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Ding W, Li X, Zhang J, Ji M, Zhang M, Zhong X, Cao Y, Liu X, Li C, Xiao C, Wang J, Li T, Yu Q, Mo F, Zhang B, Qi J, Yang JC, Qi J, Tian L, Xu X, Peng Q, Zhou WZ, Liu Z, Fu A, Zhang X, Zhang JJ, Sun Y, Hu B, An NA, Zhang L, Li CY. Adaptive functions of structural variants in human brain development. SCIENCE ADVANCES 2024; 10:eadl4600. [PMID: 38579006 DOI: 10.1126/sciadv.adl4600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 03/01/2024] [Indexed: 04/07/2024]
Abstract
Quantifying the structural variants (SVs) in nonhuman primates could provide a niche to clarify the genetic backgrounds underlying human-specific traits, but such resource is largely lacking. Here, we report an accurate SV map in a population of 562 rhesus macaques, verified by in-house benchmarks of eight macaque genomes with long-read sequencing and another one with genome assembly. This map indicates stronger selective constrains on inversions at regulatory regions, suggesting a strategy for prioritizing them with the most important functions. Accordingly, we identified 75 human-specific inversions and prioritized them. The top-ranked inversions have substantially shaped the human transcriptome, through their dual effects of reconfiguring the ancestral genomic architecture and introducing regional mutation hotspots at the inverted regions. As a proof of concept, we linked APCDD1, located on one of these inversions and down-regulated specifically in humans, to neuronal maturation and cognitive ability. We thus highlight inversions in shaping the human uniqueness in brain development.
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Affiliation(s)
- Wanqiu Ding
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xiangshang Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jie Zhang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Mingjun Ji
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Mengling Zhang
- State Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Xiaoming Zhong
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- Center of Excellence for Leukemia Studies, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Yong Cao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119S Fourth Ring Rd W, Fengtai District, Beijing, China
| | - Xiaoge Liu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Chunqiong Li
- Chinese Institute for Brain Research, Beijing, China
| | - Chunfu Xiao
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jiaxin Wang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Ting Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Qing Yu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Fan Mo
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Boya Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jianhuan Qi
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jie-Chun Yang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Juntian Qi
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Lu Tian
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xinwei Xu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Qi Peng
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Wei-Zhen Zhou
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhijin Liu
- College of Life Sciences, Capital Normal University, Beijing, China
| | - Aisi Fu
- Wuhan Dgensee Clinical Laboratory, Wuhan, China
| | - Xiuqin Zhang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jian-Jun Zhang
- Shanxi Key Laboratory of Chinese Medicine Encephalopathy, National International Joint Research Center for Molecular Chinese Medicine, Shanxi University of Chinese Medicine, Jinzhong, China
| | - Yujie Sun
- State Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Baoyang Hu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Ni A An
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
| | - Li Zhang
- Chinese Institute for Brain Research, Beijing, China
| | - Chuan-Yun Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
- Southwest United Graduate School, Kunming 650092, China
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Voinescu CD, Mozere M, Genovese G, Downie ML, Gupta S, Gale DP, Bockenhauer D, Kleta R, Arcos-Burgos M, Stanescu HC. A Neanderthal haplotype introgressed into the human genome confers protection against membranous nephropathy. Kidney Int 2024; 105:791-798. [PMID: 38367960 DOI: 10.1016/j.kint.2024.01.017] [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: 01/19/2023] [Revised: 12/27/2023] [Accepted: 01/08/2024] [Indexed: 02/19/2024]
Abstract
Class 2 HLA and PLA2R1 alleles are exceptionally strong genetic risk factors for membranous nephropathy (MN), leading, through an unknown mechanism, to a targeted autoimmune response. Introgressed archaic haplotypes (introduced from an archaic human genome into the modern human genome) might influence phenotypes through gene dysregulation. Here, we investigated the genomic region surrounding the PLA2R1 gene. We reconstructed the phylogeny of Neanderthal and modern haplotypes in this region and calculated the probability of the observed clustering being the result of introgression or common descent. We imputed variants for the participants in our previous genome-wide association study and we compared the distribution of Neanderthal variants between MN cases and controls. The region associated with the lead MN risk locus in the PLA2R1 gene was confirmed and showed that, within a 507 kb region enriched in introgressed sequence, a stringently defined 105 kb haplotype, intersecting the coding regions for PLA2R1 and ITGB6, is inherited from Neanderthals. Thus, introgressed Neanderthal haplotypes overlapping PLA2R1 are differentially represented in MN cases and controls, with enrichment In controls suggesting a protective effect.
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Affiliation(s)
- Cătălin D Voinescu
- Centre for Genetics and Genomics, Department of Renal Medicine, UCL Division of Medicine, University College London, London, UK
| | - Monika Mozere
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Vilnius, Lithuania
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Mallory L Downie
- Centre for Genetics and Genomics, Department of Renal Medicine, UCL Division of Medicine, University College London, London, UK
| | - Sanjana Gupta
- Centre for Genetics and Genomics, Department of Renal Medicine, UCL Division of Medicine, University College London, London, UK
| | - Daniel P Gale
- Centre for Genetics and Genomics, Department of Renal Medicine, UCL Division of Medicine, University College London, London, UK
| | - Detlef Bockenhauer
- Centre for Genetics and Genomics, Department of Renal Medicine, UCL Division of Medicine, University College London, London, UK
| | - Robert Kleta
- Centre for Genetics and Genomics, Department of Renal Medicine, UCL Division of Medicine, University College London, London, UK
| | - Mauricio Arcos-Burgos
- Grupo de Investigación en Psiquiatría, Departamento de Psiquiatría, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - Horia C Stanescu
- Centre for Genetics and Genomics, Department of Renal Medicine, UCL Division of Medicine, University College London, London, UK.
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Subramanian K, Chopra M, Kahali B. Landscape of genomic structural variations in Indian population-based cohorts: Deeper insights into their prevalence and clinical relevance. HGG ADVANCES 2024; 5:100285. [PMID: 38521976 PMCID: PMC11007539 DOI: 10.1016/j.xhgg.2024.100285] [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: 09/14/2023] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 03/25/2024] Open
Abstract
Structural variations (SV) are large (>50 base pairs) genomic rearrangements comprising deletions, duplications, insertions, inversions, and translocations. Studying SVs is important because they play active and critical roles in regulating gene expression, determining disease predispositions, and identifying population-specific differences among individuals of diverse ancestries. However, SV discoveries in the Indian population using whole-genome sequencing (WGS) have been limited. In this study, using short-read WGS having an average 42X depth of coverage, we identify and characterize 36,210 SVs from 529 individuals enrolled in population-based cohorts in India. These SVs include 24,574 deletions, 2,913 duplications, 8,710 insertions, and 13 inversions; 1.26% (456 out of 36,210) of the identified SVs can potentially impact the coding regions of genes. Furthermore, 56 of these SVs are highly intolerant to loss-of-function changes to the mapped genes, and five SVs impacting ADAMTS17, CCDC40, and RHCE are common in our study individuals. Seven rare SVs significantly impact dosage sensitivity of genes known to be associated with various clinical phenotypes. Most of the SVs in our study are rare and heterozygous. This fine-scale SV discovery in the underrepresented Indian population provides valuable insights that extend beyond Eurocentric human genetic studies.
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Affiliation(s)
- Krithika Subramanian
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India; Manipal Academy of Higher Education, Manipal, Karnataka 576104, India
| | - Mehak Chopra
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India
| | - Bratati Kahali
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India.
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4
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Wu Z, Li T, Jiang Z, Zheng J, Gu Y, Liu Y, Liu Y, Xie Z. Human pangenome analysis of sequences missing from the reference genome reveals their widespread evolutionary, phenotypic, and functional roles. Nucleic Acids Res 2024; 52:2212-2230. [PMID: 38364871 PMCID: PMC10954445 DOI: 10.1093/nar/gkae086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 01/18/2024] [Accepted: 01/27/2024] [Indexed: 02/18/2024] Open
Abstract
Nonreference sequences (NRSs) are DNA sequences present in global populations but absent in the current human reference genome. However, the extent and functional significance of NRSs in the human genomes and populations remains unclear. Here, we de novo assembled 539 genomes from five genetically divergent human populations using long-read sequencing technology, resulting in the identification of 5.1 million NRSs. These were merged into 45284 unique NRSs, with 29.7% being novel discoveries. Among these NRSs, 38.7% were common across the five populations, and 35.6% were population specific. The use of a graph-based pangenome approach allowed for the detection of 565 transcript expression quantitative trait loci on NRSs, with 426 of these being novel findings. Moreover, 26 NRS candidates displayed evidence of adaptive selection within human populations. Genes situated in close proximity to or intersecting with these candidates may be associated with metabolism and type 2 diabetes. Genome-wide association studies revealed 14 NRSs to be significantly associated with eight phenotypes. Additionally, 154 NRSs were found to be in strong linkage disequilibrium with 258 phenotype-associated SNPs in the GWAS catalogue. Our work expands the understanding of human NRSs and provides novel insights into their functions, facilitating evolutionary and biomedical researches.
