR, Mackey K, Miller R, Chomczynski P. Whole blood RNA extraction efficiency contributes to variability in RNA sequencing data sets. PLoS One 2023; 18:e0291209. [PMID: 37972054 PMCID: PMC10653446 DOI: 10.1371/journal.pone.0291209] [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: 02/28/2023] [Accepted: 08/23/2023] [Indexed: 11/19/2023] Open
Abstract
Numerous methodologies are used for blood RNA extraction, and large quantitative differences in recovered RNA content are reported. We evaluated three archived data sets to determine how extraction methodologies might influence mRNA and lncRNA sequencing results. The total quantity of RNA recovered /ml of blood affects RNA sequencing by impacting the recovery of weakly expressed mRNA, and lncRNA transcripts. Transcript expression (TPM counts) plotted in relation to transcript size (base pairs, bp) revealed a 30% loss of short to midsized transcripts in some data sets. Quantitative recovery of RNA is of considerable importance, and it should be viewed more judiciously. Transcripts common to the three data sets were subsequently normalized and transcript mean TPM counts and TPM count coefficient of variation (CV) were plotted in relation to increasing transcript size. Regression analysis of mean TPM counts versus transcript size revealed negative slopes in two of the three data sets suggesting a reduction of TPM transcript counts with increasing transcript size. In the third data set, the regression slope line of mRNA transcript TPM counts approximates zero and TPM counts increased in proportion to transcript size over a range of 200 to 30,000 bp. Similarly, transcript TPM count CV values also were uniformly distributed over the range of transcript sizes. In the other data sets, the regression CV slopes increased in relation to transcript size. The recovery of weakly expressed and /or short to midsized mRNA and lncRNA transcripts varies with different RNA extraction methodologies thereby altering the fundamental sequencing relationship between transcript size and TPM counts. Our analysis identifies differences in RNA sequencing results that are dependent upon the quantity of total RNA recovery from whole blood. We propose that incomplete RNA extraction directly impacts the recovery of mRNA and lncRNA transcripts from human blood and speculate these differences contribute to the "batch" effects commonly identified between sequencing results from different archived data sets.
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Affiliation(s)
| | - Hamid R. Eghbalnia
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT, United States of America
| | - Karol Mackey
- Molecular Research Center, Inc. Cincinnati, OH, United States of America
| | - Robert Miller
- Robert Miller Enterprises, LLC, Cincinnati, OH, United States of America
| | - Piotr Chomczynski
- Molecular Research Center, Inc. Cincinnati, OH, United States of America
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15
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Meng X, Lin Q, Zeng X, Jiang J, Li M, Luo X, Chen K, Wu H, Hu Y, Liu C, Su B. Brain developmental and cortical connectivity changes in transgenic monkeys carrying the human-specific duplicated gene SRGAP2C. Natl Sci Rev 2023; 10:nwad281. [PMID: 38090550 PMCID: PMC10712708 DOI: 10.1093/nsr/nwad281] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/18/2023] [Accepted: 11/01/2023] [Indexed: 02/12/2024] Open
Abstract
Human-specific duplicated genes contributed to phenotypic innovations during the origin of our own species, such as an enlarged brain and highly developed cognitive abilities. While prior studies on transgenic mice carrying the human-specific SRGAP2C gene have shown enhanced brain connectivity, the relevance to humans remains unclear due to the significant evolutionary gap between humans and rodents. In this study, to investigate the phenotypic outcome and underlying genetic mechanism of SRGAP2C, we generated transgenic cynomolgus macaques (Macaca fascicularis) carrying the human-specific SRGAP2C gene. Longitudinal MRI imaging revealed delayed brain development with region-specific volume changes, accompanied by altered myelination levels in the temporal and occipital regions. On a cellular level, the transgenic monkeys exhibited increased deep-layer neurons during fetal neurogenesis and delayed synaptic maturation in adolescence. Moreover, transcriptome analysis detected neotenic expression in molecular pathways related to neuron ensheathment, synaptic connections, extracellular matrix and energy metabolism. Cognitively, the transgenic monkeys demonstrated improved motor planning and execution skills. Together, our findings provide new insights into the mechanisms by which the newly evolved gene shapes the unique development and circuitry of the human brain.
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Affiliation(s)
- Xiaoyu Meng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Qiang Lin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Xuerui Zeng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Jin Jiang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Min Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Xin Luo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
| | - Kaimin Chen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Haixu Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Yan Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Cirong Liu
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
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16
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Steyaert W, Haer-Wigman L, Pfundt R, Hellebrekers D, Steehouwer M, Hampstead J, de Boer E, Stegmann A, Yntema H, Kamsteeg EJ, Brunner H, Hoischen A, Gilissen C. Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation. Nat Commun 2023; 14:6845. [PMID: 37891200 PMCID: PMC10611741 DOI: 10.1038/s41467-023-42531-9] [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: 11/22/2022] [Accepted: 10/13/2023] [Indexed: 10/29/2023] Open
Abstract
The short lengths of short-read sequencing reads challenge the analysis of paralogous genomic regions in exome and genome sequencing data. Most genetic variants within these homologous regions therefore remain unidentified in standard analyses. Here, we present a method (Chameleolyser) that accurately identifies single nucleotide variants and small insertions/deletions (SNVs/Indels), copy number variants and ectopic gene conversion events in duplicated genomic regions using whole-exome sequencing data. Application to a cohort of 41,755 exome samples yields 20,432 rare homozygous deletions and 2,529,791 rare SNVs/Indels, of which we show that 338,084 are due to gene conversion events. None of the SNVs/Indels are detectable using regular analysis techniques. Validation by high-fidelity long-read sequencing in 20 samples confirms >88% of called variants. Focusing on variation in known disease genes leads to a direct molecular diagnosis in 25 previously undiagnosed patients. Our method can readily be applied to existing exome data.
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Affiliation(s)
- Wouter Steyaert
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands
| | - Lonneke Haer-Wigman
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Rolph Pfundt
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Debby Hellebrekers
- Maastricht University Medical Center + , Department of Clinical Genetics, Maastricht, Netherlands
| | - Marloes Steehouwer
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Juliet Hampstead
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Elke de Boer
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Alexander Stegmann
- Maastricht University Medical Center + , Department of Clinical Genetics, Maastricht, Netherlands
| | - Helger Yntema
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Erik-Jan Kamsteeg
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Han Brunner
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Maastricht University Medical Center + , Department of Clinical Genetics, Maastricht, Netherlands
| | - Alexander Hoischen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands
- Radboud University Medical Center, Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Nijmegen, Netherlands
| | - Christian Gilissen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands.
- Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands.
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17
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Clifton BD, Hariyani I, Kimura A, Luo F, Nguyen A, Ranz JM. Paralog transcriptional differentiation in the D. melanogaster-specific gene family Sdic across populations and spermatogenesis stages. Commun Biol 2023; 6:1069. [PMID: 37864070 PMCID: PMC10589255 DOI: 10.1038/s42003-023-05427-4] [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: 05/12/2023] [Accepted: 10/05/2023] [Indexed: 10/22/2023] Open
Abstract
How recently originated gene copies become stable genomic components remains uncertain as high sequence similarity of young duplicates precludes their functional characterization. The tandem multigene family Sdic is specific to Drosophila melanogaster and has been annotated across multiple reference-quality genome assemblies. Here we show the existence of a positive correlation between Sdic copy number and total expression, plus vast intrastrain differences in mRNA abundance among paralogs, using RNA-sequencing from testis of four strains with variable paralog composition. Single cell and nucleus RNA-sequencing data expose paralog expression differentiation in meiotic cell types within testis from third instar larva and adults. Additional RNA-sequencing across synthetic strains only differing in their Y chromosomes reveal a tissue-dependent trans-regulatory effect on Sdic: upregulation in testis and downregulation in male accessory gland. By leveraging paralog-specific expression information from tissue- and cell-specific data, our results elucidate the intraspecific functional diversification of a recently expanded tandem gene family.
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Affiliation(s)
- Bryan D Clifton
- Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA.
| | - Imtiyaz Hariyani
- Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA
| | - Ashlyn Kimura
- Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA
| | - Fangning Luo
- Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA
| | - Alvin Nguyen
- Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA
| | - José M Ranz
- Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, CA, 92697, USA.
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18
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Wang Z, Liu Y, Wang H, Roy A, Liu H, Han F, Zhang X, Lu Q. Genome and transcriptome of Ips nitidus provide insights into high-altitude hypoxia adaptation and symbiosis. iScience 2023; 26:107793. [PMID: 37731610 PMCID: PMC10507238 DOI: 10.1016/j.isci.2023.107793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 05/15/2023] [Accepted: 08/29/2023] [Indexed: 09/22/2023] Open
Abstract
Ips nitidus is a well-known conifer pest that has contributed significantly to spruce forest disturbance in the Qinghai-Tibet Plateau and seriously threatens the ecological balance of these areas. We report a chromosome-level genome of I. nitidus determined by PacBio and Hi-C technology. Phylogenetic inference showed that it diverged from the common ancestor of I. typographus ∼2.27 mya. Gene family expansion in I. nitidus was characterized by DNA damage repair and energy metabolism, which may facilitate adaptation to high-altitude hypoxia. Interestingly, differential gene expression analysis revealed upregulated genes associated with high-altitude hypoxia adaptation and downregulated genes associated with detoxification after feeding and tunneling in fungal symbiont Ophiostoma bicolor-colonized substrates. Our findings provide evidence of the potential adaptability of I. nitidus to conifer host, high-altitude hypoxia and insight into how fungal symbiont assist in this process. This study enhances our understanding of insect adaptation, symbiosis, and pest management.
