1
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Forien R, Ringbauer H, Coop G. Demographic inference for spatially heterogeneous populations using long shared haplotypes. Theor Popul Biol 2024; 159:108-124. [PMID: 38492811 DOI: 10.1016/j.tpb.2024.03.002] [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: 06/09/2023] [Revised: 03/04/2024] [Accepted: 03/12/2024] [Indexed: 03/18/2024]
Abstract
We introduce a modified spatial Λ-Fleming-Viot process to model the ancestry of individuals in a population occupying a continuous spatial habitat divided into two areas by a sharp discontinuity of the dispersal rate and effective population density. We derive an analytical formula for the expected number of shared haplotype segments between two individuals depending on their sampling locations. This formula involves the transition density of a skew diffusion which appears as a scaling limit of the ancestral lineages of individuals in this model. We then show that this formula can be used to infer the dispersal parameters and the effective population density of both regions, using a composite likelihood approach, and we demonstrate the efficiency of this method on a range of simulated data sets.
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Affiliation(s)
- Raphaël Forien
- INRAE - BioSP, Centre INRAE PACA, 228 route de l'aérodrome, Domaine St-Paul - Site Agroparc, 84914, Avignon Cedex 9, France.
| | - Harald Ringbauer
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103, Leipzig, Germany.
| | - Graham Coop
- Center for Population Biology, Department of Evolution and Ecology, University of California, 2320 Storer Hall, CA 95616, Davis, United States.
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2
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McCann RS, Courneya JP, Donnelly MJ, Laufer MK, Mzilahowa T, Stewart K, Agossa F, Tezzo FW, Miles A, Takala-Harrison S, O'Connor TD. Variation in spatial population structure in the Anopheles gambiae species complex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.26.595955. [PMID: 38853983 PMCID: PMC11160690 DOI: 10.1101/2024.05.26.595955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Anopheles gambiae , Anopheles coluzzii , and Anopheles arabiensis are three of the most widespread vectors of malaria parasites, with geographical ranges stretching across wide swaths of Africa. Understanding the population structure of these closely related species, including the extent to which populations are connected by gene flow, is essential for understanding how vector control implemented in one location might indirectly affect vector populations in other locations. Here, we assessed the population structure of each species based on a combined data set of publicly available and newly processed whole-genome sequences. The data set included single nucleotide polymorphisms from whole genomes of 2,410 individual mosquitoes sampled from 128 locations across 19 African countries. We found that A. gambiae sampled from several countries in West and Central Africa showed low genetic differentiation from each other according to principal components analysis (PCA) and ADMIXTURE modeling. Using Estimated Effective Migration Surfaces (EEMS), we showed that this low genetic differentiation indicates high effective migration rates for A. gambiae across this region. Outside of this region, we found eight groups of sampling locations from Central, East, and Southern Africa for which A. gambiae showed higher genetic differentiation, and lower effective migration rates, between each other and the West/Central Africa group. These results indicate that the barriers to and corridors for migration between populations of A. gambiae differ across the geographical range of this malaria vector species. Using the same methods, we found higher genetic differentiation and lower migration rates between populations of A. coluzzii in West and Central Africa than for A. gambiae in the same region. In contrast, we found lower genetic differentiation and higher migration rates between populations of A. arabiensis in Tanzania, compared to A. gambiae in the same region. These differences between A. gambiae , A. coluzzii , and A. arabiensis indicate that migration barriers and corridors may vary, even between very closely related species. Overall, our results demonstrate that migration rates vary both within and between species of Anopheles mosquitoes, presumably based on species-specific responses to the ecological or environmental conditions that may impede or facilitate migration, and the geographical patterns of these conditions across the landscape. Together with previous findings, this study provides robust evidence that migration rates between populations of malaria vectors depend on the ecological context, which should be considered when planning surveillance of vector populations, monitoring for insecticide resistance, and evaluating interventions.
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3
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Smith CCR, Patterson G, Ralph PL, Kern AD. Estimation of spatial demographic maps from polymorphism data using a neural network. Mol Ecol Resour 2024:e14005. [PMID: 39152666 DOI: 10.1111/1755-0998.14005] [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: 03/26/2024] [Revised: 07/16/2024] [Accepted: 08/06/2024] [Indexed: 08/19/2024]
Abstract
A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity-by-descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN.
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Affiliation(s)
- Chris C R Smith
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA
| | - Gilia Patterson
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA
| | - Peter L Ralph
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA
| | - Andrew D Kern
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, USA
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4
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Smith CCR, Patterson G, Ralph PL, Kern AD. Estimation of spatial demographic maps from polymorphism data using a neural network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585300. [PMID: 38559192 PMCID: PMC10980082 DOI: 10.1101/2024.03.15.585300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity by descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology, and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN .
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5
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Guo B, Takala-Harrison S, O’Connor TD. Benchmarking and Optimization of Methods for the Detection of Identity-By-Descent in High-Recombining Plasmodium falciparum Genomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.04.592538. [PMID: 38746392 PMCID: PMC11092787 DOI: 10.1101/2024.05.04.592538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is increasingly being used in Plasmodium population genomics to estimate genetic relatedness, effective population size (N e ), population structure, and signals of positive selection. Despite its potential, a thorough evaluation of IBD segment detection tools for species with high recombination rates, such as P. falciparum, remains absent. Here, we perform comprehensive benchmarking of IBD callers - probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD) - using population genetic simulations tailored for high recombination, and IBD quality metrics at both the IBD segment level and the IBD-based downstream inference level. Our results demonstrate that low marker density per genetic unit, related to high recombination relative to mutation, significantly compromises the accuracy of detected IBD segments. In genomes with high recombination rates resembling P. falciparum, most IBD callers exhibit high false negative rates for shorter IBD segments, which can be partially mitigated through optimization of IBD caller parameters, especially those related to marker density. Notably, IBD detected with optimized parameters allows for more accurate capture of selection signals and population structure; IBD-based N e inference is very sensitive to IBD detection errors, with IBD called from hmmIBD uniquely providing less biased estimates of N e in this context. Validation with empirical data from the MalariaGEN Pf 7 database, representing different transmission settings, corroborates these findings. We conclude that context-specific evaluation and parameter optimization are essential for accurate IBD detection in high-recombining species and recommend hmmIBD for quality-sensitive analysis, such as estimation of N e in these species. Our optimization and high-level benchmarking methods not only improve IBD segment detection in high-recombining genomes but also enhance overall genomic analysis, paving the way for more accurate genomic surveillance and targeted intervention strategies for malaria.
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Affiliation(s)
- Bing Guo
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD USA
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shannon Takala-Harrison
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD USA
| | - Timothy D. O’Connor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
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6
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Lasky JR, Takou M, Gamba D, Keitt TH. Estimating scale-specific and localized spatial patterns in allele frequency. Genetics 2024; 227:iyae082. [PMID: 38758968 PMCID: PMC11339607 DOI: 10.1093/genetics/iyae082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 09/07/2023] [Accepted: 04/28/2024] [Indexed: 05/19/2024] Open
Abstract
Characterizing spatial patterns in allele frequencies is fundamental to evolutionary biology because these patterns contain evidence of underlying processes. However, the spatial scales at which gene flow, changing selection, and drift act are often unknown. Many of these processes can operate inconsistently across space, causing nonstationary patterns. We present a wavelet approach to characterize spatial pattern in allele frequency that helps solve these problems. We show how our approach can characterize spatial patterns in relatedness at multiple spatial scales, i.e. a multilocus wavelet genetic dissimilarity. We also develop wavelet tests of spatial differentiation in allele frequency and quantitative trait loci (QTL). With simulation, we illustrate these methods under different scenarios. We also apply our approach to natural populations of Arabidopsis thaliana to characterize population structure and identify locally adapted loci across scales. We find, for example, that Arabidopsis flowering time QTL show significantly elevated genetic differentiation at 300-1,300 km scales. Wavelet transforms of allele frequencies offer a flexible way to reveal geographic patterns and underlying evolutionary processes.
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Affiliation(s)
- Jesse R Lasky
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Margarita Takou
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Diana Gamba
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Timothy H Keitt
- Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA
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7
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Vilà-Valls L, Abdeli A, Lucas-Sánchez M, Bekada A, Calafell F, Benhassine T, Comas D. Understanding the genomic heterogeneity of North African Imazighen: from broad to microgeographical perspectives. Sci Rep 2024; 14:9979. [PMID: 38693301 PMCID: PMC11063056 DOI: 10.1038/s41598-024-60568-8] [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: 02/01/2024] [Accepted: 04/24/2024] [Indexed: 05/03/2024] Open
Abstract
The strategic location of North Africa has led to cultural and demographic shifts, shaping its genetic structure. Historical migrations brought different genetic components that are evident in present-day North African genomes, along with autochthonous components. The Imazighen (plural of Amazigh) are believed to be the descendants of autochthonous North Africans and speak various Amazigh languages, which belong to the Afro-Asiatic language family. However, the arrival of different human groups, especially during the Arab conquest, caused cultural and linguistic changes in local populations, increasing their heterogeneity. We aim to characterize the genetic structure of the region, using the largest Amazigh dataset to date and other reference samples. Our findings indicate microgeographical genetic heterogeneity among Amazigh populations, modeled by various admixture waves and different effective population sizes. A first admixture wave is detected group-wide around the twelfth century, whereas a second wave appears in some Amazigh groups around the nineteenth century. These events involved populations with higher genetic ancestry from south of the Sahara compared to the current North Africans. A plausible explanation would be the historical trans-Saharan slave trade, which lasted from the Roman times to the nineteenth century. Furthermore, our investigation shows that assortative mating in North Africa has been rare.
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Affiliation(s)
- Laura Vilà-Valls
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain
| | - Amine Abdeli
- Laboratoire de Biologie Cellulaire et Moléculaire, Faculté Des Sciences Biologiques, Université des Sciences et de la Technologie Houari Boumediene, Alger, Algeria
| | - Marcel Lucas-Sánchez
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain
| | - Asmahan Bekada
- Département de Biotechnologie, Faculté des Sciences de la Nature et de la Vie, Université Oran 1 (Ahmad Ben Bella), Oran, Algeria
| | - Francesc Calafell
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain
| | - Traki Benhassine
- Laboratoire de Biologie Cellulaire et Moléculaire, Faculté Des Sciences Biologiques, Université des Sciences et de la Technologie Houari Boumediene, Alger, Algeria
| | - David Comas
- Departament de Medicina i Ciències de la Vida, Institut de Biologia Evolutiva (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Spain.
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8
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Guo B, Borda V, Laboulaye R, Spring MD, Wojnarski M, Vesely BA, Silva JC, Waters NC, O'Connor TD, Takala-Harrison S. Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum. Nat Commun 2024; 15:2499. [PMID: 38509066 PMCID: PMC10954658 DOI: 10.1038/s41467-024-46659-0] [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: 07/27/2023] [Accepted: 02/28/2024] [Indexed: 03/22/2024] Open
Abstract
Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.
