1
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Boitard S, Liaubet L, Paris C, Fève K, Dehais P, Bouquet A, Riquet J, Mercat MJ. Whole-genome sequencing of cryopreserved resources from French Large White pigs at two distinct sampling times reveals strong signatures of convergent and divergent selection between the dam and sire lines. Genet Sel Evol 2023; 55:13. [PMID: 36864379 PMCID: PMC9979506 DOI: 10.1186/s12711-023-00789-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 02/15/2023] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND Numerous genomic scans for positive selection have been performed in livestock species within the last decade, but often a detailed characterization of the detected regions (gene or trait under selection, timing of selection events) is lacking. Cryopreserved resources stored in reproductive or DNA gene banks offer a great opportunity to improve this characterization by providing direct access to recent allele frequency dynamics, thereby differentiating between signatures from recent breeding objectives and those related to more ancient selection constraints. Improved characterization can also be achieved by using next-generation sequencing data, which helps narrowing the size of the detected regions while reducing the number of associated candidate genes. METHODS We estimated genetic diversity and detected signatures of recent selection in French Large White pigs by sequencing the genomes of 36 animals from three distinct cryopreserved samples: two recent samples from dam (LWD) and sire (LWS) lines, which had diverged from 1995 and were selected under partly different objectives, and an older sample from 1977 prior to the divergence. RESULTS French LWD and LWS lines have lost approximately 5% of the SNPs that segregated in the 1977 ancestral population. Thirty-eight genomic regions under recent selection were detected in these lines and the corresponding selection events were further classified as convergent between lines (18 regions), divergent between lines (10 regions), specific to the dam line (6 regions) or specific to the sire line (4 regions). Several biological functions were found to be significantly enriched among the genes included in these regions: body size, body weight and growth regardless of the category, early life survival and calcium metabolism more specifically in the signatures in the dam line and lipid and glycogen metabolism more specifically in the signatures in the sire line. Recent selection on IGF2 was confirmed and several other regions were linked to a single candidate gene (ARHGAP10, BMPR1B, GNA14, KATNA1, LPIN1, PKP1, PTH, SEMA3E or ZC3HAV1, among others). CONCLUSIONS These results illustrate that sequencing the genome of animals at several recent time points generates considerable insight into the traits, genes and variants under recent selection in a population. This approach could be applied to other livestock populations, e.g. by exploiting the rich biological resources stored in cryobanks.
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Affiliation(s)
- Simon Boitard
- CBGP, CIRAD, INRAE, Institut Agro, IRD, Université de Montpellier, Montferrier-sur-Lez, France. .,GenPhySE, INRAE, INP, Université de Toulouse, Castanet-Tolosan, France.
| | - Laurence Liaubet
- grid.507621.7GenPhySE, INRAE, INP, Université de Toulouse, Castanet-Tolosan, France
| | - Cyriel Paris
- grid.507621.7GenPhySE, INRAE, INP, Université de Toulouse, Castanet-Tolosan, France
| | - Katia Fève
- grid.507621.7GenPhySE, INRAE, INP, Université de Toulouse, Castanet-Tolosan, France
| | - Patrice Dehais
- grid.507621.7GenPhySE, INRAE, INP, Université de Toulouse, Castanet-Tolosan, France
| | - Alban Bouquet
- IFIP Institut du porc/Alliance R & D, Le Rheu, France
| | - Juliette Riquet
- grid.507621.7GenPhySE, INRAE, INP, Université de Toulouse, Castanet-Tolosan, France
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2
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Vecchyo DOD, Lohmueller KE, Novembre J. Haplotype-based inference of the distribution of fitness effects. Genetics 2022; 220:6501446. [PMID: 35100400 PMCID: PMC8982047 DOI: 10.1093/genetics/iyac002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 12/18/2021] [Indexed: 11/13/2022] Open
Abstract
Abstract
Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.
