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Rick JA, Brock CD, Lewanski AL, Golcher-Benavides J, Wagner CE. Reference Genome Choice and Filtering Thresholds Jointly Influence Phylogenomic Analyses. Syst Biol 2024; 73:76-101. [PMID: 37881861 DOI: 10.1093/sysbio/syad065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 09/20/2023] [Accepted: 10/20/2023] [Indexed: 10/27/2023] Open
Abstract
Molecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate the extent to which the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find the greatest topological accuracy when filtering sites for minor allele count (MAC) >3-4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with MAC >1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short-read genomic data for phylogenetic inference.
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Affiliation(s)
- Jessica A Rick
- School of Natural Resources & the Environment, University of Arizona, Tucson, AZ 85719, USA
| | - Chad D Brock
- Department of Biological Sciences, Tarleton State University, Stephenville, TX 76401, USA
| | - Alexander L Lewanski
- Department of Integrative Biology and W.K. Kellogg Biological Station, Michigan State University, East Lansing, MI 48824, USA
| | - Jimena Golcher-Benavides
- Department of Natural Resource Ecology and Management, Iowa State University, Ames, IA 50011, USA
| | - Catherine E Wagner
- Program in Ecology and Evolution, University of Wyoming, Laramie, WY 82071, USA
- Department of Botany, University of Wyoming, Laramie, WY 82071, USA
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2
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Liu X, Lin L, Sinding MHS, Bertola LD, Hanghøj K, Quinn L, Garcia-Erill G, Rasmussen MS, Schubert M, Pečnerová P, Balboa RF, Li Z, Heaton MP, Smith TPL, Pinto RR, Wang X, Kuja J, Brüniche-Olsen A, Meisner J, Santander CG, Ogutu JO, Masembe C, da Fonseca RR, Muwanika V, Siegismund HR, Albrechtsen A, Moltke I, Heller R. Introgression and disruption of migration routes have shaped the genetic integrity of wildebeest populations. Nat Commun 2024; 15:2921. [PMID: 38609362 PMCID: PMC11014984 DOI: 10.1038/s41467-024-47015-y] [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: 10/31/2023] [Accepted: 03/11/2024] [Indexed: 04/14/2024] Open
Abstract
The blue wildebeest (Connochaetes taurinus) is a keystone species in savanna ecosystems from southern to eastern Africa, and is well known for its spectacular migrations and locally extreme abundance. In contrast, the black wildebeest (C. gnou) is endemic to southern Africa, barely escaped extinction in the 1900s and is feared to be in danger of genetic swamping from the blue wildebeest. Despite the ecological importance of the wildebeest, there is a lack of understanding of how its unique migratory ecology has affected its gene flow, genetic structure and phylogeography. Here, we analyze whole genomes from 121 blue and 22 black wildebeest across the genus' range. We find discrete genetic structure consistent with the morphologically defined subspecies. Unexpectedly, our analyses reveal no signs of recent interspecific admixture, but rather a late Pleistocene introgression of black wildebeest into the southern blue wildebeest populations. Finally, we find that migratory blue wildebeest populations exhibit a combination of long-range panmixia, higher genetic diversity and lower inbreeding levels compared to neighboring populations whose migration has recently been disrupted. These findings provide crucial insights into the evolutionary history of the wildebeest, and tangible genetic evidence for the negative effects of anthropogenic activities on highly migratory ungulates.
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Affiliation(s)
- Xiaodong Liu
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Long Lin
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | - Laura D Bertola
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kristian Hanghøj
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Liam Quinn
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Mikkel Schubert
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | | | - Renzo F Balboa
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Zilong Li
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Michael P Heaton
- USDA, ARS, U.S. Meat Animal Research Center (USMARC), Clay Center, NE, USA
| | - Timothy P L Smith
- USDA, ARS, U.S. Meat Animal Research Center (USMARC), Clay Center, NE, USA
| | - Rui Resende Pinto
- CIIMAR-Interdisciplinary Centre of Marine and Environmental Research-University of Porto, Porto, Portugal
- Section for Biodiversity, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Xi Wang
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Josiah Kuja
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | - Jonas Meisner
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Copenhagen Research Centre for Mental Health, Copenhagen University Hospital, Copenhagen, Denmark
| | - Cindy G Santander
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Joseph O Ogutu
- Biostatistics Unit, Institute of Crop Science, University of Hohenheim, Stuttgart, Germany
| | - Charles Masembe
- Department of Zoology, Entomology and Fisheries Sciences, Makerere University, P. O. Box 7062, Kampala, Uganda
| | - Rute R da Fonseca
- CIIMAR-Interdisciplinary Centre of Marine and Environmental Research-University of Porto, Porto, Portugal
- Section for Biodiversity, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Vincent Muwanika
- Department of Environmental Management, Makerere University, PO Box 7062, Kampala, Uganda
| | - Hans R Siegismund
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | - Ida Moltke
- Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Rasmus Heller
- Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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3
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Colangelo P, Di Civita M, Bento CM, Franchini P, Meyer A, Orel N, das Neves LCBG, Mulandane FC, Almeida JS, Senczuk G, Pilla F, Sabatelli S. Genome-wide diversity, population structure and signatures of inbreeding in the African buffalo in Mozambique. BMC Ecol Evol 2024; 24:29. [PMID: 38433185 PMCID: PMC10910738 DOI: 10.1186/s12862-024-02209-2] [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: 10/30/2023] [Accepted: 02/01/2024] [Indexed: 03/05/2024] Open
Abstract
The African buffalo, Syncerus caffer, is a key species in African ecosystems. Like other large herbivores, it plays a fundamental role in its habitat acting as an ecosystem engineer. Over the last few centuries, African buffalo populations have declined because of range contraction and demographic decline caused by direct or indirect human activities. In Mozambique, historically home to large buffalo herds, the combined effect of colonialism and subsequent civil wars has created a critical situation that urgently needs to be addressed. In this study, we focused on the analysis of genetic diversity of Syncerus caffer caffer populations from six areas of Mozambique. Using genome-wide SNPs obtained from ddRAD sequencing, we examined the population structure across the country, estimated gene flow between areas under conservation management, including national reserves, and assessed the inbreeding coefficients. Our results indicate that all studied populations of Syncerus caffer caffer are genetically depauperate, with a high level of inbreeding. Moreover, buffaloes in Mozambique present a significant population differentiation between southern and central areas. We found an unexpected genotype in the Gorongosa National Park, where buffaloes experienced a dramatic population size reduction, that shares a common ancestry with southern populations of Catuane and Namaacha. This could suggest the past occurrence of a connection between southern and central Mozambique and that the observed population structuring could reflect recent events of anthropogenic origin. All the populations analysed showed high levels of homozygosity, likely due to extensive inbreeding over the last few decades, which could have increased the frequency of recessive deleterious alleles. Improving the resilience of Syncerus caffer caffer in Mozambique is essential for preserving the ecosystem integrity. The most viable approach appears to be facilitating translocations and re-establishing connectivity between isolated herds. However, our results also highlight the importance of assessing intraspecific genetic diversity when considering interventions aimed at enhancing population viability such as selecting suitable source populations.
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Affiliation(s)
- Paolo Colangelo
- National Research Council, Research Institute on Terrestrial Ecosystems, Via Salaria km 29.300, 00015, Montelibretti (Roma), Italy
| | - Marika Di Civita
- Department of Agricultural, Environmental and Food Sciences, University of Molise, 86100, Campobasso, Italy
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University, Viale dell'Università 32, 00185, Roma, Italy
| | - Carlos M Bento
- Natural History Museum, Eduardo Mondlane University, Travessia do Zambeze 104, 1100, Maputo, Mozambique
| | - Paolo Franchini
- Department of Biology, University of Konstanz, Konstanz, Germany.
- Department of Ecological and Biological Sciences, University of Tuscia, Viale dell'Università s.n.c, 01100, Viterbo, Italy.
| | - Axel Meyer
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Nadiya Orel
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Luis C B G das Neves
- Biotechnology Centre of Eduardo Mondlane University, Maputo, Mozambique
- Department of Veterinary Tropical Diseases, Faculty of Veterinary Sciences, University of Pretoria, Pretoria, South Africa
| | | | | | - Gabriele Senczuk
- Department of Agricultural, Environmental and Food Sciences, University of Molise, 86100, Campobasso, Italy
| | - Fabio Pilla
- Department of Agricultural, Environmental and Food Sciences, University of Molise, 86100, Campobasso, Italy
| | - Simone Sabatelli
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University, Viale dell'Università 32, 00185, Roma, Italy
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Lukaszewicz M, Salia OI, Hohenlohe PA, Buzbas EO. Approximate Bayesian computational methods to estimate the strength of divergent selection in population genomics models. JOURNAL OF COMPUTATIONAL MATHEMATICS AND DATA SCIENCE 2024; 10:100091. [PMID: 38616846 PMCID: PMC11014422 DOI: 10.1016/j.jcmds.2024.100091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Statistical estimation of parameters in large models of evolutionary processes is often too computationally inefficient to pursue using exact model likelihoods, even with single-nucleotide polymorphism (SNP) data, which offers a way to reduce the size of genetic data while retaining relevant information. Approximate Bayesian Computation (ABC) to perform statistical inference about parameters of large models takes the advantage of simulations to bypass direct evaluation of model likelihoods. We develop a mechanistic model to simulate forward-in-time divergent selection with variable migration rates, modes of reproduction (sexual, asexual), length and number of migration-selection cycles. We investigate the computational feasibility of ABC to perform statistical inference and study the quality of estimates on the position of loci under selection and the strength of selection. To expand the parameter space of positions under selection, we enhance the model by implementing an outlier scan on summarized observed data. We evaluate the usefulness of summary statistics well-known to capture the strength of selection, and assess their informativeness under divergent selection. We also evaluate the effect of genetic drift with respect to an idealized deterministic model with single-locus selection. We discuss the role of the recombination rate as a confounding factor in estimating the strength of divergent selection, and emphasize its importance in break down of linkage disequilibrium (LD). We answer the question for which part of the parameter space of the model we recover strong signal for estimating the selection, and determine whether population differentiation-based summary statistics or LD-based summary statistics perform well in estimating selection.
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Affiliation(s)
- Martyna Lukaszewicz
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
- Department of Biological Sciences, University of Idaho, Moscow, ID, United States of America
| | - Ousseini Issaka Salia
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Institute for Modeling Collaboration and Innovation (IMCI), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
- Department of Biological Sciences, University of Idaho, Moscow, ID, United States of America
- Department of Horticulture, Washington State University, Pullman, WA, United States of America
| | - Paul A. Hohenlohe
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Institute for Modeling Collaboration and Innovation (IMCI), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
- Department of Biological Sciences, University of Idaho, Moscow, ID, United States of America
| | - Erkan O. Buzbas
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Institute for Modeling Collaboration and Innovation (IMCI), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
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5
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Chen W, Xiang D, Gao S, Zhu S, Wu Z, Li Y, Li J. Whole-genome resequencing confirms the genetic effects of dams on an endangered fish Hemibagrus guttatus (Siluriformes: Bagridae): A case study in a tributary of the Pearl River. Gene 2024; 895:148000. [PMID: 37979951 DOI: 10.1016/j.gene.2023.148000] [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: 09/02/2023] [Revised: 10/31/2023] [Accepted: 11/08/2023] [Indexed: 11/20/2023]
Abstract
Dam construction in riverine ecosystems has fragmented natural aquatic habitats and has altered environmental conditions. As a result, damming has been demonstrated to threaten aquatic biodiversity by reducing species distribution ranges and hindering gene exchange, leading to the inability to adapt to environmental changes. Knowledge of the contemporary genetic diversity and genetic structure of fish populations that are separated by dams is vital to developing effective conservation strategies, particularly for endangered fish species. We chose the Lianjiang River, a tributary of the Pearl River, as a case study to assess the effects of dams on the genetic diversity and genetic structure of an endangered fish species, Hemibagrus guttatus, using whole-genome resequencing data from 63 fish samples. The results indicated low levels of genetic diversity, high levels of inbreeding and decreasing trend of effective population size in fragmented H. guttatus populations. In addition, there were significant genetic structure and genetic differentiation among populations, suggesting that the dams might have affected H. guttatus populations. Our findings may benefit management and conservation practices for this endangered species that is currently suffering from the effects of dam construction.
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Affiliation(s)
- Weitao Chen
- Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China; Key Laboratory of Aquatic Animal Immune Technology of Guangdong Province, Guangzhou 510380, China; Guangzhou Scientific Observing and Experimental Station of National Fisheries Resources and Environment, Guangzhou 510380, China
| | - Denggao Xiang
- Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China
| | - Shang Gao
- Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China
| | - Shuli Zhu
- Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China; Key Laboratory of Aquatic Animal Immune Technology of Guangdong Province, Guangzhou 510380, China; Guangzhou Scientific Observing and Experimental Station of National Fisheries Resources and Environment, Guangzhou 510380, China
| | - Zhi Wu
- Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China; Key Laboratory of Aquatic Animal Immune Technology of Guangdong Province, Guangzhou 510380, China; Guangzhou Scientific Observing and Experimental Station of National Fisheries Resources and Environment, Guangzhou 510380, China
| | - Yuefei Li
- Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China; Key Laboratory of Aquatic Animal Immune Technology of Guangdong Province, Guangzhou 510380, China; Guangzhou Scientific Observing and Experimental Station of National Fisheries Resources and Environment, Guangzhou 510380, China
| | - Jie Li
- Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China; Key Laboratory of Aquatic Animal Immune Technology of Guangdong Province, Guangzhou 510380, China; Guangzhou Scientific Observing and Experimental Station of National Fisheries Resources and Environment, Guangzhou 510380, China.
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6
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Xu X, Wang C, Xu C, Yuan J, Wang G, Wu Y, Huang C, Jing H, Yang P, Xu L, Peng S, Shan F, Xia X, Jin F, Hou F, Wang J, Mi D, Ren Y, Liu Y, Irwin DM, Li X, Chen W, Li G. Genomic evolution of island birds from the view of the Swinhoe's pheasant (Lophura swinhoii). Mol Ecol Resour 2024; 24:e13896. [PMID: 37955396 DOI: 10.1111/1755-0998.13896] [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: 07/05/2023] [Revised: 10/26/2023] [Accepted: 10/31/2023] [Indexed: 11/14/2023]
Abstract
Island endemic birds account for the majority of extinct vertebrates in the past few centuries. To date, the evolutionary characteristics of island endemic bird's is poorly known. In this research, we de novo assembled a high-quality chromosome-level reference genome for the Swinhoe's pheasant, which is a typical endemic island bird. Results of collinearity tests suggest rapid ancient chromosome rearrangement that may have contributed to the initial species radiation within Phasianidae, and a role for the insertions of CR1 transposable elements in rearranging chromosomes in Phasianidae. During the evolution of the Swinhoe's pheasant, natural selection positively selected genes involved in fecundity and body size functions, at both the species and population levels, which reflect genetic variation associated with island adaptation. We further tested for variation in population genomic traits between the Swinhoe's pheasant and its phylogenetically closely related mainland relative the silver pheasant, and found higher levels of genetic drift and inbreeding in the Swinhoe's pheasant genome. Divergent demographic histories of insular and mainland bird species during the last glacial period may reflect the differing impact of insular and continental climates on the evolution of species. Our research interprets the natural history and population genetic characteristics of the insular endemic bird the Swinhoe's pheasant, at a genome-wide scale, provides a broader perspective on insular speciation, and adaptive evolution and contributes to the genetic conservation of island endemic birds.
