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Williams MP, Flegontov P, Maier R, Huber CD. Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA. Genetics 2024; 228:iyae110. [PMID: 39013011 PMCID: PMC11373510 DOI: 10.1093/genetics/iyae110] [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: 04/08/2024] [Revised: 04/08/2024] [Accepted: 06/11/2024] [Indexed: 07/18/2024] Open
Abstract
Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches-firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes-and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while complex gene flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible among a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.
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Affiliation(s)
- Matthew P Williams
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Pavel Flegontov
- Department of Biology and Ecology, University of Ostrava, Ostrava 701 03, Czechia
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Robert Maier
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Christian D Huber
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
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2
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Cádiz MI, Tengstedt ANB, Sørensen IH, Pedersen ES, Fox AD, Hansen MM. Demographic History and Inbreeding in Two Declining Sea Duck Species Inferred From Whole-Genome Sequence Data. Evol Appl 2024; 17:e70008. [PMID: 39257569 PMCID: PMC11386304 DOI: 10.1111/eva.70008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 08/16/2024] [Accepted: 08/19/2024] [Indexed: 09/12/2024] Open
Abstract
Anthropogenic impact has transitioned from threatening already rare species to causing significant declines in once numerous organisms. Long-tailed duck (Clangula hyemalis) and velvet scoter (Melanitta fusca) were once important quarry sea duck species in NW Europe, but recent declines resulted in their reclassification as vulnerable on the IUCN Red List. We sequenced and assembled genomes for both species and resequenced 15 individuals of each. Using analyses based on site frequency spectra and sequential Markovian coalescence, we found C. hyemalis to show more historical demographic stability, whereas M. fusca was affected particularly by the Last (Weichselian) Glaciation. This likely reflects C. hyemalis breeding continuously across the Arctic, with cycles of glaciation primarily shifting breeding areas south or north without major population declines, whereas the more restricted southern range of M. fusca would lead to significant range contraction during glaciations. Both species showed evidence of declines over the past thousands of years, potentially reflecting anthropogenic pressures with the recent decline indicating an accelerated process. Analysis of runs of homozygosity (ROH) showed low but nontrivial inbreeding, with F ROH from 0.012 to 0.063 in C. hyemalis and ranging from 0 to 0.047 in M. fusca. Lengths of ROH suggested that this was due to ongoing background inbreeding rather than recent declines. Overall, despite demographically important declines, this has not yet led to strong inbreeding and genetic erosion, and the most pressing conservation concern may be the risk of density-dependent (Allee) effects. We recommend monitoring of inbreeding using ROH analysis as a cost-efficient method to track future developments to support effective conservation of these species.
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Affiliation(s)
- María I Cádiz
- Department of Biology Aarhus University Aarhus Denmark
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Diamantidis D, Fan WTL, Birkner M, Wakeley J. Bursts of coalescence within population pedigrees whenever big families occur. Genetics 2024; 227:iyae030. [PMID: 38408329 DOI: 10.1093/genetics/iyae030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 01/23/2024] [Accepted: 02/18/2024] [Indexed: 02/28/2024] Open
Abstract
We consider a simple diploid population-genetic model with potentially high variability of offspring numbers among individuals. Specifically, against a backdrop of Wright-Fisher reproduction and no selection, there is an additional probability that a big family occurs, meaning that a pair of individuals has a number of offspring on the order of the population size. We study how the pedigree of the population generated under this model affects the ancestral genetic process of a sample of size two at a single autosomal locus without recombination. Our population model is of the type for which multiple-merger coalescent processes have been described. We prove that the conditional distribution of the pairwise coalescence time given the random pedigree converges to a limit law as the population size tends to infinity. This limit law may or may not be the usual exponential distribution of the Kingman coalescent, depending on the frequency of big families. But because it includes the number and times of big families, it differs from the usual multiple-merger coalescent models. The usual multiple-merger coalescent models are seen as describing the ancestral process marginal to, or averaging over, the pedigree. In the limiting ancestral process conditional on the pedigree, the intervals between big families can be modeled using the Kingman coalescent but each big family causes a discrete jump in the probability of coalescence. Analogous results should hold for larger samples and other population models. We illustrate these results with simulations and additional analysis, highlighting their implications for inference and understanding of multilocus data.
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Affiliation(s)
| | - Wai-Tong Louis Fan
- Department of Mathematics, Indiana University, Bloomington, IN 47405, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Matthias Birkner
- Institut für Mathematik, Johannes-Gutenberg-Universität, 55099 Mainz, Germany
| | - John Wakeley
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
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Tengstedt ANB, Liu S, Jacobsen MW, Gundlund C, Møller PR, Berg S, Bekkevold D, Hansen MM. Genomic insights on conservation priorities for North Sea houting and European lake whitefish (Coregonus spp.). Mol Ecol 2024:e17367. [PMID: 38686435 DOI: 10.1111/mec.17367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/08/2024] [Accepted: 04/12/2024] [Indexed: 05/02/2024]
Abstract
Population genomics analysis holds great potential for informing conservation of endangered populations. We focused on a controversial case of European whitefish (Coregonus spp.) populations. The endangered North Sea houting is the only coregonid fish that tolerates oceanic salinities and was previously considered a species (C. oxyrhinchus) distinct from European lake whitefish (C. lavaretus). However, no firm evidence for genetic-based salinity adaptation has been available. Also, studies based on microsatellite and mitogenome data suggested surprisingly recent divergence (c. 2500 years bp) between houting and lake whitefish. These data types furthermore have provided no evidence for possible inbreeding. Finally, a controversial taxonomic revision recently classified all whitefish in the region as C. maraena, calling conservation priorities of houting into question. We used whole-genome and ddRAD sequencing to analyse six lake whitefish populations and the only extant indigenous houting population. Demographic inference indicated post-glacial expansion and divergence between lake whitefish and houting occurring not long after the Last Glaciation, implying deeper population histories than previous analyses. Runs of homozygosity analysis suggested not only high inbreeding (FROH up to 30.6%) in some freshwater populations but also FROH up to 10.6% in the houting prompting conservation concerns. Finally, outlier scans provided evidence for adaptation to high salinities in the houting. Applying a framework for defining conservation units based on current and historical reproductive isolation and adaptive divergence led us to recommend that the houting be treated as a separate conservation unit regardless of species status. In total, the results underscore the potential of genomics to inform conservation practices, in this case clarifying conservation units and highlighting populations of concern.
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Affiliation(s)
| | - Shenglin Liu
- Department of Biology, Aarhus University, Aarhus C, Denmark
| | - Magnus W Jacobsen
- National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
| | | | - Peter Rask Møller
- Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
| | - Søren Berg
- National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
| | - Dorte Bekkevold
- National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
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Luo CS, Li TT, Jiang XL, Song Y, Fan TT, Shen XB, Yi R, Ao XP, Xu GB, Deng M. High-quality haplotype-resolved genome assembly for ring-cup oak (Quercus glauca) provides insight into oaks demographic dynamics. Mol Ecol Resour 2024; 24:e13914. [PMID: 38108568 DOI: 10.1111/1755-0998.13914] [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: 08/15/2022] [Revised: 11/15/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023]
Abstract
Quercus section Cyclobalanopsis represents a dominant woody lineage in East Asian evergreen broadleaved forests. Regardless of its ecological and economic importance, little is known about the genomes of species in this unique oak lineage. Quercus glauca is one of the most widespread tree species in the section Cyclobalanopsis. In this study, a high-quality haplotype-resolved reference genome was assembled for Q. glauca from PacBio HiFi and Hi-C reads. The genome size, contig N50, and scaffold N50 measured 902.88, 7.60, and 69.28 Mb, respectively, for haplotype1, and 913.28, 7.20, and 71.53 Mb, respectively, for haplotype2. A total of 37,457 and 38,311 protein-coding genes were predicted in haplotype1 and haplotype2, respectively. Homologous chromosomes in the Q. glauca genome had excellent gene pair collinearity. The number of R-genes in Q. glauca was similar to most East Asian oaks but less than oak species from Europe and America. Abundant structural variation in the Q. glauca genome could contribute to environmental stress tolerance in Q. glauca. Sections Cyclobalanopsis and Cerris diverged in the Oligocene, in agreement with fossil records for section Cyclobalanopsis, which document its presence in East Asia since the early Miocene. The demographic dynamics of closely related oak species were largely similar. The high-quality reference genome provided here for the most widespread species in section Cyclobalanopsis will serve as an essential genomic resource for evolutionary studies of key oak lineages while also supporting studies of interspecific introgression, local adaptation, and speciation in oaks.
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Affiliation(s)
- Chang-Sha Luo
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Tian-Tian Li
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Xiao-Long Jiang
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Ying Song
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Ting-Ting Fan
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Xiang-Bao Shen
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Rong Yi
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Xiao-Ping Ao
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Gang-Biao Xu
- The Laboratory of Forestry Genetics, Central South University of Forestry and Technology, Changsha, Hunan, China
| | - Min Deng
- School of Ecology and Environmental Science, Yunnan University, Kunming, Yunnan, China
- Yunnan Key Laboratory of Plant Reproductive Adaptation and Evolutionary Ecology and Institute of Biodiversity, Yunnan University, Kunming, Yunnan, China
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6
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Gao Y, Zhang X, Chen H, Lu Y, Ma S, Yang Y, Zhang M, Xu S. Reconstructing the ancestral gene pool to uncover the origins and genetic links of Hmong-Mien speakers. BMC Biol 2024; 22:59. [PMID: 38475771 PMCID: PMC10935854 DOI: 10.1186/s12915-024-01838-9] [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: 10/10/2023] [Accepted: 02/01/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Hmong-Mien (HM) speakers are linguistically related and live primarily in China, but little is known about their ancestral origins or the evolutionary mechanism shaping their genomic diversity. In particular, the lack of whole-genome sequencing data on the Yao population has prevented a full investigation of the origins and evolutionary history of HM speakers. As such, their origins are debatable. RESULTS Here, we made a deep sequencing effort of 80 Yao genomes, and our analysis together with 28 East Asian populations and 968 ancient Asian genomes suggested that there is a strong genetic basis for the formation of the HM language family. We estimated that the most recent common ancestor dates to 5800 years ago, while the genetic divergence between the HM and Tai-Kadai speakers was estimated to be 8200 years ago. We proposed that HM speakers originated from the Yangtze River Basin and spread with agricultural civilization. We identified highly differentiated variants between HM and Han Chinese, in particular, a deafness-related missense variant (rs72474224) in the GJB2 gene is in a higher frequency in HM speakers than in others. CONCLUSIONS Our results indicated complex gene flow and medically relevant variants involved in the HM speakers' evolution history.
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Affiliation(s)
- Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xiaoxi Zhang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Sen Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Menghan Zhang
- Institute of Modern Languages and Linguistics, and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, 200433, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.
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Kessler C, Shafer ABA. Genomic Analyses Capture the Human-Induced Demographic Collapse and Recovery in a Wide-Ranging Cervid. Mol Biol Evol 2024; 41:msae038. [PMID: 38378172 PMCID: PMC10917209 DOI: 10.1093/molbev/msae038] [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: 08/15/2023] [Revised: 02/08/2024] [Accepted: 02/14/2024] [Indexed: 02/22/2024] Open
Abstract
The glacial cycles of the Quaternary heavily impacted species through successions of population contractions and expansions. Similarly, populations have been intensely shaped by human pressures such as unregulated hunting and land use changes. White-tailed and mule deer survived in different refugia through the Last Glacial Maximum, and their populations were severely reduced after the European colonization. Here, we analyzed 73 resequenced deer genomes from across their North American range to understand the consequences of climatic and anthropogenic pressures on deer demographic and adaptive history. We found strong signals of climate-induced vicariance and demographic decline; notably, multiple sequentially Markovian coalescent recovers a severe decline in mainland white-tailed deer effective population size (Ne) at the end of the Last Glacial Maximum. We found robust evidence for colonial overharvest in the form of a recent and dramatic drop in Ne in all analyzed populations. Historical census size and restocking data show a clear parallel to historical Ne estimates, and temporal Ne/Nc ratio shows patterns of conservation concern for mule deer. Signatures of selection highlight genes related to temperature, including a cold receptor previously highlighted in woolly mammoth. We also detected immune genes that we surmise reflect the changing land use patterns in North America. Our study provides a detailed picture of anthropogenic and climatic-induced decline in deer diversity and clues to understanding the conservation concerns of mule deer and the successful demographic recovery of white-tailed deer.
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Affiliation(s)
- Camille Kessler
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
| | - Aaron B A Shafer
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
- Department of Forensic Science, Trent University, Peterborough, Ontario, Canada
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8
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Padilla-Iglesias C, Derkx I. Hunter-gatherer genetics research: Importance and avenues. EVOLUTIONARY HUMAN SCIENCES 2024; 6:e15. [PMID: 38516374 PMCID: PMC10955370 DOI: 10.1017/ehs.2024.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 01/17/2024] [Accepted: 02/02/2024] [Indexed: 03/23/2024] Open
Abstract
Major developments in the field of genetics in the past few decades have revolutionised notions of what it means to be human. Although currently only a few populations around the world practise a hunting and gathering lifestyle, this mode of subsistence has characterised members of our species since its very origins and allowed us to migrate across the planet. Therefore, the geographical distribution of hunter-gatherer populations, dependence on local ecosystems and connections to past populations and neighbouring groups have provided unique insights into our evolutionary origins. However, given the vulnerable status of hunter-gatherers worldwide, the development of the field of anthropological genetics requires that we reevaluate how we conduct research with these communities. Here, we review how the inclusion of hunter-gatherer populations in genetics studies has advanced our understanding of human origins, ancient population migrations and interactions as well as phenotypic adaptations and adaptability to different environments, and the important scientific and medical applications of these advancements. At the same time, we highlight the necessity to address yet unresolved questions and identify areas in which the field may benefit from improvements.