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Affiliation(s)
- Diego Ortega-Del Vecchyo
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, 76230, México
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - Kirk E Lohmueller
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, Illinois, 60637, United States of America
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, 60637, United States of America
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3
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Boitard S, Paris C, Sevane N, Servin B, Bazi-Kabbaj K, Dunner S. Gene Banks as Reservoirs to Detect Recent Selection: The Example of the Asturiana de los Valles Bovine Breed. Front Genet 2021; 12:575405. [PMID: 33633776 PMCID: PMC7901938 DOI: 10.3389/fgene.2021.575405] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 01/05/2021] [Indexed: 11/13/2022] Open
Abstract
Gene banks, framed within the efforts for conserving animal genetic resources to ensure the adaptability of livestock production systems to population growth, income, and climate change challenges, have emerged as invaluable resources for biodiversity and scientific research. Allele frequency trajectories over the few last generations contain rich information about the selection history of populations, which cannot be obtained from classical selection scan approaches based on present time data only. Here we apply a new statistical approach taking advantage of genomic time series and a state of the art statistic (nSL) based on present time data to disentangle both old and recent signatures of selection in the Asturiana de los Valles cattle breed. This local Spanish originally multipurpose breed native to Asturias has been selected for beef production over the last few generations. With the use of SNP chip and whole-genome sequencing (WGS) data, we detect candidate regions under selection reflecting the effort of breeders to produce economically valuable beef individuals, e.g., by improving carcass and meat traits with genes such as MSTN, FLRT2, CRABP2, ZNF215, RBPMS2, OAZ2, or ZNF609, while maintaining the ability to thrive under a semi-intensive production system, with the selection of immune (GIMAP7, GIMAP4, GIMAP8, and TICAM1) or olfactory receptor (OR2D2, OR2D3, OR10A4, and 0R6A2) genes. This kind of information will allow us to take advantage of the invaluable resources provided by gene bank collections from local less competitive breeds, enabling the livestock industry to exploit the different mechanisms fine-tuned by natural and human-driven selection on different populations to improve productivity.
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Affiliation(s)
- Simon Boitard
- GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet-Tolosan, France
| | - Cyriel Paris
- GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet-Tolosan, France
| | - Natalia Sevane
- Dpto. Animal Production, Facultad de Veterinaria, Universidad Complutense de Madrid, Madrid, Spain
| | - Bertrand Servin
- GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet-Tolosan, France
| | - Kenza Bazi-Kabbaj
- GABI, INRAE, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France.,SIGENAE, INRA, Jouy-en-Josas, France
| | - Susana Dunner
- Dpto. Animal Production, Facultad de Veterinaria, Universidad Complutense de Madrid, Madrid, Spain
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4
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Platt A, Pivirotto A, Knoblauch J, Hey J. An estimator of first coalescent time reveals selection on young variants and large heterogeneity in rare allele ages among human populations. PLoS Genet 2019; 15:e1008340. [PMID: 31425500 PMCID: PMC6715256 DOI: 10.1371/journal.pgen.1008340] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 08/29/2019] [Accepted: 08/01/2019] [Indexed: 11/18/2022] Open
Abstract
Allele age has long been a focus of population genetic research, primarily because it can be an important clue to the fitness effects of an allele. By virtue of their effects on fitness, alleles under directional selection are expected to be younger than neutral alleles of the same frequency. We developed a new coalescent-based estimator of a close proxy for allele age, the time when a copy of an allele first shares common ancestry with other chromosomes in a sample not carrying that allele. The estimator performs well, including for the very rarest of alleles that occur just once in a sample, with a bias that is typically negative. The estimator is mostly insensitive to population demography and to factors that can arise in population genomic pipelines, including the statistical phasing of chromosomes. Applications to 1000 Genomes Data and UK10K genome data confirm predictions that singleton alleles that alter proteins are significantly younger than those that do not, with a greater difference in the larger UK10K dataset, as expected. The 1000 Genomes populations varied markedly in their distributions for singleton allele ages, suggesting that these distributions can be used to inform models of demographic history, including recent events that are only revealed by their impacts on the ages of very rare alleles.