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Affiliation(s)
- Zheng Wang
- Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
- Shandong Research Center for Forestry Harmful Biological Control Engineering and Technology, College of Plant Protection, Shandong Agricultural University, Tai’an 271018, China
| | - Ya Liu
- Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
| | - Huimin Wang
- Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
| | - Amit Roy
- Faculty of Forestry and Wood Sciences, EXTEMIT-K and EVA.4.0 Unit, Czech University of Life Sciences, Kamýcká 1176, Prague 6, 165 00 Suchdol, Czech Republic
| | - Huixiang Liu
- Shandong Research Center for Forestry Harmful Biological Control Engineering and Technology, College of Plant Protection, Shandong Agricultural University, Tai’an 271018, China
| | | | - Xingyao Zhang
- Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
| | - Quan Lu
- Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
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19
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Pajuste FD, Remm M. GeneToCN: an alignment-free method for gene copy number estimation directly from next-generation sequencing reads. Sci Rep 2023; 13:17765. [PMID: 37853040 PMCID: PMC10584998 DOI: 10.1038/s41598-023-44636-z] [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: 05/04/2023] [Accepted: 10/10/2023] [Indexed: 10/20/2023] Open
Abstract
Genomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specific k-mers in FASTQ files and uses this information to infer copy number of the gene. We validated the copy number predictions for amylase genes (AMY1, AMY2A, AMY2B) using experimental data from digital droplet PCR (ddPCR) on 39 individuals and observed a strong correlation (R = 0.99) between GeneToCN predictions and experimentally determined copy numbers. An additional validation on FCGR3 genes showed a higher concordance for FCGR3A compared to two other methods, but reduced accuracy for FCGR3B. We further tested the method on three different genomic regions (SMN, NPY4R, and LPA Kringle IV-2 domain). Predicted copy number distributions of these genes in a set of 500 individuals from the Estonian Biobank were in good agreement with the previously published studies. In addition, we investigated the possibility to use GeneToCN on sequencing data generated by different technologies by comparing copy number predictions from Illumina, PacBio, and Oxford Nanopore data of the same sample. Despite the differences in variability of k-mer frequencies, all three sequencing technologies give similar predictions with GeneToCN.
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Affiliation(s)
- Fanny-Dhelia Pajuste
- Institute of Molecular and Cell Biology, University of Tartu, 23 Riia Str., 51010, Tartu, Estonia.
| | - Maido Remm
- Institute of Molecular and Cell Biology, University of Tartu, 23 Riia Str., 51010, Tartu, Estonia
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20
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Kim CN, Shin D, Wang A, Nowakowski TJ. Spatiotemporal molecular dynamics of the developing human thalamus. Science 2023; 382:eadf9941. [PMID: 37824646 PMCID: PMC10758299 DOI: 10.1126/science.adf9941] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 09/15/2023] [Indexed: 10/14/2023]
Abstract
The thalamus plays a central coordinating role in the brain. Thalamic neurons are organized into spatially distinct nuclei, but the molecular architecture of thalamic development is poorly understood, especially in humans. To begin to delineate the molecular trajectories of cell fate specification and organization in the developing human thalamus, we used single-cell and multiplexed spatial transcriptomics. We show that molecularly defined thalamic neurons differentiate in the second trimester of human development and that these neurons organize into spatially and molecularly distinct nuclei. We identified major subtypes of glutamatergic neuron subtypes that are differentially enriched in anatomically distinct nuclei and six subtypes of γ-aminobutyric acid-mediated (GABAergic) neurons that are shared and distinct across thalamic nuclei.
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Affiliation(s)
- Chang N Kim
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 94143, USA
- Department of Anatomy, University of California, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - David Shin
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 94143, USA
- Department of Anatomy, University of California, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Albert Wang
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
| | - Tomasz J Nowakowski
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 94143, USA
- Department of Anatomy, University of California, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
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21
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Sharp NP, Smith DR, Driscoll G, Sun K, Vickerman CM, Martin SCT. Contribution of Spontaneous Mutations to Quantitative and Molecular Variation at the Highly Repetitive rDNA Locus in Yeast. Genome Biol Evol 2023; 15:evad179. [PMID: 37847861 PMCID: PMC10581546 DOI: 10.1093/gbe/evad179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2023] [Indexed: 10/19/2023] Open
Abstract
The ribosomal DNA array in Saccharomyces cerevisiae consists of many tandem repeats whose copy number is believed to be functionally important but highly labile. Regulatory mechanisms have evolved to maintain copy number by directed mutation, but how spontaneous variation at this locus is generated and selected has not been well characterized. We applied a mutation accumulation approach to quantify the impacts of mutation and selection on this unique genomic feature across hundreds of mutant strains. We find that mutational variance for this trait is relatively high, and that unselected mutations elsewhere in the genome can disrupt copy number maintenance. In consequence, copy number generally declines gradually, consistent with a previously proposed model of rDNA maintenance where a downward mutational bias is normally compensated by mechanisms that increase copy number when it is low. This pattern holds across ploidy levels and strains in the standard lab environment but differs under some stressful conditions. We identify several alleles, gene categories, and genomic features that likely affect copy number, including aneuploidy for chromosome XII. Copy number change is associated with reduced growth in diploids, consistent with stabilizing selection. Levels of standing variation in copy number are well predicted by a balance between mutation and stabilizing selection, suggesting this trait is not subject to strong diversifying selection in the wild. The rate and spectrum of point mutations within the rDNA locus itself are distinct from the rest of the genome and predictive of polymorphism locations. Our findings help differentiate the roles of mutation and selection and indicate that spontaneous mutation patterns shape several aspects of ribosomal DNA evolution.
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Affiliation(s)
- Nathaniel P Sharp
- Department of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Denise R Smith
- Department of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Gregory Driscoll
- Department of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Kexin Sun
- Present address: Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Sterling C T Martin
- Present address: Department of Biology, Washington University, St. Louis, Missouri, USA
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22
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Allou L, Mundlos S. Disruption of regulatory domains and novel transcripts as disease-causing mechanisms. Bioessays 2023; 45:e2300010. [PMID: 37381881 DOI: 10.1002/bies.202300010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 05/24/2023] [Accepted: 06/06/2023] [Indexed: 06/30/2023]
Abstract
Deletions, duplications, insertions, inversions, and translocations, collectively called structural variations (SVs), affect more base pairs of the genome than any other sequence variant. The recent technological advancements in genome sequencing have enabled the discovery of tens of thousands of SVs per human genome. These SVs primarily affect non-coding DNA sequences, but the difficulties in interpreting their impact limit our understanding of human disease etiology. The functional annotation of non-coding DNA sequences and methodologies to characterize their three-dimensional (3D) organization in the nucleus have greatly expanded our understanding of the basic mechanisms underlying gene regulation, thereby improving the interpretation of SVs for their pathogenic impact. Here, we discuss the various mechanisms by which SVs can result in altered gene regulation and how these mechanisms can result in rare genetic disorders. Beyond changing gene expression, SVs can produce novel gene-intergenic fusion transcripts at the SV breakpoints.
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Affiliation(s)
- Lila Allou
- RG Development & Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Mundlos
- RG Development & Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, Berlin, Germany
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23
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Mollon J, Schultz LM, Huguet G, Knowles EEM, Mathias SR, Rodrigue A, Alexander-Bloch A, Saci Z, Jean-Louis M, Kumar K, Douard E, Almasy L, Jacquemont S, Glahn DC. Impact of Copy Number Variants and Polygenic Risk Scores on Psychopathology in the UK Biobank. Biol Psychiatry 2023; 94:591-600. [PMID: 36764568 PMCID: PMC10409883 DOI: 10.1016/j.biopsych.2023.01.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 01/31/2023] [Accepted: 01/31/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Our understanding of the impact of copy number variants (CNVs) on psychopathology and their joint influence with polygenic risk scores (PRSs) remains limited. METHODS The UK Biobank recruited 502,534 individuals ages 37 to 73 years living in the United Kingdom between 2006 and 2010. After quality control, genotype data from 459,855 individuals were available for CNV calling. A total of 61 commonly studied recurrent neuropsychiatric CNVs were selected for analyses and examined individually and in aggregate (any CNV, deletion, or duplication). CNV risk scores were used to quantify intolerance of CNVs to haploinsufficiency. Major depressive disorder and generalized anxiety disorder PRSs were generated for White British individuals (N = 408,870). Mood/anxiety factor scores were generated using item-level questionnaire data (N = 501,289). RESULTS CNV carriers showed higher mood/anxiety scores than noncarriers, with the largest effects seen for intolerant deletions. A total of 11 individual deletions and 8 duplications were associated with higher mood/anxiety. Carriers of the 9p24.3 (DMRT1) duplication showed lower mood/anxiety. Associations remained significant for most CNVs when excluding individuals with psychiatric diagnoses. Nominally significant CNV × PRS interactions provided preliminary evidence that associations between select individual CNVs, but not CNVs in aggregate, and mood/anxiety may be modulated by PRSs. CONCLUSIONS CNVs associated with risk for psychiatric disorders showed small to large effects on dimensional mood/anxiety scores in a general population cohort, even when excluding individuals with psychiatric diagnoses. CNV × PRS interactions showed that associations between select CNVs and mood/anxiety may be modulated by PRSs.
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Affiliation(s)
- Josephine Mollon
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
| | - Laura M Schultz
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Guillaume Huguet
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Emma E M Knowles
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Samuel R Mathias
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Amanda Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Zohra Saci
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Martineau Jean-Louis
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Kuldeep Kumar
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Elise Douard
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Laura Almasy
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Department of Genetics, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sebastien Jacquemont
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts; Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut
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24
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Pollen AA, Kilik U, Lowe CB, Camp JG. Human-specific genetics: new tools to explore the molecular and cellular basis of human evolution. Nat Rev Genet 2023; 24:687-711. [PMID: 36737647 PMCID: PMC9897628 DOI: 10.1038/s41576-022-00568-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/05/2023]
Abstract
Our ancestors acquired morphological, cognitive and metabolic modifications that enabled humans to colonize diverse habitats, develop extraordinary technologies and reshape the biosphere. Understanding the genetic, developmental and molecular bases for these changes will provide insights into how we became human. Connecting human-specific genetic changes to species differences has been challenging owing to an abundance of low-effect size genetic changes, limited descriptions of phenotypic differences across development at the level of cell types and lack of experimental models. Emerging approaches for single-cell sequencing, genetic manipulation and stem cell culture now support descriptive and functional studies in defined cell types with a human or ape genetic background. In this Review, we describe how the sequencing of genomes from modern and archaic hominins, great apes and other primates is revealing human-specific genetic changes and how new molecular and cellular approaches - including cell atlases and organoids - are enabling exploration of the candidate causal factors that underlie human-specific traits.
