1
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Ping J, Liu X, Lu Y, Quan C, Fan P, Lu H, Li Q, Wang C, Zhang Z, Liu M, Chen S, Chang L, Jiang Y, Huang Q, Liu J, Wuren T, Liu H, Hao Y, Kang L, Liu G, Lu H, Wei X, Wang Y, Li Y, Guo H, Cui Y, Zhang H, Zhang Y, Zhai Y, He Y, Zheng W, Qi X, Ouzhuluobu, Ma H, Yang L, Wang X, Jin W, Cui Y, Ge R, Wu S, Wei Y, Su B, He F, Zhang H, Zhou G. A highland-adaptation variant near MCUR1 reduces its transcription and attenuates erythrogenesis in Tibetans. CELL GENOMICS 2025; 5:100782. [PMID: 40043709 PMCID: PMC11960549 DOI: 10.1016/j.xgen.2025.100782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 09/03/2024] [Accepted: 02/03/2025] [Indexed: 03/15/2025]
Abstract
To identify genomic regions subject to positive selection that might contain genes involved in high-altitude adaptation (HAA), we performed a genome-wide scan by whole-genome sequencing of Tibetan highlanders and Han lowlanders. We revealed a collection of candidate genes located in 30 genomic loci under positive selection. Among them, MCUR1 at 6p23 was a novel pronounced candidate. By single-cell RNA sequencing and comprehensive functional studies, we demonstrated that MCUR1 depletion leads to impairment of erythropoiesis under hypoxia and normoxia. Mechanistically, MCUR1 knockdown reduced mitochondrial Ca2+ uptake and then concomitantly increased cytosolic Ca2+ levels, which thereby reduced erythropoiesis via the CAMKK2-AMPK-mTOR axis. Further, we revealed rs61644582 at 6p23 as an expression quantitative trait locus for MCUR1 and a functional variant that confers an allele-specific transcriptional regulation of MCUR1. Overall, MCUR1-mediated mitochondrial Ca2+ homeostasis is highlighted as a novel regulator of erythropoiesis, deepening our understanding of the genetic mechanism of HAA.
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Affiliation(s)
- Jie Ping
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Xinyi Liu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Yiming Lu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Cheng Quan
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Pengcheng Fan
- Pharmacy Department, General Hospital of Lanzhou, Lanzhou City 730050, P.R. China; State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, P.R. China
| | - Hao Lu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Qi Li
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Cuiling Wang
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Zheng Zhang
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Mengyu Liu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Shunqi Chen
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Lingle Chang
- Medical College of Guizhou University, Guiyang City 550025, P.R. China
| | - Yuqing Jiang
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing City 211166, P.R. China
| | - Qilin Huang
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing City 211166, P.R. China
| | - Jie Liu
- Research Center for High-Altitude Medicine, Qinghai University Medical School, Xining City 810001, P.R. China; Qinghai Provincial People's Hospital, Xining City 810001, P.R. China
| | - Tana Wuren
- Research Center for High-Altitude Medicine, Qinghai University Medical School, Xining City 810001, P.R. China
| | - Huifang Liu
- Research Center for High-Altitude Medicine, Qinghai University Medical School, Xining City 810001, P.R. China
| | - Ying Hao
- College of Life Sciences, Beijing University of Chinese Medicine, Beijing 102488, P.R. China
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research on High-Altitude Disease of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang City 712082, P.R. China; Key Laboratory of High-Altitude Environment and Genes Related to Diseases of Tibet Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang City 712082, P.R. China
| | - Guanjun Liu
- Henan Provincial People's Hospital, Zhengzhou City 450000, P.R. China; Affiliated Cancer Hospital of Guangxi Medical University, Nanning City 530021, P.R. China
| | - Hui Lu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Xiaojun Wei
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Yuting Wang
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Yuanfeng Li
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China
| | - Hao Guo
- No. 945 Hospital of Joint Logistic Support Force of Chinese PLA, Ya'an City 625000, P.R. China
| | - Yongquan Cui
- No. 945 Hospital of Joint Logistic Support Force of Chinese PLA, Ya'an City 625000, P.R. China
| | - Haoxiang Zhang
- No. 954 Hospital of Joint Logistic Support Force of Chinese PLA, Shannan City 856000, P.R. China
| | - Yang Zhang
- Medical Center for Human Reproduction, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China
| | - Yujia Zhai
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, P.R. China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming City 650223, P.R. China
| | - Wangshan Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming City 650223, P.R. China
| | - Xuebin Qi
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650000, China; Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China
| | - Ouzhuluobu
- Fukang Obstetrics, Gynecology and Children Branch Hospital, Tibetan Fukang Hospital, Lhasa 850000, China
| | - Huiping Ma
- Pharmacy Department, General Hospital of Lanzhou, Lanzhou City 730050, P.R. China
| | - Linpeng Yang
- Pharmacy Department, General Hospital of Lanzhou, Lanzhou City 730050, P.R. China
| | - Xin Wang
- Pharmacy Department, General Hospital of Lanzhou, Lanzhou City 730050, P.R. China
| | - Wanjun Jin
- Pharmacy Department, General Hospital of Lanzhou, Lanzhou City 730050, P.R. China
| | - Ying Cui
- Affiliated Cancer Hospital of Guangxi Medical University, Nanning City 530021, P.R. China
| | - Rili Ge
- Research Center for High-Altitude Medicine, Qinghai University Medical School, Xining City 810001, P.R. China
| | - Shizheng Wu
- Research Center for High-Altitude Medicine, Qinghai University Medical School, Xining City 810001, P.R. China; Qinghai Provincial People's Hospital, Xining City 810001, P.R. China
| | - Yuan Wei
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, P.R. China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming City 650223, P.R. China
| | - Fuchu He
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, P.R. China
| | - Hongxing Zhang
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, P.R. China.
| | - Gangqiao Zhou
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Radiation Medicine, Beijing 100850, P.R. China; Medical College of Guizhou University, Guiyang City 550025, P.R. China; Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing City 211166, P.R. China.
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2
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Gong J, Sun H, Wang K, Zhao Y, Huang Y, Chen Q, Qiao H, Gao Y, Zhao J, Ling Y, Cao R, Tan J, Wang Q, Ma Y, Li J, Luo J, Wang S, Wang J, Zhang G, Xu S, Qian F, Zhou F, Tang H, Li D, Sedlazeck FJ, Jin L, Guan Y, Fan S. Long-read sequencing of 945 Han individuals identifies structural variants associated with phenotypic diversity and disease susceptibility. Nat Commun 2025; 16:1494. [PMID: 39929826 PMCID: PMC11811171 DOI: 10.1038/s41467-025-56661-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 01/22/2025] [Indexed: 02/13/2025] Open
Abstract
Genomic structural variants (SVs) are a major source of genetic diversity in humans. Here, through long-read sequencing of 945 Han Chinese genomes, we identify 111,288 SVs, including 24.56% unreported variants, many with predicted functional importance. By integrating human population-level phenotypic and multi-omics data as well as two humanized mouse models, we demonstrate the causal roles of two SVs: one SV that emerges at the common ancestor of modern humans, Neanderthals, and Denisovans in GSDMD for bone mineral density and one modern-human-specific SV in WWP2 impacting height, weight, fat, craniofacial phenotypes and immunity. Our results suggest that the GSDMD SV could serve as a rapid and cost-effective biomarker for assessing the risk of cisplatin-induced acute kidney injury. The functional conservation from human to mouse and widespread signals of positive natural selection suggest that both SVs likely influence local adaptation, phenotypic diversity, and disease susceptibility across diverse human populations.
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Affiliation(s)
- Jiao Gong
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Huiru Sun
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Kaiyuan Wang
- Shanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China
| | - Yanhui Zhao
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Yechao Huang
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Qinsheng Chen
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Hui Qiao
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Jialin Zhao
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Yunchao Ling
- Bio-Med Big Data Center, Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Ruifang Cao
- Bio-Med Big Data Center, Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jingze Tan
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Qi Wang
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Yanyun Ma
- Department of Anthropology and Human Genetics, Institute for Six-sector Economy, and MOE Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, China
| | - Jing Li
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Jingchun Luo
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
- Research Unit of dissecting the population genetics and developing new technologies for treatment and prevention of skin phenotypes and dermatological diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China
| | - Guoqing Zhang
- Bio-Med Big Data Center, Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Feng Qian
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Fang Zhou
- School of Data Science and Engineering, East China Normal University, Shanghai, China
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Dali Li
- Shanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China.
- Research Unit of dissecting the population genetics and developing new technologies for treatment and prevention of skin phenotypes and dermatological diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China.
| | - Yuting Guan
- Shanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
| | - Shaohua Fan
- State Key Laboratory of Genetic Engineering, Lab for Evolutionary Synthesis, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China.
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3
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Dishuck PC, Munson KM, Lewis AP, Dougherty ML, Underwood JG, Harvey WT, Hsieh P, Pastinen T, Eichler EE. Structural variation, selection, and diversification of the NPIP gene family from the human pangenome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.04.636496. [PMID: 39975192 PMCID: PMC11838601 DOI: 10.1101/2025.02.04.636496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
The NPIP (nuclear pore interacting protein) gene family has expanded to high copy number in humans and African apes where it has been subject to an excess of amino acid replacement consistent with positive selection (1). Due to the limitations of short-read sequencing, NPIP human genetic diversity has been poorly understood. Using highly accurate assemblies generated from long-read sequencing as part of the human pangenome, we completely characterize 169 human haplotypes (4,665 NPIP paralogs and alleles). Of the 28 NPIP paralogs, just three (NPIPB2, B11, and B14) are fixed at a single copy, and only a single locus, B2, shows no structural variation. Four NPIP paralogs map to large segmental duplication blocks that mediate polymorphic inversions (355 kbp-1.6 Mbp) corresponding to microdeletions associated with developmental delay and autism. Haplotype-based tests of positive selection and selective sweeps identify two paralogs, B9 and B15, within the top percentile for both tests. Using full-length cDNA data from 101 tissue/cell types, we construct paralog-specific gene models and show that 56% (31/55 most abundant isoforms) have not been previously described in RefSeq. We define six distinct translation start sites and other protein structural features that distinguish paralogs, including a variable number tandem repeat that encodes a beta helix of variable size that emerged ~3.1 million years ago in human evolution. Among the 28 NPIP paralogs, we identify distinct tissue and developmental patterns of expression with only a few maintaining the ancestral testis-enriched expression. A subset of paralogs (NPIPA1, A5, A6-9, B3-5, and B12/B13) show increased brain expression. Our results suggest ongoing positive selection in the human population and rapid diversification of NPIP gene models.