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Affiliation(s)
- Bing Guo
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Victor Borda
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Roland Laboulaye
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Michele D Spring
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Mariusz Wojnarski
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Brian A Vesely
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Joana C Silva
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD, USA
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (NOVA), Lisbon, Portugal
| | - Norman C Waters
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Timothy D O'Connor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Shannon Takala-Harrison
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA.
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9
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Schiebelhut LM, Guillaume AS, Kuhn A, Schweizer RM, Armstrong EE, Beaumont MA, Byrne M, Cosart T, Hand BK, Howard L, Mussmann SM, Narum SR, Rasteiro R, Rivera-Colón AG, Saarman N, Sethuraman A, Taylor HR, Thomas GWC, Wellenreuther M, Luikart G. Genomics and conservation: Guidance from training to analyses and applications. Mol Ecol Resour 2024; 24:e13893. [PMID: 37966259 DOI: 10.1111/1755-0998.13893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 10/25/2023] [Accepted: 10/30/2023] [Indexed: 11/16/2023]
Abstract
Environmental change is intensifying the biodiversity crisis and threatening species across the tree of life. Conservation genomics can help inform conservation actions and slow biodiversity loss. However, more training, appropriate use of novel genomic methods and communication with managers are needed. Here, we review practical guidance to improve applied conservation genomics. We share insights aimed at ensuring effectiveness of conservation actions around three themes: (1) improving pedagogy and training in conservation genomics including for online global audiences, (2) conducting rigorous population genomic analyses properly considering theory, marker types and data interpretation and (3) facilitating communication and collaboration between managers and researchers. We aim to update students and professionals and expand their conservation toolkit with genomic principles and recent approaches for conserving and managing biodiversity. The biodiversity crisis is a global problem and, as such, requires international involvement, training, collaboration and frequent reviews of the literature and workshops as we do here.
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Affiliation(s)
- Lauren M Schiebelhut
- Life and Environmental Sciences, University of California, Merced, California, USA
| | - Annie S Guillaume
- Geospatial Molecular Epidemiology group (GEOME), Laboratory for Biological Geochemistry (LGB), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arianna Kuhn
- Department of Biological Sciences, University of Lethbridge, Lethbridge, Alberta, Canada
- Virginia Museum of Natural History, Martinsville, Virginia, USA
| | - Rena M Schweizer
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
| | | | - Mark A Beaumont
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Margaret Byrne
- Department of Biodiversity, Conservation and Attractions, Biodiversity and Conservation Science, Perth, Western Australia, Australia
| | - Ted Cosart
- Flathead Lake Biology Station, University of Montana, Missoula, Montana, USA
| | - Brian K Hand
- Flathead Lake Biological Station, University of Montana, Polson, Montana, USA
| | - Leif Howard
- Flathead Lake Biology Station, University of Montana, Missoula, Montana, USA
| | - Steven M Mussmann
- Southwestern Native Aquatic Resources and Recovery Center, U.S. Fish & Wildlife Service, Dexter, New Mexico, USA
| | - Shawn R Narum
- Hagerman Genetics Lab, University of Idaho, Hagerman, Idaho, USA
| | - Rita Rasteiro
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Angel G Rivera-Colón
- Department of Evolution, Ecology, and Behavior, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
| | - Norah Saarman
- Department of Biology and Ecology Center, Utah State University, Logan, Utah, USA
| | - Arun Sethuraman
- Department of Biology, San Diego State University, San Diego, California, USA
| | - Helen R Taylor
- Royal Zoological Society of Scotland, Edinburgh, Scotland
| | - Gregg W C Thomas
- Informatics Group, Harvard University, Cambridge, Massachusetts, USA
| | - Maren Wellenreuther
- Plant and Food Research, Nelson, New Zealand
- University of Auckland, Auckland, New Zealand
| | - Gordon Luikart
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
- Flathead Lake Biology Station, University of Montana, Missoula, Montana, USA
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10
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Ringbauer H, Huang Y, Akbari A, Mallick S, Olalde I, Patterson N, Reich D. Accurate detection of identity-by-descent segments in human ancient DNA. Nat Genet 2024; 56:143-151. [PMID: 38123640 PMCID: PMC10786714 DOI: 10.1038/s41588-023-01582-w] [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: 03/21/2023] [Accepted: 10/20/2023] [Indexed: 12/23/2023]
Abstract
Long DNA segments shared between two individuals, known as identity-by-descent (IBD), reveal recent genealogical connections. Here we introduce ancIBD, a method for identifying IBD segments in ancient human DNA (aDNA) using a hidden Markov model and imputed genotype probabilities. We demonstrate that ancIBD accurately identifies IBD segments >8 cM for aDNA data with an average depth of >0.25× for whole-genome sequencing or >1× for 1240k single nucleotide polymorphism capture data. Applying ancIBD to 4,248 ancient Eurasian individuals, we identify relatives up to the sixth degree and genealogical connections between archaeological groups. Notably, we reveal long IBD sharing between Corded Ware and Yamnaya groups, indicating that the Yamnaya herders of the Pontic-Caspian Steppe and the Steppe-related ancestry in various European Corded Ware groups share substantial co-ancestry within only a few hundred years. These results show that detecting IBD segments can generate powerful insights into the growing aDNA record, both on a small scale relevant to life stories and on a large scale relevant to major cultural-historical events.
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Affiliation(s)
- Harald Ringbauer
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA.
| | - Yilei Huang
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Bioinformatics Group, Institute of Computer Science, Universität Leipzig, Leipzig, Germany
| | - Ali Akbari
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Swapan Mallick
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Iñigo Olalde
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- BIOMICs Research Group, University of the Basque Country, Vitoria-Gasteiz, Spain
- Ikerbasque-Basque Foundation of Science, Bilbao, Spain
| | - Nick Patterson
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - David Reich
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA.
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA.
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11
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Fortes-Lima CA, Burgarella C, Hammarén R, Eriksson A, Vicente M, Jolly C, Semo A, Gunnink H, Pacchiarotti S, Mundeke L, Matonda I, Muluwa JK, Coutros P, Nyambe TS, Cikomola JC, Coetzee V, de Castro M, Ebbesen P, Delanghe J, Stoneking M, Barham L, Lombard M, Meyer A, Steyn M, Malmström H, Rocha J, Soodyall H, Pakendorf B, Bostoen K, Schlebusch CM. The genetic legacy of the expansion of Bantu-speaking peoples in Africa. Nature 2024; 625:540-547. [PMID: 38030719 PMCID: PMC10794141 DOI: 10.1038/s41586-023-06770-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023]
Abstract
The expansion of people speaking Bantu languages is the most dramatic demographic event in Late Holocene Africa and fundamentally reshaped the linguistic, cultural and biological landscape of the continent1-7. With a comprehensive genomic dataset, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we contribute insights into this expansion that started 6,000-4,000 years ago in western Africa. We genotyped 1,763 participants, including 1,526 Bantu speakers from 147 populations across 14 African countries, and generated whole-genome sequences from 12 Late Iron Age individuals8. We show that genetic diversity amongst Bantu-speaking populations declines with distance from western Africa, with current-day Zambia and the Democratic Republic of Congo as possible crossroads of interaction. Using spatially explicit methods9 and correlating genetic, linguistic and geographical data, we provide cross-disciplinary support for a serial-founder migration model. We further show that Bantu speakers received significant gene flow from local groups in regions they expanded into. Our genetic dataset provides an exhaustive modern-day African comparative dataset for ancient DNA studies10 and will be important to a wide range of disciplines from science and humanities, as well as to the medical sector studying human genetic variation and health in African and African-descendant populations.
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Affiliation(s)
- Cesar A Fortes-Lima
- Human Evolution Program, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Concetta Burgarella
- Human Evolution Program, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
- AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Rickard Hammarén
- Human Evolution Program, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Anders Eriksson
- cGEM, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mário Vicente
- Centre for Palaeogenetics, University of Stockholm, Stockholm, Sweden
- Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden
| | - Cecile Jolly
- Human Evolution Program, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Armando Semo
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
| | - Hilde Gunnink
- UGent Centre for Bantu Studies (BantUGent), Department of Languages and Cultures, Ghent University, Ghent, Belgium
- Leiden University Centre for Linguistics, Leiden, the Netherlands
| | - Sara Pacchiarotti
- UGent Centre for Bantu Studies (BantUGent), Department of Languages and Cultures, Ghent University, Ghent, Belgium
| | - Leon Mundeke
- University of Kinshasa, Kinshasa, Democratic Republic of Congo
| | - Igor Matonda
- University of Kinshasa, Kinshasa, Democratic Republic of Congo
| | - Joseph Koni Muluwa
- Institut Supérieur Pédagogique de Kikwit, Kikwit, Democratic Republic of Congo
| | - Peter Coutros
- UGent Centre for Bantu Studies (BantUGent), Department of Languages and Cultures, Ghent University, Ghent, Belgium
| | | | | | - Vinet Coetzee
- Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa
| | - Minique de Castro
- Biotechnology Platform, Agricultural Research Council, Onderstepoort, Pretoria, South Africa
| | - Peter Ebbesen
- Department of Health Science and Technology, University of Aalborg, Aalborg, Denmark
| | - Joris Delanghe
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, Université Lyon 1, CNRS, Villeurbanne, France
| | - Lawrence Barham
- Department of Archaeology, Classics & Egyptology, University of Liverpool, Liverpool, UK
| | - Marlize Lombard
- Palaeo-Research Institute, University of Johannesburg, Johannesburg, South Africa
| | - Anja Meyer
- Human Variation and Identification Research Unit, School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Maryna Steyn
- Human Variation and Identification Research Unit, School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Helena Malmström
- Human Evolution Program, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
- Palaeo-Research Institute, University of Johannesburg, Johannesburg, South Africa
| | - Jorge Rocha
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
| | - Himla Soodyall
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Academy of Science of South Africa, Pretoria, South Africa
| | | | - Koen Bostoen
- UGent Centre for Bantu Studies (BantUGent), Department of Languages and Cultures, Ghent University, Ghent, Belgium
| | - Carina M Schlebusch
- Human Evolution Program, Department of Organismal Biology, Uppsala University, Uppsala, Sweden.
- Palaeo-Research Institute, University of Johannesburg, Johannesburg, South Africa.
- SciLifeLab, Uppsala, Sweden.
