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Freudiger A, Jovanovic VM, Huang Y, Snyder-Mackler N, Conrad DF, Miller B, Montague MJ, Westphal H, Stadler PF, Bley S, Horvath JE, Brent LJN, Platt ML, Ruiz-Lambides A, Tung J, Nowick K, Ringbauer H, Widdig A. Taking identity-by-descent analysis into the wild: Estimating realized relatedness in free-ranging macaques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.09.574911. [PMID: 38260273 PMCID: PMC10802400 DOI: 10.1101/2024.01.09.574911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of DNA segments that are identical-by-descent (IBD) yield the most precise estimates of relatedness. Here, we leverage novel methods for estimating locus-specific IBD from low coverage whole genome resequencing data to demonstrate the feasibility and value of resolving fine-scaled gradients of relatedness in free-living animals. Using primarily 4-6× coverage data from a rhesus macaque (Macaca mulatta) population with available long-term pedigree data, we show that we can call the number and length of IBD segments across the genome with high accuracy even at 0.5× coverage. The resulting estimates demonstrate substantial variation in genetic relatedness within kin classes, leading to overlapping distributions between kin classes. They identify cryptic genetic relatives that are not represented in the pedigree and reveal elevated recombination rates in females relative to males, which allows us to discriminate maternal and paternal kin using genotype data alone. Our findings represent a breakthrough in the ability to understand the predictors and consequences of genetic relatedness in natural populations, contributing to our understanding of a fundamental component of population structure in the wild.
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Affiliation(s)
- Annika Freudiger
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Vladimir M Jovanovic
- Human Biology and Primate Evolution, Institut für Zoologie, Freie Universität Berlin, Berlin, Germany
- Bioinformatics Solution Center, Freie Universität Berlin, Berlin, Germany
| | - Yilei Huang
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Bioinformatics Group, Institute of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Noah Snyder-Mackler
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, USA
| | - Donald F Conrad
- Division of Genetics, Oregon National Primate Research Center, Portland, Oregon, USA
| | - Brian Miller
- Division of Genetics, Oregon National Primate Research Center, Portland, Oregon, USA
| | - Michael J Montague
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hendrikje Westphal
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Bioinformatics Group, Institute of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Peter F Stadler
- Bioinformatics Group, Institute of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
- Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
- Institute for Theoretical Chemistry, University of Vienna, Austria
- Facultad de Ciencias, Universidad Nacional de Colombia, Bogotá, Colombia
- Santa Fe Institute, Santa Fe, NM, USA
| | - Stefanie Bley
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Julie E Horvath
- Department of Biological and Biomedical Sciences, North Carolina Central University, North Carolina, Durham, USA
- Research and Collections Section, North Carolina Museum of Natural Sciences, North Carolina, Raleigh, USA
- Department of Biological Sciences, North Carolina State University, North Carolina, Raleigh, USA
- Department of Evolutionary Anthropology, Duke University, North Carolina, Durham, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Lauren J N Brent
- Centre for Research in Animal Behaviour, University of Exeter, Exeter, UK
| | - Michael L Platt
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Marketing Department, the Wharton School of Business, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Angelina Ruiz-Lambides
- Cayo Santiago Field Station, Caribbean Primate Research Center, University of Puerto Rico, Punta Santiago, Puerto Rico
| | - Jenny Tung
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Department of Evolutionary Anthropology, Duke University, North Carolina, Durham, USA
- Department of Biology, Duke University, Durham, North Carolina, USA
- Duke University Population Research Institute, Durham, North Carolina, USA
| | - Katja Nowick
- Human Biology and Primate Evolution, Institut für Zoologie, Freie Universität Berlin, Berlin, Germany
- Bioinformatics Solution Center, Freie Universität Berlin, Berlin, Germany
| | - Harald Ringbauer
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Anja Widdig
- Behavioral Ecology Research Group, Faculty of Life Sciences, Institute of Biology, Leipzig University, Leipzig, Germany
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany
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2
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Versoza CJ, Weiss S, Johal R, La Rosa B, Jensen JD, Pfeifer SP. Novel Insights into the Landscape of Crossover and Noncrossover Events in Rhesus Macaques (Macaca mulatta). Genome Biol Evol 2024; 16:evad223. [PMID: 38051960 PMCID: PMC10773715 DOI: 10.1093/gbe/evad223] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/04/2023] [Accepted: 11/28/2023] [Indexed: 12/07/2023] Open
Abstract
Meiotic recombination landscapes differ greatly between distantly and closely related taxa, populations, individuals, sexes, and even within genomes; however, the factors driving this variation are yet to be well elucidated. Here, we directly estimate contemporary crossover rates and, for the first time, noncrossover rates in rhesus macaques (Macaca mulatta) from four three-generation pedigrees comprising 32 individuals. We further compare these results with historical, demography-aware, linkage disequilibrium-based recombination rate estimates. From paternal meioses in the pedigrees, 165 crossover events with a median resolution of 22.3 kb were observed, corresponding to a male autosomal map length of 2,357 cM-approximately 15% longer than an existing linkage map based on human microsatellite loci. In addition, 85 noncrossover events with a mean tract length of 155 bp were identified-similar to the tract lengths observed in the only other two primates in which noncrossovers have been studied to date, humans and baboons. Consistent with observations in other placental mammals with PRDM9-directed recombination, crossover (and to a lesser extent noncrossover) events in rhesus macaques clustered in intergenic regions and toward the chromosomal ends in males-a pattern in broad agreement with the historical, sex-averaged recombination rate estimates-and evidence of GC-biased gene conversion was observed at noncrossover sites.