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Affiliation(s)
| | - Inez Derkx
- Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
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9
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Lescroart J, Bonilla-Sánchez A, Napolitano C, Buitrago-Torres DL, Ramírez-Chaves HE, Pulido-Santacruz P, Murphy WJ, Svardal H, Eizirik E. Extensive Phylogenomic Discordance and the Complex Evolutionary History of the Neotropical Cat Genus Leopardus. Mol Biol Evol 2023; 40:msad255. [PMID: 37987559 PMCID: PMC10701098 DOI: 10.1093/molbev/msad255] [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: 08/31/2023] [Revised: 11/07/2023] [Accepted: 11/13/2023] [Indexed: 11/22/2023] Open
Abstract
Even in the genomics era, the phylogeny of Neotropical small felids comprised in the genus Leopardus remains contentious. We used whole-genome resequencing data to construct a time-calibrated consensus phylogeny of this group, quantify phylogenomic discordance, test for interspecies introgression, and assess patterns of genetic diversity and demographic history. We infer that the Leopardus radiation started in the Early Pliocene as an initial speciation burst, followed by another in its subgenus Oncifelis during the Early Pleistocene. Our findings challenge the long-held notion that ocelot (Leopardus pardalis) and margay (L. wiedii) are sister species and instead indicate that margay is most closely related to the enigmatic Andean cat (L. jacobita), whose whole-genome data are reported here for the first time. In addition, we found that the newly sampled Andean tiger cat (L. tigrinus pardinoides) population from Colombia associates closely with Central American tiger cats (L. tigrinus oncilla). Genealogical discordance was largely attributable to incomplete lineage sorting, yet was augmented by strong gene flow between ocelot and the ancestral branch of Oncifelis, as well as between Geoffroy's cat (L. geoffroyi) and southern tiger cat (L. guttulus). Contrasting demographic trajectories have led to disparate levels of current genomic diversity, with a nearly tenfold difference in heterozygosity between Andean cat and ocelot, spanning the entire range of variability found in extant felids. Our analyses improved our understanding of the speciation history and diversity patterns in this felid radiation, and highlight the benefits to phylogenomic inference of embracing the many heterogeneous signals scattered across the genome.
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Affiliation(s)
- Jonas Lescroart
- Department of Biology, University of Antwerp, Antwerp, Belgium
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Alejandra Bonilla-Sánchez
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Faculty of Exact and Natural Sciences, University of Antioquia, Medellín, Colombia
| | - Constanza Napolitano
- Department of Biological Sciences and Biodiversity, University of Los Lagos, Osorno, Chile
- Institute of Ecology and Biodiversity, Concepción, Chile
- Cape Horn International Center, Puerto Williams, Chile
- Andean Cat Alliance, Villa Carlos Paz, Argentina
| | - Diana L Buitrago-Torres
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Héctor E Ramírez-Chaves
- Department of Biological Sciences, University of Caldas, Manizales, Colombia
- Centro de Museos, Museo de Historia Natural, University of Caldas, Manizales, Colombia
| | | | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics & Genomics, Texas A&M University, College Station, TX, USA
| | - Hannes Svardal
- Department of Biology, University of Antwerp, Antwerp, Belgium
- Naturalis Biodiversity Center, Leiden, Netherlands
| | - Eduardo Eizirik
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Instituto Pró-Carnívoros, Atibaia, Brazil
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10
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Kusuma P, Cox MP, Barker G, Sudoyo H, Lansing JS, Jacobs GS. Deep ancestry of Bornean hunter-gatherers supports long-term local ancestry dynamics. Cell Rep 2023; 42:113346. [PMID: 37917587 DOI: 10.1016/j.celrep.2023.113346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 06/30/2023] [Accepted: 10/10/2023] [Indexed: 11/04/2023] Open
Abstract
Borneo was a crossroad of ancient dispersals, with some of the earliest Southeast Asian human remains and rock art. The island is home to traditionally hunter-gatherer Punan communities, whose origins, whether of subsistence reversion or long-term foraging, are unclear. The connection between its past and present-day agriculturalist inhabitants, who currently speak Austronesian languages and have composite and complex genetic ancestry, is equally opaque. Here, we analyze the genetic ancestry of the northeastern Bornean Punan Batu (who still practice some mobile hunting and gathering), Tubu, and Aput. We find deep ancestry connections, with a shared Asian signal outgrouping modern and ancient Austronesian-ancestry proxies, suggesting a time depth of more than 7,500 years. They also largely lack the mainland Southeast Asian signals of agricultural Borneans, who are themselves genetically heterogeneous. Our results support long-term inhabitation of Borneo by some Punan ancestors and reveal unexpected complexity in the origins and dispersal of Austronesian-expansion-related ancestry.
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Affiliation(s)
- Pradiptajati Kusuma
- Division of Genome Diversity and Diseases, Mochtar Riady Institute for Nanotechnology, Banten, Indonesia.
| | - Murray P Cox
- Department of Statistics, University of Auckland, Auckland, New Zealand; School of Natural Sciences, Massey University, Palmerston North, New Zealand
| | - Graeme Barker
- Department of Archaeology, University of Cambridge, Cambridge, UK
| | - Herawati Sudoyo
- Division of Genome Diversity and Diseases, Mochtar Riady Institute for Nanotechnology, Banten, Indonesia
| | - J Stephen Lansing
- Santa Fe Institute, Santa Fe, NM, USA; Complexity Science Hub Vienna, Vienna, Austria
| | - Guy S Jacobs
- Department of Archaeology, University of Cambridge, Cambridge, UK.
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11
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Williams MP, Flegontov P, Maier R, Huber CD. Testing Times: Challenges in Disentangling Admixture Histories in Recent and Complex Demographies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.13.566841. [PMID: 38014190 PMCID: PMC10680674 DOI: 10.1101/2023.11.13.566841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Paleogenomics has expanded our knowledge of human evolutionary history. Since the 2020s, the study of ancient DNA has increased its focus on reconstructing the recent past. However, the accuracy of paleogenomic methods in answering questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation within the historical period remains an open question. We used two simulation approaches to evaluate the limitations and behavior of commonly used methods, qpAdm and the f3-statistic, on admixture inference. The first is based on branch-length data simulated from four simple demographic models of varying complexities and configurations. The second, an analysis of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudo-haploidization. We show that under conditions resembling historical populations, qpAdm can identify a small candidate set of true sources and populations closely related to them. However, in typical ancient DNA conditions, qpAdm is unable to further distinguish between them, limiting its utility for resolving fine-scaled hypotheses. Notably, we find that complex gene-flow histories generally lead to improvements in the performance of qpAdm and observe no bias in the estimation of admixture weights. We offer a heuristic for admixture inference that incorporates admixture weight estimate and P-values of qpAdm models, and f3-statistics to enhance the power to distinguish between multiple plausible candidates. Finally, we highlight the future potential of qpAdm through whole-genome branch-length f2-statistics, demonstrating the improved demographic inference that could be achieved with advancements in f-statistic estimations.
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Affiliation(s)
- Matthew P. Williams
- Pennsylvania State University, Department of Biology, University Park, PA 16802, USA
| | - Pavel Flegontov
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Robert Maier
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Christian D. Huber
- Pennsylvania State University, Department of Biology, University Park, PA 16802, USA
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12
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Peng MS, Liu YH, Shen QK, Zhang XH, Dong J, Li JX, Zhao H, Zhang H, Zhang X, He Y, Shi H, Cui C, Ouzhuluobu, Wu TY, Liu SM, Gonggalanzi, Baimakangzhuo, Bai C, Duojizhuoma, Liu T, Dai SS, Murphy RW, Qi XB, Dong G, Su B, Zhang YP. Genetic and cultural adaptations underlie the establishment of dairy pastoralism in the Tibetan Plateau. BMC Biol 2023; 21:208. [PMID: 37798721 PMCID: PMC10557253 DOI: 10.1186/s12915-023-01707-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 09/20/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND Domestication and introduction of dairy animals facilitated the permanent human occupation of the Tibetan Plateau. Yet the history of dairy pastoralism in the Tibetan Plateau remains poorly understood. Little is known how Tibetans adapted to milk and dairy products. RESULTS We integrated archeological evidence and genetic analysis to show the picture that the dairy ruminants, together with dogs, were introduced from West Eurasia into the Tibetan Plateau since ~ 3600 years ago. The genetic admixture between the exotic and indigenous dogs enriched the candidate lactase persistence (LP) allele 10974A > G of West Eurasian origin in Tibetan dogs. In vitro experiments demonstrate that - 13838G > A functions as a LP allele in Tibetans. Unlike multiple LP alleles presenting selective signatures in West Eurasians and South Asians, the de novo origin of Tibetan-specific LP allele - 13838G > A with low frequency (~ 6-7%) and absence of selection corresponds - 13910C > T in pastoralists across eastern Eurasia steppe. CONCLUSIONS Results depict a novel scenario of genetic and cultural adaptations to diet and expand current understanding of the establishment of dairy pastoralism in the Tibetan Plateau.
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Affiliation(s)
- Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yan-Hu Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Quan-Kuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiao-Hua Zhang
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China
- Institute of Medical Biology, Chinese Academy of Medical Science, Peking Union Medical College, Kunming, 650118, China
| | - Jiajia Dong
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Jin-Xiu Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Hui Zhao
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China
| | - Hui Zhang
- State Key Laboratory of Primate Biomedical Research (LPBR), School of Primate Translational Medicine, Kunming University of Science and Technology (KUST), Kunming, 650000, China
| | - Xiaoming Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hong Shi
- State Key Laboratory of Primate Biomedical Research (LPBR), School of Primate Translational Medicine, Kunming University of Science and Technology (KUST), Kunming, 650000, China
| | - Chaoying Cui
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Ouzhuluobu
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Tian-Yi Wu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining, 810000, China
| | - Shi-Ming Liu
- National Key Laboratory of High Altitude Medicine, High Altitude Medical Research Institute, Xining, 810000, China
| | - Gonggalanzi
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Baimakangzhuo
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Caijuan Bai
- The First People's Hospital of Gansu Province, Lanzhou, 730000, China
| | - Duojizhuoma
- High Altitude Medical Research Center, School of Medicine, Tibetan University, Lhasa, 850000, China
| | - Ti Liu
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China
| | - Shan-Shan Dai
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Robert W Murphy
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- Centre for Biodiversity and Conservation Biology, Royal Ontario Museum, Toronto, ON, M5S 2C6, Canada
| | - Xue-Bin Qi
- State Key Laboratory of Primate Biomedical Research (LPBR), School of Primate Translational Medicine, Kunming University of Science and Technology (KUST), Kunming, 650000, China.
- Tibetan Fukang Hospital, Lhasa, 850000, China.
| | - Guanghui Dong
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- Yunnan Key Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory for Conservation and Utilization of Bio-Resources, Yunnan University, Kunming, 650091, China.
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13
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Martchenko D, Shafer ABA. Contrasting whole-genome and reduced representation sequencing for population demographic and adaptive inference: an alpine mammal case study. Heredity (Edinb) 2023; 131:273-281. [PMID: 37532838 PMCID: PMC10539292 DOI: 10.1038/s41437-023-00643-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 07/22/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023] Open
Abstract
Genomes capture the adaptive and demographic history of a species, but the choice of sequencing strategy and sample size can impact such inferences. We compared whole genome and reduced representation sequencing approaches to study the population demographic and adaptive signals of the North American mountain goat (Oreamnos americanus). We applied the restriction site-associated DNA sequencing (RADseq) approach to 254 individuals and whole genome resequencing (WGS) approach to 35 individuals across the species range at mid-level coverage (9X) and to 5 individuals at high coverage (30X). We used ANGSD to estimate the genotype likelihoods and estimated the effective population size (Ne), population structure, and explicitly modelled the demographic history with δaδi and MSMC2. The data sets were overall concordant in supporting a glacial induced vicariance and extremely low Ne in mountain goats. We evaluated a set of climatic variables and geographic location as predictors of genetic diversity using redundancy analysis. A moderate proportion of total variance (36% for WGS and 21% for RADseq data sets) was explained by geography and climate variables; both data sets support a large impact of drift and some degree of local adaptation. The empirical similarities of WGS and RADseq presented herein reassuringly suggest that both approaches will recover large demographic and adaptive signals in a population; however, WGS offers several advantages over RADseq, such as inferring adaptive processes and calculating runs-of-homozygosity estimates. Considering the predicted climate-induced changes in alpine environments and the genetically depauperate mountain goat, the long-term adaptive capabilities of this enigmatic species are questionable.