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Affiliation(s)
- Zhikun Wu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Tong Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Zehang Jiang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Jingjing Zheng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Yizhou Gu
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
- University of Wisconsin-Madison, WI, USA
| | - Yizhi Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Yun Liu
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China
| | - Zhi Xie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, China
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5
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Neves PD, Watanabe A, Watanabe EH, Narcizo AM, Nunes K, Lerario AM, Ferreira FM, Cavalcante LB, Wongboonsin J, Malheiros DM, Jorge LB, Sampson MG, Noronha IL, Onuchic LF. Idiopathic collapsing glomerulopathy is associated with APOL1 high-risk genotypes or Mendelian variants in most affected individuals in a highly admixed population. Kidney Int 2024; 105:593-607. [PMID: 38143038 DOI: 10.1016/j.kint.2023.11.028] [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: 04/19/2023] [Revised: 09/04/2023] [Accepted: 11/16/2023] [Indexed: 12/26/2023]
Abstract
Collapsing glomerulopathy (CG) is most often associated with fast progression to kidney failure with an incidence apparently higher in Brazil than in other countries. However, the reason for this occurrence is unknown. To better understand this, we performed an integrated analysis of clinical, histological, therapeutic, causative genetic and genetic ancestry data in a highly genetically admixed cohort of 70 children and adult patients with idiopathic CG (ICG). The disease onset occurred at 23 (interquartile range: 17-31) years and approximately half of patients progressed to chronic kidney disease requiring kidney replacement therapy (CKD-KRT) 36 months after diagnosis. Causative genetic bases, assessed by targeted-gene panel or whole-exome sequencing, were identified in 58.6% of patients. Among these cases, 80.5% harbored APOL1 high-risk genotypes (HRG) and 19.5% causative Mendelian variants (MV). Self-reported non-White patients more frequently had HRG. MV was an independent risk factor for progression to CKD-KRT by 36 months and the end of follow-up, while remission was an independent protective factor. All patients with HRG manifested CG at 9-44 years of age, whereas in those with APOL1 low-risk genotype, the disease arose throughout life. HRGs were associated with higher proportion of African genetic ancestry. Novel causative MVs were identified in COL4A5, COQ2 and PLCE1 and previously described causative MVs were identified in MYH9, TRPC6, COQ2, COL4A3 and TTC21B. Three patients displayed HRG combined with a variant of uncertain significance (ITGB4, LAMA5 or PTPRO). MVs were associated with worse kidney prognosis. Thus, our data reveal that the genetic status plays a major role in ICG pathogenesis, accounting for more than half of cases in a highly admixed Brazilian population.
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Affiliation(s)
- Precil D Neves
- Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil; Division of Molecular Medicine, University of São Paulo School of Medicine, São Paulo, Brazil; Nephrology and Dialysis Center, Oswaldo Cruz German Hospital, São Paulo, Brazil
| | - Andreia Watanabe
- Division of Molecular Medicine, University of São Paulo School of Medicine, São Paulo, Brazil; Division of Pediatric Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Elieser H Watanabe
- Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil; Division of Molecular Medicine, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Amanda M Narcizo
- Large-Scale Sequencing Laboratory, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Kelly Nunes
- Human Genome Center, Institute of Biosciences/University of São Paulo, São Paulo, Brazil
| | - Antonio M Lerario
- Division of Endocrinology, University of Michigan, Ann Arbor, Michigan, USA
| | - Frederico M Ferreira
- Department of Pathology, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Lívia B Cavalcante
- Department of Pathology, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Janewit Wongboonsin
- Division of Pediatric Nephrology, Boston Children's Hospital, Boston, Massachusetts, USA; Division of Nephrology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Denise M Malheiros
- Department of Pathology, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Lectícia B Jorge
- Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Matthew G Sampson
- Division of Pediatric Nephrology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Irene L Noronha
- Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Luiz F Onuchic
- Division of Nephrology, University of São Paulo School of Medicine, São Paulo, Brazil; Division of Molecular Medicine, University of São Paulo School of Medicine, São Paulo, Brazil.
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6
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An X, Mao L, Wang Y, Xu Q, Liu X, Zhang S, Qiao Z, Li B, Li F, Kuang Z, Wan N, Liang X, Duan Q, Feng Z, Yang X, Liu S, Nevo E, Liu J, Storz JF, Li K. Genomic structural variation is associated with hypoxia adaptation in high-altitude zokors. Nat Ecol Evol 2024; 8:339-351. [PMID: 38195998 DOI: 10.1038/s41559-023-02275-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 11/20/2023] [Indexed: 01/11/2024]
Abstract
Zokors, an Asiatic group of subterranean rodents, originated in lowlands and colonized high-elevational zones following the uplift of the Qinghai-Tibet plateau about 3.6 million years ago. Zokors live at high elevation in subterranean burrows and experience hypobaric hypoxia, including both hypoxia (low oxygen concentration) and hypercapnia (elevated partial pressure of CO2). Here we report a genomic analysis of six zokor species (genus Eospalax) with different elevational ranges to identify structural variants (deletions and inversions) that may have contributed to high-elevation adaptation. Based on an assembly of a chromosome-level genome of the high-elevation species, Eospalax baileyi, we identified 18 large inversions that distinguished this species from congeners native to lower elevations. Small-scale structural variants in the introns of EGLN1, HIF1A, HSF1 and SFTPD of E. baileyi were associated with the upregulated expression of those genes. A rearrangement on chromosome 1 was associated with altered chromatin accessibility, leading to modified gene expression profiles of key genes involved in the physiological response to hypoxia. Multigene families that underwent copy-number expansions in E. baileyi were enriched for autophagy, HIF1 signalling and immune response. E. baileyi show a significantly larger lung mass than those of other Eospalax species. These findings highlight the key role of structural variants underlying hypoxia adaptation of high-elevation species in Eospalax.
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Affiliation(s)
- Xuan An
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Leyan Mao
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Yinjia Wang
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Qinqin Xu
- Department of Medical Oncology, Qinghai Provincial People's Hospital, Xining, China
| | - Xi Liu
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Shangzhe Zhang
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Zhenglei Qiao
- College of Life Sciences and Technology, Mudanjiang Normal University, Mudanjiang, China
| | - Bowen Li
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Fang Li
- College of Life Sciences and Technology, Mudanjiang Normal University, Mudanjiang, China
| | - Zhuoran Kuang
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Na Wan
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Xiaolong Liang
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Qijiao Duan
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Zhilong Feng
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Xiaojie Yang
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Sanyuan Liu
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China
| | - Eviatar Nevo
- Institute of Evolution, University of Haifa, Haifa, Israel
| | - Jianquan Liu
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China.
| | - Jay F Storz
- School of Biological Sciences, University of Nebraska, Lincoln, NE, USA.
| | - Kexin Li
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, China.
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7
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He G, Wang P, Chen J, Liu Y, Sun Y, Hu R, Duan S, Sun Q, Tang R, Yang J, Wang Z, Yun L, Hu L, Yan J, Nie S, Wei L, Liu C, Wang M. Differentiated genomic footprints suggest isolation and long-distance migration of Hmong-Mien populations. BMC Biol 2024; 22:18. [PMID: 38273256 PMCID: PMC10809681 DOI: 10.1186/s12915-024-01828-x] [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: 01/23/2023] [Accepted: 01/12/2024] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND The underrepresentation of Hmong-Mien (HM) people in Asian genomic studies has hindered our comprehensive understanding of the full landscape of their evolutionary history and complex trait architecture. South China is a multi-ethnic region and indigenously settled by ethnolinguistically diverse HM, Austroasiatic (AA), Tai-Kadai (TK), Austronesian (AN), and Sino-Tibetan (ST) people, which is regarded as East Asia's initial cradle of biodiversity. However, previous fragmented genetic studies have only presented a fraction of the landscape of genetic diversity in this region, especially the lack of haplotype-based genomic resources. The deep characterization of demographic history and natural-selection-relevant genetic architecture of HM people was necessary. RESULTS We reported one HM-specific genomic resource and comprehensively explored the fine-scale genetic structure and adaptative features inferred from the genome-wide SNP data of 440 HM individuals from 33 ethnolinguistic populations, including previously unreported She. We identified solid genetic differentiation between HM people and Han Chinese at 7.64‒15.86 years ago (kya) and split events between southern Chinese inland (Miao/Yao) and coastal (She) HM people in the middle Bronze Age period and the latter obtained more gene flow from Ancient Northern East Asians. Multiple admixture models further confirmed that extensive gene flow from surrounding ST, TK, and AN people entangled in forming the gene pool of Chinese coastal HM people. Genetic findings of isolated shared unique ancestral components based on the sharing alleles and haplotypes deconstructed that HM people from the Yungui Plateau carried the breadth of previously unknown genomic diversity. We identified a direct and recent genetic connection between Chinese inland and Southeast Asian HM people as they shared the most extended identity-by-descent fragments, supporting the long-distance migration hypothesis. Uniparental phylogenetic topology and network-based phylogenetic relationship reconstruction found ancient uniparental founding lineages in southwestern HM people. Finally, the population-specific biological adaptation study identified the shared and differentiated natural selection signatures among inland and coastal HM people associated with physical features and immune functions. The allele frequency spectrum of cancer susceptibility alleles and pharmacogenomic genes showed significant differences between HM and northern Chinese people. CONCLUSIONS Our extensive genetic evidence combined with the historical documents supported the view that ancient HM people originated from the Yungui regions associated with ancient "Three-Miao tribes" descended from the ancient Daxi-Qujialing-Shijiahe people. Then, some have recently migrated rapidly to Southeast Asia, and some have migrated eastward and mixed respectively with Southeast Asian indigenes, Liangzhu-related coastal ancient populations, and incoming southward ST people. Generally, complex population migration, admixture, and adaptation history contributed to the complicated patterns of population structure of geographically diverse HM people.
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Affiliation(s)
- Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China.
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
| | - Peixin Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Medical Information, Chongqing Medical University, Chongqing, 400331, China
| | - Jing Chen
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Yan Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Yuntao Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Institute of Forensic Medicine, West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Rong Hu
- School of Sociology and Anthropology, Xiamen University, Xiamen, 361005, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Qiuxia Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Renkuan Tang
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Junbao Yang
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Zhiyong Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Libing Yun
- Institute of Forensic Medicine, West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Liping Hu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Jiangwei Yan
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Shengjie Nie
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Lanhai Wei
- School of Ethnology and Anthropology, Inner Mongolia Normal University, Inner Mongolia, 010028, China
| | - Chao Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
| | - Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China.