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12
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Petr M, Haller BC, Ralph PL, Racimo F. slendr: a framework for spatio-temporal population genomic simulations on geographic landscapes. PEER COMMUNITY JOURNAL 2023; 3:e121. [PMID: 38984034 PMCID: PMC11233137 DOI: 10.24072/pcjournal.354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
One of the goals of population genetics is to understand how evolutionary forces shape patterns of genetic variation over time. However, because populations evolve across both time and space, most evolutionary processes also have an important spatial component, acting through phenomena such as isolation by distance, local mate choice, or uneven distribution of resources. This spatial dimension is often neglected, partly due to the lack of tools specifically designed for building and evaluating complex spatio-temporal population genetic models. To address this methodological gap, we present a new framework for simulating spatially-explicit genomic data, implemented in a new R package called slendr (www.slendr.net), which leverages a SLiM simulation back-end script bundled with the package. With this framework, the users can programmatically and visually encode spatial population ranges and their temporal dynamics (i.e., population displacements, expansions, and contractions) either on real Earth landscapes or on abstract custom maps, and schedule splits and gene-flow events between populations using a straightforward declarative language. Additionally, slendr can simulate data from traditional, non-spatial models, either with SLiM or using an alternative built-in coalescent msprime back end. Together with its R-idiomatic interface to the tskit library for tree-sequence processing and analysis, slendr opens up the possibility of performing efficient, reproducible simulations of spatio-temporal genomic data entirely within the R environment, leveraging its wealth of libraries for geospatial data analysis, statistics, and visualization. Here, we present the design of the slendr R package and demonstrate its features on several practical example workflows.
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Affiliation(s)
- Martin Petr
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Denmark
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Denmark
| | - Benjamin C Haller
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Peter L Ralph
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR, USA
| | - Fernando Racimo
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Denmark
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Denmark
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13
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Tallman S, Sungo MDD, Saranga S, Beleza S. Whole genomes from Angola and Mozambique inform about the origins and dispersals of major African migrations. Nat Commun 2023; 14:7967. [PMID: 38042927 PMCID: PMC10693643 DOI: 10.1038/s41467-023-43717-x] [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] [Accepted: 11/17/2023] [Indexed: 12/04/2023] Open
Abstract
As the continent of origin for our species, Africa harbours the highest levels of diversity anywhere on Earth. However, many regions of Africa remain under-sampled genetically. Here we present 350 whole genomes from Angola and Mozambique belonging to ten Bantu ethnolinguistic groups, enabling the construction of a reference variation catalogue including 2.9 million novel SNPs. We investigate the emergence of Bantu speaker population structure, admixture involving migrations across sub-Saharan Africa and model the demographic histories of Angolan and Mozambican Bantu speakers. Our results bring together concordant views from genomics, archaeology, and linguistics to paint an updated view of the complexity of the Bantu Expansion. Moreover, we generate reference panels that better represents the diversity of African populations involved in the trans-Atlantic slave trade, improving imputation accuracy in African Americans and Brazilians. We anticipate that our collection of genomes will form the foundation for future African genomic healthcare initiatives.
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Affiliation(s)
- Sam Tallman
- University of Leicester, Department of Genetics & Genome Biology, University Road, Leicester, LE1 7RH, UK
- Genomics England, 1 Canada Square, London, E14 5AB, UK
| | | | - Sílvio Saranga
- Universidade Pedagógica, Avenida Eduardo Mondlane, CP 2107, Maputo, Mozambique
| | - Sandra Beleza
- University of Leicester, Department of Genetics & Genome Biology, University Road, Leicester, LE1 7RH, UK.
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14
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Patterson CW, Drury JP. Interspecific behavioural interference and range dynamics: current insights and future directions. Biol Rev Camb Philos Soc 2023; 98:2012-2027. [PMID: 37364865 DOI: 10.1111/brv.12993] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 06/08/2023] [Accepted: 06/12/2023] [Indexed: 06/28/2023]
Abstract
Novel biotic interactions in shifting communities play a key role in determining the ability of species' ranges to track suitable habitat. To date, the impact of biotic interactions on range dynamics have predominantly been studied in the context of interactions between different trophic levels or, to a lesser extent, exploitative competition between species of the same trophic level. Yet, both theory and a growing number of empirical studies show that interspecific behavioural interference, such as interspecific territorial and mating interactions, can slow down range expansions, preclude coexistence, or drive local extinction, even in the absence of resource competition. We conducted a systematic review of the current empirical research into the consequences of interspecific behavioural interference on range dynamics. Our findings demonstrate there is abundant evidence that behavioural interference by one species can impact the spatial distribution of another. Furthermore, we identify several gaps where more empirical work is needed to test predictions from theory robustly. Finally, we outline several avenues for future research, providing suggestions for how interspecific behavioural interference could be incorporated into existing scientific frameworks for understanding how biotic interactions influence range expansions, such as species distribution models, to build a stronger understanding of the potential consequences of behavioural interference on the outcome of future range dynamics.
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Affiliation(s)
| | - Jonathan P Drury
- Department of Biosciences, Durham University, Stockton Road, Durham, DH1 3LE, UK
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15
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Kumar L, Chowdhari A, Sequeira JJ, Mustak MS, Banerjee M, Thangaraj K. Genetic Affinities and Adaptation of the South-West Coast Populations of India. Genome Biol Evol 2023; 15:evad225. [PMID: 38079532 PMCID: PMC10745260 DOI: 10.1093/gbe/evad225] [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] [Accepted: 11/29/2023] [Indexed: 12/24/2023] Open
Abstract
Evolutionary event has not only altered the genetic structure of human populations but also associated with social and cultural transformation. South Asian populations were the result of migration and admixture of genetically and culturally diverse groups. Most of the genetic studies pointed to large-scale admixture events between Ancestral North Indian (ANI) and Ancestral South Indian (ASI) groups, also additional layers of recent admixture. In the present study, we have analyzed 213 individuals inhabited in South-west coast India with traditional warriors and feudal lord status and historically associated with migratory events from North/North West India and possible admixture with West Eurasian populations, whose genetic links are still missing. Analysis of autosomal Single Nucleotide Polymorphism (SNP) markers suggests that these groups possibly derived their ancestry from some groups of North West India having additional Middle Eastern genetic components. Higher distribution of West Eurasian mitochondrial haplogroups also points to female-mediated admixture. Estimation of Effective Migration Surface (EEMS) analysis indicates Central India and Godavari basin as a crucial transition zone for population migration from North and North West India to South-west coastal India. Selection screen using 3 distinct outlier-based approaches revealed genetic signatures related to Immunity and protection from Viral infections. Thus, our study suggests that the South-west coastal groups with traditional warriors and feudal lords' status are of a distinct lineage compared to Dravidian and Gangetic plain Indo-Europeans and are remnants of very early migrations from North West India following the Godavari basin to Karnataka and Kerala.
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Affiliation(s)
- Lomous Kumar
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Anuhya Chowdhari
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad 500007, India
| | - Jaison J Sequeira
- Department of Applied Zoology, Mangalore University, Mangalore 574199, India
| | - Mohammed S Mustak
- Department of Applied Zoology, Mangalore University, Mangalore 574199, India
| | - Moinak Banerjee
- Human Molecular Genetics Laboratory, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram 695014, Kerala, India
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16
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Vyas DN, Koncz I, Modi A, Mende BG, Tian Y, Francalacci P, Lari M, Vai S, Straub P, Gallina Z, Szeniczey T, Hajdu T, Pejrani Baricco L, Giostra C, Radzevičiūtė R, Hofmanová Z, Évinger S, Bernert Z, Pohl W, Caramelli D, Vida T, Geary PJ, Veeramah KR. Fine-scale sampling uncovers the complexity of migrations in 5th-6th century Pannonia. Curr Biol 2023; 33:3951-3961.e11. [PMID: 37633281 DOI: 10.1016/j.cub.2023.07.063] [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: 04/06/2023] [Revised: 06/20/2023] [Accepted: 07/31/2023] [Indexed: 08/28/2023]
Abstract
As the collapse of the Western Roman Empire accelerated during the 4th and 5th centuries, arriving "barbarian" groups began to establish new communities in the border provinces of the declining (and eventually former) empire. This was a time of significant cultural and political change throughout not only these border regions but Europe as a whole.1,2 To better understand post-Roman community formation in one of these key frontier zones after the collapse of the Hunnic movement, we generated new paleogenomic data for a set of 38 burials from a time series of three 5th century cemeteries3,4,5 at Lake Balaton, Hungary. We utilized a comprehensive sampling approach to characterize these cemeteries along with data from 38 additional burials from a previously published mid-6th century site6 and analyzed them alongside data from over 550 penecontemporaneous individuals.7,8,9,10,11,12,13,14,15,16,17,18,19 The range of genetic diversity in all four of these local burial communities is extensive and wider ranging than penecontemporaneous Europeans sequenced to date. Despite many commonalities in burial customs and demography, we find that there were substantial differences in genetic ancestry between the sites. We detect evidence of northern European gene flow into the Lake Balaton region. Additionally, we observe a statistically significant association between dress artifacts and genetic ancestry among 5th century genetically female burials. Our analysis shows that the formation of early Medieval communities was a multifarious process even at a local level, consisting of genetically heterogeneous groups.
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Affiliation(s)
- Deven N Vyas
- Department of Ecology and Evolution, Stony Brook University, 650 Life Sciences Building, Stony Brook, NY 11794, USA
| | - István Koncz
- Institute of Archaeological Sciences, ELTE - Eötvös Loránd University, Múzeum krt. 4/B, 1088 Budapest, Hungary
| | - Alessandra Modi
- Dipartimento di Biologia, Università degli Studi di Firenze, Via del Proconsolo 12, 50122 Firenze, Italy
| | - Balázs Gusztáv Mende
- Institute of Archaeogenomics, Research Centre for the Humanities, Tóth Kálmán utca 4, 1097 Budapest, Hungary
| | - Yijie Tian
- Department of Ecology and Evolution, Stony Brook University, 650 Life Sciences Building, Stony Brook, NY 11794, USA
| | - Paolo Francalacci
- Dipartimento di Scienze della Vita e dell'Ambiente, Università di Cagliari, Via T. Fiorelli 1, 09126 Cagliari, Italy
| | - Martina Lari
- Dipartimento di Biologia, Università degli Studi di Firenze, Via del Proconsolo 12, 50122 Firenze, Italy
| | - Stefania Vai
- Dipartimento di Biologia, Università degli Studi di Firenze, Via del Proconsolo 12, 50122 Firenze, Italy
| | | | | | - Tamás Szeniczey
- Department of Biological Anthropology, ELTE - Eötvös Loránd University, Pázmány Péter sétány 1/c, 1117 Budapest, Hungary
| | - Tamás Hajdu
- Department of Biological Anthropology, ELTE - Eötvös Loránd University, Pázmány Péter sétány 1/c, 1117 Budapest, Hungary
| | - Luisella Pejrani Baricco
- Soprintendenza Archeologia, Belle Arti e Paesaggio per la Città Metropolitana di Torino, piazza San Giovanni 2, 10122 Torino, Italy
| | - Caterina Giostra
- Dipartimento di Storia, Archeologia e Storia dell'Arte, Università Cattolica del Sacro Cuore, Largo A. Gemelli, 1, 20123 Milano, Italy
| | - Rita Radzevičiūtė
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany
| | - Zuzana Hofmanová
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany; Department of Archaeology and Museology, Faculty of Arts, Masaryk University, Arna Nováka 1/1, Brno 60200, Czech Republic
| | - Sándor Évinger
- Department of Anthropology, Hungarian Natural History Museum, Ludovika tér 2-6, 1083 Budapest, Hungary
| | - Zsolt Bernert
- Department of Anthropology, Hungarian Natural History Museum, Ludovika tér 2-6, 1083 Budapest, Hungary
| | - Walter Pohl
- Institute for Medieval Research, Austrian Academy of Sciences, Dr-Ignaz-Seipel-Platz 2, 1020 Vienna, Austria; Institute for Austrian Historical Research, University of Vienna, Universitätsring 1, 1010 Vienna, Austria
| | - David Caramelli
- Dipartimento di Biologia, Università degli Studi di Firenze, Via del Proconsolo 12, 50122 Firenze, Italy.
| | - Tivadar Vida
- Institute of Archaeological Sciences, ELTE - Eötvös Loránd University, Múzeum krt. 4/B, 1088 Budapest, Hungary.
| | - Patrick J Geary
- School of Historical Studies, Institute for Advanced Study, 1 Einstein Drive, Princeton, NJ 08540, USA.
| | - Krishna R Veeramah
- Department of Ecology and Evolution, Stony Brook University, 650 Life Sciences Building, Stony Brook, NY 11794, USA.