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Affiliation(s)
- Daria Martchenko
- Environmental and Life Sciences Graduate Program, Trent University, 2140 East Bank Drive, Peterborough, ON, K9J 7B8, Canada.
| | - Aaron B A Shafer
- Environmental and Life Sciences Graduate Program, Trent University, 2140 East Bank Drive, Peterborough, ON, K9J 7B8, Canada
- Department of Forensics & Environmental and Life Sciences Graduate Program, Trent University, 2140 East Bank Drive, Peterborough, ON, K9J 7B8, Canada
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14
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Crossman CA, Fontaine MC, Frasier TR. A comparison of genomic diversity and demographic history of the North Atlantic and Southwest Atlantic southern right whales. Mol Ecol 2023. [PMID: 37577945 DOI: 10.1111/mec.17099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 07/25/2023] [Accepted: 07/31/2023] [Indexed: 08/15/2023]
Abstract
Right whales (genus Eubalaena) were among the first, and most extensively pursued, targets of commercial whaling. However, understanding the impacts of this persecution requires knowledge of the demographic histories of these species prior to exploitation. We used deep whole genome sequencing (~40×) of 12 North Atlantic (E. glacialis) and 10 Southwest Atlantic southern (E. australis) right whales to quantify contemporary levels of genetic diversity and infer their demographic histories over time. Using coalescent- and identity-by-descent-based modelling to estimate ancestral effective population sizes from genomic data, we demonstrate that North Atlantic right whales have lived with smaller effective population sizes (Ne ) than southern right whales in the Southwest Atlantic since their divergence and describe the decline in both populations around the time of whaling. North Atlantic right whales exhibit reduced genetic diversity and longer runs of homozygosity leading to higher inbreeding coefficients compared to the sampled population of southern right whales. This study represents the first comprehensive assessment of genome-wide diversity of right whales in the western Atlantic and underscores the benefits of high coverage, genome-wide datasets to help resolve long-standing questions about how historical changes in effective population size over different time scales shape contemporary diversity estimates. This knowledge is crucial to improve our understanding of the right whales' history and inform our approaches to address contemporary conservation issues. Understanding and quantifying the cumulative impact of long-term small Ne , low levels of diversity and recent inbreeding on North Atlantic right whale recovery will be important next steps.
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Affiliation(s)
- Carla A Crossman
- Biology Department, Saint Mary's University, Halifax, Nova Scotia, Canada
| | - Michael C Fontaine
- Laboratoire MIVEGEC (Université de Montpellier, CNRS 5290, IRD 224), Montpellier, France
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, The Netherlands
| | - Timothy R Frasier
- Biology Department, Saint Mary's University, Halifax, Nova Scotia, Canada
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15
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Schweiger R, Durbin R. Ultrafast genome-wide inference of pairwise coalescence times. Genome Res 2023; 33:1023-1031. [PMID: 37562965 PMCID: PMC10538485 DOI: 10.1101/gr.277665.123] [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: 01/06/2023] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
The pairwise sequentially Markovian coalescent (PSMC) algorithm and its extensions infer the coalescence time of two homologous chromosomes at each genomic position. This inference is used in reconstructing demographic histories, detecting selection signatures, studying genome-wide associations, constructing ancestral recombination graphs, and more. Inference of coalescence times between each pair of haplotypes in a large data set is of great interest, as they may provide rich information about the population structure and history of the sample. Here, we introduce a new method, Gamma-SMC, which is more than 10 times faster than current methods. To obtain this speed-up, we represent the posterior coalescence time distributions succinctly as a gamma distribution with just two parameters; in contrast, PSMC and its extensions hold these in a vector over discrete intervals of time. Thus, Gamma-SMC has constant time-complexity per site, without dependence on the number of discrete time states. Additionally, because of this continuous representation, our method is able to infer times spanning many orders of magnitude and, as such, is robust to parameter misspecification. We describe how this approach works, show its performance on simulated and real data, and illustrate its use in studying recent positive selection in the 1000 Genomes Project data set.
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Affiliation(s)
- Regev Schweiger
- Department of Genetics, University of Cambridge, Cambridge CB2 1TN, United Kingdom
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Cambridge CB2 1TN, United Kingdom
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16
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Witt KE, Funk A, Añorve-Garibay V, Fang LL, Huerta-Sánchez E. The Impact of Modern Admixture on Archaic Human Ancestry in Human Populations. Genome Biol Evol 2023; 15:evad066. [PMID: 37103242 PMCID: PMC10194819 DOI: 10.1093/gbe/evad066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 03/07/2023] [Accepted: 04/17/2023] [Indexed: 04/28/2023] Open
Abstract
Admixture, the genetic merging of parental populations resulting in mixed ancestry, has occurred frequently throughout the course of human history. Numerous admixture events have occurred between human populations across the world, which have shaped genetic ancestry in modern humans. For example, populations in the Americas are often mosaics of different ancestries due to recent admixture events as part of European colonization. Admixed individuals also often have introgressed DNA from Neanderthals and Denisovans that may have come from multiple ancestral populations, which may affect how archaic ancestry is distributed across an admixed genome. In this study, we analyzed admixed populations from the Americas to assess whether the proportion and location of admixed segments due to recent admixture impact an individual's archaic ancestry. We identified a positive correlation between non-African ancestry and archaic alleles, as well as a slight increase of Denisovan alleles in Indigenous American segments relative to European segments in admixed genomes. We also identify several genes as candidates for adaptive introgression, based on archaic alleles present at high frequency in admixed American populations but low frequency in East Asian populations. These results provide insights into how recent admixture events between modern humans redistributed archaic ancestry in admixed genomes.
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Affiliation(s)
- Kelsey E Witt
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
| | - Alyssa Funk
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
- Molecular Biology, Cell Biology, & Biochemistry, Brown University, Providence, Rhode Island
| | - Valeria Añorve-Garibay
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
- Licenciatura en Ciencias Genómicas, Escuela Nacional de Estudios Superiores Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, Mexico
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Lesly Lopez Fang
- Department of Life & Environmental Sciences, University of California, Merced, California, United States of America
| | - Emilia Huerta-Sánchez
- Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island
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17
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Scerri EML, Will M. The revolution that still isn't: The origins of behavioral complexity in Homo sapiens. J Hum Evol 2023; 179:103358. [PMID: 37058868 DOI: 10.1016/j.jhevol.2023.103358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 03/13/2023] [Accepted: 03/14/2023] [Indexed: 04/16/2023]
Abstract
The behavioral origins of Homo sapiens can be traced back to the first material culture produced by our species in Africa, the Middle Stone Age (MSA). Beyond this broad consensus, the origins, patterns, and causes of behavioral complexity in modern humans remain debated. Here, we consider whether recent findings continue to support popular scenarios of: (1) a modern human 'package,' (2) a gradual and 'pan-African' emergence of behavioral complexity, and (3) a direct connection to changes in the human brain. Our geographically structured review shows that decades of scientific research have continuously failed to find a discrete threshold for a complete 'modernity package' and that the concept is theoretically obsolete. Instead of a continent-wide, gradual accumulation of complex material culture, the record exhibits a predominantly asynchronous presence and duration of many innovations across different regions of Africa. The emerging pattern of behavioral complexity from the MSA conforms to an intricate mosaic characterized by spatially discrete, temporally variable, and historically contingent trajectories. This archaeological record bears no direct relation to a simplistic shift in the human brain but rather reflects similar cognitive capacities that are variably manifested. The interaction of multiple causal factors constitutes the most parsimonious explanation driving the variable expression of complex behaviors, with demographic processes such as population structure, size, and connectivity playing a key role. While much emphasis has been given to innovation and variability in the MSA record, long periods of stasis and a lack of cumulative developments argue further against a strictly gradualistic nature in the record. Instead, we are confronted with humanity's deep, variegated roots in Africa, and a dynamic metapopulation that took many millennia to reach the critical mass capable of producing the ratchet effect commonly used to define contemporary human culture. Finally, we note a weakening link between 'modern' human biology and behavior from around 300 ka ago.
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Affiliation(s)
- Eleanor M L Scerri
- Pan-African Evolution Research Group, Max Planck Institute for Geoanthropology, Kahlaische Str. 10, 07749, Jena, Germany; Department of Classics and Archaeology, University of Malta, Msida, MSD 2080, Malta; Department of Prehistory, University of Cologne, 50931, Cologne, Germany.
| | - Manuel Will
- Department of Early Prehistory and Quaternary Ecology, University of Tübingen, Schloss Hohentübingen, Burgsteige 11, 72070, Tübingen, Germany
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18
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Pfennig A, Petersen LN, Kachambwa P, Lachance J. Evolutionary Genetics and Admixture in African Populations. Genome Biol Evol 2023; 15:evad054. [PMID: 36987563 PMCID: PMC10118306 DOI: 10.1093/gbe/evad054] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 03/15/2023] [Accepted: 03/22/2023] [Indexed: 03/30/2023] Open
Abstract
As the ancestral homeland of our species, Africa contains elevated levels of genetic diversity and substantial population structure. Importantly, African genomes are heterogeneous: They contain mixtures of multiple ancestries, each of which have experienced different evolutionary histories. In this review, we view population genetics through the lens of admixture, highlighting how multiple demographic events have shaped African genomes. Each of these historical vignettes paints a recurring picture of population divergence followed by secondary contact. First, we give a brief overview of genetic variation in Africa and examine deep population structure within Africa, including the evidence of ancient introgression from archaic "ghost" populations. Second, we describe the genetic legacies of admixture events that have occurred during the past 10,000 years. This includes gene flow between different click-speaking Khoe-San populations, the stepwise spread of pastoralism from eastern to southern Africa, multiple migrations of Bantu speakers across the continent, as well as admixture from the Middle East and Europe into the Sahel region and North Africa. Furthermore, the genomic signatures of more recent admixture can be found in the Cape Peninsula and throughout the African diaspora. Third, we highlight how natural selection has shaped patterns of genetic variation across the continent, noting that gene flow provides a potent source of adaptive variation and that selective pressures vary across Africa. Finally, we explore the biomedical implications of population structure in Africa on health and disease and call for more ethically conducted studies of genetic variation in Africa.
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Affiliation(s)
- Aaron Pfennig
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | | | | | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
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19
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Reboud EL, Nabholz B, Chevalier E, Tilak MK, Bito D, Condamine FL. Genomics, Population Divergence, and Historical Demography of the World's Largest and Endangered Butterfly, The Queen Alexandra's Birdwing. Genome Biol Evol 2023; 15:evad040. [PMID: 36896590 PMCID: PMC10101050 DOI: 10.1093/gbe/evad040] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 02/24/2023] [Indexed: 03/11/2023] Open
Abstract
The world's largest butterfly is the microendemic Papua New Guinean Ornithoptera alexandrae. Despite years of conservation efforts to protect its habitat and breed this up-to-28-cm butterfly, this species still figures as endangered in the IUCN Red List and is only known from two allopatric populations occupying a total of only ∼140 km². Here we aim at assembling reference genomes for this species to investigate its genomic diversity, historical demography and determine whether the population is structured, which could provide guidance for conservation programs attempting to (inter)breed the two populations. Using a combination of long and short DNA reads and RNA sequencing, we assembled six reference genomes of the tribe Troidini, with four annotated genomes of O. alexandrae and two genomes of related species Ornithoptera priamus and Troides oblongomaculatus. We estimated the genomic diversity of the three species, and we proposed scenarios for the historical population demography using two polymorphism-based methods taking into account the characteristics of low-polymorphic invertebrates. Indeed, chromosome-scale assemblies reveal very low levels of nuclear heterozygosity across Troidini, which appears to be exceptionally low for O. alexandrae (lower than 0.01%). Demographic analyses demonstrate low and steadily declining Ne throughout O. alexandrae history, with a divergence into two distinct populations about 10,000 years ago. These results suggest that O. alexandrae distribution has been microendemic for a long time. It should also make local conservation programs aware of the genomic divergence of the two populations, which should not be ignored if any attempt is made to cross the two populations.
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Affiliation(s)
- Eliette L Reboud
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Benoit Nabholz
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
- Institut Universitaire de France (IUF), Paris, France
| | - Emmanuelle Chevalier
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Marie-ka Tilak
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | - Darren Bito
- Pacific Adventist University, Private Mail Bag, BOROKO 111, National Capital District, Port Moresby, Papua New Guinea
| | - Fabien L Condamine
- Institut des Sciences de l’Evolution de Montpellier, Université Montpellier, CNRS, IRD, EPHE, Montpellier, France
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20
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Vilaça ST, Donaldson ME, Benazzo A, Wheeldon TJ, Vizzari MT, Bertorelle G, Patterson BR, Kyle CJ. Tracing Eastern Wolf Origins From Whole-Genome Data in Context of Extensive Hybridization. Mol Biol Evol 2023; 40:msad055. [PMID: 37046402 PMCID: PMC10098045 DOI: 10.1093/molbev/msad055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/14/2023] Open
Abstract
Southeastern Canada is inhabited by an amalgam of hybridizing wolf-like canids, raising fundamental questions regarding their taxonomy, origins, and timing of hybridization events. Eastern wolves (Canis lycaon), specifically, have been the subject of significant controversy, being viewed as either a distinct taxonomic entity of conservation concern or a recent hybrid of coyotes (C. latrans) and grey wolves (C. lupus). Mitochondrial DNA analyses show some evidence of eastern wolves being North American evolved canids. In contrast, nuclear genome studies indicate eastern wolves are best described as a hybrid entity, but with unclear timing of hybridization events. To test hypotheses related to these competing findings we sequenced whole genomes of 25 individuals, representative of extant Canadian wolf-like canid types of known origin and levels of contemporary hybridization. Here we present data describing eastern wolves as a distinct taxonomic entity that evolved separately from grey wolves for the past ∼67,000 years with an admixture event with coyotes ∼37,000 years ago. We show that Great Lakes wolves originated as a product of admixture between grey wolves and eastern wolves after the last glaciation (∼8,000 years ago) while eastern coyotes originated as a product of admixture between "western" coyotes and eastern wolves during the last century. Eastern wolf nuclear genomes appear shaped by historical and contemporary gene flow with grey wolves and coyotes, yet evolutionary uniqueness remains among eastern wolves currently inhabiting a restricted range in southeastern Canada.