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
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8
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Sun Y, Wang M, Sun Q, Liu Y, Duan S, Wang Z, Zhou Y, Zhong J, Huang Y, Huang X, Yang Q, Li X, Su H, Cai Y, Jiang X, Chen J, Yan J, Nie S, Hu L, Yang J, Tang R, Wang CC, Liu C, Deng X, Yun L, He G. Distinguished biological adaptation architecture aggravated population differentiation of Tibeto-Burman-speaking people. J Genet Genomics 2023:S1673-8527(23)00210-2. [PMID: 37827489 DOI: 10.1016/j.jgg.2023.10.002] [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: 08/25/2023] [Revised: 09/28/2023] [Accepted: 10/04/2023] [Indexed: 10/14/2023]
Abstract
Tibeto-Burman (TB) people have endeavored to adapt to the hypoxic, cold, and high-UV high-altitude environments in the Tibetan Plateau and complex disease exposures in lowland rainforests since the late Paleolithic period. However, the full landscape of genetic history and biological adaptation of geographically diverse TB-speaking people, as well as their interaction mechanism, remain unknown. Here, we generate a whole-genome meta-database of 500 individuals from 39 TB-speaking populations and present a comprehensive landscape of genetic diversity, admixture history, and differentiated adaptative features of geographically different TB-speaking people. We identify genetic differentiation related to geography and language among TB-speaking people, consistent with their differentiated admixture process with incoming or indigenous ancestral source populations. A robust genetic connection between the Tibetan-Yi corridor and the ancient Yellow River people supports their Northern China origin hypothesis. We finally report substructure-related differentiated biological adaptative signatures between highland Tibetans and Loloish speakers. Adaptative signatures associated with the physical pigmentation (EDAR and SLC24A5) and metabolism (ALDH9A1) are identified in Loloish people, which differed from the high-altitude adaptative genetic architecture in Tibetan. TB-related genomic resources provide new insights into the genetic basis of biological adaptation and better reference for the anthropologically informed sampling design in biomedical and genomic cohort research.
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Affiliation(s)
- Yuntao Sun
- West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, China; Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610000, China
| | - Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610000, China; Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510275, China; Guangzhou Forensic Science Institute, Guangzhou, Guangdong 510055, China.
| | - Qiuxia Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Yan Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; School of Clinical Medical Sciences, North Sichuan Medical College, Nanchong, Sichuan 637100, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, Sichuan 637100, China
| | - Zhiyong Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan 650500, China
| | - Yunyu Zhou
- School of Stomatology, North Sichuan Medical College, Nanchong, Sichuan 637100, China
| | - Jun Zhong
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, Sichuan 637100, China
| | - Yuguo Huang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China
| | - Xinyu Huang
- West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qingxin Yang
- School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan 650500, China
| | - Xiangping Li
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan 650500, China
| | - Haoran Su
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, Sichuan 637100, China
| | - Yan Cai
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, Sichuan 637100, China; Department of Medical Laboratory, North Sichuan Medical College, Nanchong, Sichuan 637007, China
| | - Xiucheng Jiang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, Sichuan 637100, China
| | - Jing Chen
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; School of Forensic Medicine, Shanxi Medical University, Jinzhong, Sichuan 030001, China
| | - Jiangwei Yan
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, Sichuan 030001, China
| | - Shengjie Nie
- School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan 650500, China
| | - Liping Hu
- School of Forensic Medicine, Kunming Medical University, Kunming, Yunnan 650500, China
| | - Junbao Yang
- School of Clinical Medical Sciences, North Sichuan Medical College, Nanchong, Sichuan 637100, China
| | - Renkuan Tang
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Chuan-Chao Wang
- School of Life Sciences, Xiamen University, Xiamen, Fujian 361005, China
| | - Chao Liu
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, Guangdong 510230, China
| | - Xiaohui Deng
- West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Libing Yun
- West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610000, China.
| | - Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610000, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610000, China.
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9
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Yang C, Zhou Y, Song Y, Wu D, Zeng Y, Nie L, Liu P, Zhang S, Chen G, Xu J, Zhou H, Zhou L, Qian X, Liu C, Tan S, Zhou C, Dai W, Xu M, Qi Y, Wang X, Guo L, Fan G, Wang A, Deng Y, Zhang Y, Jin J, He Y, Guo C, Guo G, Zhou Q, Xu X, Yang H, Wang J, Xu S, Mao Y, Jin X, Ruan J, Zhang G. The complete and fully-phased diploid genome of a male Han Chinese. Cell Res 2023; 33:745-761. [PMID: 37452091 PMCID: PMC10542383 DOI: 10.1038/s41422-023-00849-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 06/29/2023] [Indexed: 07/18/2023] Open
Abstract
Since the release of the complete human genome, the priority of human genomic study has now been shifting towards closing gaps in ethnic diversity. Here, we present a fully phased and well-annotated diploid human genome from a Han Chinese male individual (CN1), in which the assemblies of both haploids achieve the telomere-to-telomere (T2T) level. Comparison of this diploid genome with the CHM13 haploid T2T genome revealed significant variations in the centromere. Outside the centromere, we discovered 11,413 structural variations, including numerous novel ones. We also detected thousands of CN1 alleles that have accumulated high substitution rates and a few that have been under positive selection in the East Asian population. Further, we found that CN1 outperforms CHM13 as a reference genome in mapping and variant calling for the East Asian population owing to the distinct structural variants of the two references. Comparison of SNP calling for a large cohort of 8869 Chinese genomes using CN1 and CHM13 as reference respectively showed that the reference bias profoundly impacts rare SNP calling, with nearly 2 million rare SNPs miss-called with different reference genomes. Finally, applying the CN1 as a reference, we discovered 5.80 Mb and 4.21 Mb putative introgression sequences from Neanderthal and Denisovan, respectively, including many East Asian specific ones undetected using CHM13 as the reference. Our analyses reveal the advances of using CN1 as a reference for population genomic studies and paleo-genomic studies. This complete genome will serve as an alternative reference for future genomic studies on the East Asian population.
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Affiliation(s)
- Chentao Yang
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Yang Zhou
- BGI-Shenzhen, Shenzhen, Guangdong, China
- BGI Research-Wuhan, BGI, Wuhan, Hubei, China
| | - Yanni Song
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Dongya Wu
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yan Zeng
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Lei Nie
- BGI-Shenzhen, Shenzhen, Guangdong, 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
| | - Guangji Chen
- BGI-Shenzhen, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jinjin Xu
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Hongling Zhou
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Long Zhou
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaobo Qian
- BGI-Shenzhen, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Chenlu Liu
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | | | | | - Wei Dai
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Mengyang Xu
- BGI-Shenzhen, Shenzhen, Guangdong, China
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Yanwei Qi
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Xiaobo Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Lidong Guo
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Guangyi Fan
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Aijun Wang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Yuan Deng
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Yong Zhang
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | | | - Yunqiu He
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Chunxue Guo
- BGI-Shenzhen, Shenzhen, Guangdong, China
- BGI-Hangzhou, Hangzhou, Zhejiang, China
| | - Guoji Guo
- School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qing Zhou
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | | | - Jian Wang
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
- Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, China
- Jiangsu Key Laboratory of Phylogenomics & Comparative Genomics, International Joint Center of Genomics of Jiangsu Province School of Life Sciences, Jiangsu Normal University, Xuzhou, Jiangsu, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, 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
| | - Xin Jin
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Jue Ruan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China.
| | - Guojie Zhang
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China.
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China.
- Innovation Center of Yangtze River Delta, Zhejiang University, Hangzhou, Zhejiang, China.
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
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10
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Xia X, Zhang F, Li S, Luo X, Peng L, Dong Z, Pausch H, Leonard AS, Crysnanto D, Wang S, Tong B, Lenstra JA, Han J, Li F, Xu T, Gu L, Jin L, Dang R, Huang Y, Lan X, Ren G, Wang Y, Gao Y, Ma Z, Cheng H, Ma Y, Chen H, Pang W, Lei C, Chen N. Structural variation and introgression from wild populations in East Asian cattle genomes confer adaptation to local environment. Genome Biol 2023; 24:211. [PMID: 37723525 PMCID: PMC10507960 DOI: 10.1186/s13059-023-03052-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/07/2023] [Indexed: 09/20/2023] Open
Abstract
BACKGROUND Structural variations (SVs) in individual genomes are major determinants of complex traits, including adaptability to environmental variables. The Mongolian and Hainan cattle breeds in East Asia are of taurine and indicine origins that have evolved to adapt to cold and hot environments, respectively. However, few studies have investigated SVs in East Asian cattle genomes and their roles in environmental adaptation, and little is known about adaptively introgressed SVs in East Asian cattle. RESULTS In this study, we examine the roles of SVs in the climate adaptation of these two cattle lineages by generating highly contiguous chromosome-scale genome assemblies. Comparison of the two assemblies along with 18 Mongolian and Hainan cattle genomes obtained by long-read sequencing data provides a catalog of 123,898 nonredundant SVs. Several SVs detected from long reads are in exons of genes associated with epidermal differentiation, skin barrier, and bovine tuberculosis resistance. Functional investigations show that a 108-bp exonic insertion in SPN may affect the uptake of Mycobacterium tuberculosis by macrophages, which might contribute to the low susceptibility of Hainan cattle to bovine tuberculosis. Genotyping of 373 whole genomes from 39 breeds identifies 2610 SVs that are differentiated along a "north-south" gradient in China and overlap with 862 related genes that are enriched in pathways related to environmental adaptation. We identify 1457 Chinese indicine-stratified SVs that possibly originate from banteng and are frequent in Chinese indicine cattle. CONCLUSIONS Our findings highlight the unique contribution of SVs in East Asian cattle to environmental adaptation and disease resistance.
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Affiliation(s)
- Xiaoting Xia
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Fengwei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Shuang Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Xiaoyu Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Lixin Peng
- National Engineering Research Center for Non-Food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, China
| | - Zheng Dong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Alexander S Leonard
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Danang Crysnanto
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Shikang Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Bin Tong
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Jianlin Han
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
- CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agriculture Sciences (CAAS), Beijing, China
| | - Fuyong Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Tieshan Xu
- Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Lihong Gu
- Institute of Animal Science & Veterinary Medicine, Hainan Academy of Agricultural Sciences, Haikou, China
| | - Liangliang Jin
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Ruihua Dang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yongzhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Xianyong Lan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Gang Ren
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yuanpeng Gao
- College of Veterinary Medicine, Northwest A&F University, Xianyang, Yangling, China
| | - Zhijie Ma
- Qinghai Academy of Animal Science and Veterinary Medicine, Qinghai University, Xining, China
| | - Haijian Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Shandong Key Lab of Animal Disease Control and Breeding, Jinan, China
| | - Yun Ma
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, School of Agriculture, Ningxia University, Yinchuan, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Weijun Pang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
| | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
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11
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Antinucci M, Comas D, Calafell F. Population history modulates the fitness effects of Copy Number Variation in the Roma. Hum Genet 2023; 142:1327-1343. [PMID: 37311904 PMCID: PMC10449987 DOI: 10.1007/s00439-023-02579-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 06/02/2023] [Indexed: 06/15/2023]
Abstract
We provide the first whole genome Copy Number Variant (CNV) study addressing Roma, along with reference populations from South Asia, the Middle East and Europe. Using CNV calling software for short-read sequence data, we identified 3171 deletions and 489 duplications. Taking into account the known population history of the Roma, as inferred from whole genome nucleotide variation, we could discern how this history has shaped CNV variation. As expected, patterns of deletion variation, but not duplication, in the Roma followed those obtained from single nucleotide polymorphisms (SNPs). Reduced effective population size resulting in slightly relaxed natural selection may explain our observation of an increase in intronic (but not exonic) deletions within Loss of Function (LoF)-intolerant genes. Over-representation analysis for LoF-intolerant gene sets hosting intronic deletions highlights a substantial accumulation of shared biological processes in Roma, intriguingly related to signaling, nervous system and development features, which may be related to the known profile of private disease in the population. Finally, we show the link between deletions and known trait-related SNPs reported in the genome-wide association study (GWAS) catalog, which exhibited even frequency distributions among the studied populations. This suggests that, in general human populations, the strong association between deletions and SNPs associated to biomedical conditions and traits could be widespread across continental populations, reflecting a common background of potentially disease/trait-related CNVs.