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Affiliation(s)
- Xiao Xu
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Chen Wang
- Guangzhou Zoo, Guangzhou, China
- Guangzhou Collaborative Innovation Center on Science-Tech of Ecology and Landscape, Guangzhou, China
| | - Chunzhong Xu
- Shanghai Wild Animal Park Development Co., Ltd, Shanghai, China
| | - Jiaqing Yuan
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Guiqiang Wang
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Yajiang Wu
- Guangzhou Zoo, Guangzhou, China
- Guangzhou Collaborative Innovation Center on Science-Tech of Ecology and Landscape, Guangzhou, China
| | - Chen Huang
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Haohao Jing
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Peng Yang
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Lulu Xu
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Shiming Peng
- Guangzhou Zoo, Guangzhou, China
- Guangzhou Collaborative Innovation Center on Science-Tech of Ecology and Landscape, Guangzhou, China
| | - Fen Shan
- Guangzhou Zoo, Guangzhou, China
- Guangzhou Collaborative Innovation Center on Science-Tech of Ecology and Landscape, Guangzhou, China
| | - Xiaochao Xia
- Guangdong Wildlife Monitoring, Rescue and Conservation Center, Guangzhou, China
| | - Fuyuan Jin
- Guangdong Maoming Forest Park Administrative Office, Maoming, China
| | - Fanghui Hou
- Shanghai Wild Animal Park Development Co., Ltd, Shanghai, China
| | - Jinhong Wang
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Da Mi
- Xi'an Haorui Genomics Technology Co., Ltd, Xi'an, China
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Yandong Ren
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Yang Liu
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - David M Irwin
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Xuejuan Li
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Wu Chen
- Guangzhou Zoo, Guangzhou, China
- Guangzhou Collaborative Innovation Center on Science-Tech of Ecology and Landscape, Guangzhou, China
| | - Gang Li
- College of Life Sciences, Shaanxi Normal University, Xi'an, China
- Guangzhou Zoo, Guangzhou, China
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7
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Naji MM, Gualdrón Duarte JL, Forneris NS, Druet T. Inbreeding depression is associated with recent homozygous-by-descent segments in Belgian Blue beef cattle. Genet Sel Evol 2024; 56:10. [PMID: 38297209 PMCID: PMC10832232 DOI: 10.1186/s12711-024-00878-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 01/19/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Cattle populations harbor generally high inbreeding levels that can lead to inbreeding depression (ID). Here, we study ID with different estimators of the inbreeding coefficient F, evaluate their sensitivity to used allele frequencies (founder versus sample allele frequencies), and compare effects from recent and ancient inbreeding. METHODS We used data from 14,205 Belgian Blue beef cattle genotyped cows that were phenotyped for 11 linear classification traits. We computed estimators of F based on the pedigree information (FPED), on the correlation between uniting gametes (FUNI), on the genomic relationship matrix (FGRM), on excess homozygosity (FHET), or on homozygous-by-descent (HBD) segments (FHBD). RESULTS FUNI and FGRM were sensitive to used allele frequencies, whereas FHET and FHBD were more robust. We detected significant ID for four traits related to height and length; FHBD and FUNI presenting the strongest associations. Then, we took advantage of the classification of HBD segments in different age-related classes (the length of an HBD segment being inversely related to the number of generations to the common ancestors) to determine that recent HBD classes (common ancestors present approximately up to 15 generations in the past) presented stronger ID than more ancient HBD classes. We performed additional analyses to check whether these observations could result from a lower level of variation in ancient HBD classes, or from a reduced precision to identify these shorter segments. CONCLUSIONS Overall, our results suggest that mutational load decreases with haplotype age, and that mating plans should consider mainly the levels of recent inbreeding.
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Affiliation(s)
- Maulana Mughitz Naji
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Quartier Hôpital, Avenue de l'Hôpital, 11, 4000, Liege, Belgium.
| | - José Luis Gualdrón Duarte
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Quartier Hôpital, Avenue de l'Hôpital, 11, 4000, Liege, Belgium
- Walloon Breeders Association (awe groupe), 5590, Ciney, Belgium
| | - Natalia Soledad Forneris
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Quartier Hôpital, Avenue de l'Hôpital, 11, 4000, Liege, Belgium
| | - Tom Druet
- Unit of Animal Genomics, GIGA-R & Faculty of Veterinary Medicine, University of Liège, Quartier Hôpital, Avenue de l'Hôpital, 11, 4000, Liege, Belgium
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8
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Sang H, Li Y, Tan S, Gao P, Wang B, Guo S, Luo S, Sun C. Conservation genomics analysis reveals recent population decline and possible causes in bumblebee Bombus opulentus. INSECT SCIENCE 2024. [PMID: 38297451 DOI: 10.1111/1744-7917.13324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 11/29/2023] [Accepted: 12/07/2023] [Indexed: 02/02/2024]
Abstract
Bumblebees are a genus of pollinators (Bombus) that play important roles in natural ecosystem and agricultural production. Several bumblebee species have been recorded as under population decline, and the proportion of species experiencing population decline within subgenus Thoracobombus is higher than average. Bombus opulentus is 1 species in Thoracobombus, but little is known about its recent population dynamics. Here, we employed conservation genomics methods to investigate the population dynamics of B. opulentus during the recent past and identify the likely environmental factors that may cause population decline. Firstly, we placed the scaffold-level of B. opulentus reference genome sequence onto chromosome-level using Hi-C technique. Then, based on this reference genome and whole-genome resequencing data for 51 B. opulentus samples, we reconstructed the population structure and effective population size (Ne ) trajectories of B. opulentus and identified genes that were under positive selection. Our results revealed that the collected B. opulentus samples could be divided into 2 populations, and 1 of them experienced a recent population decline; the declining population also exhibited lower genetic diversity and higher inbreeding levels. Genes related to high-temperature tolerance, immune response, and detoxication showed signals of positive selection in the declining population, suggesting that climate warming and pathogen/pesticide exposures may contribute to the decline of this B. opulentus population. Taken together, our study provided insights into the demography of B. opulentus populations and highlighted that populations of the same bumblebee species could have contrasting Ne trajectories and population decline could be caused by a combination of various stressors.
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Affiliation(s)
- Huiling Sang
- College of Life Sciences, Capital Normal University, Beijing, China
- State Key Laboratory of Resource Insects, Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yancan Li
- State Key Laboratory of Resource Insects, Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
- Western Research Institute, Chinese Academy of Agricultural Sciences, Changji, Xinjiang, China
| | - Shuxin Tan
- College of Life Sciences, Capital Normal University, Beijing, China
| | - Pu Gao
- College of Life Sciences, Capital Normal University, Beijing, China
| | - Bei Wang
- Yan'an Beekeeping Experimental Station, Yan'an, Shannxi, China
| | - Shengnan Guo
- Hengshui center for Disease Prevention and Control, Hengshui, Hebei, China
| | - Shudong Luo
- State Key Laboratory of Resource Insects, Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
- Western Research Institute, Chinese Academy of Agricultural Sciences, Changji, Xinjiang, China
| | - Cheng Sun
- College of Life Sciences, Capital Normal University, Beijing, China
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9
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Balboa RF, Bertola LD, Brüniche-Olsen A, Rasmussen MS, Liu X, Besnard G, Salmona J, Santander CG, He S, Zinner D, Pedrono M, Muwanika V, Masembe C, Schubert M, Kuja J, Quinn L, Garcia-Erill G, Stæger FF, Rakotoarivony R, Henrique M, Lin L, Wang X, Heaton MP, Smith TPL, Hanghøj K, Sinding MHS, Atickem A, Chikhi L, Roos C, Gaubert P, Siegismund HR, Moltke I, Albrechtsen A, Heller R. African bushpigs exhibit porous species boundaries and appeared in Madagascar concurrently with human arrival. Nat Commun 2024; 15:172. [PMID: 38172616 PMCID: PMC10764920 DOI: 10.1038/s41467-023-44105-1] [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: 08/23/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
Several African mammals exhibit a phylogeographic pattern where closely related taxa are split between West/Central and East/Southern Africa, but their evolutionary relationships and histories remain controversial. Bushpigs (Potamochoerus larvatus) and red river hogs (P. porcus) are recognised as separate species due to morphological distinctions, a perceived lack of interbreeding at contact, and putatively old divergence times, but historically, they were considered conspecific. Moreover, the presence of Malagasy bushpigs as the sole large terrestrial mammal shared with the African mainland raises intriguing questions about its origin and arrival in Madagascar. Analyses of 67 whole genomes revealed a genetic continuum between the two species, with putative signatures of historical gene flow, variable FST values, and a recent divergence time (<500,000 years). Thus, our study challenges key arguments for splitting Potamochoerus into two species and suggests their speciation might be incomplete. Our findings also indicate that Malagasy bushpigs diverged from southern African populations and underwent a limited bottleneck 1000-5000 years ago, concurrent with human arrival in Madagascar. These results shed light on the evolutionary history of an iconic and widespread African mammal and provide insight into the longstanding biogeographic puzzle surrounding the bushpig's presence in Madagascar.
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Affiliation(s)
- Renzo F Balboa
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Laura D Bertola
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Xiaodong Liu
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Guillaume Besnard
- Laboratoire Evolution et Diversité Biologique (EDB), UMR 5174, CNRS, IRD, Université Toulouse Paul Sabatier, 31062, Toulouse, France
| | - Jordi Salmona
- Laboratoire Evolution et Diversité Biologique (EDB), UMR 5174, CNRS, IRD, Université Toulouse Paul Sabatier, 31062, Toulouse, France
| | - Cindy G Santander
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Shixu He
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Dietmar Zinner
- Cognitive Ecology Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077, Göttingen, Germany
- Department of Primate Cognition, Georg-August-Universität Göttingen, 37077, Göttingen, Germany
- Leibniz Science Campus Primate Cognition, 37077, Göttingen, Germany
| | - Miguel Pedrono
- UMR ASTRE, CIRAD, Campus International de Baillarguet, Montpellier, France
| | - Vincent Muwanika
- College of Agricultural and Environmental Sciences, Makerere University, Kampala, Uganda
| | - Charles Masembe
- College of Natural Sciences, Makerere University, Kampala, Uganda
| | - Mikkel Schubert
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Josiah Kuja
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Liam Quinn
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | | | | | | | - Long Lin
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Xi Wang
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Kristian Hanghøj
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | - Anagaw Atickem
- Department of Zoological Sciences, Addis Ababa University, PO Box 1176, Addis Ababa, Ethiopia
| | - Lounès Chikhi
- Laboratoire Evolution et Diversité Biologique (EDB), UMR 5174, CNRS, IRD, Université Toulouse Paul Sabatier, 31062, Toulouse, France
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077, Göttingen, Germany
| | - Philippe Gaubert
- Laboratoire Evolution et Diversité Biologique (EDB), UMR 5174, CNRS, IRD, Université Toulouse Paul Sabatier, 31062, Toulouse, France
- Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR), Universidade do Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos, s/n, 4450-208, Porto, Portugal
| | - Hans R Siegismund
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Ida Moltke
- Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | | | - Rasmus Heller
- Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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10
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Pečnerová P, Lord E, Garcia-Erill G, Hanghøj K, Rasmussen MS, Meisner J, Liu X, van der Valk T, Santander CG, Quinn L, Lin L, Liu S, Carøe C, Dalerum F, Götherström A, Måsviken J, Vartanyan S, Raundrup K, Al-Chaer A, Rasmussen L, Hvilsom C, Heide-Jørgensen MP, Sinding MHS, Aastrup P, Van Coeverden de Groot PJ, Schmidt NM, Albrechtsen A, Dalén L, Heller R, Moltke I, Siegismund HR. Population genomics of the muskox' resilience in the near absence of genetic variation. Mol Ecol 2024; 33:e17205. [PMID: 37971141 DOI: 10.1111/mec.17205] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/07/2023] [Accepted: 11/01/2023] [Indexed: 11/19/2023]
Abstract
Genomic studies of species threatened by extinction are providing crucial information about evolutionary mechanisms and genetic consequences of population declines and bottlenecks. However, to understand how species avoid the extinction vortex, insights can be drawn by studying species that thrive despite past declines. Here, we studied the population genomics of the muskox (Ovibos moschatus), an Ice Age relict that was at the brink of extinction for thousands of years at the end of the Pleistocene yet appears to be thriving today. We analysed 108 whole genomes, including present-day individuals representing the current native range of both muskox subspecies, the white-faced and the barren-ground muskox (O. moschatus wardi and O. moschatus moschatus) and a ~21,000-year-old ancient individual from Siberia. We found that the muskox' demographic history was profoundly shaped by past climate changes and post-glacial re-colonizations. In particular, the white-faced muskox has the lowest genome-wide heterozygosity recorded in an ungulate. Yet, there is no evidence of inbreeding depression in native muskox populations. We hypothesize that this can be explained by the effect of long-term gradual population declines that allowed for purging of strongly deleterious mutations. This study provides insights into how species with a history of population bottlenecks, small population sizes and low genetic diversity survive against all odds.