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Oliveira S, Fehn AM, Amorim B, Stoneking M, Rocha J. Genome-wide variation in the Angolan Namib Desert reveals unique pre-Bantu ancestry. SCIENCE ADVANCES 2023; 9:eadh3822. [PMID: 37738339 PMCID: PMC10516492 DOI: 10.1126/sciadv.adh3822] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 08/18/2023] [Indexed: 09/24/2023]
Abstract
Ancient DNA studies reveal the genetic structure of Africa before the expansion of Bantu-speaking agriculturalists; however, the impact of now extinct hunter-gatherer and herder societies on the genetic makeup of present-day African groups remains elusive. Here, we uncover the genetic legacy of pre-Bantu populations from the Angolan Namib Desert, where we located small-scale groups associated with enigmatic forager traditions, as well as the last speakers of the Khoe-Kwadi family's Kwadi branch. By applying an ancestry decomposition approach to genome-wide data from these and other African populations, we reconstructed the fine-scale histories of contact emerging from the migration of Khoe-Kwadi-speaking pastoralists and identified a deeply divergent ancestry, which is exclusively shared between groups from the Angolan Namib and adjacent areas of Namibia. The unique genetic heritage of the Namib peoples shows how modern DNA research targeting understudied regions of high ethnolinguistic diversity can complement ancient DNA studies in probing the deep genetic structure of the African continent.
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Affiliation(s)
- Sandra Oliveira
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04103, Germany
- Computational and Molecular Population Genetics, Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland
| | - Anne-Maria Fehn
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal
- Biopolis Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
| | - Beatriz Amorim
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal
- Biopolis Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4099-002 Porto, Portugal
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04103, Germany
- Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive, UMR 5558 Villeurbanne, France
| | - Jorge Rocha
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal
- Biopolis Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4099-002 Porto, Portugal
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18
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Antunes B, Figueiredo-Vázquez C, Dudek K, Liana M, Pabijan M, Zieliński P, Babik W. Landscape genetics reveals contrasting patterns of connectivity in two newt species (Lissotriton montandoni and L. vulgaris). Mol Ecol 2023; 32:4515-4530. [PMID: 35593303 DOI: 10.1111/mec.16543] [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: 08/05/2021] [Revised: 03/28/2022] [Accepted: 04/04/2022] [Indexed: 11/30/2022]
Abstract
Ecologically distinct species may respond to landscape changes in different ways. In addition to basic ecological data, the extent of the geographic range has been successfully used as an indicator of species sensitivity to anthropogenic landscapes, with widespread species usually found to be less sensitive compared to range-restricted species. In this study, we investigate connectivity patterns of two closely related but ecologically distinct newt species - the range-restricted, Lissotriton montandoni and the widespread, L. vulgaris - using genomic data, a highly replicated setting (six geographic regions per species), and tools from landscape genetics. Our results show the importance of forest for connectivity in both species, but at the same time suggest differential use of forested habitat, with L. montandoni and L. vulgaris showing the highest connectivity at forest-core and forest-edges, respectively. Anthropogenic landscapes (i.e., higher crop- or urban-cover) increased resistance in both species, but the effect was one to three orders of magnitude stronger in L. montandoni than in L. vulgaris. This result is consistent with a view of L. vulgaris as an ecological generalist. Even so, currently, the negative impact of anthropogenic landscapes is mainly seen in connectivity among L. vulgaris populations, which show significantly stronger isolation and lower effective sizes relative to L. montandoni. Overall, this study emphasizes how habitat destruction is compromising genetic connectivity not only in endemic, range-restricted species of conservation concern but also in widespread generalist species, despite their comparatively lower sensitivity to anthropogenic landscape changes.
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Affiliation(s)
- Bernardo Antunes
- Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland
| | - Clara Figueiredo-Vázquez
- Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
| | - Katarzyna Dudek
- Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland
| | | | - Maciej Pabijan
- Institute of Zoology and Biomedical Research, Faculty of Biology, Jagiellonian University, Kraków, Poland
| | - Piotr Zieliński
- Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland
| | - Wiesław Babik
- Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland
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19
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Halili B, Yang X, Wang R, Zhu K, Hai X, Wang CC. Inferring the population history of Kyrgyz in Xinjiang, Northwest China from genome-wide array genotyping. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023; 181:611-625. [PMID: 37310136 DOI: 10.1002/ajpa.24794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 04/29/2023] [Accepted: 05/26/2023] [Indexed: 06/14/2023]
Abstract
OBJECTIVES Xinjiang plays a vital role in the trans-Eurasian population migration, language diffusion, and culture and technology exchange. However, the underrepresentation of Xinjiang's genomes has hindered a more comprehensive understanding of Xinjiang's genetic structure and population history. MATERIALS AND METHODS We collected and genotyped 70 southern Xinjiang's Kyrgyz (SXJK) individuals and combined the data with modern and ancient Eurasians published. We used allele-frequency methods, including PCA, ADMIXTURE, f-statistics, qpWave/qpAdm, ALDER, Treemix, and haplotype-shared methods including shared-IBD segments, fineSTRUCTURE, and GLOBETROTTER to unveil the fine-scale population structure and reconstruct admixture history. RESULTS We identified genetic substructure within the SXJK population with subgroups showing different genetic affinities to West and East Eurasians. All SXJK subgroups were suggested to have close genetic relationships with surrounding Turkic-speaking groups that is, Uyghur, Kyrgyz from north Xinjiang and Tajikistan, and Chinese Kazakh, suggesting a shared ancestry among those populations. Outgroup-f3 and symmetrical f4 statistics showed a high genetic affinity of SXJK to present-day Tungusic, Mongolic-speaking populations and Ancient Northeast Asian (ANA) related groups. Allele sharing and haplotype sharing profiles revealed the east-west admixture pattern of SXJK. The qpAdm-based admixture models showed that SXJK derived ancestry from East Eurasian (ANA and East Asian, 42.7%-83.3%) and West Eurasian (Western Steppe herders and Central Asian, 16.7%-57.3%), the recent east-west admixture event could be traced to 1000 years ago based on ALDER and GLOBETROTTER analysis. DISCUSSION The high genetic affinity of SXJK to present-day Tungusic and Mongolic-speaking populations and short-shared IBD segments indicated their shared common ancestry. SXJK harbored a close genetic affinity to ANA-related populations, indicating the Northeast Asian origin of SXJK. The West and East Eurasian admixture models observed in SXJK further provided evidence of the dynamic admixture history in Xinjiang. The east-west admixture pattern and the identified ancestral makeup of SXJK suggested a genetic continuity from some Iron Age Xinjiang populations to present-day SXJK.
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Affiliation(s)
- Bubibatima Halili
- Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China
| | - Xiaomin Yang
- Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China
| | - Rui Wang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Kongyang Zhu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Xiangjun Hai
- Key Laboratory of Environmental Ecology and Population Health in Northwest Minority Areas, Northwest Minzu University, Lanzhou, China
| | - Chuan-Chao Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
- State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
- Institute of Artificial Intelligence, Xiamen University, Xiamen, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
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20
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Guo B, Borda V, Laboulaye R, Spring MD, Wojnarski M, Vesely BA, Silva JC, Waters NC, O'Connor TD, Takala-Harrison S. Strong Positive Selection Biases Identity-By-Descent-Based Inferences of Recent Demography and Population Structure in Plasmodium falciparum. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.14.549114. [PMID: 37502843 PMCID: PMC10370022 DOI: 10.1101/2023.07.14.549114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD). Yet, strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we utilized simulations, a true IBD inference algorithm, and empirical datasets from different malaria transmission settings to investigate the extent of such bias and explore potential correction strategies. We analyzed whole genome sequence data generated from 640 new and 4,026 publicly available Plasmodium falciparum clinical isolates. Our findings demonstrated that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discovered that the removal of IBD peak regions partially restored the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.
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Affiliation(s)
- Bing Guo
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD USA
| | - Victor Borda
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Roland Laboulaye
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Michele D Spring
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Mariusz Wojnarski
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Brian A Vesely
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Joana C Silva
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Norman C Waters
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Timothy D O'Connor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shannon Takala-Harrison
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD USA
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21
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Smith CCR, Tittes S, Ralph PL, Kern AD. Dispersal inference from population genetic variation using a convolutional neural network. Genetics 2023; 224:iyad068. [PMID: 37052957 PMCID: PMC10213498 DOI: 10.1093/genetics/iyad068] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 02/08/2023] [Accepted: 04/07/2023] [Indexed: 04/14/2023] Open
Abstract
The geographic nature of biological dispersal shapes patterns of genetic variation over landscapes, making it possible to infer properties of dispersal from genetic variation data. Here, we present an inference tool that uses geographically distributed genotype data in combination with a convolutional neural network to estimate a critical population parameter: the mean per-generation dispersal distance. Using extensive simulation, we show that our deep learning approach is competitive with or outperforms state-of-the-art methods, particularly at small sample sizes. In addition, we evaluate varying nuisance parameters during training-including population density, demographic history, habitat size, and sampling area-and show that this strategy is effective for estimating dispersal distance when other model parameters are unknown. Whereas competing methods depend on information about local population density or accurate inference of identity-by-descent tracts, our method uses only single-nucleotide-polymorphism data and the spatial scale of sampling as input. Strikingly, and unlike other methods, our method does not use the geographic coordinates of the genotyped individuals. These features make our method, which we call "disperseNN," a potentially valuable new tool for estimating dispersal distance in nonmodel systems with whole genome data or reduced representation data. We apply disperseNN to 12 different species with publicly available data, yielding reasonable estimates for most species. Importantly, our method estimated consistently larger dispersal distances than mark-recapture calculations in the same species, which may be due to the limited geographic sampling area covered by some mark-recapture studies. Thus genetic tools like ours complement direct methods for improving our understanding of dispersal.