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Affiliation(s)
- Alexander Platt
- Center for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America
| | - Alyssa Pivirotto
- Center for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America
| | - Jared Knoblauch
- Center for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America
| | - Jody Hey
- Center for Computational Genetics and Genomics, Dept. Biology, Temple University, Philadelphia, Pennsylvania, United States of America
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5
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Edge MD, Coop G. Reconstructing the History of Polygenic Scores Using Coalescent Trees. Genetics 2019; 211:235-262. [PMID: 30389808 PMCID: PMC6325695 DOI: 10.1534/genetics.118.301687] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 10/23/2018] [Indexed: 11/18/2022] Open
Abstract
Genome-wide association studies (GWAS) have revealed that many traits are highly polygenic, in that their within-population variance is governed, in part, by small-effect variants at many genetic loci. Standard population-genetic methods for inferring evolutionary history are ill-suited for polygenic traits: when there are many variants of small effect, signatures of natural selection are spread across the genome and are subtle at any one locus. In the last several years, various methods have emerged for detecting the action of natural selection on polygenic scores, sums of genotypes weighted by GWAS effect sizes. However, most existing methods do not reveal the timing or strength of selection. Here, we present a set of methods for estimating the historical time course of a population-mean polygenic score using local coalescent trees at GWAS loci. These time courses are estimated by using coalescent theory to relate the branch lengths of trees to allele-frequency change. The resulting time course can be tested for evidence of natural selection. We present theory and simulations supporting our procedures, as well as estimated time courses of polygenic scores for human height. Because of its grounding in coalescent theory, the framework presented here can be extended to a variety of demographic scenarios, and its usefulness will increase as both GWAS and ancestral-recombination-graph inference continue to progress.
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Affiliation(s)
- Michael D Edge
- Center for Population Biology, Department of Evolution and Ecology, University of California, Davis, California 95616
| | - Graham Coop
- Center for Population Biology, Department of Evolution and Ecology, University of California, Davis, California 95616
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6
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Corbett S, Courtiol A, Lummaa V, Moorad J, Stearns S. The transition to modernity and chronic disease: mismatch and natural selection. Nat Rev Genet 2018; 19:419-430. [DOI: 10.1038/s41576-018-0012-3] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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7
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Abstract
The haplotypes of a beneficial allele carry information about its history that can shed light on its age and the putative cause for its increase in frequency. Specifically, the signature of an allele's age is contained in the pattern of variation that mutation and recombination impose on its haplotypic background. We provide a method to exploit this pattern and infer the time to the common ancestor of a positively selected allele following a rapid increase in frequency. We do so using a hidden Markov model which leverages the length distribution of the shared ancestral haplotype, the accumulation of derived mutations on the ancestral background, and the surrounding background haplotype diversity. Using simulations, we demonstrate how the inclusion of information from both mutation and recombination events increases accuracy relative to approaches that only consider a single type of event. We also show the behavior of the estimator in cases where data do not conform to model assumptions, and provide some diagnostics for assessing and improving inference. Using the method, we analyze population-specific patterns in the 1000 Genomes Project data to estimate the timing of adaptation for several variants which show evidence of recent selection and functional relevance to diet, skin pigmentation, and morphology in humans.