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Affiliation(s)
- Patrícia Pečnerová
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
- Copenhagen Zoo, Frederiksberg, Denmark
| | - Edana Lord
- Centre for Palaeogenetics, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
- Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Genís Garcia-Erill
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kristian Hanghøj
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Malthe Sebro Rasmussen
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jonas Meisner
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Xiaodong Liu
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Tom van der Valk
- Centre for Palaeogenetics, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Cindy G Santander
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Liam Quinn
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | - Long Lin
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Shanlin Liu
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- The GLOBE Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian Carøe
- The GLOBE Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Fredrik Dalerum
- Department of Zoology, Stockholm University, Stockholm, Sweden
- Biodiversity Research Institute (CSIC-UO-PA), Mieres, Spain
- Department of Zoology and Entomology, Mammal Research Institute, University of Pretoria, Hatfield, South Africa
| | - Anders Götherström
- Centre for Palaeogenetics, Stockholm, Sweden
- Archaeological Research Laboratory, Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden
| | - Johannes Måsviken
- Centre for Palaeogenetics, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
- Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Sergey Vartanyan
- North-East Interdisciplinary Scientific Research Institute N.A.N.A. Shilo, Russian Academy of Sciences, Magadan, Russia
| | | | - Amal Al-Chaer
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Linett Rasmussen
- Copenhagen Zoo, Frederiksberg, Denmark
- The GLOBE Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Mads Peter Heide-Jørgensen
- Greenland Institute of Natural Resources, Nuuk, Greenland
- Greenland Institute of Natural Resources, Copenhagen, Denmark
| | - Mikkel-Holger S Sinding
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - Peter Aastrup
- Department of Ecoscience, Aarhus University, Roskilde, Denmark
- Arctic Research Centre, Aarhus University, Aarhus, Denmark
| | | | - Niels Martin Schmidt
- Department of Ecoscience, Aarhus University, Roskilde, Denmark
- Arctic Research Centre, Aarhus University, Aarhus, Denmark
| | - Anders Albrechtsen
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Love Dalén
- Centre for Palaeogenetics, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
- Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Ida Moltke
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Hans Redlef Siegismund
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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11
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Benjelloun B, Leempoel K, Boyer F, Stucki S, Streeter I, Orozco-terWengel P, Alberto FJ, Servin B, Biscarini F, Alberti A, Engelen S, Stella A, Colli L, Coissac E, Bruford MW, Ajmone-Marsan P, Negrini R, Clarke L, Flicek P, Chikhi A, Joost S, Taberlet P, Pompanon F. Multiple genomic solutions for local adaptation in two closely related species (sheep and goats) facing the same climatic constraints. Mol Ecol 2023:e17257. [PMID: 38149334 DOI: 10.1111/mec.17257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 08/18/2023] [Accepted: 12/05/2023] [Indexed: 12/28/2023]
Abstract
The question of how local adaptation takes place remains a fundamental question in evolutionary biology. The variation of allele frequencies in genes under selection over environmental gradients remains mainly theoretical and its empirical assessment would help understanding how adaptation happens over environmental clines. To bring new insights to this issue we set up a broad framework which aimed to compare the adaptive trajectories over environmental clines in two domesticated mammal species co-distributed in diversified landscapes. We sequenced the genomes of 160 sheep and 161 goats extensively managed along environmental gradients, including temperature, rainfall, seasonality and altitude, to identify genes and biological processes shaping local adaptation. Allele frequencies at putatively adaptive loci were rarely found to vary gradually along environmental gradients, but rather displayed a discontinuous shift at the extremities of environmental clines. Of the 430 candidate adaptive genes identified, only 6 were orthologous between sheep and goats and those responded differently to environmental pressures, suggesting different putative mechanisms involved in local adaptation in these two closely related species. Interestingly, the genomes of the 2 species were impacted differently by the environment, genes related to signatures of selection were most related to altitude, slope and rainfall seasonality for sheep, and summer temperature and spring rainfall for goats. The diversity of candidate adaptive pathways may result from a high number of biological functions involved in the adaptations to multiple eco-climatic gradients, and a differential role of climatic drivers on the two species, despite their co-distribution along the same environmental gradients. This study describes empirical examples of clinal variation in putatively adaptive alleles with different patterns in allele frequency distributions over continuous environmental gradients, thus showing the diversity of genetic responses in adaptive landscapes and opening new horizons for understanding genomics of adaptation in mammalian species and beyond.
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Affiliation(s)
- Badr Benjelloun
- Livestock Genomics Laboratory, Regional Center of Agricultural Research Tadla, National Institute of Agricultural Research INRA, Rabat, Morocco
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Kevin Leempoel
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Frédéric Boyer
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Sylvie Stucki
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ian Streeter
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Pablo Orozco-terWengel
- School of Biosciences, Cardiff University, Wales, UK
- Sustainable Places Research Institute, Cardiff University, Cardiff, UK
| | - Florian J Alberto
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Bertrand Servin
- GenPhySE, Université de Toulouse, INRAE, INPT, ENVT, Castanet-Tolosan, France
| | - Filippo Biscarini
- Institute of Agricultural Biology and Biotechnology, Consiglio Nazionale delle Ricerche (CNR), Milan, Italy
| | - Adriana Alberti
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ. Evry, Université Paris-Saclay, Evry, France
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette, France
| | - Stefan Engelen
- Genoscope, Institut de biologie François-Jacob, Commissariat à l'Energie Atomique CEA, Université Paris-Saclay, Evry, France
| | - Alessandra Stella
- Institute of Agricultural Biology and Biotechnology, Consiglio Nazionale delle Ricerche (CNR), Milan, Italy
| | - Licia Colli
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
- BioDNA - Centro di Ricerca sulla Biodiversità e sul DNA Antico, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Eric Coissac
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - Michael W Bruford
- School of Biosciences, Cardiff University, Wales, UK
- Sustainable Places Research Institute, Cardiff University, Cardiff, UK
| | - Paolo Ajmone-Marsan
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
- BioDNA - Centro di Ricerca sulla Biodiversità e sul DNA Antico, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Riccardo Negrini
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, Piacenza, Italy
- AIA Associazione Italiana Allevatori, Roma, Italy
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Abdelkader Chikhi
- Livestock Genomics Laboratory, Regional Center of Agricultural Research Tadla, National Institute of Agricultural Research INRA, Rabat, Morocco
| | - Stéphane Joost
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pierre Taberlet
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | - François Pompanon
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
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12
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Carvalho J, Morales HE, Faria R, Butlin RK, Sousa VC. Integrating Pool-seq uncertainties into demographic inference. Mol Ecol Resour 2023; 23:1737-1755. [PMID: 37475177 DOI: 10.1111/1755-0998.13834] [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: 12/02/2022] [Revised: 06/16/2023] [Accepted: 06/30/2023] [Indexed: 07/22/2023]
Abstract
Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modelling Pool-seq sources of error. By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome) and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin) and to infer relevant demographic parameters (e.g. effective sizes and split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e. single origin) and are maintained despite gene flow. These results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.
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Affiliation(s)
- João Carvalho
- cE3c - Centre for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Departamento de Biologia Animal, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Portugal
| | - Hernán E Morales
- Section for Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rui Faria
- CIBIO - Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO, Laboratório Associado, Universidade do Porto, Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Vairão, Portugal
| | - Roger K Butlin
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Sheffield, UK
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Vítor C Sousa
- cE3c - Centre for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Departamento de Biologia Animal, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Portugal
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13
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Novo I, Pérez-Pereira N, Santiago E, Quesada H, Caballero A. An empirical test of the estimation of historical effective population size using Drosophila melanogaster. Mol Ecol Resour 2023; 23:1632-1640. [PMID: 37455584 DOI: 10.1111/1755-0998.13837] [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: 03/06/2023] [Revised: 06/07/2023] [Accepted: 07/05/2023] [Indexed: 07/18/2023]
Abstract
The availability of a large number of high-density markers (SNPs) allows the estimation of historical effective population size (Ne ) from linkage disequilibrium between loci. A recent refinement of methods to estimate historical Ne from the recent past has been shown to be rather accurate with simulation data. The method has also been applied to real data for numerous species. However, the simulation data cannot encompass all the complexities of real genomes, and the performance of any estimation method with real data is always uncertain, as the true demography of the populations is not known. Here, we carried out an experimental design with Drosophila melanogaster to test the method with real data following a known demographic history. We used a population maintained in the laboratory with a constant census size of about 2800 individuals and subjected the population to a drastic decline to a size of 100 individuals. After a few generations, the population was expanded back to the previous size and after a few further generations again expanded to twice the initial size. Estimates of historical Ne were obtained with the software GONE both for autosomal and X chromosomes from samples of 17 individuals sequenced for the whole genome. Estimates of the historical effective size were able to infer the patterns of changes that occurred in the populations showing generally good performance of the method. We discuss the limitations of the method and the application of the software carried out so far.
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Affiliation(s)
- Irene Novo
- Centro de Investigación Mariña, Universidade de Vigo, Facultade de Bioloxía, Vigo, Spain
| | - Noelia Pérez-Pereira
- Centro de Investigación Mariña, Universidade de Vigo, Facultade de Bioloxía, Vigo, Spain
| | - Enrique Santiago
- Departamento de Biología Funcional, Facultad de Biología, Universidad de Oviedo, Oviedo, Spain
| | - Humberto Quesada
- Centro de Investigación Mariña, Universidade de Vigo, Facultade de Bioloxía, Vigo, Spain
| | - Armando Caballero
- Centro de Investigación Mariña, Universidade de Vigo, Facultade de Bioloxía, Vigo, Spain
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14
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Moorjani P, Hellenthal G. Methods for Assessing Population Relationships and History Using Genomic Data. Annu Rev Genomics Hum Genet 2023; 24:305-332. [PMID: 37220313 PMCID: PMC11040641 DOI: 10.1146/annurev-genom-111422-025117] [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] [Indexed: 05/25/2023]
Abstract
Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.
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Affiliation(s)
- Priya Moorjani
- Department of Molecular and Cell Biology and Center for Computational Biology, University of California, Berkeley, California, USA;
| | - Garrett Hellenthal
- UCL Genetics Institute and Research Department of Genetics, Evolution, and Environment, University College London, London, United Kingdom;
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15
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Ginja C, Guimarães S, da Fonseca RR, Rasteiro R, Rodríguez-Varela R, Simões LG, Sarmento C, Belarte MC, Kallala N, Torres JR, Sanmartí J, Arruda AM, Detry C, Davis S, Matos J, Götherström A, Pires AE, Valenzuela-Lamas S. Iron age genomic data from Althiburos - Tunisia renew the debate on the origins of African taurine cattle. iScience 2023; 26:107196. [PMID: 37485357 PMCID: PMC10359934 DOI: 10.1016/j.isci.2023.107196] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 12/22/2022] [Accepted: 06/20/2023] [Indexed: 07/25/2023] Open
Abstract
The Maghreb is a key region for understanding the dynamics of cattle dispersal and admixture with local aurochs following their earliest domestication in the Fertile Crescent more than 10,000 years ago. Here, we present data on autosomal genomes and mitogenomes obtained for four archaeological specimens of Iron Age (∼2,800 cal BP-2,000 cal BP) domestic cattle from the Eastern Maghreb, i.e. Althiburos (El Kef, Tunisia). D-loop sequences were obtained for an additional eight cattle specimens from this site. Maternal lineages were assigned to the elusive R and ubiquitous African-T1 haplogroups found in two and ten Althiburos specimens, respectively. Our results can be explained by post-domestication hybridization of Althiburos cattle with local aurochs. However, we cannot rule out an independent domestication in North Africa considering the shared ancestry of Althiburos cattle with the pre-domestic Moroccan aurochs and present-day African taurine cattle.
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Affiliation(s)
- Catarina Ginja
- BIOPOLIS-CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos - ArchGen group, Universidade do Porto, Vairão, Portugal
| | - Silvia Guimarães
- BIOPOLIS-CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos - ArchGen group, Universidade do Porto, Vairão, Portugal
| | - Rute R. da Fonseca
- Center for Global Mountain Biodiversity, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rita Rasteiro
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | | | - Luciana G. Simões
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Cindy Sarmento
- BIOPOLIS-CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos - ArchGen group, Universidade do Porto, Vairão, Portugal
| | - Maria Carme Belarte
- ICREA, Institut Català de Recerca i Estudis Avançats, Barcelona, Spain
- ICAC, Institut Català d'Arqueologia Clàssica, Tarragona, Spain
| | - Nabil Kallala
- INP, Institut National du Patrimoine, Tunis, Tunisia
- Faculté des Sciences Humaines et Sociales, Université de Tunis, Tunis, Tunisia
| | | | - Joan Sanmartí
- In memoriam, Departament de Prehistòria, Història Antiga i Arqueologia, Universitat de Barcelona, Barcelona, Spain
| | - Ana Margarida Arruda
- UNIARQ, Centro de Arqueologia da Universidade de Lisboa, Faculdade de Letras da Universidade de Lisboa, Lisboa, Portugal
| | - Cleia Detry
- UNIARQ, Centro de Arqueologia da Universidade de Lisboa, Faculdade de Letras da Universidade de Lisboa, Lisboa, Portugal
| | - Simon Davis
- BIOPOLIS-CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos - ArchGen group, Universidade do Porto, Vairão, Portugal
- LARC/DGPC, Laboratório de Arqueociências, Direcção Geral do Património Cultural, Lisboa, Portugal
| | - José Matos
- Unidade Estratégica de Investigação e Serviços de Biotecnologia e Recursos Genéticos, Instituto Nacional de Investigação Agrária e Veterinária, I.P, Oeiras, Portugal
- CE3C, Centro de Ecologia, Evolução e Alterações Ambientais, Universidade de Lisboa, Lisboa, Portugal
| | | | - Ana Elisabete Pires
- BIOPOLIS-CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos - ArchGen group, Universidade do Porto, Vairão, Portugal
- Faculdade de Medicina Veterinária, Universidade Lusófona, Lisboa, Portugal
| | - Silvia Valenzuela-Lamas
- UNIARQ, Centro de Arqueologia da Universidade de Lisboa, Faculdade de Letras da Universidade de Lisboa, Lisboa, Portugal
- Archaeology of Social Dynamics, Consejo Superior de Investigaciones Científicas-Institució Milà i Fontanals d'Humanitats (CSIC-IMF), Barcelona, Spain
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16
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Chang G, Yuan X, Guo Q, Bai H, Cao X, Liu M, Wang Z, Li B, Wang S, Jiang Y, Wang Z, Zhang Y, Xu Q, Song Q, Pan R, Qiu L, Gu T, Wu X, Bi Y, Cao Z, Zhang Y, Chen Y, Li H, Liu J, Dai W, Chen G. The First Crested Duck Genome Reveals Clues to Genetic Compensation and Crest Cushion Formation. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:483-500. [PMID: 37652165 PMCID: PMC10787023 DOI: 10.1016/j.gpb.2023.08.002] [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: 01/26/2021] [Revised: 07/05/2023] [Accepted: 08/15/2023] [Indexed: 09/02/2023]
Abstract
The Chinese crested (CC) duck is a unique indigenous waterfowl breed, which has a crest cushion that affects its survival rate. Therefore, the CC duck is an ideal model to investigate the genetic compensation response to maintain genetic stability. In the present study, we first generated a chromosome-level genome of CC ducks. Comparative genomics revealed that genes related to tissue repair, immune function, and tumors were under strong positive selection, indicating that these adaptive changes might enhance cancer resistance and immune response to maintain the genetic stability of CC ducks. We also assembled a Chinese spot-billed (Csp-b) duck genome, and detected the structural variations (SVs) in the genome assemblies of three ducks (i.e., CC duck, Csp-b duck, and Peking duck). Functional analysis revealed that several SVs were related to the immune system of CC ducks, further strongly suggesting that genetic compensation in the anti-tumor and immune systems supports the survival of CC ducks. Moreover, we confirmed that the CC duck originated from the mallard ducks. Finally, we revealed the physiological and genetic basis of crest traits and identified a causative mutation in TAS2R40 that leads to crest formation. Overall, the findings of this study provide new insights into the role of genetic compensation in adaptive evolution.