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Affiliation(s)
- Marco Antinucci
- Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - David Comas
- Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Francesc Calafell
- Institute of Evolutionary Biology (UPF-CSIC), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
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12
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Zhang YX, Wang XF, Niu YQ, Wang YG, Zhang WJ, Song ZP, Yang J, Li LF. Evolutionary roles of polyploidization-derived structural variations in the phenotypic diversification of Panax species. Mol Ecol 2023; 32:4999-5012. [PMID: 37525516 DOI: 10.1111/mec.17088] [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: 02/01/2023] [Revised: 07/10/2023] [Accepted: 07/19/2023] [Indexed: 08/02/2023]
Abstract
Genomic structural variations (SVs) are widespread in plant and animal genomes and play important roles in phenotypic novelty and species adaptation. Frequent whole genome duplications followed by (re)diploidizations have resulted in high diversity of genome architecture among extant species. In this study, we identified abundant genomic SVs in the Panax genus that are hypothesized to have occurred through during the repeated polyploidizations/(re)diploidizations. Our genome-wide comparisons demonstrated that although these polyploidization-derived SVs have evolved at distinct evolutionary stages, a large number of SV-intersecting genes showed enrichment in functionally important pathways related to secondary metabolites, photosynthesis and basic cellular activities. In line with these observations, our metabolic analyses of these Panax species revealed high diversity of primary and secondary metabolites both at the tissue and interspecific levels. In particular, genomic SVs identified at ginsenoside biosynthesis genes, including copy number variation and large fragment deletion, appear to have played important roles in the evolution and diversification of ginsenosides. A further herbivore deterrence experiment demonstrated that, as major triterpenoidal saponins found exclusively in Panax, ginsenosides provide protection against insect herbivores. Our study provides new insights on how polyploidization-derived SVs have contributed to phenotypic novelty and plant adaptation.
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Affiliation(s)
- Yu-Xin Zhang
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Xin-Feng Wang
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Yu-Qian Niu
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Yu-Guo Wang
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Wen-Ju Zhang
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Zhi-Ping Song
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Ji Yang
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Lin-Feng Li
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of Life Sciences, Fudan University, Shanghai, China
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13
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Dai X, Bian P, Hu D, Luo F, Huang Y, Jiao S, Wang X, Gong M, Li R, Cai Y, Wen J, Yang Q, Deng W, Nanaei HA, Wang Y, Wang F, Zhang Z, Rosen BD, Heller R, Jiang Y. A Chinese indicine pangenome reveals a wealth of novel structural variants introgressed from other Bos species. Genome Res 2023; 33:1284-1298. [PMID: 37714713 PMCID: PMC10547261 DOI: 10.1101/gr.277481.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 06/30/2023] [Indexed: 09/17/2023]
Abstract
Chinese indicine cattle harbor a much higher genetic diversity compared with other domestic cattle, but their genome architecture remains uninvestigated. Using PacBio HiFi sequencing data from 10 Chinese indicine cattle across southern China, we assembled 20 high-quality partially phased genomes and integrated them into a multiassembly graph containing 148.5 Mb (5.6%) of novel sequence. We identified 156,009 high-confidence nonredundant structural variants (SVs) and 206 SV hotspots spanning ∼195 Mb of gene-rich sequence. We detected 34,249 archaic introgressed fragments in Chinese indicine cattle covering 1.93 Gb (73.3%) of the genome. We inferred an average of 3.8%, 3.2%, 1.4%, and 0.5% of introgressed sequence originating, respectively, from banteng-like, kouprey-like, gayal-like, and gaur-like Bos species, as well as 0.6% of unknown origin. Introgression from multiple donors might have contributed to the genetic diversity of Chinese indicine cattle. Altogether, this study highlights the contribution of interspecies introgression to the genomic architecture of an important livestock population and shows how exotic genomic elements can contribute to the genetic variation available for selection.
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Affiliation(s)
- Xuelei Dai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Peipei Bian
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Dexiang Hu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Funong Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yongzhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Shaohua Jiao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mian Gong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jiayue Wen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Qimeng Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weidong Deng
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Hojjat Asadollahpour Nanaei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
- Reproductive Biotechnology Research Center, Avicenna Research Institute, ACECR, Tehran 1983969412, Iran
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Fei Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zijing Zhang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Rasmus Heller
- Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark;
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China;
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
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14
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Kosugi S, Kamatani Y, Harada K, Tomizuka K, Momozawa Y, Morisaki T, Terao C. Detection of trait-associated structural variations using short-read sequencing. CELL GENOMICS 2023; 3:100328. [PMID: 37388916 PMCID: PMC10300613 DOI: 10.1016/j.xgen.2023.100328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 02/17/2023] [Accepted: 04/25/2023] [Indexed: 07/01/2023]
Abstract
Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.
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Affiliation(s)
- Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba 277-8562, Japan
| | - Katsutoshi Harada
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa 230-0045, Japan
| | - Takayuki Morisaki
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, 4-6-1, Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan
| | | | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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15
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Bezdvornykh I, Cherkasov N, Kanapin A, Samsonova A. A collection of read depth profiles at structural variant breakpoints. Sci Data 2023; 10:186. [PMID: 37024526 PMCID: PMC10079824 DOI: 10.1038/s41597-023-02076-4] [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: 07/18/2022] [Accepted: 03/16/2023] [Indexed: 04/08/2023] Open
Abstract
SWaveform, a newly created open genome-wide resource for read depth signal in the vicinity of structural variant (SV) breakpoints, aims to boost development of computational tools and algorithms for discovery of genomic rearrangement events from sequencing data. SVs are a dominant force shaping genomes and substantially contributing to genetic diversity. Still, there are challenges in reliable and efficient genotyping of SVs from whole genome sequencing data, thus delaying translation into clinical applications and wasting valuable resources. SWaveform includes a database containing ~7 M of read depth profiles at SV breakpoints extracted from 911 sequencing samples generated by the Human Genome Diversity Project, generalised patterns of the signal at breakpoints, an interface for navigation and download, as well as a toolbox for local deployment with user's data. The dataset can be of immense value to bioinformatics and engineering communities as it empowers smooth application of intelligent signal processing and machine learning techniques for discovery of genomic rearrangement events and thus opens the floodgates for development of innovative algorithms and software.
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Affiliation(s)
- Igor Bezdvornykh
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, 199004, Russia
| | - Nikolay Cherkasov
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, 199004, Russia
| | - Alexander Kanapin
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, 199004, Russia
| | - Anastasia Samsonova
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, 199004, Russia.
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16
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He G, Wang M, Miao L, Chen J, Zhao J, Sun Q, Duan S, Wang Z, Xu X, Sun Y, Liu Y, Liu J, Wang Z, Wei L, Liu C, Ye J, Wang L. Multiple founding paternal lineages inferred from the newly-developed 639-plex Y-SNP panel suggested the complex admixture and migration history of Chinese people. Hum Genomics 2023; 17:29. [PMID: 36973821 PMCID: PMC10045532 DOI: 10.1186/s40246-023-00476-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/15/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Non-recombining regions of the Y-chromosome recorded the evolutionary traces of male human populations and are inherited haplotype-dependently and male-specifically. Recent whole Y-chromosome sequencing studies have identified previously unrecognized population divergence, expansion and admixture processes, which promotes a better understanding and application of the observed patterns of Y-chromosome genetic diversity. RESULTS Here, we developed one highest-resolution Y-chromosome single nucleotide polymorphism (Y-SNP) panel targeted for uniparental genealogy reconstruction and paternal biogeographical ancestry inference, which included 639 phylogenetically informative SNPs. We genotyped these loci in 1033 Chinese male individuals from 33 ethnolinguistically diverse populations and identified 256 terminal Y-chromosomal lineages with frequency ranging from 0.0010 (singleton) to 0.0687. We identified six dominant common founding lineages associated with different ethnolinguistic backgrounds, which included O2a2b1a1a1a1a1a1a1-M6539, O2a1b1a1a1a1a1a1-F17, O2a2b1a1a1a1a1b1a1b-MF15397, O2a2b2a1b1-A16609, O1b1a1a1a1b2a1a1-F2517, and O2a2b1a1a1a1a1a1-F155. The AMOVA and nucleotide diversity estimates revealed considerable differences and high genetic diversity among ethnolinguistically different populations. We constructed one representative phylogenetic tree among 33 studied populations based on the haplogroup frequency spectrum and sequence variations. Clustering patterns in principal component analysis and multidimensional scaling results showed a genetic differentiation between Tai-Kadai-speaking Li, Mongolic-speaking Mongolian, and other Sinitic-speaking Han Chinese populations. Phylogenetic topology inferred from the BEAST and Network relationships reconstructed from the popART further showed the founding lineages from culturally/linguistically diverse populations, such as C2a/C2b was dominant in Mongolian people and O1a/O1b was dominant in island Li people. We also identified many lineages shared by more than two ethnolinguistically different populations with a high proportion, suggesting their extensive admixture and migration history. CONCLUSIONS Our findings indicated that our developed high-resolution Y-SNP panel included major dominant Y-lineages of Chinese populations from different ethnic groups and geographical regions, which can be used as the primary and powerful tool for forensic practice. We should emphasize the necessity and importance of whole sequencing of more ethnolinguistically different populations, which can help identify more unrecognized population-specific variations for the promotion of Y-chromosome-based forensic applications.