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Affiliation(s)
- Sibelle T Vilaça
- Environmental and Life Sciences Graduate Program, Trent University, Ontario, Canada
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Michael E Donaldson
- Environmental and Life Sciences Graduate Program, Trent University, Ontario, Canada
| | - Andrea Benazzo
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Tyler J Wheeldon
- Ontario Ministry of Natural Resources and Forestry, Wildlife Research and Monitoring Section, Trent University, Ontario, Canada
| | - Maria Teresa Vizzari
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Giorgio Bertorelle
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Brent R Patterson
- Ontario Ministry of Natural Resources and Forestry, Wildlife Research and Monitoring Section, Trent University, Ontario, Canada
| | - Christopher J Kyle
- Environmental and Life Sciences Graduate Program, Trent University, Ontario, Canada
- Forensic Science Department, Trent University, Ontario, Canada
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21
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Wei K, Silva-Arias GA, Tellier A. Selective sweeps linked to the colonization of novel habitats and climatic changes in a wild tomato species. THE NEW PHYTOLOGIST 2023; 237:1908-1921. [PMID: 36419182 DOI: 10.1111/nph.18634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 11/16/2022] [Indexed: 06/16/2023]
Abstract
Positive selection is the driving force underpinning local adaptation and leaves footprints of selective sweeps on the underlying major genes. Quantifying the timing of selection and revealing the genetic bases of adaptation in plant species occurring in steep and varying environmental gradients are crucial to predict a species' ability to colonize new niches. We use whole-genome sequence data from six populations across three different habitats of the wild tomato species Solanum chilense to infer the past demographic history and search for genes under strong positive selection. We then correlate current and past climatic projections with the demographic history, allele frequencies, the age of selection events and distribution shifts. Several selective sweeps occur at regulatory networks involved in root-hair development in low altitude and response to photoperiod and vernalization in high-altitude populations. These sweeps appear to occur in a concerted fashion in a given regulatory gene network at particular periods of substantial climatic change. Using a unique combination of genome scans and modelling of past climatic data, we quantify the timing of selection at genes likely underpinning local adaptation to semiarid habitats.
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Affiliation(s)
- Kai Wei
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Liesel-Beckmann Strasse 2, 85354, Freising, Germany
| | - Gustavo A Silva-Arias
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Liesel-Beckmann Strasse 2, 85354, Freising, Germany
| | - Aurélien Tellier
- Population Genetics, Department of Life Science Systems, School of Life Sciences, Technical University of Munich, Liesel-Beckmann Strasse 2, 85354, Freising, Germany
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22
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Kessler C, Wootton E, Shafer ABA. Speciation without gene-flow in hybridizing deer. Mol Ecol 2023; 32:1117-1132. [PMID: 36516402 DOI: 10.1111/mec.16824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 12/01/2022] [Accepted: 12/05/2022] [Indexed: 12/15/2022]
Abstract
Under the ecological speciation model, divergent selection acts on ecological differences between populations, gradually creating barriers to gene flow and ultimately leading to reproductive isolation. Hybridisation is part of this continuum and can both promote and inhibit the speciation process. Here, we used white-tailed (Odocoileus virginianus) and mule deer (O. hemionus) to investigate patterns of speciation in hybridizing sister species. We quantified genome-wide historical introgression and performed genome scans to look for signatures of four different selection scenarios. Despite ample modern evidence of hybridisation, we found negligible patterns of ancestral introgression and no signatures of divergence with gene flow, rather localized patterns of allopatric and balancing selection were detected across the genome. Genes under balancing selection were related to immunity, MHC and sensory perception of smell, the latter of which is consistent with deer biology. The deficiency of historical gene-flow suggests that white-tailed and mule deer were spatially separated during the glaciation cycles of the Pleistocene and genome wide differentiation accrued via genetic drift. Dobzhansky-Muller incompatibilities and selection against hybrids are hypothesised to be acting, and diversity correlations to recombination rates suggests these sister species are far along the speciation continuum.
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Affiliation(s)
- Camille Kessler
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
| | - Eric Wootton
- Biochemistry & Molecular Biology, Trent University, Peterborough, Ontario, Canada
| | - Aaron B A Shafer
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada
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23
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Prehistoric human migration between Sundaland and South Asia was driven by sea-level rise. Commun Biol 2023; 6:150. [PMID: 36739308 PMCID: PMC9899273 DOI: 10.1038/s42003-023-04510-0] [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: 02/05/2022] [Accepted: 01/20/2023] [Indexed: 02/06/2023] Open
Abstract
Rapid sea-level rise between the Last Glacial Maximum (LGM) and the mid-Holocene transformed the Southeast Asian coastal landscape, but the impact on human demography remains unclear. Here, we create a paleogeographic map, focusing on sea-level changes during the period spanning the LGM to the present-day and infer the human population history in Southeast and South Asia using 763 high-coverage whole-genome sequencing datasets from 59 ethnic groups. We show that sea-level rise, in particular meltwater pulses 1 A (MWP1A, ~14,500-14,000 years ago) and 1B (MWP1B, ~11,500-11,000 years ago), reduced land area by over 50% since the LGM, resulting in segregation of local human populations. Following periods of rapid sea-level rises, population pressure drove the migration of Malaysian Negritos into South Asia. Integrated paleogeographic and population genomic analysis demonstrates the earliest documented instance of forced human migration driven by sea-level rise.
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24
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The impact of modern admixture on archaic human ancestry in human populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.16.524232. [PMID: 36711776 PMCID: PMC9882123 DOI: 10.1101/2023.01.16.524232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Admixture, the genetic merging of parental populations resulting in mixed ancestry, has occurred frequently throughout the course of human history. Numerous admixture events have occurred between human populations across the world, as well as introgression between humans and archaic humans, Neanderthals and Denisovans. One example are genomes from populations in the Americas, as these are often mosaics of different ancestries due to recent admixture events as part of European colonization. In this study, we analyzed admixed populations from the Americas to assess whether the proportion and location of admixed segments due to recent admixture impact an individual’s archaic ancestry. We identified a positive correlation between non-African ancestry and archaic alleles, as well as a slight enrichment of Denisovan alleles in Indigenous American segments relative to European segments in admixed genomes. We also identify several genes as candidates for adaptive introgression, based on archaic alleles present at high frequency in admixed American populations but low frequency in East Asian populations. These results provide insights into how recent admixture events between modern humans redistributed archaic ancestry in admixed genomes.
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25
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Puckett EE, Davis IS, Harper DC, Wakamatsu K, Battu G, Belant JL, Beyer DE, Carpenter C, Crupi AP, Davidson M, DePerno CS, Forman N, Fowler NL, Garshelis DL, Gould N, Gunther K, Haroldson M, Ito S, Kocka D, Lackey C, Leahy R, Lee-Roney C, Lewis T, Lutto A, McGowan K, Olfenbuttel C, Orlando M, Platt A, Pollard MD, Ramaker M, Reich H, Sajecki JL, Sell SK, Strules J, Thompson S, van Manen F, Whitman C, Williamson R, Winslow F, Kaelin CB, Marks MS, Barsh GS. Genetic architecture and evolution of color variation in American black bears. Curr Biol 2023; 33:86-97.e10. [PMID: 36528024 PMCID: PMC10039708 DOI: 10.1016/j.cub.2022.11.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 11/08/2022] [Accepted: 11/18/2022] [Indexed: 12/23/2022]
Abstract
Color variation is a frequent evolutionary substrate for camouflage in small mammals, but the underlying genetics and evolutionary forces that drive color variation in natural populations of large mammals are mostly unexplained. The American black bear, Ursus americanus (U. americanus), exhibits a range of colors including the cinnamon morph, which has a similar color to the brown bear, U. arctos, and is found at high frequency in the American southwest. Reflectance and chemical melanin measurements showed little distinction between U. arctos and cinnamon U. americanus individuals. We used a genome-wide association for hair color as a quantitative trait in 151 U. americanus individuals and identified a single major locus (p < 10-13). Additional genomic and functional studies identified a missense alteration (R153C) in Tyrosinase-related protein 1 (TYRP1) that likely affects binding of the zinc cofactor, impairs protein localization, and results in decreased pigment production. Population genetic analyses and demographic modeling indicated that the R153C variant arose 9.36 kya in a southwestern population where it likely provided a selective advantage, spreading both northwards and eastwards by gene flow. A different TYRP1 allele, R114C, contributes to the characteristic brown color of U. arctos but is not fixed across the range.
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Affiliation(s)
- Emily E Puckett
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA.
| | - Isis S Davis
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA
| | - Dawn C Harper
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kazumasa Wakamatsu
- Institute for Melanin Chemistry, Fujita Health University, Toyoake, Japan
| | - Gopal Battu
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Jerrold L Belant
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Dean E Beyer
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Colin Carpenter
- West Virginia Division of Natural Resources, Beckley, WV 25801, USA
| | - Anthony P Crupi
- Division of Wildlife Conservation, Alaska Department of Fish and Game, Douglas, Juneau, AK 99824, USA
| | - Maria Davidson
- The Louisiana Department of Wildlife and Fisheries, Baton Rouge, LA 70898, USA
| | - Christopher S DePerno
- Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7646, USA
| | - Nicholas Forman
- New Mexico Department of Game and Fish, Santa Fe, NM 87507, USA
| | - Nicholas L Fowler
- Division of Wildlife Conservation, Alaska Department of Fish and Game, Douglas, Juneau, AK 99824, USA
| | - David L Garshelis
- Minnesota Department of Natural Resources, Grand Rapids, MN 55744, USA; IUCN SSC Bear Specialist Group
| | - Nicholas Gould
- Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7646, USA
| | - Kerry Gunther
- National Park Service, Yellowstone National Park, WY 82190-0168, USA
| | - Mark Haroldson
- U.S. Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | - Shosuke Ito
- Institute for Melanin Chemistry, Fujita Health University, Toyoake, Japan
| | - David Kocka
- Virginia Department of Wildlife Resources, Verona, VA 24482, USA
| | - Carl Lackey
- Nevada Department of Wildlife, Reno, NV 89512, USA
| | - Ryan Leahy
- National Park Service, Yosemite National Park Wildlife Management, Yosemite, CA 95389, USA
| | - Caitlin Lee-Roney
- National Park Service, Yosemite National Park Wildlife Management, Yosemite, CA 95389, USA
| | - Tania Lewis
- National Park Service, Glacier Bay National Park, Gustavus, AK 99826, USA
| | - Ashley Lutto
- U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge, Soldotna, AK 99669, USA
| | - Kelly McGowan
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | | | - Mike Orlando
- Florida Fish and Wildlife Conservation Commission, Tallahassee, FL 32399, USA
| | - Alexander Platt
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew D Pollard
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA
| | - Megan Ramaker
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | - Jaime L Sajecki
- Virginia Department of Wildlife Resources, Verona, VA 24482, USA
| | - Stephanie K Sell
- Division of Wildlife Conservation, Alaska Department of Fish and Game, Douglas, Juneau, AK 99824, USA
| | - Jennifer Strules
- Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695-7646, USA
| | - Seth Thompson
- Virginia Department of Wildlife Resources, Verona, VA 24482, USA
| | - Frank van Manen
- U.S. Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | - Craig Whitman
- U.S. Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | - Ryan Williamson
- National Park Service, Great Smoky Mountains National Park, Gatlinburg, TN 37738, USA
| | | | - Christopher B Kaelin
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Michael S Marks
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Departments of Pathology and Laboratory Medicine and of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Gregory S Barsh
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA; Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
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26
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Mooney JA, Marsden CD, Yohannes A, Wayne RK, Lohmueller KE. Long-term Small Population Size, Deleterious Variation, and Altitude Adaptation in the Ethiopian Wolf, a Severely Endangered Canid. Mol Biol Evol 2023; 40:msac277. [PMID: 36585842 PMCID: PMC9847632 DOI: 10.1093/molbev/msac277] [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: 08/18/2022] [Revised: 11/07/2022] [Accepted: 12/22/2022] [Indexed: 01/01/2023] Open
Abstract
Ethiopian wolves, a canid species endemic to the Ethiopian Highlands, have been steadily declining in numbers for decades. Currently, out of 35 extant species, it is now one of the world's most endangered canids. Most conservation efforts have focused on preventing disease, monitoring movements and behavior, and assessing the geographic ranges of sub-populations. Here, we add an essential layer by determining the Ethiopian wolf's demographic and evolutionary history using high-coverage (∼40×) whole-genome sequencing from 10 Ethiopian wolves from the Bale Mountains. We observe exceptionally low diversity and enrichment of weakly deleterious variants in the Ethiopian wolves in comparison with two North American gray wolf populations and four dog breeds. These patterns are consequences of long-term small population size, rather than recent inbreeding. We infer the demographic history of the Ethiopian wolf and find it to be concordant with historic records and previous genetic analyses, suggesting Ethiopian wolves experienced a series of both ancient and recent bottlenecks, resulting in a census population size of fewer than 500 individuals and an estimated effective population size of approximately 100 individuals. Additionally, long-term small population size may have limited the accumulation of strongly deleterious recessive mutations. Finally, as the Ethiopian wolves have inhabited high-altitude areas for thousands of years, we searched for evidence of high-altitude adaptation, finding evidence of positive selection at a transcription factor in a hypoxia-response pathway [CREB-binding protein (CREBBP)]. Our findings are pertinent to continuing conservation efforts and understanding how demography influences the persistence of deleterious variation in small populations.