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Affiliation(s)
- Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Max L. Dougherty
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Present address: Tisch Cancer Institute, Division of Hematology and Medical Oncology, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jason G. Underwood
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Pacific Biosciences (PacBio) of California, Incorporated, Menlo Park, CA, USA
| | - William T. Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genetics, Cell Biology, and Development, Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
| | - Tomi Pastinen
- Genomic Medicine Center, Department of Pediatrics, Children’s Mercy Kansas City, Kansas City, KS, USA
- UMKC School of Medicine, University of Missouri, Kansas City, Kansas City, KS, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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4
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Jeong H, Dishuck PC, Yoo D, Harvey WT, Munson KM, Lewis AP, Kordosky J, Garcia GH, Human Genome Structural Variation Consortium (HGSVC), Yilmaz F, Hallast P, Lee C, Pastinen T, Eichler EE. Structural polymorphism and diversity of human segmental duplications. Nat Genet 2025; 57:390-401. [PMID: 39779957 PMCID: PMC11821543 DOI: 10.1038/s41588-024-02051-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 12/04/2024] [Indexed: 01/11/2025]
Abstract
Segmental duplications (SDs) contribute significantly to human disease, evolution and diversity but have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies (from 85 samples representing 38 Africans and 47 non-Africans) in which the majority of autosomal SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms and sex chromosomes, we identify 173.2 Mb of duplicated sequence (47.4 Mb not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable, with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy numbers than non-African samples. Comparison to a resource of 563 million full-length isoform sequencing reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.
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Affiliation(s)
- Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Altos Labs, San Diego, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Tomi Pastinen
- Children's Mercy Hospital and University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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5
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Meyer L, Barry P, Riquet F, Foote A, Der Sarkissian C, Cunha RL, Arbiol C, Cerqueira F, Desmarais E, Bordes A, Bierne N, Guinand B, Gagnaire PA. Divergence and gene flow history at two large chromosomal inversions underlying ecotype differentiation in the long-snouted seahorse. Mol Ecol 2024; 33:e17277. [PMID: 38279695 DOI: 10.1111/mec.17277] [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: 06/20/2023] [Revised: 12/18/2023] [Accepted: 01/04/2024] [Indexed: 01/28/2024]
Abstract
Chromosomal inversions can play an important role in divergence and reproductive isolation by building and maintaining distinct allelic combinations between evolutionary lineages. Alternatively, they can take the form of balanced polymorphisms that segregate within populations until one arrangement becomes fixed. Many questions remain about how inversion polymorphisms arise, how they are maintained over the long term, and ultimately, whether and how they contribute to speciation. The long-snouted seahorse (Hippocampus guttulatus) is genetically subdivided into geographic lineages and marine-lagoon ecotypes, with shared structural variation underlying lineage and ecotype divergence. Here, we aim to characterize structural variants and to reconstruct their history and suspected role in ecotype formation. We generated a near chromosome-level genome assembly and described genome-wide patterns of diversity and divergence through the analysis of 112 whole-genome sequences from Atlantic, Mediterranean, and Black Sea populations. By also analysing linked-read sequencing data, we found evidence for two chromosomal inversions that were several megabases in length and showed contrasting allele frequency patterns between lineages and ecotypes across the species range. We reveal that these inversions represent ancient intraspecific polymorphisms, one likely being maintained by divergent selection and the other by pseudo-overdominance. A possible selective coupling between the two inversions was further supported by the absence of specific haplotype combinations and a putative functional interaction between the two inversions in reproduction. Lastly, we detected gene flux eroding divergence between inverted alleles at varying levels for the two inversions, with a likely impact on their dynamics and contribution to divergence and speciation.
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Affiliation(s)
- Laura Meyer
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Pierre Barry
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
- CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos Universidade do Porto, Vairão, Portugal
| | | | - Andrew Foote
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway
| | - Clio Der Sarkissian
- Centre for Anthropobiology and Genomics of Toulouse, CNRS, University of Toulouse Paul Sabatier, Toulouse, France
| | - Regina L Cunha
- Centre of Marine Sciences-CCMAR, University of Algarve, Faro, Portugal
| | | | | | - Erick Desmarais
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Anaïs Bordes
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Nicolas Bierne
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Bruno Guinand
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
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6
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Loh L, Saunders PM, Faoro C, Font-Porterias N, Nemat-Gorgani N, Harrison GF, Sadeeq S, Hensen L, Wong SC, Widjaja J, Clemens EB, Zhu S, Kichula KM, Tao S, Zhu F, Montero-Martin G, Fernandez-Vina M, Guethlein LA, Vivian JP, Davies J, Mentzer AJ, Oppenheimer SJ, Pomat W, Ioannidis AG, Barberena-Jonas C, Moreno-Estrada A, Miller A, Parham P, Rossjohn J, Tong SYC, Kedzierska K, Brooks AG, Norman PJ. An archaic HLA class I receptor allele diversifies natural killer cell-driven immunity in First Nations peoples of Oceania. Cell 2024; 187:7008-7024.e19. [PMID: 39476840 PMCID: PMC11606752 DOI: 10.1016/j.cell.2024.10.005] [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: 06/19/2023] [Revised: 05/24/2024] [Accepted: 10/03/2024] [Indexed: 11/02/2024]
Abstract
Genetic variation in host immunity impacts the disproportionate burden of infectious diseases that can be experienced by First Nations peoples. Polymorphic human leukocyte antigen (HLA) class I and killer cell immunoglobulin-like receptors (KIRs) are key regulators of natural killer (NK) cells, which mediate early infection control. How this variation impacts their responses across populations is unclear. We show that HLA-A∗24:02 became the dominant ligand for inhibitory KIR3DL1 in First Nations peoples across Oceania, through positive natural selection. We identify KIR3DL1∗114, widespread across and unique to Oceania, as an allele lineage derived from archaic humans. KIR3DL1∗114+NK cells from First Nations Australian donors are inhibited through binding HLA-A∗24:02. The KIR3DL1∗114 lineage is defined by phenylalanine at residue 166. Structural and binding studies show phenylalanine 166 forms multiple unique contacts with HLA-peptide complexes, increasing both affinity and specificity. Accordingly, assessing immunogenetic variation and the functional implications for immunity are fundamental toward understanding population-based disease associations.
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Affiliation(s)
- Liyen Loh
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Philippa M Saunders
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
| | - Camilla Faoro
- Infection and Immunity Program and Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Neus Font-Porterias
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Neda Nemat-Gorgani
- Department of Structural Biology and Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA
| | - Genelle F Harrison
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Suraju Sadeeq
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Luca Hensen
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
| | - Shu Cheng Wong
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
| | - Jacqueline Widjaja
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
| | - E Bridie Clemens
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia
| | - Shiying Zhu
- Infection and Immunity Program and Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Katherine M Kichula
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Sudan Tao
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO 80045, USA; Blood Center of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Faming Zhu
- Blood Center of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Gonzalo Montero-Martin
- Stanford Blood Centre, Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Marcelo Fernandez-Vina
- Stanford Blood Centre, Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Lisbeth A Guethlein
- Department of Structural Biology and Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA
| | - Julian P Vivian
- Infection and Immunity Program and Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Jane Davies
- Menzies School of Health Research, Charles Darwin University, Darwin, NT 0810, Australia; Department of Infectious Diseases, Royal Darwin Hospital, Casuarina, NT 0810, Australia
| | - Alexander J Mentzer
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Stephen J Oppenheimer
- Institute of Social and Cultural Anthropology, School of Anthropology and Museum Ethnography, University of Oxford, Oxford OX3 7LF, UK
| | - William Pomat
- Papua New Guinea Institute of Medical Research, Post Office Box 60, Goroka, Papua New Guinea
| | | | - Carmina Barberena-Jonas
- Advanced Genomics Unit, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36821, Mexico
| | - Andrés Moreno-Estrada
- Advanced Genomics Unit, Center for Research and Advanced Studies (CINVESTAV), Irapuato 36821, Mexico
| | - Adrian Miller
- Jawun Research Centre, Central Queensland University, Cairns, QLD 4870, Australia
| | - Peter Parham
- Department of Structural Biology and Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA
| | - Jamie Rossjohn
- Infection and Immunity Program and Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; Institute of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff CF14 4XN, UK.
| | - Steven Y C Tong
- Victorian Infectious Diseases Service, The Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, VIC 3000, Australia; Department of Infectious Diseases, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, VIC 3000, Australia.
| | - Katherine Kedzierska
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia.
| | - Andrew G Brooks
- Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia.
| | - Paul J Norman
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO 80045, USA; Department of Structural Biology and Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA.
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7
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Auwerx C, Kutalik Z, Reymond A. The pleiotropic spectrum of proximal 16p11.2 CNVs. Am J Hum Genet 2024; 111:2309-2346. [PMID: 39332410 PMCID: PMC11568765 DOI: 10.1016/j.ajhg.2024.08.015] [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: 03/28/2024] [Revised: 08/18/2024] [Accepted: 08/21/2024] [Indexed: 09/29/2024] Open
Abstract
Recurrent genomic rearrangements at 16p11.2 BP4-5 represent one of the most common causes of genomic disorders. Originally associated with increased risk for autism spectrum disorder, schizophrenia, and intellectual disability, as well as adiposity and head circumference, these CNVs have since been associated with a plethora of phenotypic alterations, albeit with high variability in expressivity and incomplete penetrance. Here, we comprehensively review the pleiotropy associated with 16p11.2 BP4-5 rearrangements to shine light on its full phenotypic spectrum. Illustrating this phenotypic heterogeneity, we expose many parallels between findings gathered from clinical versus population-based cohorts, which often point to the same physiological systems, and emphasize the role of the CNV beyond neuropsychiatric and anthropometric traits. Revealing the complex and variable clinical manifestations of this CNV is crucial for accurate diagnosis and personalized treatment strategies for carrier individuals. Furthermore, we discuss areas of research that will be key to identifying factors contributing to phenotypic heterogeneity and gaining mechanistic insights into the molecular pathways underlying observed associations, while demonstrating how diversity in affected individuals, cohorts, experimental models, and analytical approaches can catalyze discoveries.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
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8
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Jeong H, Dishuck PC, Yoo D, Harvey WT, Munson KM, Lewis AP, Kordosky J, Garcia GH, Human Genome Structural Variation Consortium (HGSVC), Yilmaz F, Hallast P, Lee C, Pastinen T, Eichler EE. Structural polymorphism and diversity of human segmental duplications. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.04.597452. [PMID: 38895457 PMCID: PMC11185583 DOI: 10.1101/2024.06.04.597452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Segmental duplications (SDs) contribute significantly to human disease, evolution, and diversity yet have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies where the majority of SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms, we identify 173.2 Mbp of duplicated sequence (47.4 Mbp not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy number when compared to non-African samples. A comparison to a resource of 563 million full-length Iso-Seq reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.