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Affiliation(s)
- Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China.
| | - Mengge Wang
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Lei Miao
- National Engineering Laboratory for Forensic Science, Key Laboratory of Forensic Genetics of Ministry of Public Security, Institute of Forensic Science, Ministry of Public Security, Beijing, 100038, China
| | - Jing Chen
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Jie Zhao
- National Engineering Laboratory for Forensic Science, Key Laboratory of Forensic Genetics of Ministry of Public Security, Institute of Forensic Science, Ministry of Public Security, Beijing, 100038, China
| | - Qiuxia Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
| | - Zhiyong Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Xiaofei Xu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
| | - Yuntao Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Yan Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
| | - Jing Liu
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Zheng Wang
- Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Lanhai Wei
- School of Ethnology and Anthropology, Inner Mongolia Normal University, Hohhot, 010028, Inner Mongolia, China
| | - Chao Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China
| | - Jian Ye
- National Engineering Laboratory for Forensic Science, Key Laboratory of Forensic Genetics of Ministry of Public Security, Institute of Forensic Science, Ministry of Public Security, Beijing, 100038, China.
| | - Le Wang
- National Engineering Laboratory for Forensic Science, Key Laboratory of Forensic Genetics of Ministry of Public Security, Institute of Forensic Science, Ministry of Public Security, Beijing, 100038, China.
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17
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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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18
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Zhou Y, Lauschke VM. Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy. Handb Exp Pharmacol 2023; 280:237-260. [PMID: 35792943 DOI: 10.1007/164_2022_596] [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] [Indexed: 06/15/2023]
Abstract
Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tuebingen, Tuebingen, Germany.
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19
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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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20
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Pokrovac I, Pezer Ž. Recent advances and current challenges in population genomics of structural variation in animals and plants. Front Genet 2022; 13:1060898. [PMID: 36523759 PMCID: PMC9745067 DOI: 10.3389/fgene.2022.1060898] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 11/15/2022] [Indexed: 05/02/2024] Open
Abstract
The field of population genomics has seen a surge of studies on genomic structural variation over the past two decades. These studies witnessed that structural variation is taxonomically ubiquitous and represent a dominant form of genetic variation within species. Recent advances in technology, especially the development of long-read sequencing platforms, have enabled the discovery of structural variants (SVs) in previously inaccessible genomic regions which unlocked additional structural variation for population studies and revealed that more SVs contribute to evolution than previously perceived. An increasing number of studies suggest that SVs of all types and sizes may have a large effect on phenotype and consequently major impact on rapid adaptation, population divergence, and speciation. However, the functional effect of the vast majority of SVs is unknown and the field generally lacks evidence on the phenotypic consequences of most SVs that are suggested to have adaptive potential. Non-human genomes are heavily under-represented in population-scale studies of SVs. We argue that more research on other species is needed to objectively estimate the contribution of SVs to evolution. We discuss technical challenges associated with SV detection and outline the most recent advances towards more representative reference genomes, which opens a new era in population-scale studies of structural variation.
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Affiliation(s)
| | - Željka Pezer
- Laboratory for Evolutionary Genetics, Division of Molecular Biology, Ruđer Bošković Institute, Zagreb, Croatia
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21
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Wang Y, Ling Y, Gong J, Zhao X, Zhou H, Xie B, Lou H, Zhuang X, Jin L, Fan S, Zhang G, Xu S. PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform. Nucleic Acids Res 2022; 51:D1109-D1116. [PMID: 36243989 PMCID: PMC9825616 DOI: 10.1093/nar/gkac905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 09/21/2022] [Accepted: 10/04/2022] [Indexed: 01/30/2023] Open
Abstract
Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, we developed the database PGG.SV to provide a practical platform for both regionally and globally representative structural variants. In its current version, PGG.SV archives 584 277 SVs obtained from whole-genome sequencing data of 6048 samples, including 1030 long-read sequencing genomes representing 177 global populations. PGG.SV provides (i) high-quality SVs with fine-scale and precise genomic locations in both GRCh37 and GRCh38, covering underrepresented SVs in existing sequencing and microarray data; (ii) hierarchical estimation of SV prevalence in geographical populations; (iii) informative annotations of SV-related genes, potential functions and clinical effects; (iv) an analysis platform to facilitate SV-based case-control association studies and (v) various visualization tools for understanding the SV structures in the human genome. Taken together, PGG.SV provides a user-friendly online interface, easy-to-use analysis tools and a detailed presentation of results. PGG.SV is freely accessible via https://www.biosino.org/pggsv.
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Affiliation(s)
| | | | | | - Xiaohan Zhao
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China,Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Hanwen Zhou
- Key Laboratory of Computational Biology, National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bo Xie
- Key Laboratory of Computational Biology, National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Haiyi Lou
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xinhao Zhuang
- Key Laboratory of Computational Biology, National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China,Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | | | - Shaohua Fan
- Correspondence may also be addressed to Shaohua Fan.
| | - Guoqing Zhang
- Correspondence may also be addressed to Guoqing Zhang.
| | - Shuhua Xu
- To whom correspondence should be addressed. Tel: +86 21 31246617; Fax: +86 21 31246617;
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22
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Collins RL, Glessner JT, Porcu E, Lepamets M, Brandon R, Lauricella C, Han L, Morley T, Niestroj LM, Ulirsch J, Everett S, Howrigan DP, Boone PM, Fu J, Karczewski KJ, Kellaris G, Lowther C, Lucente D, Mohajeri K, Nõukas M, Nuttle X, Samocha KE, Trinh M, Ullah F, Võsa U, Hurles ME, Aradhya S, Davis EE, Finucane H, Gusella JF, Janze A, Katsanis N, Matyakhina L, Neale BM, Sanders D, Warren S, Hodge JC, Lal D, Ruderfer DM, Meck J, Mägi R, Esko T, Reymond A, Kutalik Z, Hakonarson H, Sunyaev S, Brand H, Talkowski ME. A cross-disorder dosage sensitivity map of the human genome. Cell 2022; 185:3041-3055.e25. [PMID: 35917817 PMCID: PMC9742861 DOI: 10.1016/j.cell.2022.06.036] [Citation(s) in RCA: 99] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 03/17/2022] [Accepted: 06/20/2022] [Indexed: 02/06/2023]
Abstract
Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.
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Affiliation(s)
- Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
| | - Joseph T Glessner
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, Division of Human Genetics, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Maarja Lepamets
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | | | | | - Lide Han
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Theodore Morley
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Jacob Ulirsch
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Selin Everett
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Daniel P Howrigan
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Philip M Boone
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA
| | - Jack Fu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Konrad J Karczewski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Georgios Kellaris
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Chelsea Lowther
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Diane Lucente
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Kiana Mohajeri
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Margit Nõukas
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | - Xander Nuttle
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Kaitlin E Samocha
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | - Mi Trinh
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | - Farid Ullah
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | | | | | - Matthew E Hurles
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10, UK
| | | | - Erica E Davis
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Hilary Finucane
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - James F Gusella
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | | | - Nicholas Katsanis
- Advanced Center for Translational and Genetic Medicine, Stanley Manne Children's Research Institute, Lurie Children's Hospital, Chicago, IL 60611, USA; Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | | | - Benjamin M Neale
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | | | - Jennelle C Hodge
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Dennis Lal
- Cologne Center for Genomics, University of Cologne, 51149 Cologne, Germany; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Douglas M Ruderfer
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Center for Precision Medicine, Department of Biomedical Informatics, and Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Center for Primary Care and Public Health, University of Lausanne, 1015 Lausanne, Switzerland; Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
| | - Hakon Hakonarson
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, Division of Human Genetics, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Shamil Sunyaev
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Division of Medical Sciences and Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, MA 02114, USA.
| | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
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23
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Gong H, Liu W, Wu Z, Zhang M, Sun Y, Ling Z, Xiao S, Ai H, Xin Y, Yang B, Huang L. Evolutionary insights into porcine genomic structural variations based on a novel constructed dataset from 24 worldwide diverse populations. Evol Appl 2022. [DOI: 10.1111/eva.13455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Affiliation(s)
- Huanfa Gong
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
- Key Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences Zhejiang University Hangzhou P.R. China
- Key Laboratory of Animal Nutrition and Feed Science in Eastern China, Ministry of Agriculture, College of Animal Sciences Zhejiang University Hangzhou P.R. China
| | - Weiwei Liu
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Zhongzi Wu
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Mingpeng Zhang
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Yingchun Sun
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Ziqi Ling
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Shijun Xiao
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Huashui Ai
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Yuyun Xin
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Bin Yang
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
| | - Lusheng Huang
- State Key Laboratory of Pig Genetic Improvement and Production Technology Jiangxi Agricultural University Nanchang P.R. China
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24
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Garg P, Jadhav B, Lee W, Rodriguez OL, Martin-Trujillo A, Sharp AJ. A phenome-wide association study identifies effects of copy-number variation of VNTRs and multicopy genes on multiple human traits. Am J Hum Genet 2022; 109:1065-1076. [PMID: 35609568 PMCID: PMC9247821 DOI: 10.1016/j.ajhg.2022.04.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 04/28/2022] [Indexed: 01/04/2023] Open
Abstract
The human genome contains tens of thousands of large tandem repeats and hundreds of genes that show common and highly variable copy-number changes. Due to their large size and repetitive nature, these variable number tandem repeats (VNTRs) and multicopy genes are generally recalcitrant to standard genotyping approaches and, as a result, this class of variation is poorly characterized. However, several recent studies have demonstrated that copy-number variation of VNTRs can modify local gene expression, epigenetics, and human traits, indicating that many have a functional role. Here, using read depth from whole-genome sequencing to profile copy number, we report results of a phenome-wide association study (PheWAS) of VNTRs and multicopy genes in a discovery cohort of ∼35,000 samples, identifying 32 traits associated with copy number of 38 VNTRs and multicopy genes at 1% FDR. We replicated many of these signals in an independent cohort and observed that VNTRs showing trait associations were significantly enriched for expression QTLs with nearby genes, providing strong support for our results. Fine-mapping studies indicated that in the majority (∼90%) of cases, the VNTRs and multicopy genes we identified represent the causal variants underlying the observed associations. Furthermore, several lie in regions where prior SNV-based GWASs have failed to identify any significant associations with these traits. Our study indicates that copy number of VNTRs and multicopy genes contributes to diverse human traits and suggests that complex structural variants potentially explain some of the so-called "missing heritability" of SNV-based GWASs.