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Affiliation(s)
- Jazlyn A Mooney
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Clare D Marsden
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Abigail Yohannes
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, USA
| | - Robert K Wayne
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Kirk E Lohmueller
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Ecology & Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
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27
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Harvati K, Ackermann RR. Merging morphological and genetic evidence to assess hybridization in Western Eurasian late Pleistocene hominins. Nat Ecol Evol 2022; 6:1573-1585. [PMID: 36064759 DOI: 10.1038/s41559-022-01875-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 08/08/2022] [Indexed: 11/09/2022]
Abstract
Previous scientific consensus saw human evolution as defined by adaptive differences (behavioural and/or biological) and the emergence of Homo sapiens as the ultimate replacement of non-modern groups by a modern, adaptively more competitive group. However, recent research has shown that the process underlying our origins was considerably more complex. While archaeological and fossil evidence suggests that behavioural complexity may not be confined to the modern human lineage, recent palaeogenomic work shows that gene flow between distinct lineages (for example, Neanderthals, Denisovans, early H. sapiens) occurred repeatedly in the late Pleistocene, probably contributing elements to our genetic make-up that might have been crucial to our success as a diverse, adaptable species. Following these advances, the prevailing human origins model has shifted from one of near-complete replacement to a more nuanced view of partial replacement with considerable reticulation. Here we provide a brief introduction to the current genetic evidence for hybridization among hominins, its prevalence in, and effects on, comparative mammal groups, and especially how it manifests in the skull. We then explore the degree to which cranial variation seen in the fossil record of late Pleistocene hominins from Western Eurasia corresponds with our current genetic and comparative data. We are especially interested in understanding the degree to which skeletal data can reflect admixture. Our findings indicate some correspondence between these different lines of evidence, flag individual fossils as possibly admixed, and suggest that different cranial regions may preserve hybridization signals differentially. We urge further studies of the phenotype to expand our ability to detect the ways in which migration, interaction and genetic exchange have shaped the human past, beyond what is currently visible with the lens of ancient DNA.
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Affiliation(s)
- K Harvati
- Paleoanthropology section, Senckenberg Centre for Human Evolution and Palaeoenvironment, Institute for Archaeological Sciences, Eberhard Karls Universität Tübingen, Tübingen, Germany.
- DFG Centre for Advanced Studies 'Words, Bones, Genes, Tools', Eberhard Karls Universität Tübingen, Tübingen, Germany.
| | - R R Ackermann
- Human Evolution Research Institute, University of Cape Town, Cape Town, South Africa.
- Department of Archaeology, University of Cape Town, Cape Town, South Africa.
- DFG Centre for Advanced Studies 'Words, Bones, Genes, Tools', Eberhard Karls Universität Tübingen, Tübingen, Germany.
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28
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Upadhya G, Steinrücken M. Robust inference of population size histories from genomic sequencing data. PLoS Comput Biol 2022; 18:e1010419. [PMID: 36112715 PMCID: PMC9518926 DOI: 10.1371/journal.pcbi.1010419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 09/28/2022] [Accepted: 07/21/2022] [Indexed: 02/08/2023] Open
Abstract
Unraveling the complex demographic histories of natural populations is a central problem in population genetics. Understanding past demographic events is of general anthropological interest, but is also an important step in establishing accurate null models when identifying adaptive or disease-associated genetic variation. An important class of tools for inferring past population size changes from genomic sequence data are Coalescent Hidden Markov Models (CHMMs). These models make efficient use of the linkage information in population genomic datasets by using the local genealogies relating sampled individuals as latent states that evolve along the chromosome in an HMM framework. Extending these models to large sample sizes is challenging, since the number of possible latent states increases rapidly. Here, we present our method CHIMP (CHMM History-Inference Maximum-Likelihood Procedure), a novel CHMM method for inferring the size history of a population. It can be applied to large samples (hundreds of haplotypes) and only requires unphased genomes as input. The two implementations of CHIMP that we present here use either the height of the genealogical tree (TMRCA) or the total branch length, respectively, as the latent variable at each position in the genome. The requisite transition and emission probabilities are obtained by numerically solving certain systems of differential equations derived from the ancestral process with recombination. The parameters of the population size history are subsequently inferred using an Expectation-Maximization algorithm. In addition, we implement a composite likelihood scheme to allow the method to scale to large sample sizes. We demonstrate the efficiency and accuracy of our method in a variety of benchmark tests using simulated data and present comparisons to other state-of-the-art methods. Specifically, our implementation using TMRCA as the latent variable shows comparable performance and provides accurate estimates of effective population sizes in intermediate and ancient times. Our method is agnostic to the phasing of the data, which makes it a promising alternative in scenarios where high quality data is not available, and has potential applications for pseudo-haploid data.
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Affiliation(s)
- Gautam Upadhya
- Department of Physics, University of Chicago, Chicago, Illinois, United States of America
| | - Matthias Steinrücken
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- * E-mail:
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29
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Bergström A, Stanton DWG, Taron UH, Frantz L, Sinding MHS, Ersmark E, Pfrengle S, Cassatt-Johnstone M, Lebrasseur O, Girdland-Flink L, Fernandes DM, Ollivier M, Speidel L, Gopalakrishnan S, Westbury MV, Ramos-Madrigal J, Feuerborn TR, Reiter E, Gretzinger J, Münzel SC, Swali P, Conard NJ, Carøe C, Haile J, Linderholm A, Androsov S, Barnes I, Baumann C, Benecke N, Bocherens H, Brace S, Carden RF, Drucker DG, Fedorov S, Gasparik M, Germonpré M, Grigoriev S, Groves P, Hertwig ST, Ivanova VV, Janssens L, Jennings RP, Kasparov AK, Kirillova IV, Kurmaniyazov I, Kuzmin YV, Kosintsev PA, Lázničková-Galetová M, Leduc C, Nikolskiy P, Nussbaumer M, O'Drisceoil C, Orlando L, Outram A, Pavlova EY, Perri AR, Pilot M, Pitulko VV, Plotnikov VV, Protopopov AV, Rehazek A, Sablin M, Seguin-Orlando A, Storå J, Verjux C, Zaibert VF, Zazula G, Crombé P, Hansen AJ, Willerslev E, Leonard JA, Götherström A, Pinhasi R, Schuenemann VJ, Hofreiter M, Gilbert MTP, Shapiro B, Larson G, Krause J, Dalén L, Skoglund P. Grey wolf genomic history reveals a dual ancestry of dogs. Nature 2022; 607:313-320. [PMID: 35768506 PMCID: PMC9279150 DOI: 10.1038/s41586-022-04824-9] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 04/28/2022] [Indexed: 01/01/2023]
Abstract
The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1–8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located. DNA from ancient wolves spanning 100,000 years sheds light on wolves’ evolutionary history and the genomic origin of dogs.
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Affiliation(s)
- Anders Bergström
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK.
| | - David W G Stanton
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden.,School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Ulrike H Taron
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - Laurent Frantz
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.,Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, Munich, Germany
| | - Mikkel-Holger S Sinding
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland.,The Qimmeq Project, University of Greenland, Nuuk, Greenland.,Greenland Institute of Natural Resources, Nuuk, Greenland
| | - Erik Ersmark
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden
| | - Saskia Pfrengle
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany.,Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland
| | - Molly Cassatt-Johnstone
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Ophélie Lebrasseur
- The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Linus Girdland-Flink
- Department of Archaeology, School of Geosciences, University of Aberdeen, Aberdeen, UK.,School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK
| | - Daniel M Fernandes
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.,CIAS, Department of Life Sciences, University of Coimbra, Coimbra, Portugal
| | - Morgane Ollivier
- University of Rennes, CNRS, ECOBIO (Ecosystèmes, biodiversité, évolution)-UMR 6553, Rennes, France
| | - Leo Speidel
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK.,Genetics Institute, University College London, London, UK
| | | | - Michael V Westbury
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany.,The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | | | - Tatiana R Feuerborn
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,The Qimmeq Project, University of Greenland, Nuuk, Greenland.,Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany
| | - Ella Reiter
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany
| | - Joscha Gretzinger
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany.,Max Planck Institute for the Science of Human History, Jena, Germany
| | - Susanne C Münzel
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany
| | - Pooja Swali
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Nicholas J Conard
- Department of Early Prehistory and Quaternary Ecology, University of Tübingen, Tübingen, Germany.,Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany
| | - Christian Carøe
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - James Haile
- The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Anna Linderholm
- Centre for Palaeogenetics, Stockholm, Sweden.,The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK.,Texas A&M University, College Station, TX, USA.,Department of Geological Sciences, Stockholm University, Stockholm, Sweden
| | | | - Ian Barnes
- Department of Earth Sciences, Natural History Museum, London, UK
| | - Chris Baumann
- Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany.,Department of Geosciences and Geography, Faculty of Science, University of Helsinki, Helsinki, Finland
| | | | - Hervé Bocherens
- Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany.,Biogeology, Department of Geosciences, University of Tübingen, Tübingen, Germany
| | - Selina Brace
- Department of Earth Sciences, Natural History Museum, London, UK
| | - Ruth F Carden
- School of Archaeology, University College Dublin, Dublin, Ireland
| | - Dorothée G Drucker
- Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, Germany
| | - Sergey Fedorov
- North-Eastern Federal University, Yakutsk, Russian Federation
| | | | | | | | - Pam Groves
- University of Alaska, Fairbanks, AK, USA
| | - Stefan T Hertwig
- Naturhistorisches Museum Bern, Bern, Switzerland.,Institute of Ecology and Evolution, University of Bern, Bern, Switzerland
| | | | | | - Richard P Jennings
- School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK
| | - Aleksei K Kasparov
- Institute for the History of Material Culture, Russian Academy of Sciences, St Petersburg, Russian Federation
| | - Irina V Kirillova
- Ice Age Museum, Shidlovskiy National Alliance 'Ice Age', Moscow, Russian Federation
| | - Islam Kurmaniyazov
- Department of Archaeology, Ethnology and Museology, Al-Farabi Kazakh State University, Almaty, Kazakhstan
| | - Yaroslav V Kuzmin
- Sobolev Institute of Geology and Mineralogy, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation
| | | | | | | | - Pavel Nikolskiy
- Geological Institute, Russian Academy of Sciences, Moscow, Russian Federation
| | | | - Cóilín O'Drisceoil
- National Monuments Service, Department of Housing, Local Government and Heritage, Dublin, Ireland
| | - Ludovic Orlando
- Centre d'Anthropobiologie et de Génomique de Toulouse UMR 5288, CNRS, Faculté de Médecine Purpan, Université Paul Sabatier, Toulouse, France
| | - Alan Outram
- Department of Archaeology, University of Exeter, Exeter, UK
| | - Elena Y Pavlova
- Arctic & Antarctic Research Institute, St Petersburg, Russian Federation
| | - Angela R Perri
- PaleoWest, Henderson, NV, USA.,Department of Anthropology, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Małgorzata Pilot
- Museum & Institute of Zoology, Polish Academy of Sciences, Gdańsk, Poland
| | - Vladimir V Pitulko
- Institute for the History of Material Culture, Russian Academy of Sciences, St Petersburg, Russian Federation
| | | | | | | | - Mikhail Sablin
- Zoological Institute of the Russian Academy of Sciences, St. Petersburg, Russian Federation
| | - Andaine Seguin-Orlando
- Centre d'Anthropobiologie et de Génomique de Toulouse UMR 5288, CNRS, Faculté de Médecine Purpan, Université Paul Sabatier, Toulouse, France
| | - Jan Storå
- Stockholm University, Stockholm, Sweden
| | | | - Victor F Zaibert
- Institute of Archaeology and Steppe Civilizations, Al-Farabi Kazakh National University, Almaty, Kazakhstan
| | - Grant Zazula
- Yukon Palaeontology Program, Whitehorse, Yukon Territories, Canada.,Collections and Research, Canadian Museum of Nature, Ottawa, Ontario, Canada
| | | | - Anders J Hansen
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Eske Willerslev
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,Department of Zoology, University of Cambridge, Cambridge, UK
| | | | - Anders Götherström
- Centre for Palaeogenetics, Stockholm, Sweden.,Stockholm University, Stockholm, Sweden
| | - Ron Pinhasi
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.,Human Evolution and Archaeological Sciences, University of Vienna, Vienna, Austria
| | - Verena J Schuenemann
- Institute for Archaeological Sciences, University of Tübingen, Tübingen, Germany.,Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland.,Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Michael Hofreiter
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - M Thomas P Gilbert
- The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,University Museum, NTNU, Trondheim, Norway
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA.,Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Greger Larson
- The Palaeogenomics & Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Johannes Krause
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Love Dalén
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden
| | - Pontus Skoglund
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK.
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30
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Wang MS, Murray GGR, Mann D, Groves P, Vershinina AO, Supple MA, Kapp JD, Corbett-Detig R, Crump SE, Stirling I, Laidre KL, Kunz M, Dalén L, Green RE, Shapiro B. A polar bear paleogenome reveals extensive ancient gene flow from polar bears into brown bears. Nat Ecol Evol 2022; 6:936-944. [PMID: 35711062 DOI: 10.1038/s41559-022-01753-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 03/30/2022] [Indexed: 11/09/2022]
Abstract
Polar bears (Ursus maritimus) and brown bears (Ursus arctos) are sister species possessing distinct physiological and behavioural adaptations that evolved over the last 500,000 years. However, comparative and population genomics analyses have revealed that several extant and extinct brown bear populations have relatively recent polar bear ancestry, probably as the result of geographically localized instances of gene flow from polar bears into brown bears. Here, we generate and analyse an approximate 20X paleogenome from an approximately 100,000-year-old polar bear that reveals a massive prehistoric admixture event, which is evident in the genomes of all living brown bears. This ancient admixture event was not visible from genomic data derived from living polar bears. Like more recent events, this massive admixture event mainly involved unidirectional gene flow from polar bears into brown bears and occurred as climate changes caused overlap in the ranges of the two species. These findings highlight the complex reticulate paths that evolution can take within a regime of radically shifting climate.