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Affiliation(s)
- Guobin Chang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou 225009, China
| | - Xiaoya Yuan
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Qixin Guo
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Hao Bai
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou 225009, China
| | - Xiaofang Cao
- Novogene Bioinformatics Institute, Beijing 100080, China
| | - Meng Liu
- Novogene Bioinformatics Institute, Beijing 100080, China
| | - Zhixiu Wang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Bichun Li
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Shasha Wang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Yong Jiang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Zhiquan Wang
- Department of Agricultural, Food, and Nutritional Sciences, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Yang Zhang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Qi Xu
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Qianqian Song
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Rui Pan
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Lingling Qiu
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Tiantian Gu
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Xinsheng Wu
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Yulin Bi
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Zhengfeng Cao
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Yu Zhang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Yang Chen
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
| | - Hong Li
- Novogene Bioinformatics Institute, Beijing 100080, China
| | - Jianfeng Liu
- College of Animal Science and Technology, China Agricultural University, Beijing 100091, China
| | - Wangcheng Dai
- Zhenjiang Tiancheng Agricultural Science and Technology Co., Ltd, Zhenjiang 210034, China
| | - Guohong Chen
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou 225009, China.
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17
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Ryman N, Laikre L, Hössjer O. Variance effective population size is affected by census size in sub-structured populations. Mol Ecol Resour 2023. [PMID: 37122118 DOI: 10.1111/1755-0998.13804] [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: 01/18/2022] [Revised: 04/06/2023] [Accepted: 04/12/2023] [Indexed: 05/02/2023]
Abstract
Measurement of allele frequency shifts between temporally spaced samples has long been used for assessment of effective population size (Ne ), and this 'temporal method' provides estimates of Ne referred to as variance effective size (NeV ). We show that NeV of a local population that belongs to a sub-structured population (a metapopulation) is determined not only by genetic drift and migration rate (m), but also by the census size (Nc ). The realized NeV of a local population can either increase or decrease with increasing m, depending on the relationship between Ne and Nc in isolation. This is shown by explicit mathematical expressions for the factors affecting NeV derived for an island model of migration. We verify analytical results using high-resolution computer simulations, and show that the phenomenon is not restricted to the island model migration pattern. The effect of Nc on the realized NeV of a local subpopulation is most pronounced at high migration rates. We show that Nc only affects local NeV , whereas NeV for the metapopulation as a whole, inbreeding (NeI ), and linkage disequilibrium (NeLD ) effective size are all independent of Nc . Our results provide a possible explanation to the large variation of Ne /Nc ratios reported in the literature, where Ne is frequently estimated by NeV . They are also important for the interpretation of empirical Ne estimates in genetic management where local NeV is often used as a substitute for inbreeding effective size, and we suggest an increased focus on metapopulation NeV as a proxy for NeI .
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Affiliation(s)
- Nils Ryman
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Linda Laikre
- Division of Population Genetics, Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Ola Hössjer
- Department of Mathematics, Stockholm University, Stockholm, Sweden
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18
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Shao C, Sun S, Liu K, Wang J, Li S, Liu Q, Deagle BE, Seim I, Biscontin A, Wang Q, Liu X, Kawaguchi S, Liu Y, Jarman S, Wang Y, Wang HY, Huang G, Hu J, Feng B, De Pittà C, Liu S, Wang R, Ma K, Ying Y, Sales G, Sun T, Wang X, Zhang Y, Zhao Y, Pan S, Hao X, Wang Y, Xu J, Yue B, Sun Y, Zhang H, Xu M, Liu Y, Jia X, Zhu J, Liu S, Ruan J, Zhang G, Yang H, Xu X, Wang J, Zhao X, Meyer B, Fan G. The enormous repetitive Antarctic krill genome reveals environmental adaptations and population insights. Cell 2023; 186:1279-1294.e19. [PMID: 36868220 DOI: 10.1016/j.cell.2023.02.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 12/11/2022] [Accepted: 02/02/2023] [Indexed: 03/05/2023]
Abstract
Antarctic krill (Euphausia superba) is Earth's most abundant wild animal, and its enormous biomass is vital to the Southern Ocean ecosystem. Here, we report a 48.01-Gb chromosome-level Antarctic krill genome, whose large genome size appears to have resulted from inter-genic transposable element expansions. Our assembly reveals the molecular architecture of the Antarctic krill circadian clock and uncovers expanded gene families associated with molting and energy metabolism, providing insights into adaptations to the cold and highly seasonal Antarctic environment. Population-level genome re-sequencing from four geographical sites around the Antarctic continent reveals no clear population structure but highlights natural selection associated with environmental variables. An apparent drastic reduction in krill population size 10 mya and a subsequent rebound 100 thousand years ago coincides with climate change events. Our findings uncover the genomic basis of Antarctic krill adaptations to the Southern Ocean and provide valuable resources for future Antarctic research.
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Affiliation(s)
- Changwei Shao
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China.
| | - Shuai Sun
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China; BGI-Shenzhen, Shenzhen, Guangdong 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kaiqiang Liu
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Jiahao Wang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Shuo Li
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Qun Liu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China; Department of Biology, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Bruce E Deagle
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australian National Fish Collection, National Research Collections Australia, Hobart, TAS 7000, Australia; Australian Antarctic Division, Channel Highway, Kingston, TAS 7050, Australia
| | - Inge Seim
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China
| | | | - Qian Wang
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Xin Liu
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China; BGI-Beijing, Beijing 102601, China; State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen 518083, China; State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Murdoch University, Murdoch, WA 6150, Australia
| | - So Kawaguchi
- Australian Antarctic Division, Channel Highway, Kingston, TAS 7050, Australia
| | - Yalin Liu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Simon Jarman
- School of Molecular and Life Sciences, Curtin University, Perth, WA 6009, Australia
| | - Yue Wang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China; State Key Laboratory of Quality Research in Chinese Medicine and Institute of Chinese Medical Sciences, University of Macau, Macao 999078, China
| | - Hong-Yan Wang
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | | | - Jiang Hu
- Nextomics Biosciences Institute, Wuhan, Hubei 430073, China
| | - Bo Feng
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | | | - Shanshan Liu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Rui Wang
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Kailong Ma
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Yiping Ying
- Key Lab of Sustainable Development of Polar Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China
| | - Gabrielle Sales
- Department of Biology, University of Padova, Padova 35121, Italy
| | - Tao Sun
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Xinliang Wang
- Key Lab of Sustainable Development of Polar Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China
| | - Yaolei Zhang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China; BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Yunxia Zhao
- Key Lab of Sustainable Development of Polar Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China
| | - Shanshan Pan
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Xiancai Hao
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Yang Wang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Jiakun Xu
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Key Lab of Sustainable Development of Polar Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China
| | - Bowen Yue
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Yanxu Sun
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - He Zhang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Mengyang Xu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China; BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Yuyan Liu
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Xiaodong Jia
- Joint Laboratory for Translational Medicine Research, Liaocheng People's Hospital, Liaocheng, Shandong 252000, China
| | - Jiancheng Zhu
- Key Lab of Sustainable Development of Polar Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China
| | - Shufang Liu
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
| | - Jue Ruan
- Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong 518120, China
| | - Guojie Zhang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China; Villum Centre for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China; James D. Watson Institute of Genome Science, Hangzhou 310058, China
| | - Xun Xu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China; BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Jun Wang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Xianyong Zhao
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China; Key Lab of Sustainable Development of Polar Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong 266071, China
| | - Bettina Meyer
- Section Polar Biological Oceanography, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany; Institute for Chemistry and Biology of the Marine Environment, Carlvon Ossietzky University of Oldenburg, 26111 Oldenburg, Germany; Helmholtz Institute for Functional Marine Biodiversity (HIFMB), University of Oldenburg, 26129 Oldenburg, Germany.
| | - Guangyi Fan
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China; BGI-Shenzhen, Shenzhen, Guangdong 518083, China; Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong 518120, China; Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, BGI-Shenzhen 518120, China.
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19
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Lesturgie P, Braun CD, Clua E, Mourier J, Thorrold SR, Vignaud T, Planes S, Mona S. Like a rolling stone: Colonization and migration dynamics of the gray reef shark ( Carcharhinus amblyrhynchos). Ecol Evol 2023; 13:e9746. [PMID: 36644707 PMCID: PMC9831972 DOI: 10.1002/ece3.9746] [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: 10/06/2022] [Revised: 12/18/2022] [Accepted: 12/27/2022] [Indexed: 01/13/2023] Open
Abstract
Designing appropriate management plans requires knowledge of both the dispersal ability and what has shaped the current distribution of the species under consideration. Here, we investigated the evolutionary history of the endangered gray reef shark (Carcharhinus amblyrhynchos) across its range by sequencing thousands of RADseq loci in 173 individuals in the Indo-Pacific (IP). We first bring evidence of the occurrence of a range expansion (RE) originating close to the Indo-Australian Archipelago (IAA) where two stepping-stone waves (east and westward) colonized almost the entire IP. Coalescent modeling additionally highlighted a homogenous connectivity (Nm ~ 10 per generation) throughout the range, and isolation by distance model suggested the absence of barriers to dispersal despite the affinity of C. amblyrhynchos to coral reefs. This coincides with long-distance swims previously recorded, suggesting that the strong genetic structure at the IP scale (F ST ~ 0.56 between its ends) is the consequence of its broad current distribution and organization in a large number of demes. Our results strongly suggest that management plans for the gray reef shark should be designed on a range-wide rather than a local scale due to its continuous genetic structure. We further contrasted these results with those obtained previously for the sympatric but strictly lagoon-associated Carcharhinus melanopterus, known for its restricted dispersal ability. Carcharhinus melanopterus exhibits a similar RE dynamic but is characterized by a stronger genetic structure and a nonhomogeneous connectivity largely dependent on local coral reefs availability. This sheds new light on shark evolution, emphasizing the roles of IAA as source of biodiversity and of life-history traits in shaping the extent of genetic structure and diversity.
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Affiliation(s)
- Pierre Lesturgie
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle, EPHE‐PSLUniversité PSL, CNRS, SU, UAParisFrance
| | - Camrin D. Braun
- Biology DepartmentWoods Hole Oceanographic InstitutionWoods HoleMassachusettsUSA
| | - Eric Clua
- Laboratoire d'Excellence CORAILPapetoaiFrench Polynesia
- EPHE, PSL Research UniversityParisFrance
| | - Johann Mourier
- Laboratoire d'Excellence CORAILPapetoaiFrench Polynesia
- Université de Corse Pasquale Paoli, UMS 3514 Plateforme Marine Stella MareBigugliaFrance
| | - Simon R. Thorrold
- Biology DepartmentWoods Hole Oceanographic InstitutionWoods HoleMassachusettsUSA
| | | | - Serge Planes
- Laboratoire d'Excellence CORAILPapetoaiFrench Polynesia
- EPHE, PSL Research UniversityParisFrance
| | - Stefano Mona
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle, EPHE‐PSLUniversité PSL, CNRS, SU, UAParisFrance
- EPHE, PSL Research UniversityParisFrance
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20
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Sang H, Li Y, Sun C. Conservation Genomic Analysis of the Asian Honeybee in China Reveals Climate Factors Underlying Its Population Decline. INSECTS 2022; 13:953. [PMID: 36292899 PMCID: PMC9604051 DOI: 10.3390/insects13100953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 10/04/2022] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
The Asian honeybee, Apis cerana, is one of the most important native pollinators in Asia. Asian honeybees were believed to be under significant decline in China based on a report in 2005. On the contrary, a recent survey revealed that Asian honeybee populations in China are stable and even slightly increased in some regions. Therefore, the declining status of A. cerana populations in China is still unclear. Taking advantage of the abundant, publicly available genomic data for Asian honeybees in China, we employed conservation genomics methods to understand if Asian honeybee populations in China are declining and what the underlying climate factors are. We reconstructed the changes of effective population size (Ne) within the recent past for 6 population groups of Asian honeybees and found out that only one of them (population in Bomi, Tibet) showed a consistently declining Ne from the last 100 generations to 25 generations. Selective sweep analysis suggests that genes related to the tolerance of low temperatures and strong ultraviolet radiation are under selection in the declining population, indicating that these two climate factors most likely underlie the decline of BM populations during the recent past. Our study provides insights into the dynamic changes of Asian honeybee populations in China and identifies climate factors that underlie its population decline, which is valuable for the conservation of this important pollinator.
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Affiliation(s)
- Huiling Sang
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China
| | - Yancan Li
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China
| | - Cheng Sun
- Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China
- College of Life Sciences, Capital Normal University, Beijing 100048, China
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21
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Zhang W, Li X, Jiang Y, Zhou M, Liu L, Su S, Xu C, Li X, Wang C. Genetic architecture and selection of Anhui autochthonous pig population revealed by whole genome resequencing. Front Genet 2022; 13:1022261. [PMID: 36324508 PMCID: PMC9618877 DOI: 10.3389/fgene.2022.1022261] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 09/28/2022] [Indexed: 11/29/2022] Open
Abstract
The genetic resources among pigs in Anhui Province are diverse, but their value and potential have yet to be discovered. To illustrate the genetic diversity and population structure of the Anhui pigs population, we resequenced the genome of 150 pigs from six representative Anhui pigs populations and analyzed this data together with the sequencing data from 40 Asian wild boars and commercial pigs. Our results showed that Anhui pigs were divided into two distinct types based on ancestral descent: Wannan Spotted pig (WSP) and Wannan Black pig (WBP) origins from the same ancestor and the other four populations origins from another ancestor. We also identified several potential selective sweep regions associated with domestication characteristics among Anhui pigs, including reproduction-associated genes (CABS1, INSL6, MAP3K12, IGF1R, INSR, LIMK2, PATZ1, MAPK1), lipid- and meat-related genes (SNX19, MSTN, MC5R, PRKG1, CREBBP, ADCY9), and ear size genes (MSRB3 and SOX5). Therefore, these findings expand the catalogue and how these genetic differences among pigs and this newly generated data will be a valuable resource for future genetic studies and for improving genome-assisted breeding of pigs and other domesticated animals.