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Affiliation(s)
- Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Altos Labs, San Diego, CA, USA
| | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T. Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P. Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H. Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Tomi Pastinen
- Children’s Mercy Hospital and University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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9
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Mao Y, Harvey WT, Porubsky D, Munson KM, Hoekzema K, Lewis AP, Audano PA, Rozanski A, Yang X, Zhang S, Yoo D, Gordon DS, Fair T, Wei X, Logsdon GA, Haukness M, Dishuck PC, Jeong H, Del Rosario R, Bauer VL, Fattor WT, Wilkerson GK, Mao Y, Shi Y, Sun Q, Lu Q, Paten B, Bakken TE, Pollen AA, Feng G, Sawyer SL, Warren WC, Carbone L, Eichler EE. Structurally divergent and recurrently mutated regions of primate genomes. Cell 2024; 187:1547-1562.e13. [PMID: 38428424 PMCID: PMC10947866 DOI: 10.1016/j.cell.2024.01.052] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 11/26/2023] [Accepted: 01/31/2024] [Indexed: 03/03/2024]
Abstract
We sequenced and assembled using multiple long-read sequencing technologies the genomes of chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, owl monkey, and marmoset. We identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. We estimate that 819.47 Mbp or ∼27% of the genome has been affected by SVs across primate evolution. We identify 1,607 structurally divergent regions wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (e.g., CARD, C4, and OLAH gene families) and additional lineage-specific genes are generated (e.g., CKAP2, VPS36, ACBD7, and NEK5 paralogs), becoming targets of rapid chromosomal diversification and positive selection (e.g., RGPD gene family). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species.
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Affiliation(s)
- Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China.
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Allison Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xiangyu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Xiaoxi Wei
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ricardo Del Rosario
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vanessa L Bauer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Will T Fattor
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Gregory K Wilkerson
- Department of Veterinary Sciences, Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA; Department of Clinical Sciences, North Carolina State University, Raleigh, NC, USA
| | - Yuxiang Mao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Qiang Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science & Intelligence Technology, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Qing Lu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Guoping Feng
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sara L Sawyer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Bouder, CO, USA
| | - Wesley C Warren
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA; Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA; Institute of Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Lucia Carbone
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA; Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA; Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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10
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Peyrégne S, Slon V, Kelso J. More than a decade of genetic research on the Denisovans. Nat Rev Genet 2024; 25:83-103. [PMID: 37723347 DOI: 10.1038/s41576-023-00643-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2023] [Indexed: 09/20/2023]
Abstract
Denisovans, a group of now extinct humans who lived in Eastern Eurasia in the Middle and Late Pleistocene, were first identified from DNA sequences just over a decade ago. Only ten fragmentary remains from two sites have been attributed to Denisovans based entirely on molecular information. Nevertheless, there has been great interest in using genetic data to understand Denisovans and their place in human history. From the reconstruction of a single high-quality genome, it has been possible to infer their population history, including events of admixture with other human groups. Additionally, the identification of Denisovan DNA in the genomes of present-day individuals has provided insights into the timing and routes of dispersal of ancient modern humans into Asia and Oceania, as well as the contributions of archaic DNA to the physiology of present-day people. In this Review, we synthesize more than a decade of research on Denisovans, reconcile controversies and summarize insights into their population history and phenotype. We also highlight how our growing knowledge about Denisovans has provided insights into our own evolutionary history.
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Affiliation(s)
- Stéphane Peyrégne
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany.
| | - Viviane Slon
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany
- Department of Anatomy and Anthropology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Dan David Center for Human Evolution and Biohistory Research, Tel Aviv University, Tel Aviv, Israel
| | - Janet Kelso
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany.
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11
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Liu X, Chen W, Huang B, Wang X, Peng Y, Zhang X, Chai W, Khan MZ, Wang C. Advancements in copy number variation screening in herbivorous livestock genomes and their association with phenotypic traits. Front Vet Sci 2024; 10:1334434. [PMID: 38274664 PMCID: PMC10808162 DOI: 10.3389/fvets.2023.1334434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/27/2023] [Indexed: 01/27/2024] Open
Abstract
Copy number variations (CNVs) have garnered increasing attention within the realm of genetics due to their prevalence in human, animal, and plant genomes. These structural genetic variations have demonstrated associations with a broad spectrum of phenotypic diversity, economic traits, environmental adaptations, epidemics, and other essential aspects of both plants and animals. Furthermore, CNVs exhibit extensive sequence variability and encompass a wide array of genomes. The advancement and maturity of microarray and sequencing technologies have catalyzed a surge in research endeavors pertaining to CNVs. This is particularly prominent in the context of livestock breeding, where molecular markers have gained prominence as a valuable tool in comparison to traditional breeding methods. In light of these developments, a contemporary and comprehensive review of existing studies on CNVs becomes imperative. This review serves the purpose of providing a brief elucidation of the fundamental concepts underlying CNVs, their mutational mechanisms, and the diverse array of detection methods employed to identify these structural variations within genomes. Furthermore, it seeks to systematically analyze the recent advancements and findings within the field of CNV research, specifically within the genomes of herbivorous livestock species, including cattle, sheep, horses, and donkeys. The review also highlighted the role of CNVs in shaping various phenotypic traits including growth traits, reproductive traits, pigmentation and disease resistance etc., in herbivorous livestock. The main goal of this review is to furnish readers with an up-to-date compilation of knowledge regarding CNVs in herbivorous livestock genomes. By integrating the latest research findings and insights, it is anticipated that this review will not only offer pertinent information but also stimulate future investigations into the realm of CNVs in livestock. In doing so, it endeavors to contribute to the enhancement of breeding strategies, genomic selection, and the overall improvement of herbivorous livestock production and resistance to diseases.
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Affiliation(s)
| | | | | | | | | | | | | | - Muhammad Zahoor Khan
- Liaocheng Research Institute of Donkey High-Efficiency Breeding, Liaocheng University, Liaocheng, China
| | - Changfa Wang
- Liaocheng Research Institute of Donkey High-Efficiency Breeding, Liaocheng University, Liaocheng, China
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12
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Pollen AA, Kilik U, Lowe CB, Camp JG. Human-specific genetics: new tools to explore the molecular and cellular basis of human evolution. Nat Rev Genet 2023; 24:687-711. [PMID: 36737647 PMCID: PMC9897628 DOI: 10.1038/s41576-022-00568-4] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/05/2023]
Abstract
Our ancestors acquired morphological, cognitive and metabolic modifications that enabled humans to colonize diverse habitats, develop extraordinary technologies and reshape the biosphere. Understanding the genetic, developmental and molecular bases for these changes will provide insights into how we became human. Connecting human-specific genetic changes to species differences has been challenging owing to an abundance of low-effect size genetic changes, limited descriptions of phenotypic differences across development at the level of cell types and lack of experimental models. Emerging approaches for single-cell sequencing, genetic manipulation and stem cell culture now support descriptive and functional studies in defined cell types with a human or ape genetic background. In this Review, we describe how the sequencing of genomes from modern and archaic hominins, great apes and other primates is revealing human-specific genetic changes and how new molecular and cellular approaches - including cell atlases and organoids - are enabling exploration of the candidate causal factors that underlie human-specific traits.
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Affiliation(s)
- Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| | - Umut Kilik
- Institute of Human Biology (IHB), Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Craig B Lowe
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA.
| | - J Gray Camp
- Institute of Human Biology (IHB), Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
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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: 3] [Impact Index Per Article: 1.5] [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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Soto DC, Uribe-Salazar JM, Shew CJ, Sekar A, McGinty S, Dennis MY. Genomic structural variation: A complex but important driver of human evolution. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023; 181 Suppl 76:118-144. [PMID: 36794631 PMCID: PMC10329998 DOI: 10.1002/ajpa.24713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 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, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - José M. Uribe-Salazar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Aarthi Sekar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Sean McGinty
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
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15
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Salehian-Dehkordi H, Huang JH, Pirany N, Mehrban H, Lv XY, Sun W, Esmailizadeh A, Lv FH. Genomic Landscape of Copy Number Variations and Their Associations with Climatic Variables in the World's Sheep. Genes (Basel) 2023; 14:1256. [PMID: 37372436 PMCID: PMC10298528 DOI: 10.3390/genes14061256] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/06/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
Sheep show characteristics of phenotypic diversity and adaptation to diverse climatic regions. Previous studies indicated associations between copy number variations (CNVs) and climate-driven adaptive evolution in humans and other domestic animals. Here, we constructed a genomic landscape of CNVs (n = 39,145) in 47 old autochthonous populations genotyped at a set of high-density (600 K) SNPs to detect environment-driven signatures of CNVs using a multivariate regression model. We found 136 deletions and 52 duplications that were significantly (Padj. < 0.05) associated with climatic variables. These climate-mediated selective CNVs are involved in functional candidate genes for heat stress and cold climate adaptation (e.g., B3GNTL1, UBE2L3, and TRAF2), coat and wool-related traits (e.g., TMEM9, STRA6, RASGRP2, and PLA2G3), repairing damaged DNA (e.g., HTT), GTPase activity (e.g., COPG), fast metabolism (e.g., LMF2 and LPIN3), fertility and reproduction (e.g., SLC19A1 and CCDC155), growth-related traits (e.g., ADRM1 and IGFALS), and immune response (e.g., BEGAIN and RNF121) in sheep. In particular, we identified significant (Padj. < 0.05) associations between probes in deleted/duplicated CNVs and solar radiation. Enrichment analysis of the gene sets among all the CNVs revealed significant (Padj. < 0.05) enriched gene ontology terms and pathways related to functions such as nucleotide, protein complex, and GTPase activity. Additionally, we observed overlapping between the CNVs and 140 known sheep QTLs. Our findings imply that CNVs can serve as genomic markers for the selection of sheep adapted to specific climatic conditions.