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Affiliation(s)
- Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| | - Umut Kilik
- Institute of Human Biology (IHB), Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Craig B Lowe
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA.
| | - J Gray Camp
- Institute of Human Biology (IHB), Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
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25
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Kim CN, Shin D, Wang A, Nowakowski TJ. Spatiotemporal molecular dynamics of the developing human thalamus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.21.554174. [PMID: 37662287 PMCID: PMC10473600 DOI: 10.1101/2023.08.21.554174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The thalamus plays a central coordinating role in the brain. Thalamic neurons are organized into spatially-distinct nuclei, but the molecular architecture of thalamic development is poorly understood, especially in humans. To begin to delineate the molecular trajectories of cell fate specification and organization in the developing human thalamus, we used single cell and multiplexed spatial transcriptomics. Here we show that molecularly-defined thalamic neurons differentiate in the second trimester of human development, and that these neurons organize into spatially and molecularly distinct nuclei. We identify major subtypes of glutamatergic neuron subtypes that are differentially enriched in anatomically distinct nuclei. In addition, we identify six subtypes of GABAergic neurons that are shared and distinct across thalamic nuclei. One-Sentence Summary Single cell and spatial profiling of the developing thalamus in the first and second trimester yields molecular mechanisms of thalamic nuclei development.
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26
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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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27
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Sahajpal NS, Jeffrey DHF, DuPont BR, Hilton B. 17q25.3 copy number changes: association with neurodevelopmental disorders and cardiac malformation. Mol Cytogenet 2023; 16:15. [PMID: 37430334 DOI: 10.1186/s13039-023-00644-2] [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: 01/30/2023] [Accepted: 06/19/2023] [Indexed: 07/12/2023] Open
Abstract
Copy number variants (CNVs) have been identified as common genomic variants that play a significant role in inter-individual variability. Conversely, rare recurrent CNVs have been found to be causal for many disorders with well-established genotype-phenotype relationships. However, the phenotypic implications of rare non-recurrent CNVs remain poorly understood. Herein, we re-investigated 18,542 cases reported from chromosomal microarray at Greenwood Genetic Center from 2010 to 2022 and identified 15 cases with CNVs involving the 17q25.3 region. We report the detailed clinical features of these subjects, and compare with the cases reported in the literature to determine genotype-phenotype correlations for a subset of genes in this region. The CNVs in the 17q25.3 region were found to be rare events, with a prevalence of 0.08% (15/18542) observed in our cohort. The CNVs were dispersed across the entire 17q25.3 region with variable breakpoints and no smallest region of overlap. The subjects presented with a wide range of clinical features, with neurodevelopmental disorders (autism spectrum disorder, intellectual disability, developmental delay) being the most common features (80%), then expressive language disorder (33%), and finally cardiovascular malformations (26%). The association of CNVs involving the critical gene-rich region of 17q25.3 with neurodevelopmental disorders and cardiac malformation, implicates several genes as plausible drivers for these events.
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Affiliation(s)
| | - David H F Jeffrey
- Diagnostic Laboratories, Greenwood Genetic Center, Greenwood, SC, 29646, USA
| | - Barbara R DuPont
- Diagnostic Laboratories, Greenwood Genetic Center, Greenwood, SC, 29646, USA
| | - Benjamin Hilton
- Diagnostic Laboratories, Greenwood Genetic Center, Greenwood, SC, 29646, USA.
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28
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Yang X, Wang X, Zou Y, Zhang S, Xia M, Fu L, Vollger MR, Chen NC, Taylor DJ, Harvey WT, Logsdon GA, Meng D, Shi J, McCoy RC, Schatz MC, Li W, Eichler EE, Lu Q, Mao Y. Characterization of large-scale genomic differences in the first complete human genome. Genome Biol 2023; 24:157. [PMID: 37403156 PMCID: PMC10320979 DOI: 10.1186/s13059-023-02995-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 06/23/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUND The first telomere-to-telomere (T2T) human genome assembly (T2T-CHM13) release is a milestone in human genomics. The T2T-CHM13 genome assembly extends our understanding of telomeres, centromeres, segmental duplication, and other complex regions. The current human genome reference (GRCh38) has been widely used in various human genomic studies. However, the large-scale genomic differences between these two important genome assemblies are not characterized in detail yet. RESULTS Here, in addition to the previously reported "non-syntenic" regions, we find 67 additional large-scale discrepant regions and precisely categorize them into four structural types with a newly developed website tool called SynPlotter. The discrepant regions (~ 21.6 Mbp) excluding telomeric and centromeric regions are highly structurally polymorphic in humans, where the deletions or duplications are likely associated with various human diseases, such as immune and neurodevelopmental disorders. The analyses of a newly identified discrepant region-the KLRC gene cluster-show that the depletion of KLRC2 by a single-deletion event is associated with natural killer cell differentiation in ~ 20% of humans. Meanwhile, the rapid amino acid replacements observed within KLRC3 are probably a result of natural selection in primate evolution. CONCLUSION Our study provides a foundation for understanding the large-scale structural genomic differences between the two crucial human reference genomes, and is thereby important for future human genomics studies.
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Affiliation(s)
- Xiangyu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xuankai Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yawen Zou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Manying Xia
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Lianting Fu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Nae-Chyun Chen
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Dylan J Taylor
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Dan Meng
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Junfeng Shi
- Shanghai Engineering Research Center of Advanced Dental Technology and Materials, Shanghai, China
- Shanghai Key Laboratory of Stomatology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Weidong Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - 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
| | - Qing Lu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yafei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China.
- Shanghai Key Laboratory of Stomatology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Prodanov T, Bansal V. A multilocus approach for accurate variant calling in low-copy repeats using whole-genome sequencing. Bioinformatics 2023; 39:i279-i287. [PMID: 37387146 PMCID: PMC10311303 DOI: 10.1093/bioinformatics/btad268] [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] [Indexed: 07/01/2023] Open
Abstract
MOTIVATION Low-copy repeats (LCRs) or segmental duplications are long segments of duplicated DNA that cover > 5% of the human genome. Existing tools for variant calling using short reads exhibit low accuracy in LCRs due to ambiguity in read mapping and extensive copy number variation. Variants in more than 150 genes overlapping LCRs are associated with risk for human diseases. METHODS We describe a short-read variant calling method, ParascopyVC, that performs variant calling jointly across all repeat copies and utilizes reads independent of mapping quality in LCRs. To identify candidate variants, ParascopyVC aggregates reads mapped to different repeat copies and performs polyploid variant calling. Subsequently, paralogous sequence variants that can differentiate repeat copies are identified using population data and used for estimating the genotype of variants for each repeat copy. RESULTS On simulated whole-genome sequence data, ParascopyVC achieved higher precision (0.997) and recall (0.807) than three state-of-the-art variant callers (best precision = 0.956 for DeepVariant and best recall = 0.738 for GATK) in 167 LCR regions. Benchmarking of ParascopyVC using the genome-in-a-bottle high-confidence variant calls for HG002 genome showed that it achieved a very high precision of 0.991 and a high recall of 0.909 across LCR regions, significantly better than FreeBayes (precision = 0.954 and recall = 0.822), GATK (precision = 0.888 and recall = 0.873) and DeepVariant (precision = 0.983 and recall = 0.861). ParascopyVC demonstrated a consistently higher accuracy (mean F1 = 0.947) than other callers (best F1 = 0.908) across seven human genomes. AVAILABILITY AND IMPLEMENTATION ParascopyVC is implemented in Python and is freely available at https://github.com/tprodanov/ParascopyVC.
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Affiliation(s)
- Timofey Prodanov
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA 92093, United States
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Vikas Bansal
- School of Medicine, University of California San Diego, La Jolla, CA 92093, United States
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30
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Wang X, Zhao N, Cai L, Liu N, Zhu J, Yang B. High-quality chromosome-level scaffolds of the plant bug Pachypeltis micranthus provide insights into the availability of Mikania micrantha control. BMC Genomics 2023; 24:339. [PMID: 37340339 DOI: 10.1186/s12864-023-09445-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 06/13/2023] [Indexed: 06/22/2023] Open
Abstract
BACKGROUND The plant bug, Pachypeltis micranthus Mu et Liu (Hemiptera: Miridae), is an effective potential biological control agent for Mikania micrantha H.B.K. (Asteraceae; one of the most notorious invasive weeds worldwide). However, limited knowledge about this species hindered its practical application and research. Accordingly, sequencing the genome of this mirid bug holds great significance in controlling M. micrantha. RESULTS Here, 712.72 Mb high-quality chromosome-level scaffolds of P. micranthus were generated, of which 707.51 Mb (99.27%) of assembled sequences were anchored onto 15 chromosome-level scaffolds with contig N50 of 16.84 Mb. The P. micranthus genome had the highest GC content (42.43%) and the second highest proportion of repetitive sequences (375.82 Mb, 52.73%) than the three other mirid bugs (i.e., Apolygus lucorum, Cyrtorhinus lividipennis, and Nesidiocoris tenuis). Phylogenetic analysis showed that P. micranthus clustered with other mirid bugs and diverged from the common ancestor approximately 200 million years ago. Gene family expansion and/or contraction were analyzed, and significantly expanded gene families associated with P. micranthus feeding and adaptation to M. micrantha were manually identified. Compared with the whole body, transcriptome analysis of the salivary gland revealed that most of the upregulated genes were significantly associated with metabolism pathways and peptidase activity, particularly among cysteine peptidase, serine peptidase, and polygalacturonase; this could be one of the reasons for precisely and highly efficient feeding by the oligophagous bug P. micranthus on M. micrantha. CONCLUSION Collectively, this work provides a crucial chromosome-level scaffolds resource to study the evolutionary adaptation between mirid bug and their host. It is also helpful in searching for novel environment-friendly biological strategies to control M. micrantha.
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Affiliation(s)
- Xiafei Wang
- Key Laboratory of Forest Disaster Warning and Control of Yunnan Province, Southwest Forestry University, Kunming, China
| | - Ning Zhao
- Key Laboratory of Forest Disaster Warning and Control of Yunnan Province, Southwest Forestry University, Kunming, China
| | - Liqiong Cai
- Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming, China
| | - Naiyong Liu
- Key Laboratory of Forest Disaster Warning and Control of Yunnan Province, Southwest Forestry University, Kunming, China
| | - Jiaying Zhu
- Key Laboratory of Forest Disaster Warning and Control of Yunnan Province, Southwest Forestry University, Kunming, China
| | - Bin Yang
- Key Laboratory of Forest Disaster Warning and Control of Yunnan Province, Southwest Forestry University, Kunming, China.