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Affiliation(s)
- Cyril J Versoza
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Sarah Weiss
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Ravneet Johal
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Bruno La Rosa
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Susanne P Pfeifer
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
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3
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Dinh BL, Tang E, Taparra K, Nakatsuka N, Chen F, Chiang CWK. Recombination map tailored to Native Hawaiians may improve robustness of genomic scans for positive selection. Hum Genet 2024; 143:85-99. [PMID: 38157018 PMCID: PMC10794367 DOI: 10.1007/s00439-023-02625-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 11/25/2023] [Indexed: 01/03/2024]
Abstract
Recombination events establish the patterns of haplotypic structure in a population and estimates of recombination rates are used in several downstream population and statistical genetic analyses. Using suboptimal maps from distantly related populations may reduce the efficacy of genomic analyses, particularly for underrepresented populations such as the Native Hawaiians. To overcome this challenge, we constructed recombination maps using genome-wide array data from two study samples of Native Hawaiians: one reflecting the current admixed state of Native Hawaiians (NH map) and one based on individuals of enriched Polynesian ancestries (PNS map) with the potential to be used for less admixed Polynesian populations such as the Samoans. We found the recombination landscape to be less correlated with those from other continental populations (e.g. Spearman's rho = 0.79 between PNS and CEU (Utah residents with Northern and Western European ancestry) compared to 0.92 between YRI (Yoruba in Ibadan, Nigeria) and CEU at 50 kb resolution), likely driven by the unique demographic history of the Native Hawaiians. PNS also shared the fewest recombination hotspots with other populations (e.g. 8% of hotspots shared between PNS and CEU compared to 27% of hotspots shared between YRI and CEU). We found that downstream analyses in the Native Hawaiian population, such as local ancestry inference, imputation, and IBD segment and relatedness detections, would achieve similar efficacy when using the NH map compared to an omnibus map. However, for genome scans of adaptive loci using integrated haplotype scores, we found several loci with apparent genome-wide significant signals (|Z-score|> 4) in Native Hawaiians that would not have been significant when analyzed using NH-specific maps. Population-specific recombination maps may therefore improve the robustness of haplotype-based statistics and help us better characterize the evolutionary history that may underlie Native Hawaiian-specific health conditions that persist today.