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Affiliation(s)
- Chris C R Smith
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403, USA
| | - Silas Tittes
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403, USA
| | - Peter L Ralph
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403, USA
| | - Andrew D Kern
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403, USA
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22
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Pless E, Eckburg AM, Henn BM. Predicting Environmental and Ecological Drivers of Human Population Structure. Mol Biol Evol 2023; 40:msad094. [PMID: 37146165 PMCID: PMC10172848 DOI: 10.1093/molbev/msad094] [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: 07/12/2022] [Revised: 03/30/2023] [Accepted: 04/03/2023] [Indexed: 05/07/2023] Open
Abstract
Landscape, climate, and culture can all structure human populations, but few existing methods are designed to simultaneously disentangle among a large number of variables in explaining genetic patterns. We developed a machine learning method for identifying the variables which best explain migration rates, as measured by the coalescent-based program MAPS that uses shared identical by descent tracts to infer spatial migration across a region of interest. We applied our method to 30 human populations in eastern Africa with high-density single nucleotide polymorphism array data. The remarkable diversity of ethnicities, languages, and environments in this region offers a unique opportunity to explore the variables that shape migration and genetic structure. We explored more than 20 spatial variables relating to landscape, climate, and presence of tsetse flies. The full model explained ∼40% of the variance in migration rate over the past 56 generations. Precipitation, minimum temperature of the coldest month, and elevation were the variables with the highest impact. Among the three groups of tsetse flies, the most impactful was fusca which transmits livestock trypanosomiasis. We also tested for adaptation to high elevation among Ethiopian populations. We did not identify well-known genes related to high elevation, but we did find signatures of positive selection related to metabolism and disease. We conclude that the environment has influenced the migration and adaptation of human populations in eastern Africa; the remaining variance in structure is likely due in part to cultural or other factors not captured in our model.
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Affiliation(s)
- Evlyn Pless
- Department of Anthropology, Center for Population Biology, University of California, Davis, CA
| | - Anders M Eckburg
- Department of Anthropology, Center for Population Biology, University of California, Davis, CA
| | - Brenna M Henn
- Department of Anthropology, Center for Population Biology, University of California, Davis, CA
- UC Davis Genome Center, University of California, Davis, CA
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23
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Liu D, Ko AMS, Stoneking M. The genomic diversity of Taiwanese Austronesian groups: Implications for the "Into- and Out-of-Taiwan" models. PNAS NEXUS 2023; 2:pgad122. [PMID: 37200801 PMCID: PMC10187666 DOI: 10.1093/pnasnexus/pgad122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 05/20/2023]
Abstract
The origin and dispersal of the Austronesian language family, one of the largest and most widespread in the world, have long attracted the attention of linguists, archaeologists, and geneticists. Even though there is a growing consensus that Taiwan is the source of the spread of Austronesian languages, little is known about the migration patterns of the early Austronesians who settled in and left Taiwan, i.e. the "Into-Taiwan" and "out-of-Taiwan" events. In particular, the genetic diversity and structure within Taiwan and how this relates to the into-/out-of-Taiwan events are largely unexplored, primarily because most genomic studies have largely utilized data from just two of the 16 recognized Highland Austronesian groups in Taiwan. In this study, we generated the largest genome-wide data set of Taiwanese Austronesians to date, including six Highland groups and one Lowland group from across the island and two Taiwanese Han groups. We identified fine-scale genomic structure in Taiwan, inferred the ancestry profile of the ancestors of Austronesians, and found that the southern Taiwanese Austronesians show excess genetic affinities with the Austronesians outside of Taiwan. Our findings thus shed new light on the Into- and Out-of-Taiwan dispersals.
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Affiliation(s)
- Dang Liu
- To whom correspondence should be addressed: ;
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24
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Gilbert E, Zurel H, MacMillan ME, Demiriz S, Mirhendi S, Merrigan M, O'Reilly S, Molloy AM, Brody LC, Bodmer W, Leach RA, Scott REM, Mugford G, Randhawa R, Stephens JC, Symington AL, Cavalleri GL, Phillips MS. The Newfoundland and Labrador mosaic founder population descends from an Irish and British diaspora from 300 years ago. Commun Biol 2023; 6:469. [PMID: 37117635 PMCID: PMC10147672 DOI: 10.1038/s42003-023-04844-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 03/28/2023] [Indexed: 04/30/2023] Open
Abstract
The founder population of Newfoundland and Labrador (NL) is a unique genetic resource, in part due to its geographic and cultural isolation, where historical records describe a migration of European settlers, primarily from Ireland and England, to NL in the 18th and 19th centuries. Whilst its historical isolation, and increased prevalence of certain monogenic disorders are well appreciated, details of the fine-scale genetic structure and ancestry of the population are lacking. Understanding the genetic origins and background of functional, disease causing, genetic variants would aid genetic mapping efforts in the Province. Here, we leverage dense genome-wide SNP data on 1,807 NL individuals to reveal fine-scale genetic structure in NL that is clustered around coastal communities and correlated with Christian denomination. We show that the majority of NL European ancestry can be traced back to the south-east and south-west of Ireland and England, respectively. We date a substantial population size bottleneck approximately 10-15 generations ago in NL, associated with increased haplotype sharing and autozygosity. Our results reveal insights into the population history of NL and demonstrate evidence of a population conducive to further genetic studies and biomarker discovery.
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Affiliation(s)
- Edmund Gilbert
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland.
- FutureNeuro SFI Research Centre, Royal College of Surgeons in Ireland, Dublin, Ireland.
| | - Heather Zurel
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | | | - Sedat Demiriz
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | - Sadra Mirhendi
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | | | | | - Anne M Molloy
- School of Medicine, Trinity College, Dublin, Ireland
| | - Lawrence C Brody
- Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Walter Bodmer
- Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, Oxford, UK
| | - Richard A Leach
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | - Roderick E M Scott
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | - Gerald Mugford
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | - Ranjit Randhawa
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | | | - Alison L Symington
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
| | - Gianpiero L Cavalleri
- School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Michael S Phillips
- Sequence Bioinformatics, Inc., St. John's, Newfoundland and Labrador, Canada
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25
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Smith TB, Weissman DB. Isolation by distance in populations with power-law dispersal. G3 (BETHESDA, MD.) 2023; 13:jkad023. [PMID: 36718551 PMCID: PMC10085794 DOI: 10.1093/g3journal/jkad023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 01/07/2023] [Indexed: 02/01/2023]
Abstract
Limited dispersal of individuals between generations results in isolation by distance, in which individuals further apart in space tend to be less related. Classic models of isolation by distance assume that dispersal distances are drawn from a thin-tailed distribution and predict that the proportion of the genome that is identical by descent between a pair of individuals should decrease exponentially with the spatial separation between them. However, in many natural populations, individuals occasionally disperse over very long distances. In this work, we use mathematical analysis and coalescent simulations to study the effect of long-range (power-law) dispersal on patterns of isolation by distance. We find that it leads to power-law decay of identity-by-descent at large distances with the same exponent as dispersal. We also find that broad power-law dispersal produces another, shallow power-law decay of identity-by-descent at short distances. These results suggest that the distribution of long-range dispersal events could be estimated from sequencing large population samples taken from a wide range of spatial scales.
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Affiliation(s)
- Tyler B Smith
- Department of Physics, Emory University, Atlanta, Georgia 30322, USA
| | - Daniel B Weissman
- Corresponding author: Department of Physics, Emory University, Atlanta, Georgia 30322, USA.
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26
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Lloyd‐Jones LR, Brien ML, Feutry P, Lawrence E, Beri P, Booth S, Coulson S, Baylis SM, Villiers K, Taplin LE, Westcott DA. Implications of past and present genetic connectivity for management of the saltwater crocodile ( Crocodylus porosus). Evol Appl 2023; 16:911-935. [PMID: 37124084 PMCID: PMC10130557 DOI: 10.1111/eva.13545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 02/17/2023] [Accepted: 03/16/2023] [Indexed: 04/03/2023] Open
Abstract
Effective management of protected species requires information on appropriate evolutionary and geographic population boundaries and knowledge of how the physical environment and life-history traits combine to shape the population structure and connectivity. Saltwater crocodiles (Crocodylus porosus) are the largest and most widely distributed of living crocodilians, extending from Sri Lanka to Southeast Asia and down to northern Australia. Given the long-distance movement capabilities reported for C. porosus, management units are hypothesised to be highly connected by migration. However, the magnitude, scale, and consistency of connection across managed populations are not fully understood. Here we used an efficient genotyping method that combines DArTseq and sequence capture to survey≈ 3000 high-quality genome-wide single nucleotide polymorphisms from 1176 C. porosus sampled across nearly the entire range of the species in Queensland, Australia. We investigated historical and present-day connectivity patterns using fixation and diversity indices coupled with clustering methods and the spatial distribution of kin pairs. We inferred kinship using forward simulation coupled with a kinship estimation method that is robust to unspecified population structure. The results demonstrated that the C. porosus population has substantial genetic structure with six broad populations correlated with geographical location. The rate of gene flow was highly correlated with spatial distance, with greater differentiation along the east coast compared to the west. Kinship analyses revealed evidence of reproductive philopatry and limited dispersal, with approximately 90% of reported first and second-degree relatives showing a pairwise distance of <50 km between sampling locations. Given the limited dispersal, lack of suitable habitat, low densities of crocodiles and the high proportion of immature animals in the population, future management and conservation interventions should be considered at regional and state-wide scales.