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Affiliation(s)
- Hosein Salehian-Dehkordi
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (H.S.-D.); (J.-H.H.)
- Department of Animal Science, Faculty of Agriculture, Shahrekord University, Shahrekord 88186-34141, Iran; (N.P.); (H.M.)
| | - Jia-Hui Huang
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (H.S.-D.); (J.-H.H.)
| | - Nasrollah Pirany
- Department of Animal Science, Faculty of Agriculture, Shahrekord University, Shahrekord 88186-34141, Iran; (N.P.); (H.M.)
| | - Hossein Mehrban
- Department of Animal Science, Faculty of Agriculture, Shahrekord University, Shahrekord 88186-34141, Iran; (N.P.); (H.M.)
| | - Xiao-Yang Lv
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China; (X.-Y.L.); (W.S.)
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou 225009, China
| | - Wei Sun
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China; (X.-Y.L.); (W.S.)
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou 225009, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman 76169-14111, Iran
| | - Feng-Hua Lv
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; (H.S.-D.); (J.-H.H.)
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16
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Hamid I, Korunes KL, Schrider DR, Goldberg A. Localizing Post-Admixture Adaptive Variants with Object Detection on Ancestry-Painted Chromosomes. Mol Biol Evol 2023; 40:msad074. [PMID: 36947126 PMCID: PMC10116606 DOI: 10.1093/molbev/msad074] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 03/14/2023] [Accepted: 03/20/2023] [Indexed: 03/23/2023] Open
Abstract
Gene flow between previously differentiated populations during the founding of an admixed or hybrid population has the potential to introduce adaptive alleles into the new population. If the adaptive allele is common in one source population, but not the other, then as the adaptive allele rises in frequency in the admixed population, genetic ancestry from the source containing the adaptive allele will increase nearby as well. Patterns of genetic ancestry have therefore been used to identify post-admixture positive selection in humans and other animals, including examples in immunity, metabolism, and animal coloration. A common method identifies regions of the genome that have local ancestry "outliers" compared with the distribution across the rest of the genome, considering each locus independently. However, we lack theoretical models for expected distributions of ancestry under various demographic scenarios, resulting in potential false positives and false negatives. Further, ancestry patterns between distant sites are often not independent. As a result, current methods tend to infer wide genomic regions containing many genes as under selection, limiting biological interpretation. Instead, we develop a deep learning object detection method applied to images generated from local ancestry-painted genomes. This approach preserves information from the surrounding genomic context and avoids potential pitfalls of user-defined summary statistics. We find the method is robust to a variety of demographic misspecifications using simulated data. Applied to human genotype data from Cabo Verde, we localize a known adaptive locus to a single narrow region compared with multiple or long windows obtained using two other ancestry-based methods.
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Affiliation(s)
- Iman Hamid
- Department of Evolutionary Anthropology, Duke University, Durham, NC
| | | | - Daniel R Schrider
- Department of Genetics, University of North Carolina, Chapel Hill, NC
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke University, Durham, NC
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17
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Mao Y, Harvey WT, Porubsky D, Munson KM, Hoekzema K, Lewis AP, Audano PA, Rozanski A, Yang X, Zhang S, Gordon DS, Wei X, Logsdon GA, Haukness M, Dishuck PC, Jeong H, Del Rosario R, Bauer VL, Fattor WT, Wilkerson GK, Lu Q, Paten B, Feng G, Sawyer SL, Warren WC, Carbone L, Eichler EE. Structurally divergent and recurrently mutated regions of primate genomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.531415. [PMID: 36945442 PMCID: PMC10028934 DOI: 10.1101/2023.03.07.531415] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
To better understand the pattern of primate genome structural variation, we sequenced and assembled using multiple long-read sequencing technologies the genomes of eight nonhuman primate species, including New World monkeys (owl monkey and marmoset), Old World monkey (macaque), Asian apes (orangutan and gibbon), and African ape lineages (gorilla, bonobo, and chimpanzee). Compared to the human genome, we identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. Across 50 million years of primate evolution, we estimate that 819.47 Mbp or ~27% of the genome has been affected by SVs based on analysis of these primate lineages. We identify 1,607 structurally divergent regions (SDRs) wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (CARDs, ABCD7, OLAH) and new lineage-specific genes are generated (e.g., CKAP2, NEK5) and have become targets of rapid chromosomal diversification and positive selection (e.g., RGPDs). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species for the first time.
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Affiliation(s)
- Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Allison Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xiangyu Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Xiaoxi Wei
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ricardo Del Rosario
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vanessa L Bauer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Will T Fattor
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Gregory K Wilkerson
- Department of Veterinary Sciences, Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA
- Department of Clinical Sciences, North Carolina State University, Raleigh, NC, USA
| | - Qing Lu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Guoping Feng
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sara L Sawyer
- BioFrontiers Institute, Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Wesley C Warren
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
- Department of Surgery, School of Medicine, University of Missouri, Columbia, MO, USA
- Institute of Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Lucia Carbone
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
- Division of Genetics, Oregon National Primate Research Center, Beaverton, OR, USA
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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18
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Cheng H, Zhang Z, Wen J, Lenstra JA, Heller R, Cai Y, Guo Y, Li M, Li R, Li W, He S, Wang J, Shao J, Song Y, Zhang L, Billah M, Wang X, Liu M, Jiang Y. Long divergent haplotypes introgressed from wild sheep are associated with distinct morphological and adaptive characteristics in domestic sheep. PLoS Genet 2023; 19:e1010615. [PMID: 36821549 PMCID: PMC9949681 DOI: 10.1371/journal.pgen.1010615] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 01/13/2023] [Indexed: 02/24/2023] Open
Abstract
The worldwide sheep population comprises more than 1000 breeds. Together, these exhibit a considerable morphological diversity, which has not been extensively investigated at the molecular level. Here, we analyze whole-genome sequencing individuals of 1,098 domestic sheep from 154 breeds, and 69 wild sheep from seven Ovis species. On average, we detected 6.8%, 1.0% and 0.2% introgressed sequence in domestic sheep originating from Iranian mouflon, urial and argali, respectively, with rare introgressions from other wild species. Interestingly, several introgressed haplotypes contributed to the morphological differentiations across sheep breeds, such as a RXFP2 haplotype from Iranian mouflon conferring the spiral horn trait, a MSRB3 haplotype from argali strongly associated with ear morphology, and a VPS13B haplotype probably originating from urial and mouflon possibly associated with facial traits. Our results reveal that introgression events from wild Ovis species contributed to the high rate of morphological differentiation in sheep breeds, but also to individual variation within breeds. We propose that long divergent haplotypes are a ubiquitous source of phenotypic variation that allows adaptation to a variable environment, and that these remain intact in the receiving population probably due to reduced recombination.
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Affiliation(s)
- Hong Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
- Shenzhen Branch, Guangdong Laboratory of 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, China
| | - Zhuangbiao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 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, China
| | - Johannes A. Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yingwei Guo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 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, China
| | - Wenrong Li
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
| | - Sangang He
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
| | - Jintao Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Junjie Shao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yuxuan Song
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Lei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Masum Billah
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 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, China
| | - Mingjun Liu
- Key Laboratory of Ruminant Genetics, Breeding & Reproduction, Ministry of Agriculture, China
- Key Laboratory of Animal Biotechnology of Xinjiang, Institute of Biotechnology, Xinjiang Academy of Animal Science, Urumqi, Xinjiang, China
- * E-mail: (ML); (YJ)
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
- * E-mail: (ML); (YJ)
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19
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Ge D, Wen Z, Feijó A, Lissovsky A, Zhang W, Cheng J, Yan C, She H, Zhang D, Cheng Y, Lu L, Wu X, Mu D, Zhang Y, Xia L, Qu Y, Vogler AP, Yang Q. Genomic Consequences of and Demographic Response to Pervasive Hybridization Over Time in Climate-Sensitive Pikas. Mol Biol Evol 2022; 40:6958644. [PMID: 36562771 PMCID: PMC9847633 DOI: 10.1093/molbev/msac274] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 11/13/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
Rare and geographically restricted species may be vulnerable to genetic effects from inbreeding depression in small populations or from genetic swamping through hybridization with common species, but a third possibility is that selective gene flow can restore fitness (genetic rescue). Climate-sensitive pikas (Ochotona spp.) of the Qinghai-Tibetan Plateau (QHTP) and its vicinity have been reduced to residual populations through the movement of climatic zones during the Pleistocene and recent anthropogenic disturbance, whereas the plateau pika (O. curzoniae) remains common. Population-level whole-genome sequencing (n = 142) of six closely related species in the subgenus Ochotona revealed several phases of ancient introgression, lineage replacement, and bidirectional introgression. The strength of gene flow was the greatest from the dominant O. curzoniae to ecologically distinct species in areas peripheral to the QHTP. Genetic analyses were consistent with environmental reconstructions of past population movements. Recurrent periods of introgression throughout the Pleistocene revealed an increase in genetic variation at first but subsequent loss of genetic variation in later phases. Enhanced dispersion of introgressed genomic regions apparently contributed to demographic recovery in three peripheral species that underwent range shifts following climate oscillations on the QHTP, although it failed to drive recovery of northeastern O. dauurica and geographically isolated O. sikimaria. Our findings highlight differences in timescale and environmental background to determine the consequence of hybridization and the unique role of the QHTP in conserving key evolutionary processes of sky island species.