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22
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Aushev A, Pesonen H, Heinonen M, Corander J, Kaski S. Likelihood-free inference with deep Gaussian processes. Comput Stat Data Anal 2022. [DOI: 10.1016/j.csda.2022.107529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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23
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Chen H, Huang M, Liu D, Tang H, Zheng S, Ouyang J, Zhang H, Wang L, Luo K, Gao Y, Wu Y, Wu Y, Xiong Y, Luo T, Huang Y, Xiong R, Ren J, Huang J, Yan X. Genomic signatures and evolutionary history of the endangered blue-crowned laughingthrush and other Garrulax species. BMC Biol 2022; 20:188. [PMID: 36002819 PMCID: PMC9400264 DOI: 10.1186/s12915-022-01390-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 08/12/2022] [Indexed: 12/12/2022] Open
Abstract
Background The blue-crowned laughingthrush (Garrulax courtoisi) is a critically endangered songbird endemic to Wuyuan, China, with population of ~323 individuals. It has attracted widespread attention, but the lack of a published genome has limited research and species protection. Results We report two laughingthrush genome assemblies and reveal the taxonomic status of laughingthrush species among 25 common avian species according to the comparative genomic analysis. The blue-crowned laughingthrush, black-throated laughingthrush, masked laughingthrush, white-browed laughingthrush, and rusty laughingthrush showed a close genetic relationship, and they diverged from a common ancestor between ~2.81 and 12.31 million years ago estimated by the population structure and divergence analysis using 66 whole-genome sequencing birds from eight laughingthrush species and one out group (Cyanopica cyanus). Population inference revealed that the laughingthrush species experienced a rapid population decline during the last ice age and a serious bottleneck caused by a cold wave during the Chinese Song Dynasty (960–1279 AD). The blue-crowned laughingthrush is still in a bottleneck, which may be the result of a cold wave together with human exploitation. Interestingly, the existing blue-crowned laughingthrush exhibits extremely rich genetic diversity compared to other laughingthrushes. These genetic characteristics and demographic inference patterns suggest a genetic heritage of population abundance in the blue-crowned laughingthrush. The results also suggest that fewer deleterious mutations in the blue-crowned laughingthrush genomes have allowed them to thrive even with a small population size. We believe that cooperative breeding behavior and a long reproduction period may enable the blue-crowned laughingthrush to maintain genetic diversity and avoid inbreeding depression. We identified 43 short tandem repeats that can be used as markers to identify the sex of the blue-crowned laughingthrush and aid in its genetic conservation. Conclusions This study supplies the missing reference genome of laughingthrush, provides insight into the genetic variability, evolutionary potential, and molecular ecology of laughingthrush and provides a genomic resource for future research and conservation. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-022-01390-4.
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Affiliation(s)
- Hao Chen
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Min Huang
- College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | | | - Hongbo Tang
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Sumei Zheng
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China.,College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Jing Ouyang
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Hui Zhang
- College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Luping Wang
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Keyi Luo
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Yuren Gao
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Yongfei Wu
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Yan Wu
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Yanpeng Xiong
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Tao Luo
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Yuxuan Huang
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Rui Xiong
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China
| | - Jun Ren
- College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Jianhua Huang
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China.
| | - Xueming Yan
- College of Life Science, Jiangxi Science & Technology Normal University, Nanchang, Jiangxi Province, China.
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24
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Yang S, Lan T, Zhang Y, Wang Q, Li H, Dussex N, Sahu SK, Shi M, Hu M, Zhu Y, Cao J, Liu L, Lin J, Wan QH, Liu H, Fang SG. Genomic investigation of the Chinese alligator reveals wild-extinct genetic diversity and genomic consequences of their continuous decline. Mol Ecol Resour 2022; 23:294-311. [PMID: 35980602 PMCID: PMC10087395 DOI: 10.1111/1755-0998.13702] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 07/29/2022] [Accepted: 08/15/2022] [Indexed: 11/26/2022]
Abstract
Critically endangered species are usually restricted to small and isolated populations. High inbreeding without gene flow among populations further aggravates their threatened condition and reduces the likelihood of their long-term survival. Chinese alligator (Alligator sinensis) is one of the most endangered crocodiles in the world and has experienced a continuous decline over the past ca. 1 million years. In order to identify the genetic status of the remaining populations and aid conservation efforts, we assembled the first high-quality chromosome-level genome of Chinese alligator and explored the genomic characteristics of three extant breeding populations. Our analyses revealed the existence of at least three genetically distinct populations, comprising two breeding populations in China (Changxing and Xuancheng) and one breeding population in an American wildlife refuge. The American population does not belong to the last two populations of its native range (Xuancheng and Changxing), thus representing genetic diversity extinct in the wild and provides future opportunities for genetic rescue. Moreover, the effective population size of these three populations has been continuously declining over the past 20 ka. Consistent with this decline, the species shows extremely low genetic diversity, a large proportion of long runs of homozygous fragments, and mutational load across the genome. Finally, to provide genomic insights for future breeding management and conservation, we assessed the feasibility of mixing extant populations based on the likelihood of introducing new deleterious alleles and signatures of local adaptation. Overall, this study provides a valuable genomic resource and important genomic insights into the ecology, evolution, and conservation of critically endangered alligators.
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Affiliation(s)
- Shangchen Yang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, China
| | - Tianming Lan
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China.,BGI Life Science Joint Research Center, Northeast Forestry University, China
| | - Yi Zhang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, China
| | - Qing Wang
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Haimeng Li
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Nicolas Dussex
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691, Stockholm, Sweden.,Department of Zoology, Stockholm University, Stockholm, Sweden.,Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Sunil Kumar Sahu
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China
| | - Minhui Shi
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Mengyuan Hu
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, China
| | - Yixin Zhu
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jun Cao
- China National GeneBank, BGI-Shenzhen, Shenzhen, China.,Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, China
| | - Lirong Liu
- China National GeneBank, BGI-Shenzhen, Shenzhen, China.,Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, China
| | - Jianqing Lin
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, China
| | - Qiu-Hong Wan
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, China
| | - Huan Liu
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China.,BGI Life Science Joint Research Center, Northeast Forestry University, China
| | - Sheng-Guo Fang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, China
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25
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Tournebize R, Chu G, Moorjani P. Reconstructing the history of founder events using genome-wide patterns of allele sharing across individuals. PLoS Genet 2022; 18:e1010243. [PMID: 35737729 PMCID: PMC9223333 DOI: 10.1371/journal.pgen.1010243] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 05/08/2022] [Indexed: 11/30/2022] Open
Abstract
Founder events play a critical role in shaping genetic diversity, fitness and disease risk in a population. Yet our understanding of the prevalence and distribution of founder events in humans and other species remains incomplete, as most existing methods require large sample sizes or phased genomes. Thus, we developed ASCEND that measures the correlation in allele sharing between pairs of individuals across the genome to infer the age and strength of founder events. We show that ASCEND can reliably estimate the parameters of founder events under a range of demographic scenarios. We then apply ASCEND to two species with contrasting evolutionary histories: ~460 worldwide human populations and ~40 modern dog breeds. In humans, we find that over half of the analyzed populations have evidence for recent founder events, associated with geographic isolation, modes of sustenance, or cultural practices such as endogamy. Notably, island populations have lower population sizes than continental groups and most hunter-gatherer, nomadic and indigenous groups have evidence of recent founder events. Many present-day groups––including Native Americans, Oceanians and South Asians––have experienced more extreme founder events than Ashkenazi Jews who have high rates of recessive diseases due their known history of founder events. Using ancient genomes, we show that the strength of founder events differs markedly across geographic regions and time––with three major founder events related to the peopling of Americas and a trend in decreasing strength of founder events in Europe following the Neolithic transition and steppe migrations. In dogs, we estimate extreme founder events in most breeds that occurred in the last 25 generations, concordant with the establishment of many dog breeds during the Victorian times. Our analysis highlights a widespread history of founder events in humans and dogs and elucidates some of the demographic and cultural practices related to these events. A founder event occurs when small numbers of ancestral individuals give rise to a large fraction of the population. Founder events reduce genetic variation and increase the risk of recessive diseases. Despite their importance in evolutionary and disease studies, we still only have a limited comprehension of their prevalence and properties in humans and other species, as most existing methods require large sample sizes or phased genomes. Here, we present a flexible method, ASCEND, to infer the timing and the strength of founder events that is suitable for sparse datasets with few samples or limited coverage. ASCEND provides reliable estimates across a wide range of demographic scenarios. By applying it to data from two species (humans and dogs), we document a widespread history of recent founder events in both species and provide insights about the demographic processes related to these events. Our analysis helps to identify groups with strong founder events that should be prioritized for future studies as they offer a unique opportunity for biological discovery and reducing disease burden through mapping of recessive disease-causing genes and pathways, as previously shown in studies of Ashkenazi Jews and Finns.
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Affiliation(s)
- Rémi Tournebize
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- Center for Computational Biology, University of California, Berkeley, California, United States of America
- * E-mail: (RT); (PM)
| | - Gillian Chu
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America
| | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- Center for Computational Biology, University of California, Berkeley, California, United States of America
- * E-mail: (RT); (PM)
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26
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Searching for genetic evidence of demographic decline in an arctic seabird: beware of overlapping generations. Heredity (Edinb) 2022; 128:364-376. [PMID: 35246618 PMCID: PMC9076905 DOI: 10.1038/s41437-022-00515-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 02/12/2022] [Accepted: 02/14/2022] [Indexed: 11/09/2022] Open
Abstract
Genetic data are useful for detecting sudden population declines in species that are difficult to study in the field. Yet this indirect approach has its own drawbacks, including population structure, mutation patterns, and generation overlap. The ivory gull (Pagophila eburnea), a long-lived Arctic seabird, is currently suffering from rapid alteration of its primary habitat (i.e., sea ice), and dramatic climatic events affecting reproduction and recruitment. However, ivory gulls live in remote areas, and it is difficult to assess the population trend of the species across its distribution. Here we present complementary microsatellite- and SNP-based genetic analyses to test a recent bottleneck genetic signal in ivory gulls over a large portion of their distribution. With attention to the potential effects of population structure, mutation patterns, and sample size, we found no significant signatures of population decline worldwide. At a finer scale, we found a significant bottleneck signal at one location in Canada. These results were compared with predictions from simulations showing how generation time and generation overlap can delay and reduce the bottleneck microsatellite heterozygosity excess signal. The consistency of the results obtained with independent methods strongly indicates that the species shows no genetic evidence of an overall decline in population size. However, drawing conclusions related to the species' population trends will require a better understanding of the effect of age structure in long-lived species. In addition, estimates of the effective global population size of ivory gulls were surprisingly low (~1000 ind.), suggesting that the evolutionary potential of the species is not assured.
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27
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Dittberner H, Tellier A, de Meaux J. Approximate Bayesian computation untangles signatures of contemporary and historical hybridization between two endangered species. Mol Biol Evol 2022; 39:6516021. [PMID: 35084503 PMCID: PMC8826969 DOI: 10.1093/molbev/msac015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Contemporary gene flow, when resumed after a period of isolation, can have crucial consequences for endangered species, as it can both increase the supply of adaptive alleles and erode local adaptation. Determining the history of gene flow and thus the importance of contemporary hybridization, however, is notoriously difficult. Here, we focus on two endangered plant species, Arabis nemorensis and A. sagittata, which hybridize naturally in a sympatric population located on the banks of the Rhine. Using reduced genome sequencing, we determined the phylogeography of the two taxa but report only a unique sympatric population. Molecular variation in chloroplast DNA indicated that A. sagittata is the principal receiver of gene flow. Applying classical D-statistics and its derivatives to whole-genome data of 35 accessions, we detect gene flow not only in the sympatric population but also among allopatric populations. Using an Approximate Bayesian computation approach, we identify the model that best describes the history of gene flow between these taxa. This model shows that low levels of gene flow have persisted long after speciation. Around 10 000 years ago, gene flow stopped and a period of complete isolation began. Eventually, a hotspot of contemporary hybridization was formed in the unique sympatric population. Occasional sympatry may have helped protect these lineages from extinction in spite of their extremely low diversity.
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Affiliation(s)
- Hannes Dittberner
- Institute of Plant Sciences,University of Cologne, Zülpicher str. 47b, Germany
| | - Aurelien Tellier
- Department of Life Science Systems, Technical University of Munich, Freising, Germany
| | - Juliette de Meaux
- Institute of Plant Sciences,University of Cologne, Zülpicher str. 47b, Germany
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28
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Izuno A, Onoda Y, Amada G, Kobayashi K, Mukai M, Isagi Y, Shimizu KK. Demography and selection analysis of the incipient adaptive radiation of a Hawaiian woody species. PLoS Genet 2022; 18:e1009987. [PMID: 35061669 PMCID: PMC8782371 DOI: 10.1371/journal.pgen.1009987] [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: 06/14/2021] [Accepted: 12/09/2021] [Indexed: 11/18/2022] Open
Abstract
Ecological divergence in a species provides a valuable opportunity to study the early stages of speciation. We focused on Metrosideros polymorpha, a unique example of the incipient radiation of woody species, to examine how an ecological divergence continues in the face of gene flow. We analyzed the whole genomes of 70 plants collected throughout the island of Hawaii, which is the youngest island with the highest altitude in the archipelago and encompasses a wide range of environments. The continuous M. polymorpha forest stands on the island of Hawaii were differentiated into three genetic clusters, each of which grows in a distinctive environment and includes substantial genetic and phenotypic diversity. The three genetic clusters showed signatures of selection in genomic regions encompassing genes relevant to environmental adaptations, including genes associated with light utilization, oxidative stress, and leaf senescence, which are likely associated with the ecological differentiation of the species. Our demographic modeling suggested that the glaberrima cluster in wet environments maintained a relatively large population size and two clusters split: polymorpha in the subalpine zone and incana in dry and hot conditions. This ecological divergence possibly began before the species colonized the island of Hawaii. Interestingly, the three clusters recovered genetic connectivity coincidentally with a recent population bottleneck, in line with the weak reproductive isolation observed in the species. This study highlights that the degree of genetic differentiation between ecologically-diverged populations can vary depending on the strength of natural selection in the very early phases of speciation. Knowledge about how genetic barriers are formed between populations in distinct environments is valuable to understand the processes of speciation and conserve biodiversity. Metrosideros polymorpha, an endemic woody species in the Hawaiian Islands, is a good system to study developing genetic barriers in a species, because it colonized the diverse environments and diversified the morphology for a relatively short period of time. We analyzed the genomes of 70 M. polymorpha plants from a broad range of environments on the island of Hawaii to infer the current and past genetic barriers among them. Currently, M. polymorpha plants growing in different environments have substantially different genomes, especially at the genomic regions with genes putatively controlling physiology to fit in distinct environment. However, in its history, they had hybridized with one another, possibly because plants formerly growing in different environments came into close contact due to the climate changes. It is suggested that genetic barriers can easily strengthen or weaken depending on environments splitting the ecology of a species before reproductive isolation becomes complete.