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Affiliation(s)
- Joel Smith
- Department of Ecology and Evolution, University of Chicago, Chicago, IL
| | - Graham Coop
- Center for Population Biology, Department of Evolution and Ecology, University of California, Davis, Davis, CA
| | - Matthew Stephens
- Department of Human Genetics, University of Chicago, Chicago, IL
- Department of Statistics, University of Chicago, Chicago, IL
| | - John Novembre
- Department of Ecology and Evolution, University of Chicago, Chicago, IL
- Department of Human Genetics, University of Chicago, Chicago, IL
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8
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Villanueva‐Cañas JL, Rech GE, Cara MAR, González J. Beyond
SNP
s: how to detect selection on transposable element insertions. Methods Ecol Evol 2017. [DOI: 10.1111/2041-210x.12781] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
| | - Gabriel E. Rech
- Institute of Evolutionary Biology (CSIC‐Universitat Pompeu Fabra) Barcelona Spain
| | - Maria Angeles Rodriguez Cara
- Ecoanthropology and Ethnobiology Laboratory, UMR 7206, CNRS/MNHN/Universite Paris 7 Museum National d'HistoireNaturelle F‐75116 Paris France
| | - Josefa González
- Institute of Evolutionary Biology (CSIC‐Universitat Pompeu Fabra) Barcelona Spain
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9
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Dharmayanthi AB, Terai Y, Sulandari S, Zein MSA, Akiyama T, Satta Y. The origin and evolution of fibromelanosis in domesticated chickens: Genomic comparison of Indonesian Cemani and Chinese Silkie breeds. PLoS One 2017; 12:e0173147. [PMID: 28379963 PMCID: PMC5381777 DOI: 10.1371/journal.pone.0173147] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2016] [Accepted: 02/15/2017] [Indexed: 12/30/2022] Open
Abstract
Like Chinese Silkie, Indonesian Ayam Cemani exhibits fibromelanosis or dermal hyperpigmentation and possesses complex segmental duplications on chromosome 20 that involve the endothelin 3 gene, EDN3. A genomic region, DR1 of 127 kb, together with another region, DR2 of 171 kb, was duplicated by unequal crossing over, accompanied by inversion of one DR2. Quantitative PCR and copy number variation analyses on the Cemani genome sequence confirmed the duplication of EDN3. These genetic arrangements are identical in Cemani and Silkie, indicating a single origin of the genetic cause of Fm. The two DR1s harbor two distinct EDN3 haplotypes in a form of permanent heterozygosity, although they remain allelic in the ancestral Red Jungle Fowl population and some domesticated chicken breeds, with their allelic divergence time being as recent as 0.3 million years ago. In Cemani and Silkie breeds, artificial selection favoring the Fm phenotype has left an unambiguous record for selective sweep that extends in both directions from tandemly duplicated EDN3 loci. This highly homozygous tract is different in length between Cemani and Silkie, reflecting their distinct breeding histories. It is estimated that the Fm phenotype came into existence at least 6600-9100 years ago, prior to domestication of Cemani and Silkie, and that throughout domestication there has been intense artificial selection with strength s > 50% in each breed.
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Affiliation(s)
- Anik Budhi Dharmayanthi
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Kanagawa, Japan
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Indonesia
| | - Yohei Terai
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Kanagawa, Japan
| | - Sri Sulandari
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Indonesia
| | - M. Syamsul Arifin Zein
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Indonesia
| | | | - Yoko Satta
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Kanagawa, Japan
- * E-mail:
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10
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Bayesian Inference of Natural Selection from Allele Frequency Time Series. Genetics 2016; 203:493-511. [PMID: 27010022 DOI: 10.1534/genetics.116.187278] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 03/11/2016] [Indexed: 12/21/2022] Open
Abstract
The advent of accessible ancient DNA technology now allows the direct ascertainment of allele frequencies in ancestral populations, thereby enabling the use of allele frequency time series to detect and estimate natural selection. Such direct observations of allele frequency dynamics are expected to be more powerful than inferences made using patterns of linked neutral variation obtained from modern individuals. We developed a Bayesian method to make use of allele frequency time series data and infer the parameters of general diploid selection, along with allele age, in nonequilibrium populations. We introduce a novel path augmentation approach, in which we use Markov chain Monte Carlo to integrate over the space of allele frequency trajectories consistent with the observed data. Using simulations, we show that this approach has good power to estimate selection coefficients and allele age. Moreover, when applying our approach to data on horse coat color, we find that ignoring a relevant demographic history can significantly bias the results of inference. Our approach is made available in a C++ software package.