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Affiliation(s)
- Ming-Shan Wang
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, USA.,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Gemma G R Murray
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Daniel Mann
- Department of Geosciences, University of Alaska, Fairbanks, AK, USA.,Institute of Arctic Biology, University of Alaska, Fairbanks, AK, USA
| | - Pamela Groves
- Institute of Arctic Biology, University of Alaska, Fairbanks, AK, USA
| | - Alisa O Vershinina
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Megan A Supple
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, USA.,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Joshua D Kapp
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Sarah E Crump
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Ian Stirling
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.,Wildlife Research Division, Environment and Climate Change Canada Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Kristin L Laidre
- Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, WA, USA
| | - Michael Kunz
- University of Alaska Museum of the North, Fairbanks, AK, USA
| | - Love Dalén
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.,Centre for Palaeogenetics, Stockholm, Sweden
| | - Richard E Green
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Beth Shapiro
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, USA. .,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA.
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31
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Popadin K, Gunbin K, Peshkin L, Annis S, Fleischmann Z, Franco M, Kraytsberg Y, Markuzon N, Ackermann RR, Khrapko K. Mitochondrial Pseudogenes Suggest Repeated Inter-Species Hybridization among Direct Human Ancestors. Genes (Basel) 2022; 13:810. [PMID: 35627195 PMCID: PMC9140377 DOI: 10.3390/genes13050810] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/12/2022] [Accepted: 04/16/2022] [Indexed: 12/02/2022] Open
Abstract
The hypothesis that the evolution of humans involves hybridization between diverged species has been actively debated in recent years. We present the following novel evidence in support of this hypothesis: the analysis of nuclear pseudogenes of mtDNA ("NUMTs"). NUMTs are considered "mtDNA fossils" as they preserve sequences of ancient mtDNA and thus carry unique information about ancestral populations. Our comparison of a NUMT sequence shared by humans, chimpanzees, and gorillas with their mtDNAs implies that, around the time of divergence between humans and chimpanzees, our evolutionary history involved the interbreeding of individuals whose mtDNA had diverged as much as ~4.5 Myr prior. This large divergence suggests a distant interspecies hybridization. Additionally, analysis of two other NUMTs suggests that such events occur repeatedly. Our findings suggest a complex pattern of speciation in primate/human ancestors and provide one potential explanation for the mosaic nature of fossil morphology found at the emergence of the hominin lineage. A preliminary version of this manuscript was uploaded to the preprint server BioRxiv in 2017 (10.1101/134502).
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Affiliation(s)
- Konstantin Popadin
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland;
- Center for Mitochondrial Functional Genomics, Institute of Living Systems, Immanuel Kant Baltic Federal University, 236040 Kaliningrad, Russia
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | | | - Leonid Peshkin
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA;
| | - Sofia Annis
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
| | - Zoe Fleischmann
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
| | - Melissa Franco
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
| | | | | | - Rebecca R. Ackermann
- Human Evolution Research Institute, Department of Archaeology, University of Cape Town, Cape Town 7700, South Africa;
| | - Konstantin Khrapko
- Department of Biology, Northeastern University, Boston, MA 02115, USA; (S.A.); (Z.F.); (M.F.)
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32
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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: 5] [Impact Index Per Article: 2.5] [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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33
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Baumdicker F, Bisschop G, Goldstein D, Gower G, Ragsdale AP, Tsambos G, Zhu S, Eldon B, Ellerman EC, Galloway JG, Gladstein AL, Gorjanc G, Guo B, Jeffery B, Kretzschumar WW, Lohse K, Matschiner M, Nelson D, Pope NS, Quinto-Cortés CD, Rodrigues MF, Saunack K, Sellinger T, Thornton K, van Kemenade H, Wohns AW, Wong Y, Gravel S, Kern AD, Koskela J, Ralph PL, Kelleher J. Efficient ancestry and mutation simulation with msprime 1.0. Genetics 2022; 220:iyab229. [PMID: 34897427 PMCID: PMC9176297 DOI: 10.1093/genetics/iyab229] [Citation(s) in RCA: 116] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/03/2021] [Indexed: 11/13/2022] Open
Abstract
Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime's many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.
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Affiliation(s)
- Franz Baumdicker
- Cluster of Excellence “Controlling Microbes to Fight Infections”, Mathematical and Computational Population Genetics, University of Tübingen, 72076 Tübingen, Germany
| | - Gertjan Bisschop
- Institute of Evolutionary Biology, The University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Daniel Goldstein
- Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Graham Gower
- Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, 1350 Copenhagen K, Denmark
| | - Aaron P Ragsdale
- Department of Integrative Biology, University of Wisconsin–Madison, Madison, WI 53706, USA
| | - Georgia Tsambos
- Melbourne Integrative Genomics, School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia
| | - Sha Zhu
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Bjarki Eldon
- Leibniz Institute for Evolution and Biodiversity Science, Museum für Naturkunde, Berlin 10115, Germany
| | | | - Jared G Galloway
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98102, USA
| | - Ariella L Gladstein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7264, USA
- Embark Veterinary, Inc., Boston, MA 02111, USA
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Bing Guo
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Ben Jeffery
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Warren W Kretzschumar
- Center for Hematology and Regenerative Medicine, Karolinska Institute, 141 83 Huddinge, Sweden
| | - Konrad Lohse
- Institute of Evolutionary Biology, The University of Edinburgh, Edinburgh EH9 3FL, UK
| | | | - Dominic Nelson
- Department of Human Genetics, McGill University, Montréal, QC H3A 0C7, Canada
| | - Nathaniel S Pope
- Department of Entomology, Pennsylvania State University, State College, PA 16802, USA
| | - Consuelo D Quinto-Cortés
- National Laboratory of Genomics for Biodiversity (LANGEBIO), Unit of Advanced Genomics, CINVESTAV, Irapuato, Mexico
| | - Murillo F Rodrigues
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
| | | | - Thibaut Sellinger
- Professorship for Population Genetics, Department of Life Science Systems, Technical University of Munich, 85354 Freising, Germany
| | - Kevin Thornton
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
| | | | - Anthony W Wohns
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yan Wong
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
| | - Simon Gravel
- Department of Human Genetics, McGill University, Montréal, QC H3A 0C7, Canada
| | - Andrew D Kern
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
| | - Jere Koskela
- Department of Statistics, University of Warwick, Coventry CV4 7AL, UK
| | - Peter L Ralph
- Department of Biology, Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403-5289, USA
- Department of Mathematics, University of Oregon, Eugene, OR 97403-5289, USA
| | - Jerome Kelleher
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK
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34
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Manthey JD, Bourgeois Y, Meheretu Y, Boissinot S. Varied diversification patterns and distinct demographic trajectories in Ethiopian montane forest bird (Aves: Passeriformes) populations separated by the Great Rift Valley. Mol Ecol 2022; 31:2664-2678. [PMID: 35239243 DOI: 10.1111/mec.16417] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/16/2022] [Accepted: 02/21/2022] [Indexed: 11/30/2022]
Abstract
Taxon-specific characteristics and extrinsic climatic and geological forces may both shape population differentiation and speciation. In geographically and taxonomically focused investigations, differentiation may occur synchronously as species respond to the same external conditions. Conversely, when evolution is investigated in taxa with largely varying traits, population differentiation and speciation is complex and shaped by interactions of Earth's template and species-specific traits. As such, it is important to characterize evolutionary histories broadly across the tree of life, especially in geographic regions that are exceptionally diverse and under pressures from human activities such as in biodiversity hotspots. Here, using whole-genome sequencing data, we characterize genomic variation in populations of six Ethiopian Highlands forest bird species separated by a lowland biogeographic barrier, the Great Rift Valley (GRV). In all six species, populations on either side of the GRV exhibited significant but varying levels of genetic differentiation. Species' dispersal ability was negatively correlated with levels of population differentiation. Isolation with migration models indicated varied patterns of population differentiation and connectivity among populations of the focal species. We found that demographic histories-estimated for each individual-varied by both species and population but were consistent between individuals of the same species and sampling region. We found that genomic diversity varied by half an order of magnitude across species, and that this variation could largely be explained by the harmonic mean of effective population size over the past 200,000 years. Overall, we found that even in highly dispersive species like birds, the GRV acts as a substantial biogeographic barrier.
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35
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Zhang M, Yang Q, Ai H, Huang L. Revisiting the Evolutionary History of Pigs via De Novo Mutation Rate Estimation in A Three-generation Pedigree. GENOMICS, PROTEOMICS & BIOINFORMATICS 2022; 20:1040-1052. [PMID: 35181533 DOI: 10.1016/j.gpb.2022.02.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 12/20/2021] [Accepted: 02/09/2022] [Indexed: 12/30/2022]
Abstract
The mutation rate used in the previous analyses of pig evolution and demographics was cursory and hence invited potential bias in inferring evolutionary history. Herein, we estimated the de novo mutation rate of pigs as 3.6 × 10-9 per base per generation using high-quality whole-genome sequencing data from nine individuals in a three-generation pedigree through stringent filtering and validation. Using this mutation rate, we re-investigated the evolutionary history of pigs. The estimated divergence time of ∼ 10 kiloyears ago (KYA) between European wild and domesticated pigs was consistent with the domestication time of European pigs based on archaeological evidence. However, other divergence events inferred here were not as ancient as previously described. Our estimates suggested that Sus speciation occurred ∼ 1.36 million years ago (MYA); European wild pigs split from Asian wild pigs only ∼ 219 KYA; and south and north Chinese wild pigs split ∼ 25 KYA. Meanwhile, our results showed that the most recent divergence event between Chinese wild and domesticated pigs occurred in the Hetao plain, North China, approximately 20 KYA, supporting the possibly independent domestication in North China along the middle Yellow River. We also found that the maximum effective population size of pigs was ∼ 6 times larger than the previous estimate. An archaic migration from other Sus species originating ∼ 2 MYA to European pigs was detected during western colonization of pigs; this interfered with the previous demographic inference. Our de novo mutation rate estimation and its consequences for demographic history inference reasonably provide a new vision regarding the evolutionary history of pigs.
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Affiliation(s)
- Mingpeng Zhang
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China
| | - Qiang Yang
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China
| | - Huashui Ai
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China.
| | - Lusheng Huang
- State Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang 330045, China.
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36
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Speidel L, Cassidy L, Davies RW, Hellenthal G, Skoglund P, Myers SR. Inferring Population Histories for Ancient Genomes Using Genome-Wide Genealogies. Mol Biol Evol 2021; 38:3497-3511. [PMID: 34129037 PMCID: PMC8383901 DOI: 10.1093/molbev/msab174] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Ancient genomes anchor genealogies in directly observed historical genetic variation and contextualize ancestral lineages with archaeological insights into their geography and cultural associations. However, the majority of ancient genomes are of lower coverage and cannot be directly built into genealogies. Here, we present a fast and scalable method, Colate, the first approach for inferring ancestral relationships through time between low-coverage genomes without requiring phasing or imputation. Our approach leverages sharing patterns of mutations dated using a genealogy to infer coalescence rates. For deeply sequenced ancient genomes, we additionally introduce an extension of the Relate algorithm for joint inference of genealogies incorporating such genomes. Application to 278 present-day and 430 ancient DNA samples of >0.5x mean coverage allows us to identify dynamic population structure and directional gene flow between early farmer and European hunter-gatherer groups. We further show that the previously reported, but still unexplained, increase in the TCC/TTC mutation rate, which is strongest in West Eurasia today, was already present at similar strength and widespread in the Late Glacial Period ~10k-15k years ago, but is not observed in samples >30k years old. It is strongest in Neolithic farmers, and highly correlated with recent coalescence rates between other genomes and a 10,000-year-old Anatolian hunter-gatherer. This suggests gene-flow among ancient peoples postdating the last glacial maximum as widespread and localizes the driver of this mutational signal in both time and geography in that region. Our approach should be widely applicable in future for addressing other evolutionary questions, and in other species.