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31
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Leonard S, Benfante R. Unanswered questions in the regulation and function of the duplicated α7 nicotinic receptor gene CHRFAM7A. Pharmacol Res 2023; 192:106783. [PMID: 37164281 DOI: 10.1016/j.phrs.2023.106783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/20/2023] [Accepted: 04/30/2023] [Indexed: 05/12/2023]
Abstract
The α7 nicotinic receptor (α7 nAChR) is an important entry point for Ca2+ into the cell, which has broad and important effects on gene expression and function. The gene (CHRNA7), mapping to chromosome (15q14), has been genetically linked to a large number of diseases, many of which involve defects in cognition. While numerous mutations in CHRNA7 are associated with mental illness and inflammation, an important control point may be the function of a recently discovered partial duplication CHRNA7, CHRFAM7A, that negatively regulates the function of the α7 receptor, through the formation of heteropentamers; other functions cannot be excluded. The deregulation of this human specific gene (CHRFAM7A) has been linked to neurodevelopmental, neurodegenerative, and inflammatory disorders and has important copy number variations. Much effort is being made to understand its function and regulation both in healthy and pathological conditions. However, many questions remain to be answered regarding its functional role, its regulation, and its role in the etiogenesis of neurological and inflammatory disorders. Missing knowledge on the pharmacology of the heteroreceptor has limited the discovery of new molecules capable of modulating its activity. Here we review the state of the art on the role of CHRFAM7A, highlighting unanswered questions to be addressed. A possible therapeutic approach based on genome editing protocols is also discussed.
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Affiliation(s)
- Sherry Leonard
- Department of Psychiatry - University of Colorado Anschutz, Aurora, Colorado, USA
| | - Roberta Benfante
- CNR - Institute of Neuroscience, Vedano al Lambro (MB), Italy; Dept. Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy; NeuroMI - Milan Center for Neuroscience, University of Milano Bicocca, Milan, Italy.
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32
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Liao WW, Asri M, Ebler J, Doerr D, Haukness M, Hickey G, Lu S, Lucas JK, Monlong J, Abel HJ, Buonaiuto S, Chang XH, Cheng H, Chu J, Colonna V, Eizenga JM, Feng X, Fischer C, Fulton RS, Garg S, Groza C, Guarracino A, Harvey WT, Heumos S, Howe K, Jain M, Lu TY, Markello C, Martin FJ, Mitchell MW, Munson KM, Mwaniki MN, Novak AM, Olsen HE, Pesout T, Porubsky D, Prins P, Sibbesen JA, Sirén J, Tomlinson C, Villani F, Vollger MR, Antonacci-Fulton LL, Baid G, Baker CA, Belyaeva A, Billis K, Carroll A, Chang PC, Cody S, Cook DE, Cook-Deegan RM, Cornejo OE, Diekhans M, Ebert P, Fairley S, Fedrigo O, Felsenfeld AL, Formenti G, Frankish A, Gao Y, Garrison NA, Giron CG, Green RE, Haggerty L, Hoekzema K, Hourlier T, Ji HP, Kenny EE, Koenig BA, Kolesnikov A, Korbel JO, Kordosky J, Koren S, Lee H, Lewis AP, Magalhães H, Marco-Sola S, Marijon P, McCartney A, McDaniel J, Mountcastle J, Nattestad M, Nurk S, Olson ND, Popejoy AB, Puiu D, Rautiainen M, Regier AA, Rhie A, Sacco S, Sanders AD, Schneider VA, Schultz BI, Shafin K, Smith MW, Sofia HJ, Abou Tayoun AN, Thibaud-Nissen F, Tricomi FF, Wagner J, Walenz B, Wood JMD, Zimin AV, Bourque G, Chaisson MJP, Flicek P, Phillippy AM, Zook JM, Eichler EE, Haussler D, Wang T, Jarvis ED, Miga KH, Garrison E, Marschall T, Hall IM, Li H, Paten B. A draft human pangenome reference. Nature 2023; 617:312-324. [PMID: 37165242 PMCID: PMC10172123 DOI: 10.1038/s41586-023-05896-x] [Citation(s) in RCA: 182] [Impact Index Per Article: 182.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 02/28/2023] [Indexed: 05/12/2023]
Abstract
Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.
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Affiliation(s)
- Wen-Wei Liao
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Mobin Asri
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Jana Ebler
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Daniel Doerr
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Marina Haukness
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Glenn Hickey
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Shuangjia Lu
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA
| | - Julian K Lucas
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Jean Monlong
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Haley J Abel
- Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Silvia Buonaiuto
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
| | - Xian H Chang
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Justin Chu
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Vincenza Colonna
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jordan M Eizenga
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Xiaowen Feng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Christian Fischer
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Robert S Fulton
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Shilpa Garg
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
| | - Cristian Groza
- Quantitative Life Sciences, McGill University, Montréal, Québec, Canada
| | - Andrea Guarracino
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
- Genomics Research Centre, Human Technopole, Milan, Italy
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Simon Heumos
- Quantitative Biology Center (QBiC), University of Tübingen, Tübingen, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Kerstin Howe
- Tree of Life, Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Miten Jain
- Northeastern University, Boston, MA, USA
| | - Tsung-Yu Lu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Charles Markello
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Adam M Novak
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Hugh E Olsen
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Trevor Pesout
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Pjotr Prins
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jonas A Sibbesen
- Center for Health Data Science, University of Copenhagen, Copenhagen, Denmark
| | - Jouni Sirén
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Chad Tomlinson
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Carl A Baker
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | | | - Sarah Cody
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Robert M Cook-Deegan
- Barrett and O'Connor Washington Center, Arizona State University, Washington, DC, USA
| | - Omar E Cornejo
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, USA
| | - Mark Diekhans
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Peter Ebert
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
- Core Unit Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Susan Fairley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Olivier Fedrigo
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Adam L Felsenfeld
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | - Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Yan Gao
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nanibaa' A Garrison
- Institute for Society and Genetics, College of Letters and Science, University of California, Los Angeles, CA, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Carlos Garcia Giron
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Richard E Green
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA
- Dovetail Genomics, Scotts Valley, CA, USA
| | - Leanne Haggerty
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Hanlee P Ji
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Barbara A Koenig
- Program in Bioethics and Institute for Human Genetics, University of California, San Francisco, CA, USA
| | | | - Jan O Korbel
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - HoJoon Lee
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Hugo Magalhães
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Santiago Marco-Sola
- Computer Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain
- Departament d'Arquitectura de Computadors i Sistemes Operatius, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Pierre Marijon
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Ann McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | | | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Alice B Popejoy
- Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Daniela Puiu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Allison A Regier
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Samuel Sacco
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, USA
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Valerie A Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Baergen I Schultz
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Michael W Smith
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | - Heidi J Sofia
- National Institutes of Health (NIH)-National Human Genome Research Institute, Bethesda, MD, USA
| | - Ahmad N Abou Tayoun
- Al Jalila Genomics Center of Excellence, Al Jalila Children's Specialty Hospital, Dubai, UAE
- Center for Genomic Discovery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Francesca Floriana Tricomi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Brian Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Aleksey V Zimin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
- Canadian Center for Computational Genomics, McGill University, Montréal, Québec, Canada
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - David Haussler
- Genomics Institute, University of California, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Ting Wang
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Erich D Jarvis
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY, USA
| | - Karen H Miga
- Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany.
| | - Ira M Hall
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA.
- Center for Genomic Health, Yale University School of Medicine, New Haven, CT, USA.
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | - Benedict Paten
- Genomics Institute, University of California, Santa Cruz, CA, USA.
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33
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Porubsky D, Vollger MR, Harvey WT, Rozanski AN, Ebert P, Hickey G, Hasenfeld P, Sanders AD, Stober C, Korbel JO, Paten B, Marschall T, Eichler EE. Gaps and complex structurally variant loci in phased genome assemblies. Genome Res 2023; 33:496-510. [PMID: 37164484 PMCID: PMC10234299 DOI: 10.1101/gr.277334.122] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 12/07/2022] [Indexed: 05/12/2023]
Abstract
There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Allison N Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Peter Ebert
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, 40225 Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Glenn Hickey
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, California 95064, USA
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany
- Berlin Institute of Health (BIH), 10178 Berlin, Germany
- Charité-Universitätsmedizin, 10117 Berlin, Germany
| | - Catherine Stober
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, California 95064, USA
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, 40225 Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA;
- Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA
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34
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Youm DJ, Ko BJ, Kim D, Park M, Won S, Lee YH, Kim B, Seol D, Chai HH, Lim D, Jeong C, Kim H. The idiosyncratic genome of Korean long-tailed chicken as a valuable genetic resource. iScience 2023; 26:106236. [PMID: 36915682 PMCID: PMC10006692 DOI: 10.1016/j.isci.2023.106236] [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: 11/03/2022] [Revised: 11/28/2022] [Accepted: 02/15/2023] [Indexed: 02/19/2023] Open
Abstract
Today, breeds with ornamental traits such as exceptionally long tail feathers are economically valuable. However, the genetic basis of long-tail feathers is yet to be understood. To provide better understanding of long tail feathers, we sequenced Korean long-tailed chicken (KLC) genomes and compared them with genomes of other chicken breeds. We first analyzed the genome structure of KLC and its genomic relationship with other chickens and observed unique characteristics. Subsequently, we searched for genomic regions under selection. Feather keratin 1-like enriched region and several genes were found to have novel putative functions and effects on the long tail trait in KLC. Our findings support the value of KLC as a unique genetic resource and cast light on the genetic basis of long tail traits in avian species. We expect this novel knowledge to provide new genomic evidence and options for designing and implementing genetic improvements of ornamental chicken productivity through precision crossbreeding aids.