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11
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Thurman TJ, Barrett RDH. The genetic consequences of selection in natural populations. Mol Ecol 2016; 25:1429-48. [DOI: 10.1111/mec.13559] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2015] [Revised: 12/21/2015] [Accepted: 01/27/2016] [Indexed: 01/06/2023]
Affiliation(s)
- Timothy J. Thurman
- Redpath Museum and Department of Biology; McGill University; Sherbrooke Street West Montreal Quebec Canada H3A 1B1 Canada
- Smithsonian Tropical Research Institute; Panamá Panamá
| | - Rowan D. H. Barrett
- Redpath Museum and Department of Biology; McGill University; Sherbrooke Street West Montreal Quebec Canada H3A 1B1 Canada
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12
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Yang Z, Zhong H, Chen J, Zhang X, Zhang H, Luo X, Xu S, Chen H, Lu D, Han Y, Li J, Fu L, Qi X, Peng Y, Xiang K, Lin Q, Guo Y, Li M, Cao X, Zhang Y, Liao S, Peng Y, Zhang L, Guo X, Dong S, Liang F, Wang J, Willden A, Seang Aun H, Serey B, Sovannary T, Bunnath L, Samnom H, Mardon G, Li Q, Meng A, Shi H, Su B. A Genetic Mechanism for Convergent Skin Lightening during Recent Human Evolution. Mol Biol Evol 2016; 33:1177-87. [PMID: 26744415 PMCID: PMC4839214 DOI: 10.1093/molbev/msw003] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Skin lightening among Eurasians is thought to have been a convergence occurring independently in Europe and East Asia as an adaptation to high latitude environments. Among Europeans, several genes responsible for such lightening have been found, but the information available for East Asians is much more limited. Here, a genome-wide comparison between dark-skinned Africans and Austro-Asiatic speaking aborigines and light-skinned northern Han Chinese identified the pigmentation gene OCA2, showing unusually deep allelic divergence between these groups. An amino acid substitution (His615Arg) of OCA2 prevalent in most East Asian populations—but absent in Africans and Europeans—was significantly associated with skin lightening among northern Han Chinese. Further transgenic and targeted gene modification analyses of zebrafish and mouse both exhibited the phenotypic effect of the OCA2 variant manifesting decreased melanin production. These results indicate that OCA2 plays an important role in the convergent skin lightening of East Asians during recent human evolution.
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Affiliation(s)
- Zhaohui Yang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, China Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Hua Zhong
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX
| | - Jing Chen
- State Key Laboratory of Membrane Biology, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, China
| | - Xiaoming Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Hui Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xin Luo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Shuhua Xu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society (CAS-MPG) Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Hua Chen
- Center for Computational Genomics, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Dongsheng Lu
- Max Planck Independent Research Group on Population Genomics, Chinese Academy of Sciences and Max Planck Society (CAS-MPG) Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yinglun Han
- College of Life Science, Liaoning Normal University, Dalian, China
| | - Jinkun Li
- Department of Urology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Lijie Fu
- Department of Urology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xuebin Qi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yi Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Kun Xiang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Qiang Lin
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Yan Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Ming Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xiangyu Cao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yanfeng Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Shiyu Liao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yingmei Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Lin Zhang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, China
| | - Xiaosen Guo
- BGI-Shenzhen, Shenzhen, China Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Jun Wang
- BGI-Shenzhen, Shenzhen, China Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Andrew Willden
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Hong Seang Aun
- Geography and Land Management, Royal University of Phnom Penh, Phnom Penh, Kingdom of Cambodia
| | - Bun Serey
- Geography and Land Management, Royal University of Phnom Penh, Phnom Penh, Kingdom of Cambodia
| | - Tuot Sovannary
- Geography and Land Management, Royal University of Phnom Penh, Phnom Penh, Kingdom of Cambodia
| | - Long Bunnath
- Geography and Land Management, Royal University of Phnom Penh, Phnom Penh, Kingdom of Cambodia
| | - Ham Samnom
- Capacity Development Facilitator for Handicap International Federation and Freelance Researcher, Battambang, Kingdom of Cambodia