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Affiliation(s)
- Leo Speidel
- Francis Crick Institute, London, United Kingdom
- Genetics Institute, University College London, London, United Kingdom
| | - Lara Cassidy
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Republic of Ireland
| | - Robert W Davies
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | | | | | - Simon R Myers
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
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37
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Almarri MA, Haber M, Lootah RA, Hallast P, Al Turki S, Martin HC, Xue Y, Tyler-Smith C. The genomic history of the Middle East. Cell 2021; 184:4612-4625.e14. [PMID: 34352227 PMCID: PMC8445022 DOI: 10.1016/j.cell.2021.07.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 05/17/2021] [Accepted: 07/09/2021] [Indexed: 11/22/2022]
Abstract
The Middle East region is important to understand human evolution and migrations but is underrepresented in genomic studies. Here, we generated 137 high-coverage physically phased genome sequences from eight Middle Eastern populations using linked-read sequencing. We found no genetic traces of early expansions out-of-Africa in present-day populations but found Arabians have elevated Basal Eurasian ancestry that dilutes their Neanderthal ancestry. Population sizes within the region started diverging 15–20 kya, when Levantines expanded while Arabians maintained smaller populations that derived ancestry from local hunter-gatherers. Arabians suffered a population bottleneck around the aridification of Arabia 6 kya, while Levantines had a distinct bottleneck overlapping the 4.2 kya aridification event. We found an association between movement and admixture of populations in the region and the spread of Semitic languages. Finally, we identify variants that show evidence of selection, including polygenic selection. Our results provide detailed insights into the genomic and selective histories of the Middle East. Middle Easterners do not have ancestry from an early out-of-Africa expansion Basal Eurasian and African ancestry in Arabians deplete their Neanderthal ancestry Populations experienced bottlenecks overlapping aridification events Identification of recent single and polygenic signals of selection in Arabia
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Affiliation(s)
- Mohamed A Almarri
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK; Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates.
| | - Marc Haber
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2TT, UK; Centre for Computational Biology, University of Birmingham, Birmingham B15 2TT, UK.
| | - Reem A Lootah
- Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates
| | - Pille Hallast
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK; Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu 50411, Estonia
| | - Saeed Al Turki
- Translational Pathology, Department of Pathology and Laboratory Medicine, King Abdulaziz Medical City, Ministry of National Guard-Health Affairs, Riyadh, Saudi Arabia; Department of Genetics & Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Hilary C Martin
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Yali Xue
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Chris Tyler-Smith
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
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38
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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: 3.7] [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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39
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Sellinger TPP, Abu-Awad D, Tellier A. Limits and convergence properties of the sequentially Markovian coalescent. Mol Ecol Resour 2021; 21:2231-2248. [PMID: 33978324 DOI: 10.1111/1755-0998.13416] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 04/19/2021] [Accepted: 04/29/2021] [Indexed: 02/07/2023]
Abstract
Several methods based on the sequentially Markovian coalescent (SMC) make use of full genome sequence data from samples to infer population demographic history including past changes in population size, admixture, migration events and population structure. More recently, the original theoretical framework has been extended to allow the simultaneous estimation of population size changes along with other life history traits such as selfing or seed banking. The latter developments enhance the applicability of SMC methods to nonmodel species. Although convergence proofs have been given using simulated data in a few specific cases, an in-depth investigation of the limitations of SMC methods is lacking. In order to explore such limits, we first develop a tool inferring the best case convergence of SMC methods assuming the true underlying coalescent genealogies are known. This tool can be used to quantify the amount and type of information that can be confidently retrieved from given data sets prior to the analysis of the real data. Second, we assess the inference accuracy when the assumptions of SMC approaches are violated due to departures from the model, namely the presence of transposable elements, variable recombination and mutation rates along the sequence, and SNP calling errors. Third, we deliver a new interpretation of SMC methods by highlighting the importance of the transition matrix, which we argue can be used as a set of summary statistics in other statistical inference methods, uncoupling the SMC from hidden Markov models (HMMs). We finally offer recommendations to better apply SMC methods and build adequate data sets under budget constraints.
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Affiliation(s)
| | - Diala Abu-Awad
- Department of Life Science Systems, Technical University of Munich, Munchen, Germany
| | - Aurélien Tellier
- Department of Life Science Systems, Technical University of Munich, Munchen, Germany
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40
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Sjödin P, McKenna J, Jakobsson M. Estimating divergence times from DNA sequences. Genetics 2021; 217:iyab008. [PMID: 33769498 PMCID: PMC8049563 DOI: 10.1093/genetics/iyab008] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 12/11/2020] [Indexed: 11/23/2022] Open
Abstract
The patterns of genetic variation within and among individuals and populations can be used to make inferences about the evolutionary forces that generated those patterns. Numerous population genetic approaches have been developed in order to infer evolutionary history. Here, we present the "Two-Two (TT)" and the "Two-Two-outgroup (TTo)" methods; two closely related approaches for estimating divergence time based in coalescent theory. They rely on sequence data from two haploid genomes (or a single diploid individual) from each of two populations. Under a simple population-divergence model, we derive the probabilities of the possible sample configurations. These probabilities form a set of equations that can be solved to obtain estimates of the model parameters, including population split times, directly from the sequence data. This transparent and computationally efficient approach to infer population divergence time makes it possible to estimate time scaled in generations (assuming a mutation rate), and not as a compound parameter of genetic drift. Using simulations under a range of demographic scenarios, we show that the method is relatively robust to migration and that the TTo method can alleviate biases that can appear from drastic ancestral population size changes. We illustrate the utility of the approaches with some examples, including estimating split times for pairs of human populations as well as providing further evidence for the complex relationship among Neandertals and Denisovans and their ancestors.
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Affiliation(s)
- Per Sjödin
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18 A, Uppsala 752 36, Sweden
| | - James McKenna
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18 A, Uppsala 752 36, Sweden
| | - Mattias Jakobsson
- Human Evolution, Department of Organismal Biology, Uppsala University, Norbyvägen 18 A, Uppsala 752 36, Sweden
- Science for Life Laboratory, Uppsala University, Norbyvägen 18 A, Uppsala 752 36, Sweden
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41
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Arredondo A, Mourato B, Nguyen K, Boitard S, Rodríguez W, Noûs C, Mazet O, Chikhi L. Inferring number of populations and changes in connectivity under the n-island model. Heredity (Edinb) 2021; 126:896-912. [PMID: 33846579 PMCID: PMC8178352 DOI: 10.1038/s41437-021-00426-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 12/11/2022] Open
Abstract
Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.
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Affiliation(s)
- Armando Arredondo
- Université de Toulouse, Institut National des Sciences Appliquées, Institut de Mathématiques de Toulouse, Toulouse, France. .,Institut de Mathématiques de Toulouse; UMR5219. Université de Toulouse, Toulouse, France.
| | - Beatriz Mourato
- Institut de Mathématiques de Toulouse; UMR5219. Université de Toulouse, Toulouse, France.,Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Khoa Nguyen
- Université de Toulouse, Institut National des Sciences Appliquées, Institut de Mathématiques de Toulouse, Toulouse, France
| | - Simon Boitard
- CBGP, Université de Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France
| | - Willy Rodríguez
- Institut de Mathématiques de Toulouse; UMR5219. Université de Toulouse, Toulouse, France.,ENAC - Ecole Nationale de l'Aviation Civile, Université de Toulouse, Toulouse, France
| | | | - Olivier Mazet
- Université de Toulouse, Institut National des Sciences Appliquées, Institut de Mathématiques de Toulouse, Toulouse, France.,Institut de Mathématiques de Toulouse; UMR5219. Université de Toulouse, Toulouse, France
| | - Lounès Chikhi
- Instituto Gulbenkian de Ciência, Oeiras, Portugal. .,Laboratoire Évolution & Diversité Biologique (EDB UMR 5174), CNRS, IRD, UPS, Université de Toulouse Midi-Pyrénées, Toulouse, France.
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42
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Wang CC, Yeh HY, Popov AN, Zhang HQ, Matsumura H, Sirak K, Cheronet O, Kovalev A, Rohland N, Kim AM, Mallick S, Bernardos R, Tumen D, Zhao J, Liu YC, Liu JY, Mah M, Wang K, Zhang Z, Adamski N, Broomandkhoshbacht N, Callan K, Candilio F, Carlson KSD, Culleton BJ, Eccles L, Freilich S, Keating D, Lawson AM, Mandl K, Michel M, Oppenheimer J, Özdoğan KT, Stewardson K, Wen S, Yan S, Zalzala F, Chuang R, Huang CJ, Looh H, Shiung CC, Nikitin YG, Tabarev AV, Tishkin AA, Lin S, Sun ZY, Wu XM, Yang TL, Hu X, Chen L, Du H, Bayarsaikhan J, Mijiddorj E, Erdenebaatar D, Iderkhangai TO, Myagmar E, Kanzawa-Kiriyama H, Nishino M, Shinoda KI, Shubina OA, Guo J, Cai W, Deng Q, Kang L, Li D, Li D, Lin R, Nini, Shrestha R, Wang LX, Wei L, Xie G, Yao H, Zhang M, He G, Yang X, Hu R, Robbeets M, Schiffels S, Kennett DJ, Jin L, Li H, Krause J, Pinhasi R, Reich D. Genomic insights into the formation of human populations in East Asia. Nature 2021; 591:413-419. [PMID: 33618348 PMCID: PMC7993749 DOI: 10.1038/s41586-021-03336-2] [Citation(s) in RCA: 135] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 02/05/2021] [Indexed: 01/31/2023]
Abstract
The deep population history of East Asia remains poorly understood owing to a lack of ancient DNA data and sparse sampling of present-day people1,2. Here we report genome-wide data from 166 East Asian individuals dating to between 6000 BC and AD 1000 and 46 present-day groups. Hunter-gatherers from Japan, the Amur River Basin, and people of Neolithic and Iron Age Taiwan and the Tibetan Plateau are linked by a deeply splitting lineage that probably reflects a coastal migration during the Late Pleistocene epoch. We also follow expansions during the subsequent Holocene epoch from four regions. First, hunter-gatherers from Mongolia and the Amur River Basin have ancestry shared by individuals who speak Mongolic and Tungusic languages, but do not carry ancestry characteristic of farmers from the West Liao River region (around 3000 BC), which contradicts theories that the expansion of these farmers spread the Mongolic and Tungusic proto-languages. Second, farmers from the Yellow River Basin (around 3000 BC) probably spread Sino-Tibetan languages, as their ancestry dispersed both to Tibet-where it forms approximately 84% of the gene pool in some groups-and to the Central Plain, where it has contributed around 59-84% to modern Han Chinese groups. Third, people from Taiwan from around 1300 BC to AD 800 derived approximately 75% of their ancestry from a lineage that is widespread in modern individuals who speak Austronesian, Tai-Kadai and Austroasiatic languages, and that we hypothesize derives from farmers of the Yangtze River Valley. Ancient people from Taiwan also derived about 25% of their ancestry from a northern lineage that is related to, but different from, farmers of the Yellow River Basin, which suggests an additional north-to-south expansion. Fourth, ancestry from Yamnaya Steppe pastoralists arrived in western Mongolia after around 3000 BC but was displaced by previously established lineages even while it persisted in western China, as would be expected if this ancestry was associated with the spread of proto-Tocharian Indo-European languages. Two later gene flows affected western Mongolia: migrants after around 2000 BC with Yamnaya and European farmer ancestry, and episodic influences of later groups with ancestry from Turan.
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Affiliation(s)
- Chuan-Chao Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany.
- MOE Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China.
| | - Hui-Yuan Yeh
- School of Humanities, Nanyang Technological University, Nanyang, Singapore
| | - Alexander N Popov
- Scientific Museum, Far Eastern Federal University, Vladivostok, Russia
| | - Hu-Qin Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | | | - Kendra Sirak
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Olivia Cheronet
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Alexey Kovalev
- Institute of Archaeology, Russian Academy of Sciences, Moscow, Russia
| | - Nadin Rohland
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Alexander M Kim
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Anthropology, Harvard University, Cambridge, MA, USA
| | - Swapan Mallick
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | | | - Dashtseveg Tumen
- Department of Anthropology and Archaeology, National University of Mongolia, Ulaanbaatar, Mongolia
| | - Jing Zhao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Yi-Chang Liu
- Institute of Archaeology, National Cheng Kung University, Tainan, Taiwan
| | - Jiun-Yu Liu
- Department of Anthropology, University of Washington, Seattle, WA, USA
| | - Matthew Mah
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Ke Wang
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Zhao Zhang
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Nicole Adamski
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Nasreen Broomandkhoshbacht
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Kimberly Callan
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Francesca Candilio
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | | | - Brendan J Culleton
- Institutes of Energy and the Environment, The Pennsylvania State University, University Park, PA, USA
| | - Laurie Eccles
- Department of Anthropology, Pennsylvania State University, University Park, PA, USA
| | - Suzanne Freilich
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Denise Keating
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Ann Marie Lawson
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Kirsten Mandl
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Megan Michel
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Jonas Oppenheimer
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | | | - Kristin Stewardson
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Shaoqing Wen
- Institute of Archaeological Science, Fudan University, Shanghai, China
| | - Shi Yan
- School of Ethnology and Sociology, Minzu University of China, Beijing, China
| | - Fatma Zalzala
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Richard Chuang
- Institute of Archaeology, National Cheng Kung University, Tainan, Taiwan
| | - Ching-Jung Huang
- Institute of Archaeology, National Cheng Kung University, Tainan, Taiwan
| | - Hana Looh
- Institute of History and Philology, Institute of History and Philology, Academia Sinica, Taipei, Taiwan
| | - Chung-Ching Shiung
- Institute of Archaeology, National Cheng Kung University, Tainan, Taiwan
| | - Yuri G Nikitin
- Museum of Archaeology and Ethnology, Institute of History, Archaeology and Ethnology, Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia
| | - Andrei V Tabarev
- Institute of Archaeology and Ethnography, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
| | - Alexey A Tishkin
- Department of Archeology, Ethnography and Museology, Altai State University, Barnaul, Russia
| | - Song Lin
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Zhou-Yong Sun
- Shaanxi Provincial Institute of Archaeology, Xi'an, China
| | - Xiao-Ming Wu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Xi Hu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Liang Chen
- School of Cultural Heritage, Northwest University, Xi'an, China
| | - Hua Du
- Xi'an AMS Center, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
| | | | - Enkhbayar Mijiddorj
- Department of Archaeology, Ulaanbaatar State University, Ulaanbaatar, Mongolia
| | | | | | - Erdene Myagmar
- Department of Anthropology and Archaeology, National University of Mongolia, Ulaanbaatar, Mongolia
| | | | | | - Ken-Ichi Shinoda
- Department of Anthropology, National Museum of Nature and Science, Tsukuba, Japan
| | - Olga A Shubina
- Department of Archeology, Sakhalin Regional Museum, Yuzhno-Sakhalinsk, Russia
| | - Jianxin Guo
- Department of Anthropology and Ethnology, Institute of Anthropology, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Wangwei Cai
- Department of Biochemistry and Molecular Biology, Hainan Medical University, Haikou, China
| | - Qiongying Deng
- Department of Human Anatomy and Center for Genomics and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research on High Altitude Disease of Tibet Autonomous Region, Ministry of Education, School of Medicine, Xizang Minzu University (Tibet University for Nationalities), Xianyang, China
| | - Dawei Li
- Institute for History and Culture of Science & Technology, Guangxi University for Nationalities, Nanning, China
| | - Dongna Li
- Department of Biology, Hainan Medical University, Haikou, China
| | - Rong Lin
- Department of Biology, Hainan Medical University, Haikou, China
| | - Nini
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research on High Altitude Disease of Tibet Autonomous Region, Ministry of Education, School of Medicine, Xizang Minzu University (Tibet University for Nationalities), Xianyang, China
| | - Rukesh Shrestha
- MOE Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Ling-Xiang Wang
- MOE Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Lanhai Wei
- Department of Anthropology and Ethnology, Institute of Anthropology, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Guangmao Xie
- College of History, Culture and Tourism, Guangxi Normal University, Guilin, China
- Guangxi Institute of Cultural Relics Protection and Archaeology, Nanning, China
| | - Hongbing Yao
- Belt and Road Research Center for Forensic Molecular Anthropology, Key Laboratory of Evidence Science of Gansu Province, Gansu Institute of Political Science and Law, Lanzhou, China
| | - Manfei Zhang
- MOE Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Guanglin He
- Department of Anthropology and Ethnology, Institute of Anthropology, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Xiaomin Yang
- Department of Anthropology and Ethnology, Institute of Anthropology, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Rong Hu
- Department of Anthropology and Ethnology, Institute of Anthropology, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Martine Robbeets
- Eurasia3angle Research group, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Stephan Schiffels
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Douglas J Kennett
- Department of Anthropology, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Li Jin
- MOE Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Hui Li
- MOE Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Johannes Krause
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany.
| | - Ron Pinhasi
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.
| | - David Reich
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA.