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Affiliation(s)
| | | | | | | | | | - Jilong Cheng
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Chaochao Yan
- CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Huishang She
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Dezhi Zhang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yalin Cheng
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Liang Lu
- State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Xinlai Wu
- The Key Laboratory of Zoological Systematics and Application, School of Life Science, Institute of Life Science and Green Development, Hebei University, Baoding, 071002, China
| | - Danping Mu
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, 830046, China
| | - Yubo Zhang
- State Key Laboratory for Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences at College of Life Sciences, Peking University, Beijing, 100871, China
| | - Lin Xia
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
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20
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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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21
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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: 9] [Impact Index Per Article: 3.0] [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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22
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Wang Y, Ling Y, Gong J, Zhao X, Zhou H, Xie B, Lou H, Zhuang X, Jin L, The Han100K Initiative, 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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23
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Reilly PF, Tjahjadi A, Miller SL, Akey JM, Tucci S. The contribution of Neanderthal introgression to modern human traits. Curr Biol 2022; 32:R970-R983. [PMID: 36167050 PMCID: PMC9741939 DOI: 10.1016/j.cub.2022.08.027] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Neanderthals, our closest extinct relatives, lived in western Eurasia from 400,000 years ago until they went extinct around 40,000 years ago. DNA retrieved from ancient specimens revealed that Neanderthals mated with modern human contemporaries. As a consequence, introgressed Neanderthal DNA survives scattered across the human genome such that 1-4% of the genome of present-day people outside Africa are inherited from Neanderthal ancestors. Patterns of Neanderthal introgressed genomic sequences suggest that Neanderthal alleles had distinct fates in the modern human genetic background. Some Neanderthal alleles facilitated human adaptation to new environments such as novel climate conditions, UV exposure levels and pathogens, while others had deleterious consequences. Here, we review the body of work on Neanderthal introgression over the past decade. We describe how evolutionary forces shaped the genomic landscape of Neanderthal introgression and highlight the impact of introgressed alleles on human biology and phenotypic variation.
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Affiliation(s)
| | - Audrey Tjahjadi
- Department of Anthropology, Yale University, New Haven, CT, USA
| | | | - Joshua M Akey
- Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
| | - Serena Tucci
- Department of Anthropology, Yale University, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.
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24
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Ding R, Zhuang Z, Qiu Y, Wang X, Wu J, Zhou S, Ruan D, Xu C, Hong L, Gu T, Zheng E, Cai G, Huang W, Wu Z, Yang J. A composite strategy of genome-wide association study and copy number variation analysis for carcass traits in a Duroc pig population. BMC Genomics 2022; 23:590. [PMID: 35964005 PMCID: PMC9375371 DOI: 10.1186/s12864-022-08804-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/31/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Carcass traits are important in pig breeding programs for improving pork production. Understanding the genetic variants underlies complex phenotypes can help explain trait variation in pigs. In this study, we integrated a weighted single-step genome-wide association study (wssGWAS) and copy number variation (CNV) analyses to map genetic variations and genes associated with loin muscle area (LMA), loin muscle depth (LMD) and lean meat percentage (LMP) in Duroc pigs. RESULTS Firstly, we performed a genome-wide analysis for CNV detection using GeneSeek Porcine SNP50 Bead chip data of 3770 pigs. A total of 11,100 CNVs were detected, which were aggregated by overlapping 695 CNV regions (CNVRs). Next, we investigated CNVs of pigs from the same population by whole-genome resequencing. A genome-wide analysis of 21 pigs revealed 23,856 CNVRs that were further divided into three categories (851 gain, 22,279 loss, and 726 mixed), which covered 190.8 Mb (~ 8.42%) of the pig autosomal genome. Further, the identified CNVRs were used to determine an overall validation rate of 68.5% for the CNV detection accuracy of chip data. CNVR association analyses identified one CNVR associated with LMA, one with LMD and eight with LMP after applying stringent Bonferroni correction. The wssGWAS identified eight, six and five regions explaining more than 1% of the additive genetic variance for LMA, LMD and LMP, respectively. The CNVR analyses and wssGWAS identified five common regions, of which three regions were associated with LMA and two with LMP. Four genes (DOK7, ARAP1, ELMO2 and SLC13A3) were highlighted as promising candidates according to their function. CONCLUSIONS We determined an overall validation rate for the CNV detection accuracy of low-density chip data and constructed a genomic CNV map for Duroc pigs using resequencing, thereby proving a value genetic variation resource for pig genome research. Furthermore, our study utilized a composite genetic strategy for complex traits in pigs, which will contribute to the study for elucidating the genetic architecture that may be influenced and regulated by multiple forms of variations.
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Affiliation(s)
- Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Guangdong Wens Breeding Swine Technology Co., Ltd, Guangdong, 527439, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Cineng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Linjun Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Wen Huang
- Department of Animal Science, Michigan State University, East Lansing, MI, USA
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China.
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China.
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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: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [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
| | - 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
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26
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Brand CM, Colbran LL, Capra JA. Predicting Archaic Hominin Phenotypes from Genomic Data. Annu Rev Genomics Hum Genet 2022; 23:591-612. [PMID: 35440148 DOI: 10.1146/annurev-genom-111521-121903] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Ancient DNA provides a powerful window into the biology of extant and extinct species, including humans' closest relatives: Denisovans and Neanderthals. Here, we review what is known about archaic hominin phenotypes from genomic data and how those inferences have been made. We contend that understanding the influence of variants on lower-level molecular phenotypes-such as gene expression and protein function-is a promising approach to using ancient DNA to learn about archaic hominin traits. Molecular phenotypes have simpler genetic architectures than organism-level complex phenotypes, and this approach enables moving beyond association studies by proposing hypotheses about the effects of archaic variants that are testable in model systems. The major challenge to understanding archaic hominin phenotypes is broadening our ability to accurately map genotypes to phenotypes, but ongoing advances ensure that there will be much more to learn about archaic hominin phenotypes from their genomes. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Colin M Brand
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA; , .,Bakar Computational Health Sciences Institute, University of California, San Francisco, California, USA
| | - Laura L Colbran
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John A Capra
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA; , .,Bakar Computational Health Sciences Institute, University of California, San Francisco, California, USA
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27
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Witt KE, Villanea F, Loughran E, Zhang X, Huerta-Sanchez E. Apportioning archaic variants among modern populations. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200411. [PMID: 35430882 PMCID: PMC9014186 DOI: 10.1098/rstb.2020.0411] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
The apportionment of human genetic diversity within and between populations has been measured to understand human relatedness and demographic history. Likewise, the distribution of archaic ancestry in modern populations can be leveraged to better understand the interaction between our species and its archaic relatives. Resolving the interactions between modern and archaic human populations can be difficult, as archaic variants in modern populations have been shaped by genetic drift, bottlenecks and gene flow. Here, we investigate the distribution of archaic variation in Eurasian populations. We find that archaic ancestry coverage at the individual- and population-level present distinct patterns in modern human populations: South Asians have nearly twice the number of population-unique archaic alleles compared with Europeans or East Asians, indicating that these populations experienced differing demographic and archaic admixture events. We confirm previous observations that East Asian individuals have more Neanderthal ancestry than European individuals, but surprisingly, when we compare the number of single nucleotide polymorphisms with archaic alleles found across a population, Europeans have more Neanderthal ancestry than East Asians. We compare these results to simulated models and conclude that these patterns are consistent with multiple admixture events between modern humans and Neanderthals. This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.
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Affiliation(s)
- Kelsey E. Witt
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
| | - Fernando Villanea
- Department of Anthropology, University of Colorado Boulder, Boulder, CO, USA
| | - Elle Loughran
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Republic of Ireland
| | - Xinjun Zhang
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
| | - Emilia Huerta-Sanchez
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI 02912, USA
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Republic of Ireland
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28
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Vollger MR, Guitart X, Dishuck PC, Mercuri L, Harvey WT, Gershman A, Diekhans M, Sulovari A, Munson KM, Lewis AP, Hoekzema K, Porubsky D, Li R, Nurk S, Koren S, Miga KH, Phillippy AM, Timp W, Ventura M, Eichler EE. Segmental duplications and their variation in a complete human genome. Science 2022; 376:eabj6965. [PMID: 35357917 PMCID: PMC8979283 DOI: 10.1126/science.abj6965] [Citation(s) in RCA: 190] [Impact Index Per Article: 63.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Despite their importance in disease and evolution, highly identical segmental duplications (SDs) are among the last regions of the human reference genome (GRCh38) to be fully sequenced. Using a complete telomere-to-telomere human genome (T2T-CHM13), we present a comprehensive view of human SD organization. SDs account for nearly one-third of the additional sequence, increasing the genome-wide estimate from 5.4 to 7.0% [218 million base pairs (Mbp)]. An analysis of 268 human genomes shows that 91% of the previously unresolved T2T-CHM13 SD sequence (68.3 Mbp) better represents human copy number variation. Comparing long-read assemblies from human (n = 12) and nonhuman primate (n = 5) genomes, we systematically reconstruct the evolution and structural haplotype diversity of biomedically relevant and duplicated genes. This analysis reveals patterns of structural heterozygosity and evolutionary differences in SD organization between humans and other primates.
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Affiliation(s)
- Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xavi Guitart
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ludovica Mercuri
- Department of Biology, University of Bari, Aldo Moro, Bari 70125, Italy
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ruiyang Li
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Mario Ventura
- Department of Biology, University of Bari, Aldo Moro, Bari 70125, Italy
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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29
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A high-throughput real-time PCR tissue-of-origin test to distinguish blood from lymphoblastoid cell line DNA for (epi)genomic studies. Sci Rep 2022; 12:4684. [PMID: 35304543 PMCID: PMC8933453 DOI: 10.1038/s41598-022-08663-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/09/2022] [Indexed: 12/13/2022] Open
Abstract
Lymphoblastoid cell lines (LCLs) derive from blood infected in vitro by Epstein–Barr virus and were used in several genetic, transcriptomic and epigenomic studies. Although few changes were shown between LCL and blood genotypes (SNPs) validating their use in genetics, more were highlighted for other genomic features and/or in their transcriptome and epigenome. This could render them less appropriate for these studies, notably when blood DNA could still be available. Here we developed a simple, high-throughput and cost-effective real-time PCR approach allowing to distinguish blood from LCL DNA samples based on the presence of EBV relative load and rearranged T-cell receptors γ and β. Our approach was able to achieve 98.5% sensitivity and 100% specificity on DNA of known origin (458 blood and 316 LCL DNA). It was further applied to 1957 DNA samples from the CEPH Aging cohort comprising DNA of uncertain origin, identifying 784 blood and 1016 LCL DNA. A subset of these DNA was further analyzed with an epigenetic clock indicating that DNA extracted from blood should be preferred to LCL for DNA methylation-based age prediction analysis. Our approach could thereby be a powerful tool to ascertain the origin of DNA in old collections prior to (epi)genomic studies.