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Affiliation(s)
- Dong-Jae Youm
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Byung June Ko
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Donghee Kim
- School of Biological Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Myeongkyu Park
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Republic of Korea
| | - Sohyoung Won
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Republic of Korea
- eGnome, Inc, Seoul 05836, Republic of Korea
| | - Young Ho Lee
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Republic of Korea
| | - Bongsang Kim
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
- eGnome, Inc, Seoul 05836, Republic of Korea
| | - Donghyeok Seol
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Han-Ha Chai
- Animal Genomics & Bioinformatics Division, National Institute of Animal Science, RDA 1500, Wanju 55365, Republic of Korea
| | - Dajeong Lim
- Animal Genomics & Bioinformatics Division, National Institute of Animal Science, RDA 1500, Wanju 55365, Republic of Korea
| | - Choongwon Jeong
- School of Biological Sciences, Seoul National University, Seoul 08826, Republic of Korea
- Corresponding author
| | - Heebal Kim
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Republic of Korea
- eGnome, Inc, Seoul 05836, Republic of Korea
- Corresponding author
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35
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Tauber CV, Schwarz SC, Rösler TW, Arzberger T, Gentleman S, Windl O, Krumbiegel M, Reis A, Ruf VC, Herms J, Höglinger GU. Different MAPT haplotypes influence expression of total MAPT in postmortem brain tissue. Acta Neuropathol Commun 2023; 11:40. [PMID: 36906636 PMCID: PMC10008602 DOI: 10.1186/s40478-023-01534-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 02/21/2023] [Indexed: 03/13/2023] Open
Abstract
The MAPT gene, encoding the microtubule-associated protein tau on chromosome 17q21.31, is result of an inversion polymorphism, leading to two allelic variants (H1 and H2). Homozygosity for the more common haplotype H1 is associated with an increased risk for several tauopathies, but also for the synucleinopathy Parkinson's disease (PD). In the present study, we aimed to clarify whether the MAPT haplotype influences expression of MAPT and SNCA, encoding the protein α-synuclein (α-syn), on mRNA and protein levels in postmortem brains of PD patients and controls. We also investigated mRNA expression of several other MAPT haplotype-encoded genes. Postmortem tissues from cortex of fusiform gyrus (ctx-fg) and of the cerebellar hemisphere (ctx-cbl) of neuropathologically confirmed PD patients (n = 95) and age- and sex-matched controls (n = 81) were MAPT haplotype genotyped to identify cases homozygous for either H1 or H2. Relative expression of genes was quantified using real-time qPCR; soluble and insoluble protein levels of tau and α-syn were determined by Western blotting. Homozygosity for H1 versus H2 was associated with increased total MAPT mRNA expression in ctx-fg regardless of disease state. Inversely, H2 homozygosity was associated with markedly increased expression of the corresponding antisense MAPT-AS1 in ctx-cbl. PD patients had higher levels of insoluble 0N3R and 1N4R tau isoforms regardless of the MAPT genotype. The increased presence of insoluble α-syn in PD patients in ctx-fg validated the selected postmortem brain tissue. Our findings in this small, but well controlled cohort of PD and controls support a putative biological relevance of tau in PD. However, we did not identify any link between the disease-predisposing H1/H1 associated overexpression of MAPT with PD status. Further studies are required to gain a deeper understanding of the potential regulatory role of MAPT-AS1 and its association to the disease-protective H2/H2 condition in the context of PD.
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Affiliation(s)
- Christina V Tauber
- Department of Translational Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, School of Medicine, Technical University Munich, Munich, Germany.,Department of Obstetrics and Gynecology, Ludiwgs-Maximilians University of Munich, Munich, Germany
| | - Sigrid C Schwarz
- Department of Translational Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Thomas W Rösler
- Department of Translational Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, School of Medicine, Technical University Munich, Munich, Germany
| | - Thomas Arzberger
- Center for Neuropathology and Prion Research, Ludwig-Maximilians University of Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Steve Gentleman
- Parkinson's UK Brain Bank, Department of Brain Sciences, Imperial College London, London, UK.,Neuropathology Unit, Department of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Otto Windl
- Center for Neuropathology and Prion Research, Ludwig-Maximilians University of Munich, Munich, Germany
| | - Mandy Krumbiegel
- Institute of Human Genetics, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany
| | - André Reis
- Institute of Human Genetics, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany
| | - Viktoria C Ruf
- Center for Neuropathology and Prion Research, Ludwig-Maximilians University of Munich, Munich, Germany
| | - Jochen Herms
- Center for Neuropathology and Prion Research, Ludwig-Maximilians University of Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Günter U Höglinger
- Department of Translational Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany. .,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. .,Department of Neurology, Ludwig-Maximilians University of Munich, Munich, Germany.
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36
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Soto DC, Uribe-Salazar JM, Shew CJ, Sekar A, McGinty SP, Dennis MY. Genomic structural variation: A complex but important driver of human evolution. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023. [PMID: 36794631 DOI: 10.1002/ajpa.24713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 01/21/2023] [Accepted: 02/05/2023] [Indexed: 02/17/2023]
Abstract
Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.
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Affiliation(s)
- Daniela C Soto
- Genome Center, MIND Institute, Department of Biochemstry & Molecular Medicine, University of California, Davis, California, USA.,Integrative Genetics and Genomics Graduate Group, University of California, Davis, California, USA
| | - José M Uribe-Salazar
- Genome Center, MIND Institute, Department of Biochemstry & Molecular Medicine, University of California, Davis, California, USA.,Integrative Genetics and Genomics Graduate Group, University of California, Davis, California, USA
| | - Colin J Shew
- Genome Center, MIND Institute, Department of Biochemstry & Molecular Medicine, University of California, Davis, California, USA.,Integrative Genetics and Genomics Graduate Group, University of California, Davis, California, USA
| | - Aarthi Sekar
- Genome Center, MIND Institute, Department of Biochemstry & Molecular Medicine, University of California, Davis, California, USA.,Integrative Genetics and Genomics Graduate Group, University of California, Davis, California, USA
| | - Sean P McGinty
- Genome Center, MIND Institute, Department of Biochemstry & Molecular Medicine, University of California, Davis, California, USA.,Integrative Genetics and Genomics Graduate Group, University of California, Davis, California, USA
| | - Megan Y Dennis
- Genome Center, MIND Institute, Department of Biochemstry & Molecular Medicine, University of California, Davis, California, USA.,Integrative Genetics and Genomics Graduate Group, University of California, Davis, California, USA
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37
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Vanderhaeghen P, Polleux F. Developmental mechanisms underlying the evolution of human cortical circuits. Nat Rev Neurosci 2023; 24:213-232. [PMID: 36792753 PMCID: PMC10064077 DOI: 10.1038/s41583-023-00675-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2023] [Indexed: 02/17/2023]
Abstract
The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.
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Affiliation(s)
- Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium.
- Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Franck Polleux
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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38
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Vidotto T, Imada EL, Faisal F, Murali S, Mendes AA, Kaur H, Zheng S, Xu J, Schaeffer EM, Isaacs WB, Sfanos KS, Marchionni L, Lotan TL. Association of self-identified race and genetic ancestry with the immunogenomic landscape of primary prostate cancer. JCI Insight 2023; 8:e162409. [PMID: 36752203 PMCID: PMC9977441 DOI: 10.1172/jci.insight.162409] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 12/27/2022] [Indexed: 02/09/2023] Open
Abstract
The genomic and immune landscapes of prostate cancer differ by self-identified race. However, few studies have examined the genome-wide copy number landscape and immune content of matched cohorts with genetic ancestry data and clinical outcomes. Here, we assessed prostate cancer somatic copy number alterations (sCNA) and tumor immune content of a grade-matched, surgically treated cohort of 145 self-identified Black (BL) and 145 self-identified White (WH) patients with genetic ancestry estimation. A generalized linear model adjusted with age, preoperative prostate-specific antigen (PSA), and Gleason Grade Group and filtered for germline copy number variations (gCNV) identified 143 loci where copy number varied significantly by percent African ancestry, clustering on chromosomes 6p, 10q, 11p, 12p, and 17p. Multivariable Cox regression models adjusted for age, preoperative PSA levels, and Gleason Grade Group revealed that chromosome 8q gains (including MYC) were significantly associated with biochemical recurrence and metastasis, independent of genetic ancestry. Finally, Treg density in BL and WH patients was significantly correlated with percent genome altered, and these findings were validated in the TCGA cohort. Taken together, our findings identify specific sCNA linked to genetic ancestry and outcome in primary prostate cancer and demonstrate that Treg infiltration varies by global sCNA burden in primary disease.
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Affiliation(s)
- Thiago Vidotto
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Eddie L. Imada
- Department of Pathology, Weill-Cornell School of Medicine, New York, New York, USA
| | - Farzana Faisal
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Sanjana Murali
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Adrianna A. Mendes
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Harsimar Kaur
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Siqun Zheng
- Program for Personalized Cancer Care, NorthShore University Health System, Evanston, Illinois, USA
| | - Jianfeng Xu
- Program for Personalized Cancer Care, NorthShore University Health System, Evanston, Illinois, USA
| | - Edward M. Schaeffer
- Department of Urology, Northwestern University School of Medicine, Chicago, Illinois, USA
| | | | - Karen S. Sfanos
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Luigi Marchionni
- Department of Pathology, Weill-Cornell School of Medicine, New York, New York, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Tamara L. Lotan
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Urology and
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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39
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Smith EG, Surm JM, Macrander J, Simhi A, Amir G, Sachkova MY, Lewandowska M, Reitzel AM, Moran Y. Micro and macroevolution of sea anemone venom phenotype. Nat Commun 2023; 14:249. [PMID: 36646703 PMCID: PMC9842752 DOI: 10.1038/s41467-023-35794-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 01/03/2023] [Indexed: 01/18/2023] Open
Abstract
Venom is a complex trait with substantial inter- and intraspecific variability resulting from strong selective pressures acting on the expression of many toxic proteins. However, understanding the processes underlying toxin expression dynamics that determine the venom phenotype remains unresolved. By interspecific comparisons we reveal that toxin expression in sea anemones evolves rapidly and that in each species different toxin family dictates the venom phenotype by massive gene duplication events. In-depth analysis of the sea anemone, Nematostella vectensis, revealed striking variation of the dominant toxin (Nv1) diploid copy number across populations (1-24 copies) resulting from independent expansion/contraction events, which generate distinct haplotypes. Nv1 copy number correlates with expression at both the transcript and protein levels with one population having a near-complete loss of Nv1 production. Finally, we establish the dominant toxin hypothesis which incorporates observations in other venomous lineages that animals have convergently evolved a similar strategy in shaping their venom.