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Affiliation(s)
- Luke R. Lloyd‐Jones
- Commonwealth Scientific and Industrial Research OrganisationData61BrisbaneQueensland4072Australia
| | - Matthew L. Brien
- Department of Environment and ScienceQueensland GovernmentCairnsQueensland4870Australia
| | - Pierre Feutry
- Commonwealth Scientific and Industrial Research OrganisationOceans and AtmosphereHobartTasmania7000Australia
| | - Emma Lawrence
- Commonwealth Scientific and Industrial Research OrganisationData61BrisbaneQueensland4072Australia
| | - Paul Beri
- Department of Environment and ScienceQueensland GovernmentCairnsQueensland4870Australia
| | - Simon Booth
- Department of Environment and ScienceQueensland GovernmentCairnsQueensland4870Australia
| | - Steven Coulson
- Department of Environment and ScienceQueensland GovernmentCairnsQueensland4870Australia
| | - Shane M. Baylis
- Commonwealth Scientific and Industrial Research OrganisationOceans and AtmosphereHobartTasmania7000Australia
| | - Kira Villiers
- Commonwealth Scientific and Industrial Research OrganisationData61BrisbaneQueensland4072Australia
| | - Laurence E. Taplin
- Department of Environment and ScienceQueensland GovernmentCairnsQueensland4870Australia
| | - David A. Westcott
- Commonwealth Scientific and Industrial Research OrganisationLand and WaterAthertonQueensland4883Australia
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27
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Ringbauer H, Huang Y, Akbari A, Mallick S, Patterson N, Reich D. ancIBD - Screening for identity by descent segments in human ancient DNA. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.08.531671. [PMID: 36945531 PMCID: PMC10028887 DOI: 10.1101/2023.03.08.531671] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Long DNA sequences shared between two individuals, known as Identical by descent (IBD) segments, are a powerful signal for identifying close and distant biological relatives because they only arise when the pair shares a recent common ancestor. Existing methods to call IBD segments between present-day genomes cannot be straightforwardly applied to ancient DNA data (aDNA) due to typically low coverage and high genotyping error rates. We present ancIBD, a method to identify IBD segments for human aDNA data implemented as a Python package. Our approach is based on a Hidden Markov Model, using as input genotype probabilities imputed based on a modern reference panel of genomic variation. Through simulation and downsampling experiments, we demonstrate that ancIBD robustly identifies IBD segments longer than 8 centimorgan for aDNA data with at least either 0.25x average whole-genome sequencing (WGS) coverage depth or at least 1x average depth for in-solution enrichment experiments targeting a widely used aDNA SNP set ('1240k'). This application range allows us to screen a substantial fraction of the aDNA record for IBD segments and we showcase two downstream applications. First, leveraging the fact that biological relatives up to the sixth degree are expected to share multiple long IBD segments, we identify relatives between 10,156 ancient Eurasian individuals and document evidence of long-distance migration, for example by identifying a pair of two approximately fifth-degree relatives who were buried 1410km apart in Central Asia 5000 years ago. Second, by applying ancIBD, we reveal new details regarding the spread of ancestry related to Steppe pastoralists into Europe starting 5000 years ago. We find that the first individuals in Central and Northern Europe carrying high amounts of Steppe-ancestry, associated with the Corded Ware culture, share high rates of long IBD (12-25 cM) with Yamnaya herders of the Pontic-Caspian steppe, signaling a strong bottleneck and a recent biological connection on the order of only few hundred years, providing evidence that the Yamnaya themselves are a main source of Steppe ancestry in Corded Ware people. We also detect elevated sharing of long IBD segments between Corded Ware individuals and people associated with the Globular Amphora culture (GAC) from Poland and Ukraine, who were Copper Age farmers not yet carrying Steppe-like ancestry. These IBD links appear for all Corded Ware groups in our analysis, indicating that individuals related to GAC contexts must have had a major demographic impact early on in the genetic admixtures giving rise to various Corded Ware groups across Europe. These results show that detecting IBD segments in aDNA can generate new insights both on a small scale, relevant to understanding the life stories of people, and on the macroscale, relevant to large-scale cultural-historical events.
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Affiliation(s)
- Harald Ringbauer
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Yilei Huang
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Bioinformatics Group, Institute of Computer Science, Universität Leipzig, Leipzig, Germanÿ
| | - Ali Akbari
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Swapan Mallick
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
| | - Nick Patterson
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - David Reich
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
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28
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Estimating human mobility in Holocene Western Eurasia with large-scale ancient genomic data. Proc Natl Acad Sci U S A 2023; 120:e2218375120. [PMID: 36821583 PMCID: PMC9992830 DOI: 10.1073/pnas.2218375120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
The recent increase in openly available ancient human DNA samples allows for large-scale meta-analysis applications. Trans-generational past human mobility is one of the key aspects that ancient genomics can contribute to since changes in genetic ancestry-unlike cultural changes seen in the archaeological record-necessarily reflect movements of people. Here, we present an algorithm for spatiotemporal mapping of genetic profiles, which allow for direct estimates of past human mobility from large ancient genomic datasets. The key idea of the method is to derive a spatial probability surface of genetic similarity for each individual in its respective past. This is achieved by first creating an interpolated ancestry field through space and time based on multivariate statistics and Gaussian process regression and then using this field to map the ancient individuals into space according to their genetic profile. We apply this algorithm to a dataset of 3138 aDNA samples with genome-wide data from Western Eurasia in the last 10,000 y. Finally, we condense this sample-wise record with a simple summary statistic into a diachronic measure of mobility for subregions in Western, Central, and Southern Europe. For regions and periods with sufficient data coverage, our similarity surfaces and mobility estimates show general concordance with previous results and provide a meta-perspective of genetic changes and human mobility.
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29
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Wishingrad V, Thomson RC. Biogeographic inferences across spatial and evolutionary scales. Mol Ecol 2023; 32:2055-2070. [PMID: 36695049 DOI: 10.1111/mec.16861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 01/05/2023] [Accepted: 01/19/2023] [Indexed: 01/26/2023]
Abstract
The field of biogeography unites landscape genetics and phylogeography under a common conceptual framework. Landscape genetics traditionally focuses on recent-time, population-based, spatial genetics processes at small geographical scales, while phylogeography typically investigates deep past, lineage- and species-based processes at large geographical scales. Here, we evaluate the link between landscape genetics and phylogeographical methods using the western fence lizard (Sceloporus occidentalis) as a model species. First, we conducted replicated landscape genetics studies across several geographical scales to investigate how population genetics inferences change depending on the spatial extent of the study area. Then, we carried out a phylogeographical study of population structure at two evolutionary scales informed by inferences derived from landscape genetics results to identify concordance and conflict between these sets of methods. We found significant concordance in landscape genetics processes at all but the largest geographical scale. Phylogeographical results indicate major clades are restricted to distinct river drainages or distinct hydrological regions. At a more recent timescale, we find minor clades are restricted to single river canyons in the majority of cases, while the remainder of river canyons include samples from at most two clades. Overall, the broad-scale pattern implicating stream and river valleys as key features linking populations in the landscape genetics results, and high degree of clade specificity within major topographic subdivisions in the phylogeographical results, is consistent. As landscape genetics and phylogeography share many of the same objectives, synthesizing theory, models and methods between these fields will help bring about a better understanding of ecological and evolutionary processes structuring genetic variation across space and time.
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Affiliation(s)
- Van Wishingrad
- School of Life Sciences, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.,Hawai'i, Institute of Marine Biology, Kāne'ohe, Hawai'i, USA
| | - Robert C Thomson
- School of Life Sciences, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA
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30
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Balick DJ. A field theoretic approach to non-equilibrium population genetics in the strong selection regime. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.16.524324. [PMID: 36711507 PMCID: PMC9882232 DOI: 10.1101/2023.01.16.524324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Natural populations are virtually never observed in equilibrium, yet equilibrium approximations comprise the majority of our understanding of population genetics. Using standard tools from statistical physics, a formalism is presented that re-expresses the stochastic equations describing allelic evolution as a partition functional over all possible allelic trajectories ('paths') governed by selection, mutation, and drift. A perturbative field theory is developed for strong additive selection, relevant to disease variation, that facilitates the straightforward computation of closed-form approximations for time-dependent moments of the allele frequency distribution across a wide range of non-equilibrium scenarios; examples are presented for constant population size, exponential growth, bottlenecks, and oscillatory size, all of which align well to simulations and break down just above the drift barrier. Equilibration times are computed and, even for static population size, generically extend beyond the order 1/s timescale associated with exponential frequency decay. Though the mutation load is largely robust to variable population size, perturbative drift-based corrections to the deterministic trajectory are readily computed. Under strong selection, the variance of a new mutation's frequency (related to homozygosity) is dominated by drift-driven dynamics and a transient increase in variance often occurs prior to equilibrating. The excess kurtosis over skew squared is roughly constant (i.e., independent of selection, provided 2Ns ≳ 5) for static population size, and thus potentially sensitive to deviation from equilibrium. These insights highlight the value of such closed-form approximations, naturally generated from Feynman diagrams in a perturbative field theory, which can simply and accurately capture the parameter dependences describing a variety of non-equilibrium population genetic phenomena of interest.
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Affiliation(s)
- Daniel J Balick
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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31
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Alva O, Leroy A, Heiske M, Pereda-Loth V, Tisseyre L, Boland A, Deleuze JF, Rocha J, Schlebusch C, Fortes-Lima C, Stoneking M, Radimilahy C, Rakotoarisoa JA, Letellier T, Pierron D. The loss of biodiversity in Madagascar is contemporaneous with major demographic events. Curr Biol 2022; 32:4997-5007.e5. [PMID: 36334586 DOI: 10.1016/j.cub.2022.09.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/13/2022] [Accepted: 09/28/2022] [Indexed: 11/06/2022]
Abstract
Only 400 km off the coast of East Africa, the island of Madagascar is one of the last large land masses to have been colonized by humans. While many questions surround the human occupation of Madagascar, recent studies raise the question of human impact on endemic biodiversity and landscape transformation. Previous genetic and linguistic analyses have shown that the Malagasy population has emerged from an admixture that happened during the last millennium, between Bantu-speaking African populations and Austronesian-speaking Asian populations. By studying the sharing of chromosome segments between individuals (IBD determination), local ancestry information, and simulated genetic data, we inferred that the Malagasy ancestral Asian population was isolated for more than 1,000 years with an effective size of just a few hundred individuals. This isolation ended around 1,000 years before present (BP) by admixture with a small African population. Around the admixture time, there was a rapid demographic expansion due to intrinsic population growth of the newly admixed population, which coincides with extensive changes in Madagascar's landscape and the extinction of all endemic large-bodied vertebrates. Therefore, our approach can provide new insights into past human demography and associated impacts on ecosystems.
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Affiliation(s)
- Omar Alva
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Anaïs Leroy
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Margit Heiske
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Veronica Pereda-Loth
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Lenka Tisseyre
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Anne Boland
- Commissariat à l'Energie Atomique, Institut Génomique, Centre National de Génotypage, 91000 Evry, France
| | - Jean-François Deleuze
- Commissariat à l'Energie Atomique, Institut Génomique, Centre National de Génotypage, 91000 Evry, France
| | - Jorge Rocha
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal; Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4099-002 Porto, Portugal; BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
| | - Carina Schlebusch
- Human Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
| | - Cesar Fortes-Lima
- Human Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18C, 75236 Uppsala, Sweden
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany; Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, Villeurbanne, France
| | - Chantal Radimilahy
- Musée d'Art et d'Archéologie, University of Antananarivo, Antananarivo, Madagascar
| | | | - Thierry Letellier
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France
| | - Denis Pierron
- Équipe de Médecine Evolutive, EVOLSAN faculté de chirurgie dentaire, Université Toulouse III, Toulouse, France.