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43
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Bergström A, Stringer C, Hajdinjak M, Scerri EML, Skoglund P. Origins of modern human ancestry. Nature 2021; 590:229-237. [PMID: 33568824 DOI: 10.1038/s41586-021-03244-5] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 12/14/2020] [Indexed: 01/30/2023]
Abstract
New finds in the palaeoanthropological and genomic records have changed our view of the origins of modern human ancestry. Here we review our current understanding of how the ancestry of modern humans around the globe can be traced into the deep past, and which ancestors it passes through during our journey back in time. We identify three key phases that are surrounded by major questions, and which will be at the frontiers of future research. The most recent phase comprises the worldwide expansion of modern humans between 40 and 60 thousand years ago (ka) and their last known contacts with archaic groups such as Neanderthals and Denisovans. The second phase is associated with a broadly construed African origin of modern human diversity between 60 and 300 ka. The oldest phase comprises the complex separation of modern human ancestors from archaic human groups from 0.3 to 1 million years ago. We argue that no specific point in time can currently be identified at which modern human ancestry was confined to a limited birthplace, and that patterns of the first appearance of anatomical or behavioural traits that are used to define Homo sapiens are consistent with a range of evolutionary histories.
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Affiliation(s)
- Anders Bergström
- Ancient Genomics Laboratory, Francis Crick Institute, London, UK
| | - Chris Stringer
- Department of Earth Sciences, Natural History Museum, London, UK.
| | - Mateja Hajdinjak
- Ancient Genomics Laboratory, Francis Crick Institute, London, UK
| | - Eleanor M L Scerri
- Pan-African Evolution Research Group, Max Planck Institute for Science of Human History, Jena, Germany.,Department of Classics and Archaeology, University of Malta, Msida, Malta.,Institute of Prehistoric Archaeology, University of Cologne, Cologne, Germany
| | - Pontus Skoglund
- Ancient Genomics Laboratory, Francis Crick Institute, London, UK.
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44
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Kulski JK, Suzuki S, Shiina T. SNP-Density Crossover Maps of Polymorphic Transposable Elements and HLA Genes Within MHC Class I Haplotype Blocks and Junction. Front Genet 2021; 11:594318. [PMID: 33537058 PMCID: PMC7848197 DOI: 10.3389/fgene.2020.594318] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 11/24/2020] [Indexed: 12/12/2022] Open
Abstract
The genomic region (~4 Mb) of the human major histocompatibility complex (MHC) on chromosome 6p21 is a prime model for the study and understanding of conserved polymorphic sequences (CPSs) and structural diversity of ancestral haplotypes (AHs)/conserved extended haplotypes (CEHs). The aim of this study was to use a set of 95 MHC genomic sequences downloaded from a publicly available BioProject database at NCBI to identify and characterise polymorphic human leukocyte antigen (HLA) class I genes and pseudogenes, MICA and MICB, and retroelement indels as haplotypic lineage markers, and single-nucleotide polymorphism (SNP) crossover loci in DNA sequence alignments of different haplotypes across the Olfactory Receptor (OR) gene region (~1.2 Mb) and the MHC class I region (~1.8 Mb) from the GPX5 to the MICB gene. Our comparative sequence analyses confirmed the identity of 12 haplotypic retroelement markers and revealed that they partitioned the HLA-A/B/C haplotypes into distinct evolutionary lineages. Crossovers between SNP-poor and SNP-rich regions defined the sequence range of haplotype blocks, and many of these crossover junctions occurred within particular transposable elements, lncRNA, OR12D2, MUC21, MUC22, PSORS1A3, HLA-C, HLA-B, and MICA. In a comparison of more than 250 paired sequence alignments, at least 38 SNP-density crossover sites were mapped across various regions from GPX5 to MICB. In a homology comparison of 16 different haplotypes, seven CEH/AH (7.1, 8.1, 18.2, 51.x, 57.1, 62.x, and 62.1) had no detectable SNP-density crossover junctions and were SNP poor across the entire ~2.8 Mb of sequence alignments. Of the analyses between different recombinant haplotypes, more than half of them had SNP crossovers within 10 kb of LTR16B/ERV3-16A3_I, MLT1, Charlie, and/or THE1 sequences and were in close vicinity to structurally polymorphic Alu and SVA insertion sites. These studies demonstrate that (1) SNP-density crossovers are associated with putative ancestral recombination sites that are widely spread across the MHC class I genomic region from at least the telomeric OR12D2 gene to the centromeric MICB gene and (2) the genomic sequences of MHC homozygous cell lines are useful for analysing haplotype blocks, ancestral haplotypic landscapes and markers, CPSs, and SNP-density crossover junctions.
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Affiliation(s)
- Jerzy K. Kulski
- Faculty of Health and Medical Sciences, Medical School, The University of Western Australia, Crawley, WA, Australia
- Division of Basic Medical Science and Molecular Medicine, Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Japan
| | - Shingo Suzuki
- Division of Basic Medical Science and Molecular Medicine, Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Japan
| | - Takashi Shiina
- Division of Basic Medical Science and Molecular Medicine, Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Japan
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Fraïsse C, Popovic I, Mazoyer C, Spataro B, Delmotte S, Romiguier J, Loire É, Simon A, Galtier N, Duret L, Bierne N, Vekemans X, Roux C. DILS: Demographic inferences with linked selection by using ABC. Mol Ecol Resour 2021; 21:2629-2644. [PMID: 33448666 DOI: 10.1111/1755-0998.13323] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 12/09/2020] [Accepted: 12/21/2020] [Indexed: 01/21/2023]
Abstract
We present DILS, a deployable statistical analysis platform for conducting demographic inferences with linked selection from population genomic data using an Approximate Bayesian Computation framework. DILS takes as input single-population or two-population data sets (multilocus fasta sequences) and performs three types of analyses in a hierarchical manner, identifying: (a) the best demographic model to study the importance of gene flow and population size change on the genetic patterns of polymorphism and divergence, (b) the best genomic model to determine whether the effective size Ne and migration rate N, m are heterogeneously distributed along the genome (implying linked selection) and (c) loci in genomic regions most associated with barriers to gene flow. Also available via a Web interface, an objective of DILS is to facilitate collaborative research in speciation genomics. Here, we show the performance and limitations of DILS by using simulations and finally apply the method to published data on a divergence continuum composed by 28 pairs of Mytilus mussel populations/species.
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Affiliation(s)
- Christelle Fraïsse
- Institute of Science and Technology Austria, Klosterneuœburg, Austria.,Univ. Lille, CNRS, UMR 8198 - Evo-Eco-Paleo, Lille, France
| | - Iva Popovic
- School of Biological Sciences, University of Queensland, St Lucia, Qld, Australia
| | | | - Bruno Spataro
- Laboratoire de Biologie et Biométrie Évolutive CNRS UMR 5558, Université Claude Bernard, Lyon, France
| | - Stéphane Delmotte
- Laboratoire de Biologie et Biométrie Évolutive CNRS UMR 5558, Université Claude Bernard, Lyon, France
| | | | - Étienne Loire
- Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR, ASTRE, Montpellier, France
| | - Alexis Simon
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Nicolas Galtier
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | - Laurent Duret
- Laboratoire de Biologie et Biométrie Évolutive CNRS UMR 5558, Université Claude Bernard, Lyon, France
| | - Nicolas Bierne
- ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France
| | | | - Camille Roux
- Univ. Lille, CNRS, UMR 8198 - Evo-Eco-Paleo, Lille, France
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Pearson OM, Hill EC, Peppe DJ, Van Plantinga A, Blegen N, Faith JT, Tryon CA. A Late Pleistocene human humerus from Rusinga Island, Lake Victoria, Kenya. J Hum Evol 2020; 146:102855. [PMID: 32781348 DOI: 10.1016/j.jhevol.2020.102855] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 07/08/2020] [Accepted: 07/08/2020] [Indexed: 11/16/2022]
Abstract
In 2010, a hominin right humerus fragment (KNM-RU 58330) was surface collected in a small gully at Nyamita North in the Late Pleistocene Wasiriya Beds of Rusinga Island, Kenya. A combination of stratigraphic and geochronological evidence suggests the specimen is likely between ∼49 and 36 ka in age. The associated fauna is diverse and dominated by semiarid grassland taxa. The small sample of associated Middle Stone Age artifacts includes Levallois flakes, cores, and retouched points. The 139 mm humeral fragment preserves the shaft from distal to the lesser tubercle to 14 mm below the distal end of the weakly projecting deltoid tuberosity. Key morphological features include a narrow and weakly marked pectoralis major insertion and a distinctive medial bend in the diaphysis at the deltoid insertion. This bend is unusual among recent human humeri but occurs in a few Late Pleistocene humeri. The dimensions of the distal end of the fragment predict a length of 317.9 ± 16.4 mm based on recent samples of African ancestry. A novel method of predicting humeral length from the distance between the middle of the pectoralis major and the bottom of the deltoid insertion predicts a length of 317.3 mm ± 17.6 mm. Cross-sectional geometry at the midshaft shows a relatively high percentage of cortical bone and a moderate degree of flattening of the shaft. The Nyamita humerus is anatomically modern in its morphology and adds to the small sample of hominins from the Late Pleistocene associated with Middle Stone Age artifacts known from East Africa. It may sample a population closely related to the people of the out-of-Africa migration.
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Affiliation(s)
- Osbjorn M Pearson
- Department of Anthropology, MSC01-1040, University of New Mexico, Albuquerque, NM, 87131, USA.
| | - Ethan C Hill
- Department of Anthropology, MSC01-1040, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Daniel J Peppe
- Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, TX, 76706, USA
| | - Alex Van Plantinga
- Terrestrial Paleoclimatology Research Group, Department of Geosciences, Baylor University, Waco, TX, 76706, USA
| | - Nick Blegen
- Department of Geography, University of Cambridge, Downing Place, Cambridge, CB2 3EN, UK
| | - J Tyler Faith
- Natural History Museum of Utah, Rio Tinto Center, 301 Wakara Way, Salt Lake City, UT, 84108, USA; Department of Anthropology, University of Utah, 260 S. Central Campus Drive, Salt Lake City, UT, 84112, USA
| | - Christian A Tryon
- Department of Anthropology, University of Connecticut, 354 Mansfield Road, Storrs, CT, 06269, USA
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Sellinger TPP, Abu Awad D, Moest M, Tellier A. Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLoS Genet 2020; 16:e1008698. [PMID: 32251472 PMCID: PMC7173940 DOI: 10.1371/journal.pgen.1008698] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 04/21/2020] [Accepted: 02/24/2020] [Indexed: 02/04/2023] Open
Abstract
Several methods based on the Sequential Markovian coalescence (SMC) have been developed that make use of genome sequence data to uncover population demographic history, which is of interest in its own right and is a key requirement to generate a null model for selection tests. While these methods can be applied to all possible kind of species, the underlying assumptions are sexual reproduction in each generation and non-overlapping generations. However, in many plants, invertebrates, fungi and other taxa, those assumptions are often violated due to different ecological and life history traits, such as self-fertilization or long term dormant structures (seed or egg-banking). We develop a novel SMC-based method to infer 1) the rates/parameters of dormancy and of self-fertilization, and 2) the populations' past demographic history. Using simulated data sets, we demonstrate the accuracy of our method for a wide range of demographic scenarios and for sequence lengths from one to 30 Mb using four sampled genomes. Finally, we apply our method to a Swedish and a German population of Arabidopsis thaliana demonstrating a selfing rate of ca. 0.87 and the absence of any detectable seed-bank. In contrast, we show that the water flea Daphnia pulex exhibits a long lived egg-bank of three to 18 generations. In conclusion, we here present a novel method to infer accurate demographies and life-history traits for species with selfing and/or seed/egg-banks. Finally, we provide recommendations for the use of SMC-based methods for non-model organisms, highlighting the importance of the per site and the effective ratios of recombination over mutation.
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Affiliation(s)
| | - Diala Abu Awad
- Department of Population Genetics, Technische Universitaet Muenchen, Freising, Germany
| | - Markus Moest
- Department of Ecology, University of Innsbruck, Innsbruck, Austria
| | - Aurélien Tellier
- Department of Population Genetics, Technische Universitaet Muenchen, Freising, Germany
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