| | - Graeme Mardon
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX
| | - Qingwei Li
- College of Life Science, Liaoning Normal University, Dalian, China
| | - Anming Meng
- State Key Laboratory of Membrane Biology, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, China
| | - Hong Shi
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
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13
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Ormond L, Foll M, Ewing GB, Pfeifer SP, Jensen JD. Inferring the age of a fixed beneficial allele. Mol Ecol 2016; 25:157-69. [PMID: 26576754 DOI: 10.1111/mec.13478] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 10/14/2015] [Accepted: 11/09/2015] [Indexed: 12/28/2022]
Abstract
Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype-based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian-based approach that rather estimates these parameters for fixed beneficial mutations in single populations. We integrate a range of existing diversity, site frequency spectrum, haplotype- and linkage disequilibrium-based summary statistics. We show that for strong selective sweeps on de novo mutations the method can estimate allele age and selection strength even in nonequilibrium demographic scenarios. We extend our approach to models of selection on standing variation, and co-infer the frequency at which selection began to act upon the mutation. Finally, we apply our method to estimate the age and selection strength of a previously identified mutation underpinning cryptic colour adaptation in a wild deer mouse population, and compare our findings with previously published estimates as well as with geological data pertaining to the presumed shift in selective pressure.
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Affiliation(s)
- Louise Ormond
- School of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Matthieu Foll
- School of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
- International Agency for Research on Cancer (IARC), Lyon, France
| | - Gregory B Ewing
- School of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Susanne P Pfeifer
- School of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Jeffrey D Jensen
- School of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
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14
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Manel S, Perrier C, Pratlong M, Abi-Rached L, Paganini J, Pontarotti P, Aurelle D. Genomic resources and their influence on the detection of the signal of positive selection in genome scans. Mol Ecol 2015; 25:170-84. [DOI: 10.1111/mec.13468] [Citation(s) in RCA: 64] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Revised: 11/06/2015] [Accepted: 11/07/2015] [Indexed: 12/16/2022]
Affiliation(s)
- S. Manel
- CEFE UMR 5175; CNRS - Université de Montpellier - Université Paul-Valéry Montpellier -EPHE; laboratoire Biogéographie et écologie des vertébrés; 1919 route de Mende 34293 Montpellier Cedex 5 France
| | - C. Perrier
- CEFE UMR 5175; CNRS - Université de Montpellier - Université Paul-Valéry Montpellier -EPHE; laboratoire Biogéographie et écologie des vertébrés; 1919 route de Mende 34293 Montpellier Cedex 5 France
| | - M. Pratlong
- Aix Marseille Université; CNRS; IRD; Avignon Université, IMBE UMR 7263; Station Marine d'Endoume, 13007; Marseille France
- Aix Marseille Université; CNRS; Centrale Marseille; I2M UMR 7373; Evolution Biologique Modélisation; 3 Place Victor Hugo, 13331 Marseille Cedex Case 19 France
| | - L. Abi-Rached
- Equipe ATIP; URMITE UM 63 CNRS 7278 IRD 198 Inserm U1095; IHU Méditerranée Infection; Aix-Marseille Université; 27 Boulevard Jean Moulin, 13385 Marseille Cedex 05 France
| | - J. Paganini
- XEGEN SAS; 15 Rue de la République 13420 Gemenos France
| | - P. Pontarotti
- Aix Marseille Université; CNRS; Centrale Marseille; I2M UMR 7373; Evolution Biologique Modélisation; 3 Place Victor Hugo, 13331 Marseille Cedex Case 19 France
| | - D. Aurelle
- Aix Marseille Université; CNRS; IRD; Avignon Université, IMBE UMR 7263; Station Marine d'Endoume, 13007; Marseille France
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15
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Chen H. Population genetic studies in the genomic sequencing era. DONG WU XUE YAN JIU = ZOOLOGICAL RESEARCH 2015; 36:223-32. [PMID: 26228473 DOI: 10.13918/j.issn.2095-8137.2015.4.223] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
Recent advances in high-throughput sequencing technologies have revolutionized the field of population genetics. Data now routinely contain genomic level polymorphism information, and the low cost of DNA sequencing enables researchers to investigate tens of thousands of subjects at a time. This provides an unprecedented opportunity to address fundamental evolutionary questions, while posing challenges on traditional population genetic theories and methods. This review provides an overview of the recent methodological developments in the field of population genetics, specifically methods used to infer ancient population history and investigate natural selection using large-sample, large-scale genetic data. Several open questions are also discussed at the end of the review.