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Affiliation(s)
- Ayako Izuno
- Department of Forest Molecular Genetics and Biotechnology, Forestry and Forest Products Research Institute, Tsukuba, Japan
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
- * E-mail:
| | - Yusuke Onoda
- Graduate School of Agriculture, Kyoto University, Kyoto, Japan
| | - Gaku Amada
- Graduate School of Agriculture, Kyoto University, Kyoto, Japan
| | - Keito Kobayashi
- Graduate School of Agriculture, Kyoto University, Kyoto, Japan
| | - Mana Mukai
- Graduate School of Agriculture, Kyoto University, Kyoto, Japan
| | - Yuji Isagi
- Graduate School of Agriculture, Kyoto University, Kyoto, Japan
| | - Kentaro K. Shimizu
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
- Kihara Institute for Biological Research, Yokohama City University, Yokohama, Japan
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29
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Mueller JC, Botero-Delgadillo E, Espíndola-Hernández P, Gilsenan C, Ewels P, Gruselius J, Kempenaers B. Local selection signals in the genome of Blue tits emphasize regulatory and neuronal evolution. Mol Ecol 2022; 31:1504-1514. [PMID: 34995389 DOI: 10.1111/mec.16345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/18/2021] [Accepted: 12/15/2021] [Indexed: 11/30/2022]
Abstract
Understanding the genomic landscape of adaptation is central to the understanding of microevolution in wild populations. Genomic targets of selection and the underlying genomic mechanisms of adaptation can be elucidated by genome-wide scans for past selective sweeps or by scans for direct fitness associations. We sequenced and assembled 150 haplotypes of 75 Blue tits (Cyanistes caeruleus) of a single central-European population by a linked-read technology. We used these genome data in combination with coalescent simulations (1) to estimate an historical effective population size of ~250,000, which recently declined to ~10,000, and (2) to identify genome-wide distributed selective sweeps of beneficial variants most likely originating from standing genetic variation (soft sweeps). The genes linked to these soft sweeps, but also the ones linked to hard sweeps based on new beneficial mutants, showed a significant enrichment for functions associated with gene expression and transcription regulation. This emphasizes the importance of regulatory evolution in the population's adaptive history. Soft sweeps were further enriched for genes related to axon and synapse development, indicating the significance of neuronal connectivity changes in the brain potentially linked to behavioural adaptations. A previous scan of heterozygosity-fitness correlations revealed a consistent negative effect on arrival date at the breeding site for a single microsatellite in the MDGA2 gene. Here, we used the haplotype structure around this microsatellite to explain the effect as a local and direct outbreeding effect of a gene involved in synapse development.
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Affiliation(s)
- Jakob C Mueller
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Esteban Botero-Delgadillo
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Pamela Espíndola-Hernández
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Carol Gilsenan
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Phil Ewels
- Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Joel Gruselius
- Science for Life Laboratory, Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden.,current address: Vanadis Diagnostics, PerkinElmer, Sollentuna, Sweden
| | - Bart Kempenaers
- Department of Behavioural Ecology and Evolutionary Genetics, Max Planck Institute for Ornithology, Seewiesen, Germany
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30
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Bemmels JB, Mikkelsen EK, Haddrath O, Colbourne RM, Robertson HA, Weir JT. Demographic decline and lineage-specific adaptations characterize New Zealand kiwi. Proc Biol Sci 2021; 288:20212362. [PMID: 34905706 PMCID: PMC8670953 DOI: 10.1098/rspb.2021.2362] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 11/19/2021] [Indexed: 12/24/2022] Open
Abstract
Small and fragmented populations may become rapidly differentiated due to genetic drift, making it difficult to distinguish whether neutral genetic structure is a signature of recent demographic events, or of long-term evolutionary processes that could have allowed populations to adaptively diverge. We sequenced 52 whole genomes to examine Holocene demographic history and patterns of adaptation in kiwi (Apteryx), and recovered 11 strongly differentiated genetic clusters corresponding to previously recognized lineages. Demographic models suggest that all 11 lineages experienced dramatic population crashes relative to early- or mid-Holocene levels. Small population size is associated with low genetic diversity and elevated genetic differentiation (FST), suggesting that population declines have strengthened genetic structure and led to the loss of genetic diversity. However, population size is not correlated with inbreeding rates. Eight lineages show signatures of lineage-specific selective sweeps (284 sweeps total) that are unlikely to have been caused by demographic stochasticity. Overall, these results suggest that despite strong genetic drift associated with recent bottlenecks, most kiwi lineages possess unique adaptations and should be recognized as separate adaptive units in conservation contexts. Our work highlights how whole-genome datasets can address longstanding uncertainty about the evolutionary and conservation significance of small and fragmented populations of threatened species.
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Affiliation(s)
- Jordan B. Bemmels
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Canada ON M1C 1A4
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada ON M5S 3B2
| | - Else K. Mikkelsen
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Canada ON M1C 1A4
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada ON M5S 3B2
| | - Oliver Haddrath
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada ON M5S 3B2
- Department of Natural History, Royal Ontario Museum, Toronto, Canada ON M5S 2C6
| | | | | | - Jason T. Weir
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Canada ON M1C 1A4
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada ON M5S 3B2
- Department of Natural History, Royal Ontario Museum, Toronto, Canada ON M5S 2C6
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31
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Ouhrouch A, Boitard S, Boyer F, Servin B, Da Silva A, Pompanon F, Haddioui A, Benjelloun B. Genomic Uniqueness of Local Sheep Breeds From Morocco. Front Genet 2021; 12:723599. [PMID: 34925440 PMCID: PMC8675355 DOI: 10.3389/fgene.2021.723599] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 11/09/2021] [Indexed: 01/17/2023] Open
Abstract
Sheep farming is a major source of meat in Morocco and plays a key role in the country's agriculture. This study aims at characterizing the whole-genome diversity and demographic history of the main Moroccan sheep breeds, as well as to identify selection signatures within and between breeds. Whole genome data from 87 individuals representing the five predominant local breeds were used to estimate their level of neutral genetic diversity and to infer the variation of their effective population size over time. In addition, we used two methods to detect selection signatures: either for detecting selective sweeps within each breed separately or by detecting differentially selected regions by contrasting different breeds. We identified hundreds of genomic regions putatively under selection, which related to several biological terms involved in local adaptation or the expression of zootechnical performances such as Growth, UV protection, Cell maturation or Feeding behavior. The results of this study revealed selection signatures in genes that have an important role in traits of interest and increased our understanding of how genetic diversity is distributed in these local breeds. Thus, Moroccan local sheep breeds exhibit both a high genetic diversity and a large set of adaptive variations, and therefore, represent a valuable genetic resource for the conservation of sheep in the context of climate change.
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Affiliation(s)
- Abdessamad Ouhrouch
- Livestock Genomics Laboratory, Regional Center of Agricultural Research Tadla, National Institute of Agricultural Research INRA, Rabat, Morocco.,Biotechnologies and Valorization of Plant-Genetic Resources Laboratory, Sultan Moulay Slimane University, Beni Mellal, Morocco
| | - Simon Boitard
- CBGP, Université de Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France
| | - Frédéric Boyer
- Université Grenoble Alpes, Université Savoie MT-Blanc, CNRS, LECA, Grenoble, France
| | - Bertrand Servin
- GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet-Tolosan, France
| | - Anne Da Silva
- PEREINE/E2LIM, Faculty of Science and Technics, Limoges, France
| | - François Pompanon
- Université Grenoble Alpes, Université Savoie MT-Blanc, CNRS, LECA, Grenoble, France
| | - Abdelmajid Haddioui
- Biotechnologies and Valorization of Plant-Genetic Resources Laboratory, Sultan Moulay Slimane University, Beni Mellal, Morocco
| | - Badr Benjelloun
- Livestock Genomics Laboratory, Regional Center of Agricultural Research Tadla, National Institute of Agricultural Research INRA, Rabat, Morocco
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32
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Hartfield M, Poulsen NA, Guldbrandtsen B, Bataillon T. Using singleton densities to detect recent selection in Bos taurus. Evol Lett 2021; 5:595-606. [PMID: 34917399 PMCID: PMC8645200 DOI: 10.1002/evl3.263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 10/07/2021] [Accepted: 10/08/2021] [Indexed: 11/05/2022] Open
Abstract
Many quantitative traits are subject to polygenic selection, where several genomic regions undergo small, simultaneous changes in allele frequency that collectively alter a phenotype. The widespread availability of genome data, along with novel statistical techniques, has made it easier to detect these changes. We apply one such method, the "Singleton Density Score" (SDS), to the Holstein breed of Bos taurus to detect recent selection (arising up to around 740 years ago). We identify several genes as candidates for targets of recent selection, including some relating to cell regulation, catabolic processes, neural-cell adhesion and immunity. We do not find strong evidence that three traits that are important to humans-milk protein content, milk fat content, and stature-have been subject to directional selection. Simulations demonstrate that because B. taurus recently experienced a population bottleneck, singletons are depleted so the power of SDS methods is reduced. These results inform on which genes underlie recent genetic change in B. taurus, while providing information on how polygenic selection can be best investigated in future studies.
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Affiliation(s)
- Matthew Hartfield
- Bioinformatics Research CentreAarhus UniversityAarhusDK‐8000Denmark
- Institute of Evolutionary BiologyUniversity of EdinburghEdinburghEH9 3FLUnited Kingdom
| | | | - Bernt Guldbrandtsen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and GeneticsAarhus UniversityTjeleDK‐8830Denmark
- Rheinische Friedrich‐Wilhelms‐Universität BonnInstitut für TierwissenschaftenBonnDE‐53115Germany
- Department of Veterinary SciencesCopenhagen UniversityFrederiksberg CDK‐1870Denmark
| | - Thomas Bataillon
- Bioinformatics Research CentreAarhus UniversityAarhusDK‐8000Denmark
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33
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Nadachowska‐Brzyska K, Konczal M, Babik W. Navigating the temporal continuum of effective population size. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13740] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
| | | | - Wieslaw Babik
- Jagiellonian University in Kraków Faculty of Biology Institute of Environmental Sciences Kraków Poland
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34
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Lesturgie P, Planes S, Mona S. Coalescence times, life history traits and conservation concerns: An example from four coastal shark species from the Indo-Pacific. Mol Ecol Resour 2021; 22:554-566. [PMID: 34407294 DOI: 10.1111/1755-0998.13487] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/27/2021] [Accepted: 08/12/2021] [Indexed: 11/30/2022]
Abstract
Dispersal abilities play a crucial role in shaping the extent of population genetic structure, with more mobile species being panmictic over large geographical ranges and less mobile ones organized in metapopulations exchanging migrants to different degrees. In turn, population structure directly influences the coalescence pattern of the sampled lineages, but the consequences on the estimated variation of the effective population size (Ne ) over time obtained by means of unstructured demographic models remain poorly understood. However, this knowledge is crucial for biologically interpreting the observed Ne trajectory and further devising conservation strategies in endangered species. Here we investigated the demographic history of four shark species (Carharhinus melanopterus, Carharhinus limbatus, Carharhinus amblyrhynchos, Galeocerdo cuvier) with different degrees of endangered status and life history traits related to dispersal distributed in the Indo-Pacific and sampled off New Caledonia. We compared several evolutionary scenarios representing both structured (metapopulation) and unstructured models and then inferred the Ne variation through time. By performing extensive coalescent simulations, we provided a general framework relating the underlying population structure and the observed Ne dynamics. On this basis, we concluded that the recent decline observed in three out of the four considered species when assuming unstructured demographic models can be explained by the presence of population structure. Furthermore, we also demonstrated the limits of the inferences based on the sole site frequency spectrum and warn that statistics based on linkage disequilibrium will be needed to exclude recent demographic events affecting meta-populations.
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Affiliation(s)
- Pierre Lesturgie
- Institut de Systématique, Evolution, Biodiversité, ISYEB (UMR 7205), Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, Paris, France
| | - Serge Planes
- PSL Research University: EPHE-UPVD-CNRS, USR 3278 CRIOBE, Université de Perpignan, Perpignan, France.,Laboratoire d'Excellence CORAIL, Papetoai, French Polynesia
| | - Stefano Mona
- Institut de Systématique, Evolution, Biodiversité, ISYEB (UMR 7205), Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, Paris, France.,Laboratoire d'Excellence CORAIL, Papetoai, French Polynesia.,EPHE, PSL Research University, Paris, France
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35
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Ericson PGP, Irestedt M, She H, Qu Y. Genomic signatures of rapid adaptive divergence in a tropical montane species. Biol Lett 2021; 17:20210089. [PMID: 34314643 PMCID: PMC8315830 DOI: 10.1098/rsbl.2021.0089] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 07/02/2021] [Indexed: 12/14/2022] Open
Abstract
Mountain regions contain extraordinary biodiversity. The environmental heterogeneity and glacial cycles often accelerate speciation and adaptation of montane species, but how these processes influence the genomic differentiation of these species is largely unknown. Using a novel chromosome-level genome and population genomic comparisons, we study allopatric divergence and selection in an iconic bird living in a tropical mountain region in New Guinea, Archbold's bowerbird (Amblyornis papuensis). Our results show that the two populations inhabiting the eastern and western Central Range became isolated ca 11 800 years ago, probably because the suitable habitats for this cold-tolerating bird decreased when the climate got warmer. Our genomic scans detect that genes in highly divergent genomic regions are over-represented in developmental processes, which is probably associated with the observed differences in body size between the populations. Overall, our results suggest that environmental differences between the eastern and western Central Range probably drive adaptive divergence between them.