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Affiliation(s)
- Paras Garg
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, 1470 Madison Avenue, Room 8-116, Box 1498, New York, NY 10029, USA
| | - Bharati Jadhav
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, 1470 Madison Avenue, Room 8-116, Box 1498, New York, NY 10029, USA
| | - William Lee
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, 1470 Madison Avenue, Room 8-116, Box 1498, New York, NY 10029, USA
| | - Oscar L Rodriguez
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, 1470 Madison Avenue, Room 8-116, Box 1498, New York, NY 10029, USA
| | - Alejandro Martin-Trujillo
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, 1470 Madison Avenue, Room 8-116, Box 1498, New York, NY 10029, USA
| | - Andrew J Sharp
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount, Hess Center for Science and Medicine, 1470 Madison Avenue, Room 8-116, Box 1498, New York, NY 10029, USA.
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25
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Quan C, Lu H, Lu Y, Zhou G. Population-scale genotyping of structural variation in the era of long-read sequencing. Comput Struct Biotechnol J 2022; 20:2639-2647. [PMID: 35685364 PMCID: PMC9163579 DOI: 10.1016/j.csbj.2022.05.047] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 11/29/2022] Open
Abstract
Population-scale studies of structural variation (SV) are growing rapidly worldwide with the development of long-read sequencing technology, yielding a considerable number of novel SVs and complete gap-closed genome assemblies. Herein, we highlight recent studies using a hybrid sequencing strategy and present the challenges toward large-scale genotyping for SVs due to the reference bias. Genotyping SVs at a population scale remains challenging, which severely impacts genotype-based population genetic studies or genome-wide association studies of complex diseases. We summarize academic efforts to improve genotype quality through linear or graph representations of reference and alternative alleles. Graph-based genotypers capable of integrating diverse genetic information are effectively applied to large and diverse cohorts, contributing to unbiased downstream analysis. Meanwhile, there is still an urgent need in this field for efficient tools to construct complex graphs and perform sequence-to-graph alignments.
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Affiliation(s)
- Cheng Quan
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
| | - Hao Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
| | - Yiming Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
- Hebei University, Baoding, Hebei Province 071002, PR China
- Corresponding authors at: Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing 100850, PR China (G. Zhou). Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, PR China (Y. Lu).
| | - Gangqiao Zhou
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province 211166, PR China
- Medical College of Guizhou University, Guiyang, Guizhou Province 550025, PR China
- Hebei University, Baoding, Hebei Province 071002, PR China
- Corresponding authors at: Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing 100850, PR China (G. Zhou). Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, PR China (Y. Lu).
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26
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Alharbi AF, Sheng N, Nicol K, Strömberg N, Hollox EJ. Balancing selection at the human salivary agglutinin gene (DMBT1) driven by host-microbe interactions. iScience 2022; 25:104189. [PMID: 35494225 PMCID: PMC9038570 DOI: 10.1016/j.isci.2022.104189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 02/07/2022] [Accepted: 03/30/2022] [Indexed: 11/19/2022] Open
Abstract
Discovering loci under balancing selection in humans can identify loci with alleles that affect response to the environment and disease. Genome variation data have identified the 5′ region of the DMBT1 gene as undergoing balancing selection in humans. DMBT1 encodes the pattern-recognition glycoprotein DMBT1, also known as SALSA, gp340, or salivary agglutinin. DMBT1 binds to a variety of pathogens through a tandemly arranged scavenger receptor cysteine-rich (SRCR) domain, with the number of domains polymorphic in humans. We show that the signal of balancing selection is driven by one haplotype usually carrying a shorter SRCR repeat and another usually carrying a longer SRCR repeat. DMBT1 encoded by a shorter SRCR repeat allele does not bind a cariogenic and invasive Streptococcus mutans strain, in contrast to the long SRCR allele that shows binding. Our results suggest that balancing selection at DMBT1 is due to host-microbe interactions of encoded SRCR tandem repeat alleles. Clear evidence from many analyses show balancing selection at DMBT1 Scavenger-receptor cysteine-rich domain array associated with balancing selection Genetic variation, not alternative splicing, responsible for protein isoforms Long, but not short, DMBT1 isoforms bind a cariogenic strain of Streptococcus mutans
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Affiliation(s)
- Adel F. Alharbi
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
- Medina Regional Laboratory, General Directorate of Health Affairs, Ministry of Health, Medina, Saudi Arabia
| | - Nongfei Sheng
- Department of Odontology, Umeå University, Umeå, Sweden
| | - Katie Nicol
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | | | - Edward J. Hollox
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
- Corresponding author
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27
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Liu Z, Roberts R, Mercer TR, Xu J, Sedlazeck FJ, Tong W. Towards accurate and reliable resolution of structural variants for clinical diagnosis. Genome Biol 2022; 23:68. [PMID: 35241127 PMCID: PMC8892125 DOI: 10.1186/s13059-022-02636-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 02/15/2022] [Indexed: 12/17/2022] Open
Abstract
Structural variants (SVs) are a major source of human genetic diversity and have been associated with different diseases and phenotypes. The detection of SVs is difficult, and a diverse range of detection methods and data analysis protocols has been developed. This difficulty and diversity make the detection of SVs for clinical applications challenging and requires a framework to ensure accuracy and reproducibility. Here, we discuss current developments in the diagnosis of SVs and propose a roadmap for the accurate and reproducible detection of SVs that includes case studies provided from the FDA-led SEquencing Quality Control Phase II (SEQC-II) and other consortium efforts.
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Affiliation(s)
- Zhichao Liu
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Ruth Roberts
- ApconiX, BioHub at Alderley Park, Alderley Edge, SK10 4TG, UK.,University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Timothy R Mercer
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia.,Garvan Institute of Medical Research, Sydney, NSW, Australia.,St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Joshua Xu
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Weida Tong
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
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28
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Niu Y, Teng X, Zhou H, Shi Y, Li Y, Tang Y, Zhang P, Luo H, Kang Q, Xu T, He S. Characterizing mobile element insertions in 5675 genomes. Nucleic Acids Res 2022; 50:2493-2508. [PMID: 35212372 PMCID: PMC8934628 DOI: 10.1093/nar/gkac128] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 02/07/2022] [Accepted: 02/11/2022] [Indexed: 12/30/2022] Open
Abstract
Mobile element insertions (MEIs) are a major class of structural variants (SVs) and have been linked to many human genetic disorders, including hemophilia, neurofibromatosis, and various cancers. However, human MEI resources from large-scale genome sequencing are still lacking compared to those for SNPs and SVs. Here, we report a comprehensive map of 36 699 non-reference MEIs constructed from 5675 genomes, comprising 2998 Chinese samples (∼26.2×, NyuWa) and 2677 samples from the 1000 Genomes Project (∼7.4×, 1KGP). We discovered that LINE-1 insertions were highly enriched in centromere regions, implying the role of chromosome context in retroelement insertion. After functional annotation, we estimated that MEIs are responsible for about 9.3% of all protein-truncating events per genome. Finally, we built a companion database named HMEID for public use. This resource represents the latest and largest genomewide study on MEIs and will have broad utility for exploration of human MEI findings.
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Affiliation(s)
- Yiwei Niu
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xueyi Teng
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Honghong Zhou
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yirong Shi
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanyan Li
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiheng Tang
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peng Zhang
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Huaxia Luo
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Quan Kang
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Xu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.,National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Shunmin He
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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29
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Dhande IS, Braun MC, Doris PA. Emerging Insights Into Chronic Renal Disease Pathogenesis in Hypertension From Human and Animal Genomic Studies. Hypertension 2021; 78:1689-1700. [PMID: 34757770 PMCID: PMC8577298 DOI: 10.1161/hypertensionaha.121.18112] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The pathogenic links between elevated blood pressure and chronic kidney disease remain obscure. This article examines progress in population genetics and in animal models of hypertension and chronic kidney disease. It also provides a critique of the application of genome-wide association studies to understanding the heritability of renal function. Emerging themes identified indicate that heritable risk of chronic kidney disease in hypertension can arise from genetic variation in (1) glomerular and tubular protein handling mechanisms; (2) autoregulatory capacity of the renal vasculature; and (3) innate and adaptive immune mechanisms. Increased prevalence of hypertension-associated chronic kidney disease that occurs with aging may reflect amplification of heritable risks by normal aging processes affecting immunity and autoregulation.
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Affiliation(s)
- Isha S. Dhande
- Center for Human Genetics, Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas HSC, Houston (I.S.D., P.A.D.)
| | - Michael C. Braun
- Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston (M.C.B.)
| | - Peter A. Doris
- Center for Human Genetics, Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas HSC, Houston (I.S.D., P.A.D.)
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30
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Miller A, Panneerselvam J, Liu L. A review of regression and classification techniques for analysis of common and rare variants and gene-environmental factors. Neurocomputing 2021. [DOI: 10.1016/j.neucom.2021.08.150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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31
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Wu Z, Jiang Z, Li T, Xie C, Zhao L, Yang J, Ouyang S, Liu Y, Li T, Xie Z. Structural variants in the Chinese population and their impact on phenotypes, diseases and population adaptation. Nat Commun 2021; 12:6501. [PMID: 34764282 PMCID: PMC8586011 DOI: 10.1038/s41467-021-26856-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 10/21/2021] [Indexed: 02/05/2023] Open
Abstract
A complete characterization of genetic variation is a fundamental goal of human genome research. Long-read sequencing has improved the sensitivity of structural variant discovery. Here, we conduct the long-read sequencing-based structural variant analysis for 405 unrelated Chinese individuals, with 68 phenotypic and clinical measurements. We discover a landscape of 132,312 nonredundant structural variants, of which 45.2% are novel. The identified structural variants are of high-quality, with an estimated false discovery rate of 3.2%. The concatenated length of all the structural variants is approximately 13.2% of the human reference genome. We annotate 1,929 loss-of-function structural variants affecting the coding sequence of 1,681 genes. We discover rare deletions in HBA1/HBA2/HBB associated with anemia. Furthermore, we identify structural variants related to immunity which differentiate the northern and southern Chinese populations. Our study describes the landscape of structural variants in the Chinese population and their contribution to phenotypes and disease.