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Affiliation(s)
- Hua Chen
- Center for Computational Genomics, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101,
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16
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Schlebusch CM, Gattepaille LM, Engström K, Vahter M, Jakobsson M, Broberg K. Human adaptation to arsenic-rich environments. Mol Biol Evol 2015; 32:1544-55. [PMID: 25739736 DOI: 10.1093/molbev/msv046] [Citation(s) in RCA: 94] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Adaptation drives genomic changes; however, evidence of specific adaptations in humans remains limited. We found that inhabitants of the northern Argentinean Andes, an arid region where elevated arsenic concentrations in available drinking water is common, have unique arsenic metabolism, with efficient methylation and excretion of the major metabolite dimethylated arsenic and a less excretion of the highly toxic monomethylated metabolite. We genotyped women from this population for 4,301,332 single nucleotide polymorphisms (SNPs) and found a strong association between the AS3MT (arsenic [+3 oxidation state] methyltransferase) gene and mono- and dimethylated arsenic in urine, suggesting that AS3MT functions as the major gene for arsenic metabolism in humans. We found strong genetic differentiation around AS3MT in the Argentinean Andes population, compared with a highly related Peruvian population (FST = 0.014) from a region with much less environmental arsenic. Also, 13 of the 100 SNPs with the highest genome-wide Locus-Specific Branch Length occurred near AS3MT. In addition, our examination of extended haplotype homozygosity indicated a selective sweep of the Argentinean Andes population, in contrast to Peruvian and Colombian populations. Our data show that adaptation to tolerate the environmental stressor arsenic has likely driven an increase in the frequencies of protective variants of AS3MT, providing the first evidence of human adaptation to a toxic chemical.
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Affiliation(s)
- Carina M Schlebusch
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Lucie M Gattepaille
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Karin Engström
- Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden
| | - Marie Vahter
- Unit of Metals and Health, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Mattias Jakobsson
- Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Karin Broberg
- Unit of Metals and Health, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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17
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Chen H, Hey J, Slatkin M. A hidden Markov model for investigating recent positive selection through haplotype structure. Theor Popul Biol 2015; 99:18-30. [PMID: 25446961 PMCID: PMC4277924 DOI: 10.1016/j.tpb.2014.11.001] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2013] [Revised: 10/24/2014] [Accepted: 11/04/2014] [Indexed: 12/17/2022]
Abstract
Recent positive selection can increase the frequency of an advantageous mutant rapidly enough that a relatively long ancestral haplotype will be remained intact around it. We present a hidden Markov model (HMM) to identify such haplotype structures. With HMM identified haplotype structures, a population genetic model for the extent of ancestral haplotypes is then adopted for parameter inference of the selection intensity and the allele age. Simulations show that this method can detect selection under a wide range of conditions and has higher power than the existing frequency spectrum-based method. In addition, it provides good estimate of the selection coefficients and allele ages for strong selection. The method analyzes large data sets in a reasonable amount of running time. This method is applied to HapMap III data for a genome scan, and identifies a list of candidate regions putatively under recent positive selection. It is also applied to several genes known to be under recent positive selection, including the LCT, KITLG and TYRP1 genes in Northern Europeans, and OCA2 in East Asians, to estimate their allele ages and selection coefficients.