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Affiliation(s)
- Per G. P. Ericson
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, PO Box 50007, 10405, Stockholm, Sweden
| | - Martin Irestedt
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, PO Box 50007, 10405, Stockholm, Sweden
| | - Huishang She
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China
| | - Yanhua Qu
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, PO Box 50007, 10405, Stockholm, Sweden
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China
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36
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Li J, Bian C, Yi Y, Yu H, You X, Shi Q. Temporal dynamics of teleost populations during the Pleistocene: a report from publicly available genome data. BMC Genomics 2021; 22:490. [PMID: 34193045 PMCID: PMC8247217 DOI: 10.1186/s12864-021-07816-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 06/14/2021] [Indexed: 12/04/2022] Open
Abstract
Background Global climate oscillation, as a selection dynamic, is an ecologically important element resulting in global biodiversity. During the glacial geological periods, most organisms suffered detrimental selection pressures (such as food shortage and habitat loss) and went through population declines. However, during the mild interglacial periods, many species re-flourished. These temporal dynamics of effective population sizes (Ne) provide essential information for understanding and predicting evolutionary outcomes during historical and ongoing global climate changes. Results Using high-quality genome assemblies and corresponding sequencing data, we applied the Pairwise Sequentially Markovian Coalescent (PSMC) method to quantify Ne changes of twelve representative teleost species from approximately 10 million years ago (mya) to 10 thousand years ago (kya). These results revealed multiple rounds of population contraction and expansion in most of the examined teleost species during the Neogene and the Quaternary periods. We observed that 83% (10/12) of the examined teleosts had experienced a drastic decline in Ne before the last glacial period (LGP, 110–12 kya), slightly earlier than the reported pattern of Ne changes in 38 avian species. In comparison with the peaks, almost all of the examined teleosts maintained long-term lower Ne values during the last few million years. This is consistent with increasingly dramatic glaciation during this period. Conclusion In summary, these findings provide a more comprehensive understanding of the historical Ne changes in teleosts. Results presented here could lead to the development of appropriate strategies to protect species in light of ongoing global climate changes. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07816-7.
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Affiliation(s)
- Jia Li
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen, Guangdong, China.
| | - Chao Bian
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen, Guangdong, China.,Center of Reproduction, Development and Aging, Faculty of Health Sciences, University of Macau, Macau, China
| | - Yunhai Yi
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen, Guangdong, China.,BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Hui Yu
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen, Guangdong, China
| | - Xinxin You
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen, Guangdong, China.,BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Qiong Shi
- Shenzhen Key Lab of Marine Genomics, Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic Animals, BGI Academy of Marine Sciences, BGI Marine, BGI, Shenzhen, Guangdong, China. .,BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong, China. .,Laboratory of Aquatic Genomics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, Guangdong, China.
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37
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Hansson B, Morales HE, van Oosterhout C. Comment on “Individual heterozygosity predicts translocation success in threatened desert tortoises”. Science 2021; 372:372/6546/eabh1105. [DOI: 10.1126/science.abh1105] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 05/13/2021] [Indexed: 12/29/2022]
Affiliation(s)
- Bengt Hansson
- Department of Biology, Lund University, 223 62 Lund, Sweden
| | - Hernán E. Morales
- Section for Evolutionary Genomics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Cock van Oosterhout
- School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
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38
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Sherpa S, Després L. The evolutionary dynamics of biological invasions: A multi-approach perspective. Evol Appl 2021; 14:1463-1484. [PMID: 34178098 PMCID: PMC8210789 DOI: 10.1111/eva.13215] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 02/22/2021] [Accepted: 03/02/2021] [Indexed: 01/02/2023] Open
Abstract
Biological invasions, the establishment and spread of non-native species in new regions, can have extensive economic and environmental consequences. Increased global connectivity accelerates introduction rates, while climate and land-cover changes may decrease the barriers to invasive populations spread. A detailed knowledge of the invasion history, including assessing source populations, routes of spread, number of independent introductions, and the effects of genetic bottlenecks and admixture on the establishment success, adaptive potential, and further spread, is crucial from an applied perspective to mitigate socioeconomic impacts of invasive species, as well as for addressing fundamental questions on the evolutionary dynamics of the invasion process. Recent advances in genomics together with the development of geographic information systems provide unprecedented large genetic and environmental datasets at global and local scales to link population genomics, landscape ecology, and species distribution modeling into a common framework to study the invasion process. Although the factors underlying population invasiveness have been extensively reviewed, analytical methods currently available to optimally combine molecular and environmental data for inferring invasive population demographic parameters and predicting further spreading are still under development. In this review, we focus on the few recent insect invasion studies that combine different datasets and approaches to show how integrating genetic, observational, ecological, and environmental data pave the way to a more integrative biological invasion science. We provide guidelines to study the evolutionary dynamics of invasions at each step of the invasion process, and conclude on the benefits of including all types of information and up-to-date analytical tools from different research areas into a single framework.
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Affiliation(s)
- Stéphanie Sherpa
- CNRSLECAUniversité Grenoble AlpesUniversité Savoie Mont BlancGrenobleFrance
| | - Laurence Després
- CNRSLECAUniversité Grenoble AlpesUniversité Savoie Mont BlancGrenobleFrance
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39
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Bourgeois YXC, Warren BH. An overview of current population genomics methods for the analysis of whole-genome resequencing data in eukaryotes. Mol Ecol 2021; 30:6036-6071. [PMID: 34009688 DOI: 10.1111/mec.15989] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/26/2021] [Accepted: 05/11/2021] [Indexed: 01/01/2023]
Abstract
Characterizing the population history of a species and identifying loci underlying local adaptation is crucial in functional ecology, evolutionary biology, conservation and agronomy. The constant improvement of high-throughput sequencing techniques has facilitated the production of whole genome data in a wide range of species. Population genomics now provides tools to better integrate selection into a historical framework, and take into account selection when reconstructing demographic history. However, this improvement has come with a profusion of analytical tools that can confuse and discourage users. Such confusion limits the amount of information effectively retrieved from complex genomic data sets, and impairs the diffusion of the most recent analytical tools into fields such as conservation biology. It may also lead to redundancy among methods. To address these isssues, we propose an overview of more than 100 state-of-the-art methods that can deal with whole genome data. We summarize the strategies they use to infer demographic history and selection, and discuss some of their limitations. A website listing these methods is available at www.methodspopgen.com.
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Affiliation(s)
| | - Ben H Warren
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, EPHE, UA, CP 51, Paris, France
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40
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Clemente F, Unterländer M, Dolgova O, Amorim CEG, Coroado-Santos F, Neuenschwander S, Ganiatsou E, Cruz Dávalos DI, Anchieri L, Michaud F, Winkelbach L, Blöcher J, Arizmendi Cárdenas YO, Sousa da Mota B, Kalliga E, Souleles A, Kontopoulos I, Karamitrou-Mentessidi G, Philaniotou O, Sampson A, Theodorou D, Tsipopoulou M, Akamatis I, Halstead P, Kotsakis K, Urem-Kotsou D, Panagiotopoulos D, Ziota C, Triantaphyllou S, Delaneau O, Jensen JD, Moreno-Mayar JV, Burger J, Sousa VC, Lao O, Malaspinas AS, Papageorgopoulou C. The genomic history of the Aegean palatial civilizations. Cell 2021; 184:2565-2586.e21. [PMID: 33930288 PMCID: PMC8127963 DOI: 10.1016/j.cell.2021.03.039] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 09/17/2020] [Accepted: 03/18/2021] [Indexed: 12/30/2022]
Abstract
The Cycladic, the Minoan, and the Helladic (Mycenaean) cultures define the Bronze Age (BA) of Greece. Urbanism, complex social structures, craft and agricultural specialization, and the earliest forms of writing characterize this iconic period. We sequenced six Early to Middle BA whole genomes, along with 11 mitochondrial genomes, sampled from the three BA cultures of the Aegean Sea. The Early BA (EBA) genomes are homogeneous and derive most of their ancestry from Neolithic Aegeans, contrary to earlier hypotheses that the Neolithic-EBA cultural transition was due to massive population turnover. EBA Aegeans were shaped by relatively small-scale migration from East of the Aegean, as evidenced by the Caucasus-related ancestry also detected in Anatolians. In contrast, Middle BA (MBA) individuals of northern Greece differ from EBA populations in showing ∼50% Pontic-Caspian Steppe-related ancestry, dated at ca. 2,600-2,000 BCE. Such gene flow events during the MBA contributed toward shaping present-day Greek genomes.
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Affiliation(s)
- Florian Clemente
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Martina Unterländer
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece; Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Olga Dolgova
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028 Barcelona, Spain
| | - Carlos Eduardo G Amorim
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Francisco Coroado-Santos
- CE3C, Centre for Ecology, Evolution and Environmental Changes, Faculty of Sciences of the University of Lisbon, 1749-016 Lisbon, Portugal
| | - Samuel Neuenschwander
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Vital-IT, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Elissavet Ganiatsou
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Diana I Cruz Dávalos
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Lucas Anchieri
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Frédéric Michaud
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Laura Winkelbach
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Jens Blöcher
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Yami Ommar Arizmendi Cárdenas
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Bárbara Sousa da Mota
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Eleni Kalliga
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Angelos Souleles
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Ioannis Kontopoulos
- Center for GeoGenetics, GLOBE Institute, University of Copenhagen, 1350 Copenhagen, Denmark
| | | | - Olga Philaniotou
- Ephor Emerita of Antiquities, Hellenic Ministry of Culture and Sports, 10682 Athens, Greece
| | - Adamantios Sampson
- Department of Mediterranean Studies, University of the Aegean, 85132 Rhodes, Greece
| | - Dimitra Theodorou
- Ephorate of Antiquities of Kozani, Hellenic Ministry of Culture and Sports, 50004 Kozani, Greece
| | - Metaxia Tsipopoulou
- Ephor Emerita of Antiquities, Hellenic Ministry of Culture and Sports, 10682 Athens, Greece
| | - Ioannis Akamatis
- Department of History and Archaeology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Paul Halstead
- Department of Archaeology, University of Sheffield, Minalloy House, 10-16 Regent St., Sheffield S1 3NJ, UK
| | - Kostas Kotsakis
- Department of History and Archaeology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Dushka Urem-Kotsou
- Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Diamantis Panagiotopoulos
- Institute of Classical Archaeology, University of Heidelberg, Marstallhof 4, 69117 Heidelberg, Germany
| | - Christina Ziota
- Ephorate of Antiquities of Florina, Hellenic Ministry of Culture and Sports, 53100 Florina, Greece
| | - Sevasti Triantaphyllou
- Department of History and Archaeology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Olivier Delaneau
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - J Víctor Moreno-Mayar
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Center for GeoGenetics, GLOBE Institute, University of Copenhagen, 1350 Copenhagen, Denmark; National Institute of Genomic Medicine (INMEGEN), 14610 Mexico City, Mexico
| | - Joachim Burger
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Vitor C Sousa
- CE3C, Centre for Ecology, Evolution and Environmental Changes, Faculty of Sciences of the University of Lisbon, 1749-016 Lisbon, Portugal
| | - Oscar Lao
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Anna-Sapfo Malaspinas
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
| | - Christina Papageorgopoulou
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece.
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41
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Shen QK, Peng MS, Adeola AC, Kui L, Duan S, Miao YW, Eltayeb NM, Lichoti JK, Otecko NO, Strillacci MG, Gorla E, Bagnato A, Charles OS, Sanke OJ, Dawuda PM, Okeyoyin AO, Musina J, Njoroge P, Agwanda B, Kusza S, Nanaei HA, Pedar R, Xu MM, Du Y, Nneji LM, Murphy RW, Wang MS, Esmailizadeh A, Dong Y, Ommeh SC, Zhang YP. Genomic Analyses of Unveil Helmeted Guinea Fowl (Numida meleagris) Domestication in West Africa. Genome Biol Evol 2021; 13:6261762. [PMID: 34009300 PMCID: PMC8214406 DOI: 10.1093/gbe/evab090] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/30/2021] [Indexed: 12/22/2022] Open
Abstract
Domestication of the helmeted guinea fowl (HGF; Numida meleagris) in Africa remains elusive. Here we report a high-quality de novo genome assembly for domestic HGF generated by long- and short-reads sequencing together with optical and chromatin interaction mapping. Using this assembly as the reference, we performed population genomic analyses for newly sequenced whole-genomes for 129 birds from Africa, Asia, and Europe, including domestic animals (n = 89), wild progenitors (n = 34), and their closely related wild species (n = 6). Our results reveal domestication of HGF in West Africa around 1,300-5,500 years ago. Scanning for selective signals characterized the functional genes in behavior and locomotion changes involved in domestication of HGF. The pleiotropy and linkage in genes affecting plumage color and fertility were revealed in the recent breeding of Italian domestic HGF. In addition to presenting a missing piece to the jigsaw puzzle of domestication in poultry, our study provides valuable genetic resources for researchers and breeders to improve production in this species.
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Affiliation(s)
- Quan-Kuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Nairobi, Kenya.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Nairobi, Kenya.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Adeniyi C Adeola
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Nairobi, Kenya.,Centre for Biotechnology Research, Bayero University, Kano, Nigeria
| | - Ling Kui
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Yong-Wang Miao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, China
| | - Nada M Eltayeb
- Department of Animal breeding and Reproduction Technology, College of Animal Production, University of Bahri, Khartoum, Sudan
| | - Jacqueline K Lichoti
- State Department of Livestock, Ministry of Agriculture Livestock Fisheries and Irrigation, Nairobi, Kenya
| | - Newton O Otecko
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Nairobi, Kenya.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | | | - Erica Gorla
- Department of Veterinary Medicine, Università degli Studi di Milano, Italy
| | - Alessandro Bagnato
- Department of Veterinary Medicine, Università degli Studi di Milano, Italy
| | | | - Oscar J Sanke
- Taraba State Ministry of Agriculture and Natural Resources, Jalingo, Nigeria
| | - Philip M Dawuda
- Department of Veterinary Surgery and Theriogenology, College of Veterinary Medicine, University of Agriculture, Makurdi, Nigeria
| | - Agboola O Okeyoyin
- National Park Service Headquarter, Federal Capital Territory, Abuja, Nigeria
| | - John Musina
- Department of Zoology, National Museums of Kenya, Nairobi, Kenya
| | - Peter Njoroge
- Department of Zoology, National Museums of Kenya, Nairobi, Kenya
| | - Bernard Agwanda
- Department of Zoology, National Museums of Kenya, Nairobi, Kenya
| | - Szilvia Kusza
- Centre for Agricultural Genomics and Biotechnology, University of Debrecen, Debrecen, Hungary
| | | | - Rana Pedar
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Iran
| | - Ming-Min Xu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Nairobi, Kenya.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Yuan Du
- Nowbio Biotechnology Company, Kunming, China
| | - Lotanna M Nneji
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Nairobi, Kenya
| | - Robert W Murphy
- Centre for Biodiversity and Conservation Biology, Royal Ontario Museum, Toronto, Ontario, Canada
| | - Ming-Shan Wang
- Howard Hughes Medical Institute, University of California Santa Cruz, California, USA.,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, California, USA
| | - Ali Esmailizadeh
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Iran
| | - Yang Dong
- College of Biological Big Data, Yunnan Agriculture University, Kunming, China.,State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, China.,Key Laboratory for Agro-Biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, China
| | - Sheila C Ommeh
- Department of Zoology, National Museums of Kenya, Nairobi, Kenya.,Institute of Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Nairobi, Kenya.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China.,State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, Yunnan University, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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42
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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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43
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Dong F, Kuo HC, Chen GL, Wu F, Shan PF, Wang J, Chen D, Lei FM, Hung CM, Liu Y, Yang XJ. Population genomic, climatic and anthropogenic evidence suggest the role of human forces in endangerment of green peafowl ( Pavo muticus). Proc Biol Sci 2021; 288:20210073. [PMID: 33823666 DOI: 10.1098/rspb.2021.0073] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Both anthropogenic impacts and historical climate change could contribute to population decline and species extinction, but their relative importance is still unclear. Emerging approaches based on genomic, climatic and anthropogenic data provide a promising analytical framework to address this question. This study applied such an integrative approach to examine potential drivers for the endangerment of the green peafowl (Pavo muticus). Several demographic reconstructions based on population genomes congruently retrieved a drastic population declination since the mid-Holocene. Furthermore, a comparison between historical and modern genomes suggested genetic diversity decrease during the last 50 years. However, climate-based ecological niche models predicted stationary general range during these periods and imply the little impact of climate change. Further analyses suggested that human disturbance intensities were negatively correlated with the green peafowl's effective population sizes and significantly associated with its survival status (extirpation or persistence). Archaeological and historical records corroborate the critical role of humans, leaving the footprint of low genomic diversity and high inbreeding in the survival populations. This study sheds light on the potential deep-time effects of human disturbance on species endangerment and offers a multi-evidential approach in examining underlying forces for population declines.