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Affiliation(s)
- Bryan L Dinh
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Echo Tang
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Kekoa Taparra
- Department of Radiation Oncology, Stanford University, Palo Alto, CA, USA
| | | | - Fei Chen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Charleston W K Chiang
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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4
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Dinh BL, Tang E, Taparra K, Nakatsuka N, Chen F, Chiang CWK. Recombination map tailored to Native Hawaiians improves robustness of genomic scans for positive selection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.12.548735. [PMID: 37503129 PMCID: PMC10370006 DOI: 10.1101/2023.07.12.548735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Recombination events establish the patterns of haplotypic structure in a population and estimates of recombination rates are used in several downstream population and statistical genetic analyses. Using suboptimal maps from distantly related populations may reduce the efficacy of genomic analyses, particularly for underrepresented populations such as the Native Hawaiians. To overcome this challenge, we constructed recombination maps using genome-wide array data from two study samples of Native Hawaiians: one reflecting the current admixed state of Native Hawaiians (NH map), and one based on individuals of enriched Polynesian ancestries (PNS map) with the potential to be used for less admixed Polynesian populations such as the Samoans. We found the recombination landscape to be less correlated with those from other continental populations (e.g. Spearman's rho = 0.79 between PNS and CEU (Utah residents with Northern and Western European ancestry) compared to 0.92 between YRI (Yoruba in Ibadan, Nigeria) and CEU at 50 kb resolution), likely driven by the unique demographic history of the Native Hawaiians. PNS also shared the fewest recombination hotspots with other populations (e.g. 8% of hotspots shared between PNS and CEU compared to 27% of hotspots shared between YRI and CEU). We found that downstream analyses in the Native Hawaiian population, such as local ancestry inference, imputation, and IBD segment and relatedness detections, would achieve similar efficacy when using the NH map compared to an omnibus map. However, for genome scans of adaptive loci using integrated haplotype scores, we found several loci with apparent genome-wide significant signals (|Z-score| > 4) in Native Hawaiians that would not have been significant when analyzed using NH-specific maps. Population-specific recombination maps may therefore improve the robustness of haplotype-based statistics and help us better characterize the evolutionary history that may underlie Native Hawaiian-specific health conditions that persist today.
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Affiliation(s)
- Bryan L Dinh
- Department of Quantitative and Computational Biology, University of Southern California
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Echo Tang
- Department of Quantitative and Computational Biology, University of Southern California
| | - Kekoa Taparra
- Department of Radiation Oncology, Stanford University, Palo Alto, California
| | | | - Fei Chen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Charleston W K Chiang
- Department of Quantitative and Computational Biology, University of Southern California
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
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Zhang BL, Chen W, Wang Z, Pang W, Luo MT, Wang S, Shao Y, He WQ, Deng Y, Zhou L, Chen J, Yang MM, Wu Y, Wang L, Fernández-Bellon H, Molloy S, Meunier H, Wanert F, Kuderna L, Marques-Bonet T, Roos C, Qi XG, Li M, Liu Z, Schierup MH, Cooper DN, Liu J, Zheng YT, Zhang G, Wu DD. Comparative genomics reveals the hybrid origin of a macaque group. SCIENCE ADVANCES 2023; 9:eadd3580. [PMID: 37262187 PMCID: PMC10413639 DOI: 10.1126/sciadv.add3580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 01/25/2023] [Indexed: 06/03/2023]
Abstract
Although species can arise through hybridization, compelling evidence for hybrid speciation has been reported only rarely in animals. Here, we present phylogenomic analyses on genomes from 12 macaque species and show that the fascicularis group originated from an ancient hybridization between the sinica and silenus groups ~3.45 to 3.56 million years ago. The X chromosomes and low-recombination regions exhibited equal contributions from each parental lineage, suggesting that they were less affected by subsequent backcrossing and hence could have played an important role in maintaining hybrid integrity. We identified many reproduction-associated genes that could have contributed to the development of the mixed sexual phenotypes characteristic of the fascicularis group. The phylogeny within the silenus group was also resolved, and functional experimentation confirmed that all extant Western silenus species are susceptible to HIV-1 infection. Our study provides novel insights into macaque evolution and reveals a hybrid speciation event that has occurred only very rarely in primates.