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Affiliation(s)
- Hua Chen
- Center for Computational Genomics, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; Center for Computational Genetics and Genomics, Temple University, Philadelphia PA 19122, United States.
| | - Jody Hey
- Center for Computational Genetics and Genomics, Temple University, Philadelphia PA 19122, United States.
| | - Montgomery Slatkin
- Department of Integrative Biology, University of California, Berkeley, CA 94720, United States.
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18
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López S, García Ó, Yurrebaso I, Flores C, Acosta-Herrera M, Chen H, Gardeazabal J, Careaga JM, Boyano MD, Sánchez A, Ratón-Nieto JA, Sevilla A, Smith-Zubiaga I, de Galdeano AG, Martinez-Cadenas C, Izagirre N, de la Rúa C, Alonso S. The interplay between natural selection and susceptibility to melanoma on allele 374F of SLC45A2 gene in a South European population. PLoS One 2014; 9:e104367. [PMID: 25093503 PMCID: PMC4122405 DOI: 10.1371/journal.pone.0104367] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2014] [Accepted: 07/08/2014] [Indexed: 11/18/2022] Open
Abstract
We aimed to study the selective pressures interacting on SLC45A2 to investigate the interplay between selection and susceptibility to disease. Thus, we enrolled 500 volunteers from a geographically limited population (Basques from the North of Spain) and by resequencing the whole coding region and intron 5 of the 34 most and the 34 least pigmented individuals according to the reflectance distribution, we observed that the polymorphism Leu374Phe (L374F, rs16891982) was statistically associated with skin color variability within this sample. In particular, allele 374F was significantly more frequent among the individuals with lighter skin. Further genotyping an independent set of 558 individuals of a geographically wider population with known ancestry in the Spanish population also revealed that the frequency of L374F was significantly correlated with the incident UV radiation intensity. Selection tests suggest that allele 374F is being positively selected in South Europeans, thus indicating that depigmentation is an adaptive process. Interestingly, by genotyping 119 melanoma samples, we show that this variant is also associated with an increased susceptibility to melanoma in our populations. The ultimate driving force for this adaptation is unknown, but it is compatible with the vitamin D hypothesis. This shows that molecular evolution analysis can be used as a useful technology to predict phenotypic and biomedical consequences in humans.
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Affiliation(s)
- Saioa López
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
| | - Óscar García
- Ertzaintza Forensic Unit, Erandio, Bizkaia, Spain
| | | | - Carlos Flores
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario N.S. de Candelaria, Tenerife, Spain
- Applied Genomics Group (G2A), Genetics Laboratory, Instituto Universitario de Enfermedades Tropicales y Salud Pública de Canarias, Universidad de La Laguna, Tenerife, Spain
| | - Marialbert Acosta-Herrera
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario N.S. de Candelaria, Tenerife, Spain
- Research Unit, Universitary Hospital Dr. Negrin, Las Palmas de Gran Canaria, Spain
| | - Hua Chen
- Center for Computational Genetics and Genomics, Temple University, Philadelphia, Pennsylvania, United States of America
| | - Jesús Gardeazabal
- Dermatology Service, BioCruces Health Research Institute, Cruces University Hospital, Cruces-Barakaldo, Bizkaia, Spain
| | - Jesús María Careaga
- Dermatology Service, BioCruces Health Research Institute, Basurto University Hospital, Bilbao, Bizkaia, Spain
| | - María Dolores Boyano
- Department of Cell Biology and Histology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
| | - Ana Sánchez
- Dermatology Service, BioCruces Health Research Institute, Basurto University Hospital, Bilbao, Bizkaia, Spain
| | - Juan Antonio Ratón-Nieto
- Dermatology Service, BioCruces Health Research Institute, Cruces University Hospital, Cruces-Barakaldo, Bizkaia, Spain
| | - Arrate Sevilla
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
| | - Isabel Smith-Zubiaga
- Department of Zoology and Animal Cell Biology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
| | - Alicia García de Galdeano
- Department of Cell Biology and Histology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
| | | | - Neskuts Izagirre
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
| | - Concepción de la Rúa
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
| | - Santos Alonso
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
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