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Affiliation(s)
- Zhikun Wu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Zehang Jiang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Tong Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Chuanbo Xie
- Sun Yat-sen University Cancer Center, Sun Yat-sen University, Guangzhou, China
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
| | - Jiaqi Yang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Shuai Ouyang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Yizhi Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Tao Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China.
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China.
| | - Zhi Xie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
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32
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Saitou M, Masuda N, Gokcumen O. Similarity-based analysis of allele frequency distribution among multiple populations identifies adaptive genomic structural variants. Mol Biol Evol 2021; 39:6413645. [PMID: 34718708 PMCID: PMC8896759 DOI: 10.1093/molbev/msab313] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.
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Affiliation(s)
- Marie Saitou
- Dept. of Biological Sciences, University at Buffalo, State University of New York, Buffalo, NY 14260-2900, USA.,Currently at the Faculty of Biosciences, Norwegian University of Life Sciences, Universitetstunet 3, 1430 Ås, Norway.,Dept. of Medicine, The University of Chicago. Section of Genetic Medicine, 5841 S. Maryland Ave., Chicago, IL, 60637-1447, USA
| | - Naoki Masuda
- Department of Mathematics, University at Buffalo, State University of New York, Buffalo, NY 14260-2900, USA.,Computational and Data-Enabled Science and Engineering Program, University at Buffalo, State University of New York, Buffalo, NY 14260-5030, USA
| | - Omer Gokcumen
- Dept. of Biological Sciences, University at Buffalo, State University of New York, Buffalo, NY 14260-2900, USA
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33
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Wang Y, Zhao B, Choi J, Lee EA. Genomic approaches to trace the history of human brain evolution with an emerging opportunity for transposon profiling of ancient humans. Mob DNA 2021; 12:22. [PMID: 34663455 PMCID: PMC8525043 DOI: 10.1186/s13100-021-00250-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 09/27/2021] [Indexed: 12/17/2022] Open
Abstract
Transposable elements (TEs) significantly contribute to shaping the diversity of the human genome, and lines of evidence suggest TEs as one of driving forces of human brain evolution. Existing computational approaches, including cross-species comparative genomics and population genetic modeling, can be adapted for the study of the role of TEs in evolution. In particular, diverse ancient and archaic human genome sequences are increasingly available, allowing reconstruction of past human migration events and holding the promise of identifying and tracking TEs among other evolutionarily important genetic variants at an unprecedented spatiotemporal resolution. However, highly degraded short DNA templates and other unique challenges presented by ancient human DNA call for major changes in current experimental and computational procedures to enable the identification of evolutionarily important TEs. Ancient human genomes are valuable resources for investigating TEs in the evolutionary context, and efforts to explore ancient human genomes will potentially provide a novel perspective on the genetic mechanism of human brain evolution and inspire a variety of technological and methodological advances. In this review, we summarize computational and experimental approaches that can be adapted to identify and validate evolutionarily important TEs, especially for human brain evolution. We also highlight strategies that leverage ancient genomic data and discuss unique challenges in ancient transposon genomics.
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Affiliation(s)
- Yilan Wang
- Division of Genetics and Genomics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | - Boxun Zhao
- Division of Genetics and Genomics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA
| | - Jaejoon Choi
- Division of Genetics and Genomics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Eunjung Alice Lee
- Division of Genetics and Genomics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA, USA.
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34
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Yan SM, Sherman RM, Taylor DJ, Nair DR, Bortvin AN, Schatz MC, McCoy RC. Local adaptation and archaic introgression shape global diversity at human structural variant loci. eLife 2021; 10:e67615. [PMID: 34528508 PMCID: PMC8492059 DOI: 10.7554/elife.67615] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 09/14/2021] [Indexed: 12/13/2022] Open
Abstract
Large genomic insertions and deletions are a potent source of functional variation, but are challenging to resolve with short-read sequencing, limiting knowledge of the role of such structural variants (SVs) in human evolution. Here, we used a graph-based method to genotype long-read-discovered SVs in short-read data from diverse human genomes. We then applied an admixture-aware method to identify 220 SVs exhibiting extreme patterns of frequency differentiation - a signature of local adaptation. The top two variants traced to the immunoglobulin heavy chain locus, tagging a haplotype that swept to near fixation in certain southeast Asian populations, but is rare in other global populations. Further investigation revealed evidence that the haplotype traces to gene flow from Neanderthals, corroborating the role of immune-related genes as prominent targets of adaptive introgression. Our study demonstrates how recent technical advances can help resolve signatures of key evolutionary events that remained obscured within technically challenging regions of the genome.
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Affiliation(s)
- Stephanie M Yan
- Department of Biology, Johns Hopkins University, BaltimoreBaltimoreUnited States
| | - Rachel M Sherman
- Department of Computer Science, Johns Hopkins UniversityBaltimoreUnited States
| | - Dylan J Taylor
- Department of Biology, Johns Hopkins University, BaltimoreBaltimoreUnited States
| | - Divya R Nair
- Department of Biology, Johns Hopkins University, BaltimoreBaltimoreUnited States
| | - Andrew N Bortvin
- Department of Biology, Johns Hopkins University, BaltimoreBaltimoreUnited States
| | - Michael C Schatz
- Department of Biology, Johns Hopkins University, BaltimoreBaltimoreUnited States
- Department of Computer Science, Johns Hopkins UniversityBaltimoreUnited States
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, BaltimoreBaltimoreUnited States
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35
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Hollox EJ, Zuccherato LW, Tucci S. Genome structural variation in human evolution. Trends Genet 2021; 38:45-58. [PMID: 34284881 DOI: 10.1016/j.tig.2021.06.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/21/2021] [Accepted: 06/22/2021] [Indexed: 01/01/2023]
Abstract
Structural variation (SV) is a large difference (typically >100 bp) in the genomic structure of two genomes and includes both copy number variation and variation that does not change copy number of a genomic region, such as an inversion. Improved reference genomes, combined with widespread genome sequencing using short-read sequencing technology, and increasingly using long-read sequencing, have reignited interest in SV. Recent large-scale studies and functional focused analyses have highlighted the role of SV in human evolution. In this review, we highlight human-specific SVs involved in changes in the brain, population-specific SVs that affect response to the environment, including adaptation to diet and infectious diseases, and summarise the contribution of archaic hominin admixture to present-day human SV.
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Affiliation(s)
- Edward J Hollox
- Department of Genetics and Genome Biology, University of Leicester, UK.
| | - Luciana W Zuccherato
- Núcleo de Ensino e Pesquisa, Instituto Mário Penna, Belo Horizonte, Brazil; Departmento de Bioquímica e Imunologia, Universidade de Minas Gerais, Belo Horizonte, Brazil
| | - Serena Tucci
- Department of Anthropology, Yale University, New Haven, CT, USA
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36
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Quan C, Li Y, Liu X, Wang Y, Ping J, Lu Y, Zhou G. Characterization of structural variation in Tibetans reveals new evidence of high-altitude adaptation and introgression. Genome Biol 2021; 22:159. [PMID: 34034800 PMCID: PMC8146648 DOI: 10.1186/s13059-021-02382-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/14/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Structural variation (SV) acts as an essential mutational force shaping the evolution and function of the human genome. However, few studies have examined the role of SVs in high-altitude adaptation and little is known of adaptive introgressed SVs in Tibetans so far. RESULTS Here, we generate a comprehensive catalog of SVs in a Chinese Tibetan (n = 15) and Han (n = 10) population using nanopore sequencing technology. Among a total of 38,216 unique SVs in the catalog, 27% are sequence-resolved for the first time. We systematically assess the distribution of these SVs across repeat sequences and functional genomic regions. Through genotyping in additional 276 genomes, we identify 69 Tibetan-Han stratified SVs and 80 candidate adaptive genes. We also discover a few adaptive introgressed SV candidates and provide evidence for a deletion of 335 base pairs at 1p36.32. CONCLUSIONS Overall, our results highlight the important role of SVs in the evolutionary processes of Tibetans' adaptation to the Qinghai-Tibet Plateau and provide a valuable resource for future high-altitude adaptation studies.
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Affiliation(s)
- Cheng Quan
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Yuanfeng Li
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Xinyi Liu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Yahui Wang
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Jie Ping
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Yiming Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
- Hebei University, Baoding, Hebei Province 071002 People’s Republic of China
| | - Gangqiao Zhou
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
- Hebei University, Baoding, Hebei Province 071002 People’s Republic of China
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province 211166 People’s Republic of China
- Medical College of Guizhou University, Guiyang, Guizhou Province 550025 People’s Republic of China
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37
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Garg P, Martin-Trujillo A, Rodriguez OL, Gies SJ, Hadelia E, Jadhav B, Jain M, Paten B, Sharp AJ. Pervasive cis effects of variation in copy number of large tandem repeats on local DNA methylation and gene expression. Am J Hum Genet 2021; 108:809-824. [PMID: 33794196 DOI: 10.1016/j.ajhg.2021.03.016] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 03/11/2021] [Indexed: 12/27/2022] Open
Abstract
Variable number tandem repeats (VNTRs) are composed of large tandemly repeated motifs, many of which are highly polymorphic in copy number. However, because of their large size and repetitive nature, they remain poorly studied. To investigate the regulatory potential of VNTRs, we used read-depth data from Illumina whole-genome sequencing to perform association analysis between copy number of ∼70,000 VNTRs (motif size ≥ 10 bp) with both gene expression (404 samples in 48 tissues) and DNA methylation (235 samples in peripheral blood), identifying thousands of VNTRs that are associated with local gene expression (eVNTRs) and DNA methylation levels (mVNTRs). Using an independent cohort, we validated 73%-80% of signals observed in the two discovery cohorts, while allelic analysis of VNTR length and CpG methylation in 30 Oxford Nanopore genomes gave additional support for mVNTR loci, thus providing robust evidence to support that these represent genuine associations. Further, conditional analysis indicated that many eVNTRs and mVNTRs act as QTLs independently of other local variation. We also observed strong enrichments of eVNTRs and mVNTRs for regulatory features such as enhancers and promoters. Using the Human Genome Diversity Panel, we define sets of VNTRs that show highly divergent copy numbers among human populations and show that these are enriched for regulatory effects and preferentially associate with genes that have been linked with human phenotypes through GWASs. Our study provides strong evidence supporting functional variation at thousands of VNTRs and defines candidate sets of VNTRs, copy number variation of which potentially plays a role in numerous human phenotypes.