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30
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Yokoyama S. HDL Receptor in Schistosoma japonicum Mediating Egg Embryonation: Potential Molecular Basis for High Prevalence of Cholesteryl Ester Transfer Protein Deficiency in East Asia. Front Cell Dev Biol 2022; 10:807289. [PMID: 35372338 PMCID: PMC8968628 DOI: 10.3389/fcell.2022.807289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 02/21/2022] [Indexed: 12/03/2022] Open
Abstract
Schistosomiasis is a life-threatening parasitic disease caused by blood flukes, Schistosomes. In its intestinal type, the parasites reside in visceral/portal veins of the human hosts and lay eggs to excrete in feces via intestinal tracts, and some of the aberrant eggs plug into the liver via the portal blood flow. Ectopic growth of these eggs causes fatal granulomatosis and cirrhosis of the liver. The parasites ingest nutrients from the host blood plasma by using nonspecific and specific transport via their body surface and alimentary tracts. It is especially important for the female adults to obtain lipid molecules because they synthesize neither fatty acids nor sterols and yet produce egg yolk. Low-density lipoprotein receptors have been identified in the body of the Schistosomes but their functions in the parasite life cycle have not clearly been characterized. On the other hand, CD36-related protein was identified in the body and the eggs of Asian blood fluke, Schistosoma japonicum, and characterized as a molecule that mediates selective uptake of cholesteryl ester from the host plasma high-density lipoproteins (HDLs). This reaction was shown crucial for their eggs to grow to miracidia. Interestingly, abnormal large HDL generated in lack of cholesteryl ester transfer protein (CETP) is a poor substrate for this reaction, and, therefore, CETP deficiency resists pathogenic ectopic growth of the aberrant parasite eggs in the liver. This genetic mutation is exclusively found in East Asia, overlapping with the current and historic regions of Schistosoma japonicum epidemic, so that this infection could be related to high prevalence of CETP deficiency in East Asia.
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Affiliation(s)
- Shinji Yokoyama
- Food and Nutritional Sciences, Chubu University, Kasugai, Japan
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31
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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 2022; 39:msab313. [PMID: 34718708 PMCID: PMC8896759 DOI: 10.1093/molbev/msab313] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [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
- Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Naoki Masuda
- Department of Mathematics, University at Buffalo, State University of New York, Buffalo, NY, USA
- Computational and Data-Enabled Science and Engineering Program, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Omer Gokcumen
- Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, NY, 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: 27] [Impact Index Per Article: 6.8] [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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Evidence for opposing selective forces operating on human-specific duplicated TCAF genes in Neanderthals and humans. Nat Commun 2021; 12:5118. [PMID: 34433829 PMCID: PMC8387397 DOI: 10.1038/s41467-021-25435-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 08/04/2021] [Indexed: 11/30/2022] Open
Abstract
TRP channel-associated factor 1/2 (TCAF1/TCAF2) proteins antagonistically regulate the cold-sensor protein TRPM8 in multiple human tissues. Understanding their significance has been complicated given the locus spans a gap-ridden region with complex segmental duplications in GRCh38. Using long-read sequencing, we sequence-resolve the locus, annotate full-length TCAF models in primate genomes, and show substantial human-specific TCAF copy number variation. We identify two human super haplogroups, H4 and H5, and establish that TCAF duplications originated ~1.7 million years ago but diversified only in Homo sapiens by recurrent structural mutations. Conversely, in all archaic-hominin samples the fixation for a specific H4 haplotype without duplication is likely due to positive selection. Here, our results of TCAF copy number expansion, selection signals in hominins, and differential TCAF2 expression between haplogroups and high TCAF2 and TRPM8 expression in liver and prostate in modern-day humans imply TCAF diversification among hominins potentially in response to cold or dietary adaptations. Duplications of gene segments can allow novel physiological adaptations to evolve. A detailed analysis of the TCAF gene family in primates and archaic humans suggest rapid duplication and diversification in this gene family is associated with cold or dietary adaptations.
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Tedersoo L, Albertsen M, Anslan S, Callahan B. Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology. Appl Environ Microbiol 2021; 87:e0062621. [PMID: 34132589 PMCID: PMC8357291 DOI: 10.1128/aem.00626-21] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Short-read, high-throughput sequencing (HTS) methods have yielded numerous important insights into microbial ecology and function. Yet, in many instances short-read HTS techniques are suboptimal, for example, by providing insufficient phylogenetic resolution or low integrity of assembled genomes. Single-molecule and synthetic long-read (SLR) HTS methods have successfully ameliorated these limitations. In addition, nanopore sequencing has generated a number of unique analysis opportunities, such as rapid molecular diagnostics and direct RNA sequencing, and both Pacific Biosciences (PacBio) and nanopore sequencing support detection of epigenetic modifications. Although initially suffering from relatively low sequence quality, recent advances have greatly improved the accuracy of long-read sequencing technologies. In spite of great technological progress in recent years, the long-read HTS methods (PacBio and nanopore sequencing) are still relatively costly, require large amounts of high-quality starting material, and commonly need specific solutions in various analysis steps. Despite these challenges, long-read sequencing technologies offer high-quality, cutting-edge alternatives for testing hypotheses about microbiome structure and functioning as well as assembly of eukaryote genomes from complex environmental DNA samples.
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Affiliation(s)
- Leho Tedersoo
- Mycology and Microbiology Center, University of Tartu, Tartu, Estonia
| | - Mads Albertsen
- Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark
| | - Sten Anslan
- Mycology and Microbiology Center, University of Tartu, Tartu, Estonia
- Braunschweig University of Technology, Zoological Institute, Braunschweig, Germany
| | - Benjamin Callahan
- Department of Population Health and Pathobiology, College of Veterinary Medicine and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA
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Mudd-Martin G, Cirino AL, Barcelona V, Fox K, Hudson M, Sun YV, Taylor JY, Cameron VA. Considerations for Cardiovascular Genetic and Genomic Research With Marginalized Racial and Ethnic Groups and Indigenous Peoples: A Scientific Statement From the American Heart Association. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2021; 14:e000084. [PMID: 34304578 DOI: 10.1161/hcg.0000000000000084] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Historically marginalized racial and ethnic groups and Indigenous peoples are burdened by significant health inequities that are compounded by their underrepresentation in genetic and genomic research. Of all genome-wide association study participants, ≈79% are of European descent, despite this group constituting only 16% of the global population. For underrepresented populations, polygenic risk scores derived from these studies are less accurate in predicting disease phenotypes, novel population-specific genetic variations may be misclassified as potentially pathogenic, and there is a lack of understanding of how different populations metabolize drugs. Although inclusion of marginalized racial and ethnic groups and Indigenous peoples in genetic and genomic research is crucial, scientific studies must be guided by ethical principles of respect, honesty, justice, reciprocity, and care for individuals and communities. Special considerations are needed to support research that benefits the scientific community as well as Indigenous peoples and marginalized groups. Before a project begins, collaboration with community leaders and agencies can lead to successful implementation of the study. Throughout the study, consideration must be given to issues such as implications of informed consent for individuals and communities, dissemination of findings through scientific and community avenues, and implications of community identity for data governance and sharing. Attention to these issues is critical, given historical harms in biomedical research that marginalized groups and Indigenous peoples have suffered. Conducting genetic and genomic research in partnership with Indigenous peoples and marginalized groups guided by ethical principles provides a pathway for scientific advances that will enhance prevention and treatment of cardiovascular disease for everyone.
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38
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Recent ultra-rare inherited variants implicate new autism candidate risk genes. Nat Genet 2021; 53:1125-1134. [PMID: 34312540 DOI: 10.1038/s41588-021-00899-8] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 06/18/2021] [Indexed: 01/28/2023]
Abstract
Autism is a highly heritable complex disorder in which de novo mutation (DNM) variation contributes significantly to risk. Using whole-genome sequencing data from 3,474 families, we investigate another source of large-effect risk variation, ultra-rare variants. We report and replicate a transmission disequilibrium of private, likely gene-disruptive (LGD) variants in probands but find that 95% of this burden resides outside of known DNM-enriched genes. This variant class more strongly affects multiplex family probands and supports a multi-hit model for autism. Candidate genes with private LGD variants preferentially transmitted to probands converge on the E3 ubiquitin-protein ligase complex, intracellular transport and Erb signaling protein networks. We estimate that these variants are approximately 2.5 generations old and significantly younger than other variants of similar type and frequency in siblings. Overall, private LGD variants are under strong purifying selection and appear to act on a distinct set of genes not yet associated with autism.
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39
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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: 47] [Impact Index Per Article: 11.8] [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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40
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Ahlquist KD, Bañuelos MM, Funk A, Lai J, Rong S, Villanea FA, Witt KE. Our Tangled Family Tree: New Genomic Methods Offer Insight into the Legacy of Archaic Admixture. Genome Biol Evol 2021; 13:evab115. [PMID: 34028527 PMCID: PMC8480178 DOI: 10.1093/gbe/evab115] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 05/07/2021] [Accepted: 05/22/2021] [Indexed: 11/30/2022] Open
Abstract
The archaic ancestry present in the human genome has captured the imagination of both scientists and the wider public in recent years. This excitement is the result of new studies pushing the envelope of what we can learn from the archaic genetic information that has survived for over 50,000 years in the human genome. Here, we review the most recent ten years of literature on the topic of archaic introgression, including the current state of knowledge on Neanderthal and Denisovan introgression, as well as introgression from other as-yet unidentified archaic populations. We focus this review on four topics: 1) a reimagining of human demographic history, including evidence for multiple admixture events between modern humans, Neanderthals, Denisovans, and other archaic populations; 2) state-of-the-art methods for detecting archaic ancestry in population-level genomic data; 3) how these novel methods can detect archaic introgression in modern African populations; and 4) the functional consequences of archaic gene variants, including how those variants were co-opted into novel function in modern human populations. The goal of this review is to provide a simple-to-access reference for the relevant methods and novel data, which has changed our understanding of the relationship between our species and its siblings. This body of literature reveals the large degree to which the genetic legacy of these extinct hominins has been integrated into the human populations of today.