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Affiliation(s)
- Edward G Smith
- University of North Carolina at Charlotte, Department of Biological Sciences, Charlotte, NC, USA. .,School of Life Sciences, University of Warwick, Coventry, United Kingdom.
| | - Joachim M Surm
- Department of Ecology, Evolution and Behavior, Alexander Silberman Institute of Life Sciences, Faculty of Science, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Jason Macrander
- University of North Carolina at Charlotte, Department of Biological Sciences, Charlotte, NC, USA.,Florida Southern College, Biology Department, Lakeland, FL, USA
| | - Adi Simhi
- Department of Ecology, Evolution and Behavior, Alexander Silberman Institute of Life Sciences, Faculty of Science, The Hebrew University of Jerusalem, Jerusalem, Israel.,The Hebrew University of Jerusalem, The School of Computer Science & Engineering, Jerusalem, Israel
| | - Guy Amir
- Department of Ecology, Evolution and Behavior, Alexander Silberman Institute of Life Sciences, Faculty of Science, The Hebrew University of Jerusalem, Jerusalem, Israel.,The Hebrew University of Jerusalem, The School of Computer Science & Engineering, Jerusalem, Israel
| | - Maria Y Sachkova
- Department of Ecology, Evolution and Behavior, Alexander Silberman Institute of Life Sciences, Faculty of Science, The Hebrew University of Jerusalem, Jerusalem, Israel.,Sars International Centre for Marine Molecular Biology, University of Bergen, Bergen, Norway
| | - Magda Lewandowska
- Department of Ecology, Evolution and Behavior, Alexander Silberman Institute of Life Sciences, Faculty of Science, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Adam M Reitzel
- University of North Carolina at Charlotte, Department of Biological Sciences, Charlotte, NC, USA
| | - Yehu Moran
- Department of Ecology, Evolution and Behavior, Alexander Silberman Institute of Life Sciences, Faculty of Science, The Hebrew University of Jerusalem, Jerusalem, Israel.
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40
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Sánchez S, Juárez U, Domínguez J, Molina B, Barrientos R, Martínez-Hernández A, Carnevale A, Grether-González P, Mayen DG, Villarroel C, Lieberman E, Yokoyama E, Del Castillo V, Torres L, Frias S. Frequent copy number variants in a cohort of Mexican-Mestizo individuals. Mol Cytogenet 2023; 16:2. [PMID: 36631885 PMCID: PMC9835318 DOI: 10.1186/s13039-022-00631-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/13/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND The human genome presents variation at distinct levels, copy number variants (CNVs) are DNA segments of variable lengths that range from several base pairs to megabases and are present at a variable number of copies in human genomes. Common CNVs have no apparent influence on the phenotype; however, some rare CNVs have been associated with phenotypic traits, depending on their size and gene content. CNVs are detected by microarrays of different densities and are generally visualized, and their frequencies analysed using the HapMap as default reference population. Nevertheless, this default reference is inadequate when the samples analysed are from people from Mexico, since population with a Hispanic genetic background are minimally represented. In this work, we describe the variation in the frequencies of four common CNVs in Mexican-Mestizo individuals. RESULTS In a cohort of 147 unrelated Mexican-Mestizo individuals, we found that the common CNVs 2p11.2 (99.6%), 8p11.22 (54.5%), 14q32.33 (100%), and 15q11.2 (71.1%) appeared with unexpectedly high frequencies when contrasted with the HapMap reference (ChAS). Yet, while when comparing to an ethnically related reference population, these differences were significantly reduced or even disappeared. CONCLUSION The findings in this work contribute to (1) a better description of the CNVs characteristics of the Mexican Mestizo population and enhance the knowledge of genome variation in different ethnic groups. (2) emphasize the importance of contrasting CNVs identified in studied individuals against a reference group that-as best as possible-share the same ethnicity while keeping this relevant information in mind when conducting CNV studies at the population or clinical level.
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Affiliation(s)
- Silvia Sánchez
- grid.419216.90000 0004 1773 4473Laboratorio de Citogenética, Instituto Nacional de Pediatría, Insurgentes Sur 3700-C Insurgentes Cuicuilco, P01090 Ciudad de Mexico, México ,grid.9486.30000 0001 2159 0001Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Ciudad de México, México
| | - Ulises Juárez
- grid.419216.90000 0004 1773 4473Laboratorio de Citogenética, Instituto Nacional de Pediatría, Insurgentes Sur 3700-C Insurgentes Cuicuilco, P01090 Ciudad de Mexico, México
| | - Julieta Domínguez
- grid.419216.90000 0004 1773 4473Laboratorio de Citogenética, Instituto Nacional de Pediatría, Insurgentes Sur 3700-C Insurgentes Cuicuilco, P01090 Ciudad de Mexico, México
| | - Bertha Molina
- grid.419216.90000 0004 1773 4473Laboratorio de Citogenética, Instituto Nacional de Pediatría, Insurgentes Sur 3700-C Insurgentes Cuicuilco, P01090 Ciudad de Mexico, México
| | - Rehotbevely Barrientos
- grid.419216.90000 0004 1773 4473Laboratorio de Citogenética, Instituto Nacional de Pediatría, Insurgentes Sur 3700-C Insurgentes Cuicuilco, P01090 Ciudad de Mexico, México
| | - Angélica Martínez-Hernández
- grid.452651.10000 0004 0627 7633Laboratorio de Inmunogenómica y Enfermedades Metabólicas, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, México
| | - Alessandra Carnevale
- grid.452651.10000 0004 0627 7633Laboratorio de Enfermedades Mendelianas, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, México
| | - Patricia Grether-González
- grid.419218.70000 0004 1773 5302Departamento de Genética y Genómica Humana, Instituto Nacional de Perinatología, Ciudad de Mexico, México ,grid.413678.fPresent Address: Centro Médico ABC, Campus Santa Fe, Ciudad de Mexico, México
| | - Dora Gilda Mayen
- Unidad de Genética Aplicada. Hospital Ángeles Lomas, Huixquilucan, Edo. de México México
| | - Camilo Villarroel
- grid.419216.90000 0004 1773 4473Genética Humana, Instituto Nacional de Pediatría, Ciudad de Mexico, México
| | - Esther Lieberman
- grid.419216.90000 0004 1773 4473Genética Humana, Instituto Nacional de Pediatría, Ciudad de Mexico, México
| | - Emiy Yokoyama
- grid.419216.90000 0004 1773 4473Genética Humana, Instituto Nacional de Pediatría, Ciudad de Mexico, México
| | - Victoria Del Castillo
- grid.419216.90000 0004 1773 4473Genética Humana, Instituto Nacional de Pediatría, Ciudad de Mexico, México
| | - Leda Torres
- grid.419216.90000 0004 1773 4473Laboratorio de Citogenética, Instituto Nacional de Pediatría, Insurgentes Sur 3700-C Insurgentes Cuicuilco, P01090 Ciudad de Mexico, México
| | - Sara Frias
- grid.419216.90000 0004 1773 4473Laboratorio de Citogenética, Instituto Nacional de Pediatría, Insurgentes Sur 3700-C Insurgentes Cuicuilco, P01090 Ciudad de Mexico, México ,grid.9486.30000 0001 2159 0001Departamento de Medicina Genómica y Toxicología Ambiental, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Ciudad de México, México
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Dishuck PC, Rozanski AN, Logsdon GA, Porubsky D, Eichler EE. GAVISUNK: genome assembly validation via inter-SUNK distances in Oxford Nanopore reads. BIOINFORMATICS (OXFORD, ENGLAND) 2023; 39:6793851. [PMID: 36321867 PMCID: PMC9805576 DOI: 10.1093/bioinformatics/btac714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/26/2022] [Accepted: 10/31/2022] [Indexed: 11/07/2022]
Abstract
MOTIVATION Highly contiguous de novo phased diploid genome assemblies are now feasible for large numbers of species and individuals. Methods are needed to validate assembly accuracy and detect misassemblies with orthologous sequencing data to allow for confident downstream analyses. RESULTS We developed GAVISUNK, an open-source pipeline that detects misassemblies and produces a set of reliable regions genome-wide by assessing concordance of distances between unique k-mers in Pacific Biosciences high-fidelity assemblies and raw Oxford Nanopore Technologies reads. AVAILABILITY AND IMPLEMENTATION GAVISUNK is available at https://github.com/pdishuck/GAVISUNK. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Allison N Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.,Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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42
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Söylev A, Çokoglu SS, Koptekin D, Alkan C, Somel M. CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data. PLoS Comput Biol 2022; 18:e1010788. [PMID: 36516232 PMCID: PMC9873172 DOI: 10.1371/journal.pcbi.1010788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 01/24/2023] [Accepted: 12/03/2022] [Indexed: 12/15/2022] Open
Abstract
To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by typical low genome coverage (<1×) and short fragments (<80 bps), precluding standard CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, tailored for genotyping CNVs at low coverage. Simulations and down-sampling experiments suggest that CONGA can genotype deletions >1 kbps with F-scores >0.75 at ≥1×, and distinguish between heterozygous and homozygous states. We used CONGA to genotype 10,002 outgroup-ascertained deletions across a heterogenous set of 71 ancient human genomes spanning the last 50,000 years, produced using variable experimental protocols. A fraction of these (21/71) display divergent deletion profiles unrelated to their population origin, but attributable to technical factors such as coverage and read length. The majority of the sample (50/71), despite originating from nine different laboratories and having coverages ranging from 0.44×-26× (median 4×) and average read lengths 52-121 bps (median 69), exhibit coherent deletion frequencies. Across these 50 genomes, inter-individual genetic diversity measured using SNPs and CONGA-genotyped deletions are highly correlated. CONGA-genotyped deletions also display purifying selection signatures, as expected. CONGA thus paves the way for systematic CNV analyses in ancient genomes, despite the technical challenges posed by low and variable genome coverage.