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Affiliation(s)
- Feng Dong
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, People's Republic of China
| | - Hao-Chih Kuo
- Biodiversity Research Center, Academia Sinica, Taipei 115, Taiwan
| | - Guo-Ling Chen
- State Key Laboratory of Biocontrol, School of Ecology and School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People's Republic of China
| | - Fei Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, People's Republic of China
| | - Peng-Fei Shan
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, People's Republic of China
| | - Jie Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, People's Republic of China
| | - De Chen
- MOE Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Fu-Min Lei
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China
| | - Chih-Ming Hung
- Biodiversity Research Center, Academia Sinica, Taipei 115, Taiwan
| | - Yang Liu
- State Key Laboratory of Biocontrol, School of Ecology and School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, People's Republic of China
| | - Xiao-Jun Yang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, People's Republic of China
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44
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Fortes-Lima CA, Laurent R, Thouzeau V, Toupance B, Verdu P. Complex genetic admixture histories reconstructed with Approximate Bayesian Computation. Mol Ecol Resour 2021; 21:1098-1117. [PMID: 33452723 PMCID: PMC8247995 DOI: 10.1111/1755-0998.13325] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 12/11/2020] [Accepted: 01/07/2021] [Indexed: 01/19/2023]
Abstract
Admixture is a fundamental evolutionary process that has influenced genetic patterns in numerous species. Maximum‐likelihood approaches based on allele frequencies and linkage‐disequilibrium have been extensively used to infer admixture processes from genome‐wide data sets, mostly in human populations. Nevertheless, complex admixture histories, beyond one or two pulses of admixture, remain methodologically challenging to reconstruct. We developed an Approximate Bayesian Computation (ABC) framework to reconstruct highly complex admixture histories from independent genetic markers. We built the software package methis to simulate independent SNPs or microsatellites in a two‐way admixed population for scenarios with multiple admixture pulses, monotonically decreasing or increasing recurring admixture, or combinations of these scenarios. methis allows users to draw model‐parameter values from prior distributions set by the user, and, for each simulation, methis can calculate numerous summary statistics describing genetic diversity patterns and moments of the distribution of individual admixture fractions. We coupled methis with existing machine‐learning ABC algorithms and investigated the admixture history of admixed populations. Results showed that random forest ABC scenario‐choice could accurately distinguish among most complex admixture scenarios, and errors were mainly found in regions of the parameter space where scenarios were highly nested, and, thus, biologically similar. We focused on African American and Barbadian populations as two study‐cases. We found that neural network ABC posterior parameter estimation was accurate and reasonably conservative under complex admixture scenarios. For both admixed populations, we found that monotonically decreasing contributions over time, from Europe and Africa, explained the observed data more accurately than multiple admixture pulses. This approach will allow for reconstructing detailed admixture histories when maximum‐likelihood methods are intractable.
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Affiliation(s)
- Cesar A Fortes-Lima
- UMR7206 Eco-anthropologie, CNRS, Muséum National d'Histoire Naturelle, Université de Paris, Paris, France.,Sub-department of Human Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Romain Laurent
- UMR7206 Eco-anthropologie, CNRS, Muséum National d'Histoire Naturelle, Université de Paris, Paris, France
| | - Valentin Thouzeau
- UMR7534 Centre de Recherche en Mathématiques de la Décision, CNRS, Université Paris-Dauphine, PSL University, Paris, France.,Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Etudes Cognitives, ENS, PSL University, EHESS, CNRS, Paris, France
| | - Bruno Toupance
- UMR7206 Eco-anthropologie, CNRS, Muséum National d'Histoire Naturelle, Université de Paris, Paris, France
| | - Paul Verdu
- UMR7206 Eco-anthropologie, CNRS, Muséum National d'Histoire Naturelle, Université de Paris, Paris, France
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45
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Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD. The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects. Mol Biol Evol 2021; 38:2986-3003. [PMID: 33591322 PMCID: PMC8233493 DOI: 10.1093/molbev/msab050] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
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Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Kellen Riall
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Hannes Becher
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Laurent Excoffier
- Institute of Ecology and Evolution, University of Berne, Berne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
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46
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Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD. The impact of purifying and background selection on the inference of population history: problems and prospects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021. [PMID: 33501439 PMCID: PMC7836109 DOI: 10.1101/2020.04.28.066365] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Current procedures for inferring population history generally assume complete neutrality - that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects (DFE) and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the DFE as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
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Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Kellen Riall
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Hannes Becher
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Laurent Excoffier
- Institute of Ecology and Evolution, University of Berne, Berne 3012, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
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47
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Everhart S, Gambhir N, Stam R. Population Genomics of Filamentous Plant Pathogens-A Brief Overview of Research Questions, Approaches, and Pitfalls. PHYTOPATHOLOGY 2021; 111:12-22. [PMID: 33337245 DOI: 10.1094/phyto-11-20-0527-fi] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
With ever-decreasing sequencing costs, research on the population biology of plant pathogens is transitioning from population genetics-using dozens of genetic markers or polymorphism data of several genes-to population genomics-using several hundred to tens of thousands of markers or whole-genome sequence data. The field of population genomics is characterized by rapid theoretical and methodological advances and by numerous steps and pitfalls in its technical and analytical workflow. In this article, we aim to provide a brief overview of topics relevant to the study of population genomics of filamentous plant pathogens and direct readers to more extensive reviews for in-depth understanding. We briefly discuss different types of population genomics-inspired research questions and give insights into the sampling strategies that can be used to answer such questions. We then consider different sequencing strategies, the various options available for data processing, and some of the currently available tools for population genomic data analysis. We conclude by highlighting some of the hurdles along the population genomic workflow, providing cautionary warnings relative to assumptions and technical challenges, and presenting our own future perspectives of the field of population genomics for filamentous plant pathogens.
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Affiliation(s)
- Sydney Everhart
- Department of Plant Pathology, University of Nebraska, Lincoln, NE 68583, U.S.A
| | - Nikita Gambhir
- Department of Plant Pathology, University of Nebraska, Lincoln, NE 68583, U.S.A
| | - Remco Stam
- Phytopathology, School of Life Sciences Weihenstephan, Technical University Munich, Germany
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48
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Liu X, Fu YX. Stairway Plot 2: demographic history inference with folded SNP frequency spectra. Genome Biol 2020; 21:280. [PMID: 33203475 PMCID: PMC7670622 DOI: 10.1186/s13059-020-02196-9] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 11/05/2020] [Indexed: 01/27/2023] Open
Abstract
Inferring the demographic histories of populations has wide applications in population, ecological, and conservation genomics. We present Stairway Plot 2, a cross-platform program package for this task using SNP frequency spectra. It is based on a nonparametric method with the capability of handling folded SNP frequency spectra (that is, when the ancestral alleles of the SNPs are unknown) of thousands of samples produced with genotyping-by-sequencing technologies; therefore, it is particularly suitable for nonmodel organisms.
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Affiliation(s)
- Xiaoming Liu
- USF Genomics & College of Public Health, University of South Florida, Tampa, FL, USA.
| | - Yun-Xin Fu
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
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49
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Zhang P, Zhao Y, Li C, Lin M, Dong L, Zhang R, Liu M, Li K, Zhang H, Liu X, Zhang Y, Yuan Y, Liu H, Seim I, Sun S, Du X, Chang Y, Li F, Liu S, Lee SMY, Wang K, Wang D, Wang X, McGowen MR, Jefferson TA, Olsen MT, Stiller J, Zhang G, Xu X, Yang H, Fan G, Liu X, Li S. An Indo-Pacific Humpback Dolphin Genome Reveals Insights into Chromosome Evolution and the Demography of a Vulnerable Species. iScience 2020; 23:101640. [PMID: 33103078 PMCID: PMC7569330 DOI: 10.1016/j.isci.2020.101640] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 08/25/2020] [Accepted: 09/30/2020] [Indexed: 01/12/2023] Open
Abstract
The Indo-Pacific humpback dolphin (Sousa chinensis) is a small inshore species of odontocete cetacean listed as Vulnerable on the IUCN Red List. Here, we report on the evolution of S. chinensis chromosomes from its cetruminant ancestor and elucidate the evolutionary history and population genetics of two neighboring S. chinensis populations. We found that breakpoints in ancestral chromosomes leading to S. chinensis could have affected the function of genes related to kidney filtration, body development, and immunity. Resequencing of individuals from two neighboring populations in the northwestern South China Sea, Leizhou Bay and Sanniang Bay, revealed genetic differentiation, low diversity, and small contemporary effective population sizes. Demographic analyses showed a marked decrease in the population size of the two investigated populations over the last ~4,000 years, possibly related to climatic oscillations. This study implies a high risk of extinction and strong conservation requirement for the Indo-Pacific humpback dolphin. Deducing chromosome evolution from ancestral Cetruminantia and ancestral Odontoceti Reconstructing the demographic history of Sousa chinensis Implying high risk of extinction and strong conservation requirement for S. chinensis
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Affiliation(s)
- Peijun Zhang
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
| | - Yong Zhao
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Chang Li
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong 518083, China
| | - Mingli Lin
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China
| | - Lijun Dong
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China
| | - Rui Zhang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Mingzhong Liu
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China
| | - Kuan Li
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China
| | - He Zhang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
- Department of Biology, Hong Kong Baptist University, Hong Kong, China
| | - Xiaochuan Liu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Yaolei Zhang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby 2800, Denmark
| | - Yuan Yuan
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China
| | - Huan Liu
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Inge Seim
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China
- Comparative and Endocrine Biology Laboratory, Translational Research Institute-Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Brisbane 4102, Australia
| | - Shuai Sun
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Xiao Du
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Yue Chang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Feida Li
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Shanshan Liu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
| | - Simon Ming-Yuen Lee
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao 999078, China
| | - Kun Wang
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China
| | - Ding Wang
- Key Laboratory of Aquatic Biodiversity and Conservation of Chinese Academy of Sciences, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei 430072, China
| | - Xianyan Wang
- Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, Fujian 361005, China
| | - Michael R. McGowen
- Department of Vertebrate Zoology, Smithsonian National Museum of Natural History, Washington DC 20560, USA
| | | | - Morten Tange Olsen
- Evolutionary Genomics Section, Globe Institute, University of Copenhagen, Øster Farimagsgade 5, Copenhagen 1353, Denmark
| | - Josefin Stiller
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
| | - Guojie Zhang
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
- China National GeneBank, BGI-Shenzhen, Shenzhen, Guangdong 518120, China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Xun Xu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, Guangdong 518120, China
| | - Guangyi Fan
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao 999078, China
- Corresponding author
| | - Xin Liu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong 266555, China
- BGI-Shenzhen, Shenzhen, Guangdong 518083, China
- BGI-Fuyang, BGI-Shenzhen, Fuyang, Anhui 236009, China
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, Guandong 518083, China
- Corresponding author
| | - Songhai Li
- Marine Mammal and Marine Bioacoustics Laboratory, Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China
- Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong 266237, China
- Tropical Marine Science Institute, National University of Singapore, Singapore 119227, Singapore
- Corresponding author
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Ghirotto S, Vizzari MT, Tassi F, Barbujani G, Benazzo A. Distinguishing among complex evolutionary models using unphased whole-genome data through random forest approximate Bayesian computation. Mol Ecol Resour 2020; 21:2614-2628. [PMID: 33000507 DOI: 10.1111/1755-0998.13263] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 08/28/2020] [Accepted: 09/07/2020] [Indexed: 01/25/2023]
Abstract
Inferring past demographic histories is crucial in population genetics, and the amount of complete genomes now available should in principle facilitate this inference. In practice, however, the available inferential methods suffer from severe limitations. Although hundreds complete genomes can be simultaneously analysed, complex demographic processes can easily exceed computational constraints, and the procedures to evaluate the reliability of the estimates contribute to increase the computational effort. Here we present an approximate Bayesian computation framework based on the random forest algorithm (ABC-RF), to infer complex past population processes using complete genomes. To this aim, we propose to summarize the data by the full genomic distribution of the four mutually exclusive categories of segregating sites (FDSS), a statistic fast to compute from unphased genome data and that does not require the ancestral state of alleles to be known. We constructed an efficient ABC pipeline and tested how accurately it allows one to recognize the true model among models of increasing complexity, using simulated data and taking into account different sampling strategies in terms of number of individuals analysed, number and size of the genetic loci considered. We also compared the FDSS with the unfolded and folded site frequency spectrum (SFS), and for these statistics we highlighted the experimental conditions maximizing the inferential power of the ABC-RF procedure. We finally analysed real data sets, testing models on the dispersal of anatomically modern humans out of Africa and exploring the evolutionary relationships of the three species of Orangutan inhabiting Borneo and Sumatra.
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Affiliation(s)
- Silvia Ghirotto
- Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy
| | - Maria Teresa Vizzari
- Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy
| | - Francesca Tassi
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Guido Barbujani
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Andrea Benazzo
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
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