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Affiliation(s)
- K D Ahlquist
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Mayra M Bañuelos
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Alyssa Funk
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Jiaying Lai
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Brown Center for Biomedical Informatics, Brown University, Providence, Rhode Island, USA
| | - Stephen Rong
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Fernando A Villanea
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Anthropology, University of Colorado Boulder, Colorado, USA
| | - Kelsey E Witt
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, USA
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, USA
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41
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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: 31] [Impact Index Per Article: 7.8] [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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42
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Shukla V, Høffding MK, Hoffmann ER. Genome diversity and instability in human germ cells and preimplantation embryos. Semin Cell Dev Biol 2021; 113:132-147. [PMID: 33500205 PMCID: PMC8097364 DOI: 10.1016/j.semcdb.2020.12.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 12/18/2020] [Indexed: 12/26/2022]
Abstract
Genome diversity is essential for evolution and is of fundamental importance to human health. Generating genome diversity requires phases of DNA damage and repair that can cause genome instability. Humans have a high incidence of de novo congenital disorders compared to other organisms. Recent access to eggs, sperm and preimplantation embryos is revealing unprecedented rates of genome instability that may result in infertility and de novo mutations that cause genomic imbalance in at least 70% of conceptions. The error type and incidence of de novo mutations differ during developmental stages and are influenced by differences in male and female meiosis. In females, DNA repair is a critical factor that determines fertility and reproductive lifespan. In males, aberrant meiotic recombination causes infertility, embryonic failure and pregnancy loss. Evidence suggest germ cells are remarkably diverse in the type of genome instability that they display and the DNA damage responses they deploy. Additionally, the initial embryonic cell cycles are characterized by a high degree of genome instability that cause congenital disorders and may limit the use of CRISPR-Cas9 for heritable genome editing.
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Affiliation(s)
- Vallari Shukla
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Miya Kudo Høffding
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Eva R Hoffmann
- DNRF Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
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Ebert P, Audano PA, Zhu Q, Rodriguez-Martin B, Porubsky D, Bonder MJ, Sulovari A, Ebler J, Zhou W, Serra Mari R, Yilmaz F, Zhao X, Hsieh P, Lee J, Kumar S, Lin J, Rausch T, Chen Y, Ren J, Santamarina M, Höps W, Ashraf H, Chuang NT, Yang X, Munson KM, Lewis AP, Fairley S, Tallon LJ, Clarke WE, Basile AO, Byrska-Bishop M, Corvelo A, Evani US, Lu TY, Chaisson MJP, Chen J, Li C, Brand H, Wenger AM, Ghareghani M, Harvey WT, Raeder B, Hasenfeld P, Regier AA, Abel HJ, Hall IM, Flicek P, Stegle O, Gerstein MB, Tubio JMC, Mu Z, Li YI, Shi X, Hastie AR, Ye K, Chong Z, Sanders AD, Zody MC, Talkowski ME, Mills RE, Devine SE, Lee C, Korbel JO, Marschall T, Eichler EE. Haplotype-resolved diverse human genomes and integrated analysis of structural variation. Science 2021; 372:eabf7117. [PMID: 33632895 PMCID: PMC8026704 DOI: 10.1126/science.abf7117] [Citation(s) in RCA: 403] [Impact Index Per Article: 100.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 02/09/2021] [Indexed: 12/14/2022]
Abstract
Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.
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Affiliation(s)
- Peter Ebert
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Bernardo Rodriguez-Martin
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Marc Jan Bonder
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Jana Ebler
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Weichen Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
| | - Rebecca Serra Mari
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Xuefang Zhao
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Joyce Lee
- Bionano Genomics, San Diego, CA 92121, USA
| | - Sushant Kumar
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 and 437, 266 Whitney Avenue, New Haven, CT 06520, USA
| | - Jiadong Lin
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
| | - Tobias Rausch
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Yu Chen
- Department of Genetics and Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Jingwen Ren
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Martin Santamarina
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Department of Zoology, Genetics, and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Wolfram Höps
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Hufsah Ashraf
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Nelson T Chuang
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | - Xiaofei Yang
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Susan Fairley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Luke J Tallon
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | | | | | | | | | | | - Tsung-Yu Lu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Junjie Chen
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | - Chong Li
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Aaron M Wenger
- Pacific Biosciences of California, Menlo Park, CA 94025, USA
| | - Maryam Ghareghani
- Max Planck Institute for Informatics, Saarland Informatics Campus E1.4, 66123 Saarbrücken, Germany
- Saarbrücken Graduate School of Computer Science, Saarland University, Saarland Informatics Campus E1.3, 66123 Saarbrücken, Germany
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Benjamin Raeder
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Allison A Regier
- Department of Medicine, Washington University, St. Louis, MO 63108, USA
| | - Haley J Abel
- Department of Medicine, Washington University, St. Louis, MO 63108, USA
| | - Ira M Hall
- Department of Genetics, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Oliver Stegle
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 and 437, 266 Whitney Avenue, New Haven, CT 06520, USA
| | - Jose M C Tubio
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Department of Zoology, Genetics, and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Zepeng Mu
- Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL 60637, USA
| | - Yang I Li
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Xinghua Shi
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | | | - Kai Ye
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
- Department of Human Genetics, University of Michigan, 1241 E. Catherine Street, Ann Arbor, MI 48109, USA
| | - Zechen Chong
- Department of Genetics and Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Ashley D Sanders
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | | | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ryan E Mills
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, 1241 E. Catherine Street, Ann Arbor, MI 48109, USA
| | - Scott E Devine
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
- Department of Graduate Studies-Life Sciences, Ewha Womans University, Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, South Korea
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany.
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Tobias Marschall
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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44
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Changeux JP, Goulas A, Hilgetag CC. A Connectomic Hypothesis for the Hominization of the Brain. Cereb Cortex 2021; 31:2425-2449. [PMID: 33367521 PMCID: PMC8023825 DOI: 10.1093/cercor/bhaa365] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 10/30/2020] [Accepted: 11/02/2020] [Indexed: 02/06/2023] Open
Abstract
Cognitive abilities of the human brain, including language, have expanded dramatically in the course of our recent evolution from nonhuman primates, despite only minor apparent changes at the gene level. The hypothesis we propose for this paradox relies upon fundamental features of human brain connectivity, which contribute to a characteristic anatomical, functional, and computational neural phenotype, offering a parsimonious framework for connectomic changes taking place upon the human-specific evolution of the genome. Many human connectomic features might be accounted for by substantially increased brain size within the global neural architecture of the primate brain, resulting in a larger number of neurons and areas and the sparsification, increased modularity, and laminar differentiation of cortical connections. The combination of these features with the developmental expansion of upper cortical layers, prolonged postnatal brain development, and multiplied nongenetic interactions with the physical, social, and cultural environment gives rise to categorically human-specific cognitive abilities including the recursivity of language. Thus, a small set of genetic regulatory events affecting quantitative gene expression may plausibly account for the origins of human brain connectivity and cognition.
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Affiliation(s)
- Jean-Pierre Changeux
- CNRS UMR 3571, Institut Pasteur, 75724 Paris, France
- Communications Cellulaires, Collège de France, 75005 Paris, France
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, 20246 Hamburg, Germany
| | - Claus C Hilgetag
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, 20246 Hamburg, Germany
- Department of Health Sciences, Boston University, Boston, MA 02115, USA
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45
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Bredemeyer KR, Harris AJ, Li G, Zhao L, Foley NM, Roelke-Parker M, O’Brien SJ, Lyons LA, Warren WC, Murphy WJ. Ultracontinuous Single Haplotype Genome Assemblies for the Domestic Cat (Felis catus) and Asian Leopard Cat (Prionailurus bengalensis). J Hered 2021; 112:165-173. [PMID: 33305796 PMCID: PMC8006817 DOI: 10.1093/jhered/esaa057] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 12/08/2020] [Indexed: 12/11/2022] Open
Abstract
In addition to including one of the most popular companion animals, species from the cat family Felidae serve as a powerful system for genetic analysis of inherited and infectious disease, as well as for the study of phenotypic evolution and speciation. Previous diploid-based genome assemblies for the domestic cat have served as the primary reference for genomic studies within the cat family. However, these versions suffered from poor resolution of complex and highly repetitive regions, with substantial amounts of unplaced sequence that is polymorphic or copy number variable. We sequenced the genome of a female F1 Bengal hybrid cat, the offspring of a domestic cat (Felis catus) x Asian leopard cat (Prionailurus bengalensis) cross, with PacBio long sequence reads and used Illumina sequence reads from the parents to phase >99.9% of the reads into the 2 species' haplotypes. De novo assembly of the phased reads produced highly continuous haploid genome assemblies for the domestic cat and Asian leopard cat, with contig N50 statistics exceeding 83 Mb for both genomes. Whole-genome alignments reveal the Felis and Prionailurus genomes are colinear, and the cytogenetic differences between the homologous F1 and E4 chromosomes represent a case of centromere repositioning in the absence of a chromosomal inversion. Both assemblies offer significant improvements over the previous domestic cat reference genome, with a 100% increase in contiguity and the capture of the vast majority of chromosome arms in 1 or 2 large contigs. We further demonstrated that comparably accurate F1 haplotype phasing can be achieved with members of the same species when one or both parents of the trio are not available. These novel genome resources will empower studies of feline precision medicine, adaptation, and speciation.