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Affiliation(s)
- Arda Söylev
- Department of Computer Engineering, Konya Food and Agriculture University, Konya, Turkey
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- * E-mail: (AS); (MS)
| | | | - Dilek Koptekin
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey
| | - Can Alkan
- Department of Computer Engineering, Bilkent University, Ankara, Turkey
| | - Mehmet Somel
- Department of Biology, Middle East Technical University, Ankara, Turkey
- * E-mail: (AS); (MS)
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Wang R, Wu B, Jian J, Tang Y, Zhang T, Song Z, Zhang W, Qiong L. How to survive in the world's third poplar: Insights from the genome of the highest altitude woody plant, Hippophae tibetana (Elaeagnaceae). FRONTIERS IN PLANT SCIENCE 2022; 13:1051587. [PMID: 36589082 PMCID: PMC9797102 DOI: 10.3389/fpls.2022.1051587] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 11/22/2022] [Indexed: 06/17/2023]
Abstract
Hippophae tibetana (Tibetan sea-buckthorn) is one of the highest distributed woody plants in the world (3,000-5,200 meters a.s.l.). It is characterized by adaptation to extreme environment and important economic values. Here, we combined PacBio Hifi platform and Hi-C technology to assemble a 1,452.75 Mb genome encoding 33,367 genes with a Contig N50 of 74.31 Mb, and inferred its sexual chromosome. Two Hippophae-specific whole-genome duplication events (18.7-21.2 million years ago, Ma; 28.6-32.4 Ma) and long terminal repeats retroelements (LTR-RTs) amplifications were detected. Comparing with related species at lower altitude, Ziziphus jujuba (<1, 700 meters a.s.l.), H. tibetana had some significantly rapid evolving genes involved in adaptation to high altitude habitats. However, comparing with Hippophae rhamnoides (<3, 700 meters a.s.l.), no rapid evolving genes were found except microtubule and microtubule-based process genes, H. tibetana has a larger genome, with extra 2, 503 genes (7.5%) and extra 680.46 Mb transposable elements (TEs) (46.84%). These results suggest that the changes in the copy number and regulatory pattern of genes play a more important role for H. tibetana adapting to more extreme and variable environments at higher altitude by more TEs and more genes increasing genome variability and expression plasticity. This suggestion was supported by two findings: nitrogen-fixing genes of H. tibetana having more copies, and intact TEs being significantly closer genes than fragmentary TEs. This study provided new insights into the evolution of alpine plants.
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Affiliation(s)
- Ruoqiu Wang
- Tibet University-Fudan University Joint Laboratory for Biodiversity and Global Change, School of Life Sciences, Fudan University, Shanghai, China
- Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, School of Life Sciences, Fudan University, Shanghai, China
| | - Bin Wu
- BGI-Shenzhen, Shenzhen, China
| | | | - Yiwei Tang
- Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, School of Life Sciences, Fudan University, Shanghai, China
| | - Ticao Zhang
- Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, School of Life Sciences, Fudan University, Shanghai, China
| | - Zhiping Song
- Tibet University-Fudan University Joint Laboratory for Biodiversity and Global Change, School of Life Sciences, Fudan University, Shanghai, China
- Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, School of Life Sciences, Fudan University, Shanghai, China
| | - Wenju Zhang
- Tibet University-Fudan University Joint Laboratory for Biodiversity and Global Change, School of Life Sciences, Fudan University, Shanghai, China
- Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, School of Life Sciences, Fudan University, Shanghai, China
| | - La Qiong
- Tibet University-Fudan University Joint Laboratory for Biodiversity and Global Change, School of Life Sciences, Fudan University, Shanghai, China
- Research Center for Ecology, College of Science, Tibet University, Lhasa, China
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44
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Wu D, Zhang L, Qiang Y, Wang K. Improved detection of SBDS gene mutation by a new method of next-generation sequencing analysis based on the Chinese mutation spectrum. PLoS One 2022; 17:e0269029. [PMID: 36512530 PMCID: PMC9747038 DOI: 10.1371/journal.pone.0269029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 05/13/2022] [Indexed: 12/15/2022] Open
Abstract
Next-generation sequencing (NGS) is a useful molecular diagnostic tool for genetic diseases. However, due to the presence of highly homologous pseudogenes, it is challenging to use short-read NGS for analyzing mutations of the Shwachman-Bodian-Diamond syndrome (SBDS) gene. The SBDS mutation spectrum was analyzed in the Chinese population, which revealed that SBDS variants were primarily from sequence exchange between SBDS and its pseudogene at the base-pair level, predominantly in the coding region and splice junction of exon two. The c.258+2T>C and c.185_184TA>GT variants were the two most common pathogenic SBDS variants in the Chinese population, resulting in a total carrier frequency of 1.19%. When analyzing pathogenic variants in the SBDS gene from the NGS data, the misalignment was identified as a common issue, and there were different probabilities of misalignment for different pathogenic variants. Here, we present a novel mathematical method for identifying pathogenic variants in the SBDS gene from the NGS data, which utilizes read-depth of the paralogous sequence variant (PSV) loci of SBDS and its pseudogene. Combined with PCR and STR orthogonal experiments, SBDS gene mutation analysis results were improved in 40% of clinical samples, and various types of mutations such as homozygous, compound heterozygous, and uniparental diploid were explored. The findings effectively reduce the impact of misalignment in NGS-based SBDS mutation analysis and are helpful for the clinical diagnosis of SBDS-related diseases, the research into population variation, and the carrier screening.
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Affiliation(s)
- Dong Wu
- Department of Obstetrics and Gynecology, 900 Hospital of the Joint Logistics Team or Dongfang Hospital, Fuzhou, Fujian, People’s Republic of China
| | - Li Zhang
- Fulgent (Fujian) Technologies, Fuzhou, Fujian, People’s Republic of China
| | - Yuzhen Qiang
- Fulgent (Fujian) Technologies, Fuzhou, Fujian, People’s Republic of China
| | - Kaiyu Wang
- Fulgent (Fujian) Technologies, Fuzhou, Fujian, People’s Republic of China
- * E-mail:
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45
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Linker SB, Narvaiza I, Hsu JY, Wang M, Qiu F, Mendes APD, Oefner R, Kottilil K, Sharma A, Randolph-Moore L, Mejia E, Santos R, Marchetto MC, Gage FH. Human-specific regulation of neural maturation identified by cross-primate transcriptomics. Curr Biol 2022; 32:4797-4807.e5. [PMID: 36228612 DOI: 10.1016/j.cub.2022.09.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 07/08/2022] [Accepted: 09/14/2022] [Indexed: 11/06/2022]
Abstract
Unique aspects of human behavior are often attributed to differences in the relative size and organization of the human brain: these structural aspects originate during early development. Recent studies indicate that human neurodevelopment is considerably slower than that in other nonhuman primates, a finding that is termed neoteny. One aspect of neoteny is the slow onset of action potentials. However, which molecular mechanisms play a role in this process remain unclear. To examine the evolutionary constraints on the rate of neuronal maturation, we have generated transcriptional data tracking five time points, from the neural progenitor state to 8-week-old neurons, in primates spanning the catarrhine lineage, including Macaca mulatta, Gorilla gorilla, Pan paniscus, Pan troglodytes, and Homo sapiens. Despite finding an overall similarity of many transcriptional signatures, species-specific and clade-specific distinctions were observed. Among the genes that exhibited human-specific regulation, we identified a key pioneer transcription factor, GATA3, that was uniquely upregulated in humans during the neuronal maturation process. We further examined the regulatory nature of GATA3 in human cells and observed that downregulation quickened the speed of developing spontaneous action potentials, thereby modulating the human neotenic phenotype. These results provide evidence for the divergence of gene regulation as a key molecular mechanism underlying human neoteny.
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Affiliation(s)
- Sara B Linker
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Iñigo Narvaiza
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Jonathan Y Hsu
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Meiyan Wang
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Fan Qiu
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Ana P D Mendes
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Ruth Oefner
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Kalyani Kottilil
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Amandeep Sharma
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Lynne Randolph-Moore
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Eunice Mejia
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA
| | - Renata Santos
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA; Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Laboratory of Dynamics of Neuronal Structure in Health and Disease, 102 rue de la Santé, 75014 Paris, France; Institut des Sciences Biologiques, CNRS, 16 rue Pierre et Marie Curie, 75005 Paris, France
| | - Maria C Marchetto
- Department of Anthropology, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA; Center for Academic Research and Training in Anthropogeny (CARTA), University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
| | - Fred H Gage
- Laboratory of Genetics, Salk Institute for Biological Studies, 10010 North Pines Road, La Jolla, CA 92037, USA.
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Fischer J, Fernández Ortuño E, Marsoner F, Artioli A, Peters J, Namba T, Eugster Oegema C, Huttner WB, Ladewig J, Heide M. Human-specific ARHGAP11B ensures human-like basal progenitor levels in hominid cerebral organoids. EMBO Rep 2022; 23:e54728. [PMID: 36098218 PMCID: PMC9646322 DOI: 10.15252/embr.202254728] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 08/18/2022] [Accepted: 08/23/2022] [Indexed: 02/06/2023] Open
Abstract
The human-specific gene ARHGAP11B has been implicated in human neocortex expansion. However, the extent of ARHGAP11B's contribution to this expansion during hominid evolution is unknown. Here we address this issue by genetic manipulation of ARHGAP11B levels and function in chimpanzee and human cerebral organoids. ARHGAP11B expression in chimpanzee cerebral organoids doubles basal progenitor levels, the class of cortical progenitors with a key role in neocortex expansion. Conversely, interference with ARHGAP11B's function in human cerebral organoids decreases basal progenitors down to the chimpanzee level. Moreover, ARHGAP11A or ARHGAP11B rescue experiments in ARHGAP11A plus ARHGAP11B double-knockout human forebrain organoids indicate that lack of ARHGAP11B, but not of ARHGAP11A, decreases the abundance of basal radial glia-the basal progenitor type thought to be of particular relevance for neocortex expansion. Taken together, our findings demonstrate that ARHGAP11B is necessary and sufficient to ensure the elevated basal progenitor levels that characterize the fetal human neocortex, suggesting that this human-specific gene was a major contributor to neocortex expansion during human evolution.