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Affiliation(s)
- Bao-Lin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Wu Chen
- Guangzhou Zoo and Guangzhou Wildlife Research Center, Guangzhou 510070, China
| | - Zefu Wang
- Key Laboratory for Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China
- Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Wei Pang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Meng-Ting Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Yong Shao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Wen-Qiang He
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Yuan Deng
- BGI-Shenzhen, Shenzhen 518083, China
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen DK-2100, Denmark
| | - Long Zhou
- Center for Evolutionary and Organismal Biology and Women’s Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
| | | | - Min-Min Yang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Yajiang Wu
- Guangzhou Zoo and Guangzhou Wildlife Research Center, Guangzhou 510070, China
| | - Lu Wang
- Shaanxi Key Laboratory for Animal Conservation, College of Life Sciences, Northwest University, Xi’an, China
| | | | | | - Hélène Meunier
- Centre de Primatologie, de l'Université de Strasbourg, Niederhausbergen, France
- Laboratoire de Neurosciences Cognitives et Adaptatives, UMR 7364, Université de Strasbourg, Strasbourg, France
| | - Fanélie Wanert
- Plateforme SILABE, Université de Strasbourg, Niederhausbergen, France
| | - Lukas Kuderna
- Genome Interpretation Department, Illumina Inc., Foster City, CA, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, Barcelona 08003, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, Barcelona 08010, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, Barcelona 08028, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Christian Roos
- Primate Genetics Laboratory, German Primate Center, Göttingen, Germany
- Gene Bank of Primates, German Primate Center, Göttingen, Germany
| | - Xiao-Guang Qi
- Shaanxi Key Laboratory for Animal Conservation, College of Life Sciences, Northwest University, Xi’an, China
| | - Ming Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhijin Liu
- College of Life Sciences, Capital Normal University, Beijing 100048, China
| | | | - David N. Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Jianquan Liu
- Key Laboratory for Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China
- State Key Laboratory of Grassland Agro-ecosystem, Institute of Innovation Ecology and College of Life Sciences, Lanzhou University, Lanzhou 730000, China
| | - Yong-Tang Zheng
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Center for Evolutionary and Organismal Biology and Women’s Hospital at Zhejiang University School of Medicine, Hangzhou 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou 311121, China
- Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
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Wall JD, Robinson JA, Cox LA. High-Resolution Estimates of Crossover and Noncrossover Recombination from a Captive Baboon Colony. Genome Biol Evol 2022; 14:evac040. [PMID: 35325119 PMCID: PMC9048888 DOI: 10.1093/gbe/evac040] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/02/2022] [Indexed: 11/17/2022] Open
Abstract
Homologous recombination has been extensively studied in humans and a handful of model organisms. Much less is known about recombination in other species, including nonhuman primates. Here, we present a study of crossovers (COs) and noncrossover (NCO) recombination in olive baboons (Papio anubis) from two pedigrees containing a total of 20 paternal and 17 maternal meioses, and compare these results to linkage disequilibrium (LD) based recombination estimates from 36 unrelated olive baboons. We demonstrate how COs, combined with LD-based recombination estimates, can be used to identify genome assembly errors. We also quantify sex-specific differences in recombination rates, including elevated male CO and reduced female CO rates near telomeres. Finally, we add to the increasing body of evidence suggesting that while most NCO recombination tracts in mammals are short (e.g., <500 bp), there is a non-negligible fraction of longer (e.g., >1 kb) NCO tracts. For NCO tracts shorter than 10 kb, we fit a mixture of two (truncated) geometric distributions model to the NCO tract length distribution and estimate that >99% of all NCO tracts are very short (mean 24 bp), but the remaining tracts can be quite long (mean 4.3 kb). A single geometric distribution model for NCO tract lengths is incompatible with the data, suggesting that LD-based methods for estimating NCO recombination rates that make this assumption may need to be modified.
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Affiliation(s)
- Jeffrey D. Wall
- Institute for Human Genetics, University of California San Francisco, USA
| | | | - Laura A. Cox
- Center for Precision Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, USA
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7
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Genomic resources for rhesus macaques (Macaca mulatta). Mamm Genome 2022; 33:91-99. [PMID: 34999909 PMCID: PMC8742695 DOI: 10.1007/s00335-021-09922-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 09/22/2021] [Indexed: 11/10/2022]
Abstract
Rhesus macaques (Macaca mulatta) are among the most extensively studied of nonhuman primates. This species has been the subject of many investigations concerning basic primate biology and behavior, including studies of social organization, developmental psychology, physiology, endocrinology, and neurodevelopment. Rhesus macaques are also critically important as a nonhuman primate model of human health and disease, including use in studies of infectious diseases, metabolic diseases, aging, and drug or alcohol abuse. Current research addressing fundamental biological and/or applied biomedical questions benefits from various genetic and genomic analyses. As a result, the genome of rhesus macaques has been the subject of more study than most nonhuman primates. This paper briefly discusses a number of information resources that can provide interested researchers with access to genetic and genomic data describing the content of the rhesus macaque genome, available information regarding genetic variation within the species, results from studies of gene expression, and other aspects of genomic analysis. Specific online databases are discussed, including the US National Center for Biotechnology Information, the University of California Santa Cruz genome browser, Ensembl genome browser, the Macaque Genotype and Phenotype database (mGAP), Rhesusbase, and others.
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