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Liu D, Peter BM, Schiefenhövel W, Kayser M, Stoneking M. Assessing human genome-wide variation in the Massim region of Papua New Guinea and implications for the Kula trading tradition. Mol Biol Evol 2022; 39:6653776. [PMID: 35920169 PMCID: PMC9372566 DOI: 10.1093/molbev/msac165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
The Massim, a cultural region that includes the southeastern tip of mainland Papua New Guinea (PNG) and nearby PNG offshore islands, is renowned for a trading network called Kula, in which different valuable items circulate in different directions among some of the islands. Although the Massim has been a focus of anthropological investigation since the pioneering work of Malinowski in 1922, the genetic background of its inhabitants remains relatively unexplored. To characterize the Massim genomically, we generated genome-wide SNP data from 192 individuals from 15 groups spanning the entire region. Analyzing these together with comparative data, we found that all Massim individuals have variable Papuan-related (indigenous) and Austronesian-related (arriving ∼3,000 years ago) ancestries. Individuals from Rossel Island in southern Massim, speaking an isolate Papuan language, have the highest amount of a distinct Papuan ancestry. We also investigated the recent contact via sharing of identical by descent (IBD) genomic segments and found that Austronesian-related IBD tracts are widely distributed geographically, but Papuan-related tracts are shared exclusively between the PNG mainland and Massim, and between the Bismarck and Solomon Archipelagoes. Moreover, the Kula-practicing groups of the Massim show higher IBD sharing among themselves than do groups that do not participate in Kula. This higher sharing predates the formation of Kula, suggesting that extensive contact between these groups since the Austronesian settlement may have facilitated the formation of Kula. Our study provides the first comprehensive genome-wide assessment of Massim inhabitants and new insights into the fascinating Kula system.
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Affiliation(s)
- Dang Liu
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.,Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris, France
| | - Benjamin M Peter
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Wulf Schiefenhövel
- Human Ethology Group, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.,Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, Villeurbanne, France
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Population dynamics and genetic connectivity in recent chimpanzee history. CELL GENOMICS 2022; 2:None. [PMID: 35711737 PMCID: PMC9188271 DOI: 10.1016/j.xgen.2022.100133] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 12/29/2021] [Accepted: 04/15/2022] [Indexed: 11/22/2022]
Abstract
Knowledge on the population history of endangered species is critical for conservation, but whole-genome data on chimpanzees (Pan troglodytes) is geographically sparse. Here, we produced the first non-invasive geolocalized catalog of genomic diversity by capturing chromosome 21 from 828 non-invasive samples collected at 48 sampling sites across Africa. The four recognized subspecies show clear genetic differentiation correlating with known barriers, while previously undescribed genetic exchange suggests that these have been permeable on a local scale. We obtained a detailed reconstruction of population stratification and fine-scale patterns of isolation, migration, and connectivity, including a comprehensive picture of admixture with bonobos (Pan paniscus). Unlike humans, chimpanzees did not experience extended episodes of long-distance migrations, which might have limited cultural transmission. Finally, based on local rare variation, we implement a fine-grained geolocalization approach demonstrating improved precision in determining the origin of confiscated chimpanzees.
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34
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Massatti R, Winkler DE. Spatially explicit management of genetic diversity using ancestry probability surfaces. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13902] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Rob Massatti
- US Geological Survey, Southwest Biological Science Center Flagstaff AZ USA
| | - Daniel E. Winkler
- US Geological Survey, Southwest Biological Science Center Tucson AZ USA
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Sentinella AT, Moles AT, Bragg JG, Rossetto M, Sherwin WB. Detecting steps in spatial genetic data: Which diversity measures are best? PLoS One 2022; 17:e0265110. [PMID: 35287164 PMCID: PMC8920294 DOI: 10.1371/journal.pone.0265110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 02/23/2022] [Indexed: 12/05/2022] Open
Abstract
Accurately detecting sudden changes, or steps, in genetic diversity across landscapes is important for locating barriers to gene flow, identifying selectively important loci, and defining management units. However, there are many metrics that researchers could use to detect steps and little information on which might be the most robust. Our study aimed to determine the best measure/s for genetic step detection along linear gradients using biallelic single nucleotide polymorphism (SNP) data. We tested the ability to differentiate between linear and step-like gradients in genetic diversity, using a range of diversity measures derived from the q-profile, including allelic richness, Shannon Information, GST, and Jost-D, as well as Bray-Curtis dissimilarity. To determine the properties of each measure, we repeated simulations of different intensities of step and allele proportion ranges, with varying genome sample size, number of loci, and number of localities. We found that alpha diversity (within-locality) based measures were ineffective at detecting steps. Further, allelic richness-based beta (between-locality) measures (e.g., Jaccard and Sørensen dissimilarity) were not reliable for detecting steps, but instead detected departures from fixation. The beta diversity measures best able to detect steps were: Shannon Information based measures, GST based measures, a Jost-D related measure, and Bray-Curtis dissimilarity. No one measure was best overall, with a trade-off between those measures with high step detection sensitivity (GST and Bray-Curtis) and those that minimised false positives (a variant of Shannon Information). Therefore, when detecting steps, we recommend understanding the differences between measures and using a combination of approaches.
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Affiliation(s)
- Alexander T. Sentinella
- Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia
| | - Angela T. Moles
- Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia
| | - Jason G. Bragg
- Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia
- Research Centre for Ecosystem Resilience, Australian Institute of Botanical Science, The Royal Botanic Garden Sydney, Sydney, NSW, Australia
| | - Maurizio Rossetto
- Research Centre for Ecosystem Resilience, Australian Institute of Botanical Science, The Royal Botanic Garden Sydney, Sydney, NSW, Australia
| | - William B. Sherwin
- Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia
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Chang CW, Fridman E, Mascher M, Himmelbach A, Schmid K. Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum) in the Southern Levant. Heredity (Edinb) 2022; 128:107-119. [PMID: 35017679 PMCID: PMC8814169 DOI: 10.1038/s41437-021-00494-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 12/13/2021] [Accepted: 12/16/2021] [Indexed: 01/12/2023] Open
Abstract
Determining the extent of genetic variation that reflects local adaptation in crop-wild relatives is of interest for the purpose of identifying useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley (Hordeum vulgare L. ssp. spontaneum) populations of the Southern Levant using genotyping by sequencing (GBS) of 244 accessions in the Barley 1K+ collection. The inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association between lower gene flow rates and geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was solely attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). When conditioned on population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify adaptation signatures. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions, which have reduced recombination, of the chromosomes 3H, 4H, and 5H. However, selection signatures mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges had a limited effect on the genomic diversity of wild barley. This highlighted the importance of nonselective forces in genetic differentiation.
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Affiliation(s)
| | - Eyal Fridman
- Plant Sciences Institute, Agricultural Research Organization (ARO), The Volcani Center, Rishon LeZion, Israel
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany
| | - Karl Schmid
- University of Hohenheim, Stuttgart, Germany.
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Sousa R, Vasconcelos J, Vera-Escalona I, Pinto AR, Hawkins SJ, Freitas M, Delgado J, González JA, Riera R. Pleistocene expansion, anthropogenic pressure and ocean currents: Disentangling the past and ongoing evolutionary history of Patella aspera Röding, 1798 in the archipelago of Madeira. MARINE ENVIRONMENTAL RESEARCH 2021; 172:105485. [PMID: 34715642 DOI: 10.1016/j.marenvres.2021.105485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 09/12/2021] [Accepted: 09/18/2021] [Indexed: 06/13/2023]
Abstract
AIMS Rising sea-level following the Last Glacial Maximum lead to fragmentation of coastal limpet populations between islands of the Archipelago of Madeira. This fragmentation is reinforced by recent heavy exploitation reducing effective population size on Madeira Island. We use the limpet P. aspera to understand how the role of processes at different time scales (i.e. changes in the sea level and overexploitation) can influence the genetic composition of an extant species, relating these processes to reproductive phenology and seasonal shifts in ocean currents. LOCATION Madeira Island, Porto Santo and Desertas (Archipelago of Madeira, NE Atlantic Ocean). TAXON The limpet Patella aspera. METHODS Twelve microsatellite genetic markers were used. A power analysis was used to evaluate the power of the microsatellite markers to detect a signal of population differentiation. Long-term past migrations were assessed using a Bayesian Markov Montecarlo approach in the software MIGRATE-n to estimate mutation-scaled migration rates (M = m/μ; m, probability of a lineage immigrating per generation; μ, mutation rate). Two scenarios were evaluated using an Approximate Bayesian Computation (ABC) in the software DIYABC 2.1 (i) Scenario 1: considered a population scenario from a reduced Ne at time t3 to a higher Ne at time t2; and (ii) Scenario 2 considering a reduction of Ne from a time t3 to a time t2. RESULTS Colonization of the archipelago by Portuguese settlers six centuries ago probably led to an important decrease in the genetic diversity of the species (Ne). Contemporary gene flow strongly support a pattern of high asymmetric connectivity explained by the reproductive phenology of the species and spatio-temporal seasonal changes in the ocean currents. Spatio-temporal reconstructions using Bayesian methods, including coalescent and Approximate Bayesian Computation (ABC) approaches, suggest changes in the migration patterns from highly symmetric to highly asymmetric connectivity with subtle population differentiation as consequence of post-glacial maximum sea level rise during the Holocene. MAIN CONCLUSIONS Our results suggest that anthropogenic activity could have had serious effects on the genetic diversity of heavily exploited littoral species since the end of the Pleistocene, probably accelerating in recent years.
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Affiliation(s)
- Ricardo Sousa
- Observatório Oceânico da Madeira, Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação (OOM/ARDITI) - Edifício Madeira Tecnopolo, Funchal, Madeira, Portugal; Direção Regional do Mar (DRM)/ Direção de Serviços de Monitorização, Estudos e Investigação do Mar (DSEIMar), 9004-562, Funchal, Madeira, Portugal; MARE - Marine and Environmental Sciences Centre, Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação (ARDITI), Edifício Madeira Tecnopolo Piso 0, Caminho da Penteada, 9020-105, Funchal, Madeira, Portugal
| | - Joana Vasconcelos
- MARE - Marine and Environmental Sciences Centre, Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação (ARDITI), Edifício Madeira Tecnopolo Piso 0, Caminho da Penteada, 9020-105, Funchal, Madeira, Portugal; Faculdade de Ciências de Vida, Universidade da Madeira, Campus Universitário da Madeira, Caminho da Penteada, 9020-020, Funchal, Madeira, Portugal; Departamento de Ecología, Facultad de Ciencias, Universidad Católica de la Santísima Concepción, Casilla 297, Concepción, Chile
| | - Iván Vera-Escalona
- CIBAS, Facultad de Ciencias, Universidad Católica de la Santísima Concepción, Casilla 297, Concepción, Chile; IU-ECOAQUA, Group of Biodiversity and Conservation (BIOCON), Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
| | - Ana Rita Pinto
- Direção Regional do Mar (DRM)/ Direção de Serviços de Monitorização, Estudos e Investigação do Mar (DSEIMar), 9004-562, Funchal, Madeira, Portugal
| | - S J Hawkins
- Marine Biological Association of the UK, Plymouth, PL1 2PB, UK; School of Ocean and Earth Science, University of Southampton, National Oceanography Centre, Southampton, SO14 3ZH, UK
| | - Mafalda Freitas
- Observatório Oceânico da Madeira, Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação (OOM/ARDITI) - Edifício Madeira Tecnopolo, Funchal, Madeira, Portugal; Direção Regional do Mar (DRM)/ Direção de Serviços de Monitorização, Estudos e Investigação do Mar (DSEIMar), 9004-562, Funchal, Madeira, Portugal; MARE - Marine and Environmental Sciences Centre, Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação (ARDITI), Edifício Madeira Tecnopolo Piso 0, Caminho da Penteada, 9020-105, Funchal, Madeira, Portugal
| | - João Delgado
- Direção Regional do Mar (DRM)/ Direção de Serviços de Monitorização, Estudos e Investigação do Mar (DSEIMar), 9004-562, Funchal, Madeira, Portugal; Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR/CIMAR), Porto, Portugal
| | - José A González
- Ecología Marina Aplicada y Pesquerías (i-UNAT), Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
| | - Rodrigo Riera
- Departamento de Ecología, Facultad de Ciencias, Universidad Católica de la Santísima Concepción, Casilla 297, Concepción, Chile; IU-ECOAQUA, Group of Biodiversity and Conservation (BIOCON), Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain.