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Affiliation(s)
- Jan Fischer
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
- Present address:
Institute for Clinical GeneticsUniversity Hospital Carl Gustav CarusDresdenGermany
| | | | - Fabio Marsoner
- Central Institute of Mental HealthUniversity of Heidelberg/Medical Faculty MannheimMannheimGermany
- Hector Institute for Translational Brain Research (HITBR gGmbH)MannheimGermany
- German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Annasara Artioli
- Central Institute of Mental HealthUniversity of Heidelberg/Medical Faculty MannheimMannheimGermany
- Hector Institute for Translational Brain Research (HITBR gGmbH)MannheimGermany
- German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Jula Peters
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
| | - Takashi Namba
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
- Present address:
Neuroscience Center, HiLIFE ‐ Helsinki Institute of Life ScienceUniversity of HelsinkiHelsinkiFinland
| | | | - Wieland B. Huttner
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
| | - Julia Ladewig
- Central Institute of Mental HealthUniversity of Heidelberg/Medical Faculty MannheimMannheimGermany
- Hector Institute for Translational Brain Research (HITBR gGmbH)MannheimGermany
- German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Michael Heide
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
- German Primate CenterLeibniz Institute for Primate ResearchGöttingenGermany
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47
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Ding J, Pollen AA. Filling an ARHGAP in our knowledge of human brain evolution. EMBO Rep 2022; 23:e56076. [PMID: 36161459 PMCID: PMC9638863 DOI: 10.15252/embr.202256076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 09/14/2022] [Indexed: 09/29/2023] Open
Abstract
The human cerebral cortex has tripled in size since our divergence from a common ancestor with chimpanzees. This cortical expansion is driven by the increased proliferative capacity of radial glia (RG), a neural progenitor cell (NPC) population that generates cortical neurons. RG along the ventricular zone (VZ) produce neurons and also give rise to basal progenitors (BPs), which migrate to the embryonic subventricular zone (SVZ). Comparative studies suggest that the increased proliferative capacity of human NPCs involves cell-intrinsic mechanisms (Otani et al, 2016), and a number of human-specific genetic changes have recently been linked to NPC proliferation. In particular, overexpression studies in model organisms indicate that the human-specific gene ARHGAP11B is sufficient to increase BP abundance when introduced into the developing brain of non-human model organisms (Florio et al, 2015; Kalebic et al, 2018; Heide et al, 2020). However, studying human-specific mutations in a hominid genetic and developmental context, rather than in more divergent model organisms, could provide further insight into the evolutionary consequences and effect size of human mutations. Fischer et al (2022) now developed a novel organoid electroporation technique to establish the necessity and sufficiency of ARHGAP11B for BP proliferation in cells from humans and our closest living relative, chimpanzees (Fig 1).
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Affiliation(s)
- Jingwen Ding
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell ResearchUniversity of California, San FranciscoSan FranciscoCAUSA
- Department of NeurologyUniversity of California, San FranciscoSan FranciscoCAUSA
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell ResearchUniversity of California, San FranciscoSan FranciscoCAUSA
- Department of NeurologyUniversity of California, San FranciscoSan FranciscoCAUSA
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Fischer J, Fernández Ortuño E, Marsoner F, Artioli A, Peters J, Namba T, Eugster Oegema C, Huttner WB, Ladewig J, Heide M. Human-specific ARHGAP11B ensures human-like basal progenitor levels in hominid cerebral organoids. EMBO Rep 2022; 23:e54728. [PMID: 36381990 PMCID: PMC9646322 DOI: 10.1101/2020.10.01.322792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 08/18/2022] [Accepted: 08/23/2022] [Indexed: 06/16/2023] Open
Abstract
The human-specific gene ARHGAP11B has been implicated in human neocortex expansion. However, the extent of ARHGAP11B's contribution to this expansion during hominid evolution is unknown. Here we address this issue by genetic manipulation of ARHGAP11B levels and function in chimpanzee and human cerebral organoids. ARHGAP11B expression in chimpanzee cerebral organoids doubles basal progenitor levels, the class of cortical progenitors with a key role in neocortex expansion. Conversely, interference with ARHGAP11B's function in human cerebral organoids decreases basal progenitors down to the chimpanzee level. Moreover, ARHGAP11A or ARHGAP11B rescue experiments in ARHGAP11A plus ARHGAP11B double-knockout human forebrain organoids indicate that lack of ARHGAP11B, but not of ARHGAP11A, decreases the abundance of basal radial glia - the basal progenitor type thought to be of particular relevance for neocortex expansion. Taken together, our findings demonstrate that ARHGAP11B is necessary and sufficient to ensure the elevated basal progenitor levels that characterize the fetal human neocortex, suggesting that this human-specific gene was a major contributor to neocortex expansion during human evolution.
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Affiliation(s)
- Jan Fischer
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
- Present address:
Institute for Clinical GeneticsUniversity Hospital Carl Gustav CarusDresdenGermany
| | | | - Fabio Marsoner
- Central Institute of Mental HealthUniversity of Heidelberg/Medical Faculty MannheimMannheimGermany
- Hector Institute for Translational Brain Research (HITBR gGmbH)MannheimGermany
- German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Annasara Artioli
- Central Institute of Mental HealthUniversity of Heidelberg/Medical Faculty MannheimMannheimGermany
- Hector Institute for Translational Brain Research (HITBR gGmbH)MannheimGermany
- German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Jula Peters
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
| | - Takashi Namba
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
- Present address:
Neuroscience Center, HiLIFE ‐ Helsinki Institute of Life ScienceUniversity of HelsinkiHelsinkiFinland
| | | | - Wieland B. Huttner
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
| | - Julia Ladewig
- Central Institute of Mental HealthUniversity of Heidelberg/Medical Faculty MannheimMannheimGermany
- Hector Institute for Translational Brain Research (HITBR gGmbH)MannheimGermany
- German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Michael Heide
- Max Planck Institute of Molecular Cell Biology and GeneticsPfotenhauerstrasse 108DresdenGermany
- German Primate CenterLeibniz Institute for Primate ResearchGöttingenGermany
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Abstract
Paleoproteomics, the study of ancient proteins, is a rapidly growing field at the intersection of molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages the longevity and diversity of proteins to explore fundamental questions about the past. While its origins predate the characterization of DNA, it was only with the advent of soft ionization mass spectrometry that the study of ancient proteins became truly feasible. Technological gains over the past 20 years have allowed increasing opportunities to better understand preservation, degradation, and recovery of the rich bioarchive of ancient proteins found in the archaeological and paleontological records. Growing from a handful of studies in the 1990s on individual highly abundant ancient proteins, paleoproteomics today is an expanding field with diverse applications ranging from the taxonomic identification of highly fragmented bones and shells and the phylogenetic resolution of extinct species to the exploration of past cuisines from dental calculus and pottery food crusts and the characterization of past diseases. More broadly, these studies have opened new doors in understanding past human-animal interactions, the reconstruction of past environments and environmental changes, the expansion of the hominin fossil record through large scale screening of nondiagnostic bone fragments, and the phylogenetic resolution of the vertebrate fossil record. Even with these advances, much of the ancient proteomic record still remains unexplored. Here we provide an overview of the history of the field, a summary of the major methods and applications currently in use, and a critical evaluation of current challenges. We conclude by looking to the future, for which innovative solutions and emerging technology will play an important role in enabling us to access the still unexplored "dark" proteome, allowing for a fuller understanding of the role ancient proteins can play in the interpretation of the past.
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Affiliation(s)
- Christina Warinner
- Department
of Anthropology, Harvard University, Cambridge, Massachusetts 02138, United States
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04103, Germany
| | - Kristine Korzow Richter
- Department
of Anthropology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Matthew J. Collins
- Department
of Archaeology, Cambridge University, Cambridge CB2 3DZ, United Kingdom
- Section
for Evolutionary Genomics, Globe Institute,
University of Copenhagen, Copenhagen 1350, Denmark
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50
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Alhazmi S, Alzahrani M, Farsi R, Alharbi M, Algothmi K, Alburae N, Ganash M, Azhari S, Basingab F, Almuhammadi A, Alqosaibi A, Alkhatabi H, Elaimi A, Jan M, Aldhalaan HM, Alrafiah A, Alrofaidi A. Multiple Recurrent Copy Number Variations (CNVs) in Chromosome 22 Including 22q11.2 Associated with Autism Spectrum Disorder. Pharmgenomics Pers Med 2022; 15:705-720. [PMID: 35898556 PMCID: PMC9309317 DOI: 10.2147/pgpm.s366826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 07/14/2022] [Indexed: 11/29/2022] Open
Abstract
Introduction Autism spectrum disorder (ASD) is a developmental disorder that can cause substantial social, communication, and behavioral challenges. Genetic factors play a significant role in ASD, where the risk of ASD has been increased for unclear reasons. Twin studies have shown important evidence of both genetic and environmental contributions in ASD, where the level of contribution of these factors has not been proven yet. It has been suggested that copy number variation (CNV) duplication and the deletion of many genes in chromosome 22 (Ch22) may have a strong association with ASD. This study screened the CNVs in Ch22 in autistic Saudi children and assessed the candidate gene in the CNVs region of Ch22 that is most associated with ASD. Methods This study included 15 autistic Saudi children as well as 4 healthy children as controls; DNA was extracted from samples and analyzed using array comparative genomic hybridization (aCGH) and DNA sequencing. Results The aCGH detected (in only 6 autistic samples) deletion and duplication in many regions of Ch22, including some critical genes. Moreover, DNA sequencing determined a genetic mutation in the TBX1 gene sequence in autistic samples. This study, carried out using aCGH, found that six autistic patients had CNVs in Ch22, and DNA sequencing revealed mutations in the TBX1 gene in autistic samples but none in the control. Conclusion CNV deletion and the duplication of the TBX1 gene could be related to ASD; therefore, this gene needs more analysis in terms of expression levels.
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Affiliation(s)
- Safiah Alhazmi
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Maryam Alzahrani
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Reem Farsi
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mona Alharbi
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Khloud Algothmi
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Najla Alburae
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Magdah Ganash
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Sheren Azhari
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Fatemah Basingab
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Asma Almuhammadi
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Amany Alqosaibi
- Department of Biology, Imam Abdulrahman bin Faisal University, Dammam, Saudi Arabia
| | - Heba Alkhatabi
- Centre of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Medical Laboratory Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Aisha Elaimi
- Centre of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Medical Laboratory Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mohammed Jan
- College of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Hesham M Aldhalaan
- Center for Autism Research at King Faisal Specialist Hospital & Research Center, Riyadh, Saudi Arabia
| | - Aziza Alrafiah
- Department of Medical Laboratory Science, King Abdulaziz University, Jeddah, Saudi Arabia
- Correspondence: Aziza Alrafiah, Department of Medical Laboratory Science, King Abdulaziz University, P.O Box 80200, Jeddah, 21589, Saudi Arabia, Tel +966 126401000 Ext. 23495, Fax +966 126401000 Ext. 21686, Email
| | - Aisha Alrofaidi
- Department of Biological Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
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