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Affiliation(s)
- Kevin R Bredemeyer
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX
- Interdisciplinary Program in Genetics, Texas A&M University, College Station, TX
| | - Andrew J Harris
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX
- Interdisciplinary Program in Genetics, Texas A&M University, College Station, TX
| | - Gang Li
- College of Life Sciences, Shaanxi Normal University, Xi’an, Shaanxi, China
| | - Le Zhao
- College of Life Sciences, Shaanxi Normal University, Xi’an, Shaanxi, China
| | - Nicole M Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX
| | - Melody Roelke-Parker
- Frederick National Laboratory of Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD
| | - Stephen J O’Brien
- Laboratory of Genomic Diversity-Center for Computer Technologies, ITMO University, Saint Petersburg, Russian Federation
- Guy Harvey Oceanographic Center, Nova Southeastern University, Fort Lauderdale, FL
| | - Leslie A Lyons
- Department of Veterinary Medicine & Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO
| | - Wesley C Warren
- Bond Life Science Center, University of Missouri, Columbia, MO
| | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX
- Interdisciplinary Program in Genetics, Texas A&M University, College Station, TX
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46
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Zheng Z, Li Y, Li M, Li G, Du X, Hongyin H, Yin M, Lu Z, Zhang X, Shrestha N, Liu J, Yang Y. Whole-Genome Diversification Analysis of the Hornbeam Species Reveals Speciation and Adaptation Among Closely Related Species. FRONTIERS IN PLANT SCIENCE 2021; 12:581704. [PMID: 33643339 PMCID: PMC7902934 DOI: 10.3389/fpls.2021.581704] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 01/04/2021] [Indexed: 06/12/2023]
Abstract
Speciation is the key evolutionary process for generating biological diversity and has a central place in evolutionary and ecological research. How species diverge and adapt to different habitats is one of the most exciting areas in speciation studies. Here, we sequenced 55 individuals from three closely related species in the genus Carpinus: Carpinus tibetana, Carpinus monbeigiana, and Carpinus mollicoma to understand the strength and direction of gene flow and selection during the speciation process. We found low genetic diversity in C. tibetana, which reflects its extremely small effective population size. The speciation analysis between C. monbeigiana and C. mollicoma revealed that both species diverged ∼1.2 Mya with bidirectional gene flow. A total of 291 highly diverged genes, 223 copy number variants genes, and 269 positive selected genes were recovered from the two species. Genes associated with the diverged and positively selected regions were mainly involved in thermoregulation, plant development, and response to stress, which included adaptations to their habitats. We also found a great population decline and a low genetic divergence of C. tibetana, which suggests that this species is extremely vulnerable. We believe that the current diversification and adaption study and the important genomic resource sequenced herein will facilitate the speciation studies and serve as an important methodological reference for future research.
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Affiliation(s)
- Zeyu Zheng
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Ying Li
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Minjie Li
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Guiting Li
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Xin Du
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Hu Hongyin
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Mou Yin
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Zhiqiang Lu
- CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming, China
| | - Xu Zhang
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Nawal Shrestha
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Jianquan Liu
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Yongzhi Yang
- State Key Laboratory of Grassland Agro-Ecosystem, Institute of Innovation Ecology and School of Life Sciences, Lanzhou University, Lanzhou, China
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47
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Moore KJ, Hubbard AK, Williams LA, Spector LG. Childhood cancer incidence among specific Asian and Pacific Islander populations in the United States. Int J Cancer 2020; 147:3339-3348. [PMID: 32535909 PMCID: PMC7736474 DOI: 10.1002/ijc.33153] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/21/2020] [Accepted: 05/30/2020] [Indexed: 12/19/2022]
Abstract
Despite the vast genetic and environmental diversity in Asia, individuals of Asian and Pacific Islander (API) descent are often combined into a single group for epidemiologic analyses within the U.S. We used the Surveillance, Epidemiology and End Results (SEER) Detailed Asian/Pacific Islander Database to calculate incidence rates for discrete groups among children aged 0 to 19 years. Due to sample size constraints we pooled incidence among regional groups based on countries of origin: East Asians (Chinese, Japanese, Korean), Southeast (SE) Asians (Vietnamese, Laotian, Cambodian), Asian Indian/Pakistani, Oceanians (Guamanian, Samoan, Tongan) and Filipinos. Incidence rate ratios (IRR) and 95% confidence intervals (CI) were calculated comparing each API regional group to Non-Hispanic Whites (NHW) and East Asians. Finally, we calculated the correlation between incidence of cancer in specific API ethnicities in SEER and in originating countries in the Cancer Incidence in Five Continents. Incidence rates among API regional groups varied. Acute lymphoblastic leukemia (ALL) was lower in children of SE Asian descent (IRR 0.65, 95% CI 0.44, 0.96) compared to NHW. Acute myeloid leukemia (AML) was more common among children from Oceania compared to NHW (IRR 3.88, 95% CI 1.83, 8.22). East Asians had higher incidence rates than SE Asians but lower rates compared to children from Oceania. Correlation of some incidence rates between US-based API ethnicities and originating countries were similar. The variation observed in childhood cancer incidence patterns among API groups may indicate differences in underlying genetics and/or patterns of exposure.
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Affiliation(s)
- Kristin J. Moore
- Program in Health Disparities Research, University of Minnesota Medical School, University of Minnesota
| | - Aubrey K. Hubbard
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota
| | - Lindsay A. Williams
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota
- Masonic Cancer Center, University of Minnesota
| | - Logan G. Spector
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota
- Masonic Cancer Center, University of Minnesota
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48
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Murphy WJ, Foley NM, Bredemeyer KR, Gatesy J, Springer MS. Phylogenomics and the Genetic Architecture of the Placental Mammal Radiation. Annu Rev Anim Biosci 2020; 9:29-53. [PMID: 33228377 DOI: 10.1146/annurev-animal-061220-023149] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The genomes of placental mammals are being sequenced at an unprecedented rate. Alignments of hundreds, and one day thousands, of genomes spanning the rich living and extinct diversity of species offer unparalleled power to resolve phylogenetic controversies, identify genomic innovations of adaptation, and dissect the genetic architecture of reproductive isolation. We highlight outstanding questions about the earliest phases of placental mammal diversification and the promise of newer methods, as well as remaining challenges, toward using whole genome data to resolve placental mammal phylogeny. The next phase of mammalian comparative genomics will see the completion and application of finished-quality, gapless genome assemblies from many ordinal lineages and closely related species. Interspecific comparisons between the most hypervariable genomic loci will likely reveal large, but heretofore mostly underappreciated, effects on population divergence, morphological innovation, and the origin of new species.
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Affiliation(s)
- William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843, USA;
| | - Nicole M Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843, USA;
| | - Kevin R Bredemeyer
- Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843, USA;
| | - John Gatesy
- Division of Vertebrate Zoology, American Museum of Natural History, New York, NY 10024, USA
| | - Mark S Springer
- Department of Evolution, Ecology and Organismal Biology, University of California, Riverside, California 92521, USA
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49
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Logsdon GA, Vollger MR, Eichler EE. Long-read human genome sequencing and its applications. Nat Rev Genet 2020; 21:597-614. [PMID: 32504078 PMCID: PMC7877196 DOI: 10.1038/s41576-020-0236-x] [Citation(s) in RCA: 583] [Impact Index Per Article: 116.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/31/2020] [Indexed: 12/27/2022]
Abstract
Over the past decade, long-read, single-molecule DNA sequencing technologies have emerged as powerful players in genomics. With the ability to generate reads tens to thousands of kilobases in length with an accuracy approaching that of short-read sequencing technologies, these platforms have proven their ability to resolve some of the most challenging regions of the human genome, detect previously inaccessible structural variants and generate some of the first telomere-to-telomere assemblies of whole chromosomes. Long-read sequencing technologies will soon permit the routine assembly of diploid genomes, which will revolutionize genomics by revealing the full spectrum of human genetic variation, resolving some of the missing heritability and leading to the discovery of novel mechanisms of disease.
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Affiliation(s)
- Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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50
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Cantsilieris S, Sunkin SM, Johnson ME, Anaclerio F, Huddleston J, Baker C, Dougherty ML, Underwood JG, Sulovari A, Hsieh P, Mao Y, Catacchio CR, Malig M, Welch AE, Sorensen M, Munson KM, Jiang W, Girirajan S, Ventura M, Lamb BT, Conlon RA, Eichler EE. An evolutionary driver of interspersed segmental duplications in primates. Genome Biol 2020; 21:202. [PMID: 32778141 PMCID: PMC7419210 DOI: 10.1186/s13059-020-02074-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 06/08/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The complex interspersed pattern of segmental duplications in humans is responsible for rearrangements associated with neurodevelopmental disease, including the emergence of novel genes important in human brain evolution. We investigate the evolution of LCR16a, a putative driver of this phenomenon that encodes one of the most rapidly evolving human-ape gene families, nuclear pore interacting protein (NPIP). RESULTS Comparative analysis shows that LCR16a has independently expanded in five primate lineages over the last 35 million years of primate evolution. The expansions are associated with independent lineage-specific segmental duplications flanking LCR16a leading to the emergence of large interspersed duplication blocks at non-orthologous chromosomal locations in each primate lineage. The intron-exon structure of the NPIP gene family has changed dramatically throughout primate evolution with different branches showing characteristic gene models yet maintaining an open reading frame. In the African ape lineage, we detect signatures of positive selection that occurred after a transition to more ubiquitous expression among great ape tissues when compared to Old World and New World monkeys. Mouse transgenic experiments from baboon and human genomic loci confirm these expression differences and suggest that the broader ape expression pattern arose due to mutational changes that emerged in cis. CONCLUSIONS LCR16a promotes serial interspersed duplications and creates hotspots of genomic instability that appear to be an ancient property of primate genomes. Dramatic changes to NPIP gene structure and altered tissue expression preceded major bouts of positive selection in the African ape lineage, suggestive of a gene undergoing strong adaptive evolution.
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Affiliation(s)
- Stuart Cantsilieris
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Present Address: Centre for Eye Research Australia, Department of Surgery (Ophthalmology), University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, 3002, Australia
| | | | - Matthew E Johnson
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Fabio Anaclerio
- Department of Biology-Genetics, University of Bari, Bari, Italy
| | - John Huddleston
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, 98195, USA
| | - Carl Baker
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Max L Dougherty
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Jason G Underwood
- Pacific Biosciences (PacBio) of California, Incorporated, Menlo Park, CA, 94025, USA
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | | | - Maika Malig
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Present Address: Department of Molecular and Cellular Biology, University of California, Davis, CA, 95616, USA
- Present Address: Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, 95616, USA
| | - AnneMarie E Welch
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Present Address: Brain and Mitochondrial Research, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia
| | - Melanie Sorensen
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Weihong Jiang
- Case Transgenic and Targeting Facility, Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Santhosh Girirajan
- Department of Biochemistry and Molecular Biology, Department of Anthropology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Mario Ventura
- Department of Biology-Genetics, University of Bari, Bari, Italy
| | - Bruce T Lamb
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Ronald A Conlon
- Case Transgenic and Targeting Facility, Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA.
- Howard Hughes Medical Institute, University of Washington School of Medicine, 3720 15th Ave NE, S413C, Box 355065, Seattle, WA, 98195-5065, USA.
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