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38
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Kojima S, Kamada AJ, Parrish NF. Virus-derived variation in diverse human genomes. PLoS Genet 2021; 17:e1009324. [PMID: 33901175 PMCID: PMC8101998 DOI: 10.1371/journal.pgen.1009324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/06/2021] [Accepted: 03/25/2021] [Indexed: 11/19/2022] Open
Abstract
Acquisition of genetic material from viruses by their hosts can generate inter-host structural genome variation. We developed computational tools enabling us to study virus-derived structural variants (SVs) in population-scale whole genome sequencing (WGS) datasets and applied them to 3,332 humans. Although SVs had already been cataloged in these subjects, we found previously-overlooked virus-derived SVs. We detected non-germline SVs derived from squirrel monkey retrovirus (SMRV), human immunodeficiency virus 1 (HIV-1), and human T lymphotropic virus (HTLV-1); these variants are attributable to infection of the sequenced lymphoblastoid cell lines (LCLs) or their progenitor cells and may impact gene expression results and the biosafety of experiments using these cells. In addition, we detected new heritable SVs derived from human herpesvirus 6 (HHV-6) and human endogenous retrovirus-K (HERV-K). We report the first solo-direct repeat (DR) HHV-6 likely to reflect DR rearrangement of a known full-length endogenous HHV-6. We used linkage disequilibrium between single nucleotide variants (SNVs) and variants in reads that align to HERV-K, which often cannot be mapped uniquely using conventional short-read sequencing analysis methods, to locate previously-unknown polymorphic HERV-K loci. Some of these loci are tightly linked to trait-associated SNVs, some are in complex genome regions inaccessible by prior methods, and some contain novel HERV-K haplotypes likely derived from gene conversion from an unknown source or introgression. These tools and results broaden our perspective on the coevolution between viruses and humans, including ongoing virus-to-human gene transfer contributing to genetic variation between humans.
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Affiliation(s)
- Shohei Kojima
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Anselmo Jiro Kamada
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Nicholas F. Parrish
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
- * E-mail:
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39
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Wang F, Huang S, Gao R, Zhou Y, Lai C, Li Z, Xian W, Qian X, Li Z, Huang Y, Tang Q, Liu P, Chen R, Liu R, Li X, Tong X, Zhou X, Bai Y, Duan G, Zhang T, Xu X, Wang J, Yang H, Liu S, He Q, Jin X, Liu L. Initial whole-genome sequencing and analysis of the host genetic contribution to COVID-19 severity and susceptibility. Cell Discov 2020; 6:83. [PMID: 33298875 PMCID: PMC7653987 DOI: 10.1038/s41421-020-00231-4] [Citation(s) in RCA: 121] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 10/03/2020] [Indexed: 02/08/2023] Open
Abstract
The COVID-19 pandemic has accounted for millions of infections and hundreds of thousand deaths worldwide in a short-time period. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed interindividual phenotypic variability. Here, we report the first host genetic study in the Chinese population by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third People's Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe, and critical ill patients after the correction of potential confounding factors. Pedigree analysis suggested a potential monogenic effect of loss of function variants in GOLGA3 and DPP7 for critically ill and asymptomatic disease demonstration. Genome-wide association study suggests the most significant gene locus associated with severity were located in TMEM189-UBE2V1 that involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We identified that the HLA-A*11:01, B*51:01, and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial genomic study of Chinese patients provides genetic insights into the phenotypic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host-pathogen interaction for COVID-19 and other infectious and complex diseases.
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Affiliation(s)
- Fang Wang
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Shujia Huang
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China
| | - Rongsui Gao
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Yuwen Zhou
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, 518083, China
| | - Changxiang Lai
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Zhichao Li
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, 518083, China
| | - Wenjie Xian
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Xiaobo Qian
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, 518083, China
| | - Zhiyu Li
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Yushan Huang
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, 518083, China
| | - Qiyuan Tang
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Panhong Liu
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, 518083, China
| | - Ruikun Chen
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Rong Liu
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
| | - Xuan Li
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Xin Tong
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
| | - Xuan Zhou
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Yong Bai
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
| | - Gang Duan
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China
| | - Tao Zhang
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, Guangdong, 518120, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- James D. Watson Institute of Genome Science, Hangzhou, Zhejiang, 310008, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China
- James D. Watson Institute of Genome Science, Hangzhou, Zhejiang, 310008, China
| | - Siyang Liu
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China.
| | - Qing He
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China.
| | - Xin Jin
- BGI-Shenzhen, Shenzhen, Guangdong, 518083, China.
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China.
| | - Lei Liu
- The Third People's Hospital of Shenzhen, National Clinical Research Center for Infectious Disease, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, 518112, China.
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40
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de la Puente M, Ruiz-Ramírez J, Ambroa-Conde A, Xavier C, Amigo J, Casares de Cal MÁ, Gómez-Tato A, Carracedo Á, Parson W, Phillips C, Lareu MV. Broadening the Applicability of a Custom Multi-Platform Panel of Microhaplotypes: Bio-Geographical Ancestry Inference and Expanded Reference Data. Front Genet 2020; 11:581041. [PMID: 33193704 PMCID: PMC7606911 DOI: 10.3389/fgene.2020.581041] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 09/25/2020] [Indexed: 11/13/2022] Open
Abstract
The development of microhaplotype (MH) panels for massively parallel sequencing (MPS) platforms is gaining increasing relevance for forensic analysis. Here, we expand the applicability of a 102 autosomal and 11 X-chromosome panel of MHs, previously validated with both MiSeq and Ion S5 MPS platforms and designed for identification purposes. We have broadened reference population data for identification purposes, including data from 240 HGDP-CEPH individuals of native populations from North Africa, the Middle East, Oceania and America. Using the enhanced population data, the panel was evaluated as a marker set for bio-geographical ancestry (BGA) inference, providing a clear differentiation of the five main continental groups of Africa, Europe, East Asia, Native America, and Oceania. An informative degree of differentiation was also achieved for the population variation encompassing North Africa, Middle East, Europe, South Asia, and East Asia. In addition, we explored the potential for individual BGA inference from simple mixed DNA, by simulation of mixed profiles followed by deconvolution of mixture components.
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Affiliation(s)
- María de la Puente
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain.,Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - Jorge Ruiz-Ramírez
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Adrián Ambroa-Conde
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Catarina Xavier
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - Jorge Amigo
- Fundación Pública Galega de Medicina Xenómica (FPGMX), Santiago de Compostela, Spain
| | | | - Antonio Gómez-Tato
- Faculty of Mathematics, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Ángel Carracedo
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain.,Fundación Pública Galega de Medicina Xenómica (FPGMX), Santiago de Compostela, Spain
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria.,Forensic Science Program, The Pennsylvania State University, University Park, PA, United States
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - María Victoria Lareu
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Santiago de Compostela, Spain
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41
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Pakendorf B, Stoneking M. The genomic prehistory of peoples speaking Khoisan languages. Hum Mol Genet 2020; 30:R49-R55. [PMID: 33075813 PMCID: PMC8117426 DOI: 10.1093/hmg/ddaa221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 09/28/2020] [Accepted: 10/08/2020] [Indexed: 11/14/2022] Open
Abstract
Peoples speaking so-called Khoisan languages-that is, indigenous languages of southern Africa that do not belong to the Bantu family-are culturally and linguistically diverse. They comprise herders, hunter-gatherers as well as groups of mixed modes of subsistence, and their languages are classified into three distinct language families. This cultural and linguistic variation is mirrored by extensive genetic diversity. We here review the recent genomics literature and discuss the genetic evidence for a formerly wider geographic spread of peoples with Khoisan-related ancestry, for the deep divergence among populations speaking Khoisan languages overlaid by more recent gene flow among these groups and for the impact of admixture with immigrant food-producers in their prehistory.
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Affiliation(s)
- Brigitte Pakendorf
- Dynamique du Langage, UMR5596, CNRS & Université de Lyon, 14 avenue Berthelot, 69007 Lyon, France
| | - Mark Stoneking
- Department of Evolutionary Genetics, MPI for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany
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42
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Diaz-Papkovich A, Anderson-Trocmé L, Gravel S. A review of UMAP in population genetics. J Hum Genet 2020; 66:85-91. [PMID: 33057159 DOI: 10.1038/s10038-020-00851-4] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 09/10/2020] [Accepted: 09/14/2020] [Indexed: 01/25/2023]
Abstract
Uniform manifold approximation and projection (UMAP) has been rapidly adopted by the population genetics community to study population structure. It has become common in visualizing the ancestral composition of human genetic datasets, as well as searching for unique clusters of data, and for identifying geographic patterns. Here we give an overview of applications of UMAP in population genetics, provide recommendations for best practices, and offer insights on optimal uses for the technique.
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Affiliation(s)
- Alex Diaz-Papkovich
- Quantitative Life Sciences Program, McGill University, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | | | - Simon Gravel
- Department of Human Genetics, McGill University, Montreal, QC, Canada.
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43
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Montinaro F, Capelli C. A Worldwide Map of Human Structural Variants. Trends Genet 2020; 36:722-725. [PMID: 32690317 DOI: 10.1016/j.tig.2020.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 07/02/2020] [Indexed: 10/23/2022]
Abstract
Genomic variation extends from single nucleotide variants to large chromosomal rearrangements, but the extent of structural variation in Homo sapiens is still unclear. Almarri et al. provide a worldwide catalogue of structural variants present in human populations. Most of the reported variation is novel, with some variants being inherited from Neanderthals and Denisovans. Drift and selection shaped the distribution of these variants with some suggested to have functional implications.
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Affiliation(s)
- Francesco Montinaro
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia.
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