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Parental relatedness through time revealed by runs of homozygosity in ancient DNA. Nat Commun 2021; 12:5425. [PMID: 34521843 PMCID: PMC8440622 DOI: 10.1038/s41467-021-25289-w] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 07/21/2021] [Indexed: 02/08/2023] Open
Abstract
Parental relatedness of present-day humans varies substantially across the globe, but little is known about the past. Here we analyze ancient DNA, leveraging that parental relatedness leaves genomic traces in the form of runs of homozygosity. We present an approach to identify such runs in low-coverage ancient DNA data aided by haplotype information from a modern phased reference panel. Simulation and experiments show that this method robustly detects runs of homozygosity longer than 4 centimorgan for ancient individuals with at least 0.3 × coverage. Analyzing genomic data from 1,785 ancient humans who lived in the last 45,000 years, we detect low rates of first cousin or closer unions across most ancient populations. Moreover, we find a marked decay in background parental relatedness co-occurring with or shortly after the advent of sedentary agriculture. We observe this signal, likely linked to increasing local population sizes, across several geographic transects worldwide.
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Marcus J, Ha W, Barber RF, Novembre J. Fast and flexible estimation of effective migration surfaces. eLife 2021; 10:61927. [PMID: 34328078 PMCID: PMC8324296 DOI: 10.7554/elife.61927] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 06/07/2021] [Indexed: 12/12/2022] Open
Abstract
Spatial population genetic data often exhibits ‘isolation-by-distance,’ where genetic similarity tends to decrease as individuals become more geographically distant. The rate at which genetic similarity decays with distance is often spatially heterogeneous due to variable population processes like genetic drift, gene flow, and natural selection. Petkova et al., 2016 developed a statistical method called Estimating Effective Migration Surfaces (EEMS) for visualizing spatially heterogeneous isolation-by-distance on a geographic map. While EEMS is a powerful tool for depicting spatial population structure, it can suffer from slow runtimes. Here, we develop a related method called Fast Estimation of Effective Migration Surfaces (FEEMS). FEEMS uses a Gaussian Markov Random Field model in a penalized likelihood framework that allows for efficient optimization and output of effective migration surfaces. Further, the efficient optimization facilitates the inference of migration parameters per edge in the graph, rather than per node (as in EEMS). With simulations, we show conditions under which FEEMS can accurately recover effective migration surfaces with complex gene-flow histories, including those with anisotropy. We apply FEEMS to population genetic data from North American gray wolves and show it performs favorably in comparison to EEMS, with solutions obtained orders of magnitude faster. Overall, FEEMS expands the ability of users to quickly visualize and interpret spatial structure in their data.
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Affiliation(s)
- Joseph Marcus
- Department of Human Genetics, University of Chicago, Chicago, United States
| | - Wooseok Ha
- Department of Statistics, University of California, Berkeley, Berkeley, United States
| | | | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, United States.,Department of Ecology and Evolution, University of Chicago, Chicago, United States
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40
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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: 26] [Impact Index Per Article: 8.7] [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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41
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Kutanan W, Liu D, Kampuansai J, Srikummool M, Srithawong S, Shoocongdej R, Sangkhano S, Ruangchai S, Pittayaporn P, Arias L, Stoneking M. Reconstructing the Human Genetic History of Mainland Southeast Asia: Insights from Genome-Wide Data from Thailand and Laos. Mol Biol Evol 2021; 38:3459-3477. [PMID: 33905512 PMCID: PMC8321548 DOI: 10.1093/molbev/msab124] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Thailand and Laos, located in the center of Mainland Southeast Asia (MSEA), harbor diverse ethnolinguistic groups encompassing all five language families of MSEA: Tai-Kadai (TK), Austroasiatic (AA), Sino-Tibetan (ST), Hmong-Mien (HM), and Austronesian (AN). Previous genetic studies of Thai/Lao populations have focused almost exclusively on uniparental markers and there is a paucity of genome-wide studies. We therefore generated genome-wide SNP data for 33 ethnolinguistic groups, belonging to the five MSEA language families from Thailand and Laos, and analyzed these together with data from modern Asian populations and SEA ancient samples. Overall, we find genetic structure according to language family, albeit with heterogeneity in the AA-, HM-, and ST-speaking groups, and in the hill tribes, that reflects both population interactions and genetic drift. For the TK speaking groups, we find localized genetic structure that is driven by different levels of interaction with other groups in the same geographic region. Several Thai groups exhibit admixture from South Asia, which we date to ∼600-1000 years ago, corresponding to a time of intensive international trade networks that had a major cultural impact on Thailand. An AN group from Southern Thailand shows both South Asian admixture as well as overall affinities with AA-speaking groups in the region, suggesting an impact of cultural diffusion. Overall, we provide the first detailed insights into the genetic profiles of Thai/Lao ethnolinguistic groups, which should be helpful for reconstructing human genetic history in MSEA and selecting populations for participation in ongoing whole genome sequence and biomedical studies.
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Affiliation(s)
- Wibhu Kutanan
- Department of Biology, Faculty of Science, Khon Kaen University, Khon Kaen, Thailand
| | - Dang Liu
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Jatupol Kampuansai
- Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand.,Research Center in Bioresources for Agriculture, Industry and Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Metawee Srikummool
- Department of Biochemistry, Faculty of Medical Science, Naresuan University, Phitsanulok, Thailand
| | - Suparat Srithawong
- Department of Biology, Faculty of Science, Khon Kaen University, Khon Kaen, Thailand
| | - Rasmi Shoocongdej
- Department of Archaeology, Faculty of Archaeology, Silpakorn University, Bangkok, Thailand
| | - Sukrit Sangkhano
- School of Public Health, Walailak University, Nakhon Si Thammarat, Thailand
| | - Sukhum Ruangchai
- Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen, Thailand
| | - Pittayawat Pittayaporn
- Department of Linguistics and Southeast Asian Linguistics Research Unit, Faculty of Arts, Chulalongkorn University, Bangkok, Thailand
| | - Leonardo Arias
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.,Centre for Linguistics, Faculty of Humanities, Leiden University, Leiden, The Netherlands
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
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Liu D, Duong NT, Ton ND, Van Phong N, Pakendorf B, Van Hai N, Stoneking M. Extensive Ethnolinguistic Diversity in Vietnam Reflects Multiple Sources of Genetic Diversity. Mol Biol Evol 2021; 37:2503-2519. [PMID: 32344428 PMCID: PMC7475039 DOI: 10.1093/molbev/msaa099] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Vietnam features extensive ethnolinguistic diversity and occupies a key position in Mainland Southeast Asia. Yet, the genetic diversity of Vietnam remains relatively unexplored, especially with genome-wide data, because previous studies have focused mainly on the majority Kinh group. Here, we analyze newly generated genome-wide single-nucleotide polymorphism data for the Kinh and 21 additional ethnic groups in Vietnam, encompassing all five major language families in Mainland Southeast Asia. In addition to analyzing the allele and haplotype sharing within the Vietnamese groups, we incorporate published data from both nearby modern populations and ancient samples for comparison. In contrast to previous studies that suggested a largely indigenous origin for Vietnamese genetic diversity, we find that Vietnamese ethnolinguistic groups harbor multiple sources of genetic diversity that likely reflect different sources for the ancestry associated with each language family. However, linguistic diversity does not completely match genetic diversity: There have been extensive interactions between the Hmong-Mien and Tai-Kadai groups; different Austro-Asiatic groups show different affinities with other ethnolinguistic groups; and we identified a likely case of cultural diffusion in which some Austro-Asiatic groups shifted to Austronesian languages during the past 2,500 years. Overall, our results highlight the importance of genome-wide data from dense sampling of ethnolinguistic groups in providing new insights into the genetic diversity and history of an ethnolinguistically diverse region, such as Vietnam.
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Affiliation(s)
- Dang Liu
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Nguyen Thuy Duong
- Institute of Genome Research, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Nguyen Dang Ton
- Institute of Genome Research, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Nguyen Van Phong
- Institute of Genome Research, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Brigitte Pakendorf
- Laboratoire Dynamique du Langage, UMR5596, CNRS & Université de Lyon, Lyon, France
| | - Nong Van Hai
- Institute of Genome Research, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Mark Stoneking
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
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Richmond S, Zhurov AI, Ali ABM, Pirttiniemi P, Heikkinen T, Harila V, Silinevica S, Jakobsone G, Urtane I. Exploring the midline soft tissue surface changes from 12 to 15 years of age in three distinct country population cohorts. Eur J Orthod 2021; 42:517-524. [PMID: 31748803 DOI: 10.1093/ejo/cjz080] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
INTRODUCTION Several studies have highlighted differences in the facial features in a White European population. Genetics appear to have a major influence on normal facial variation, and environmental factors are likely to have minor influences on face shape directly or through epigenetic mechanisms. AIM The aim of this longitudinal cohort study is to determine the rate of change in midline facial landmarks in three distinct homogenous population groups (Finnish, Latvian, and Welsh) from 12.8 to 15.3 years of age. This age range covers the pubertal growth period for the majority of boys and girls. METHODS A cohort of children aged 12 were monitored for facial growth in three countries [Finland (n = 60), Latvia (n = 107), and Wales (n = 96)]. Three-dimensional facial surface images were acquired (using either laser or photogrammetric methods) at regular intervals (6-12 months) for 4 years. Ethical approval was granted in each country. Nine midline landmarks were identified and the relative spatial positions of these surface landmarks were measured relative to the mid-endocanthion (men) over a 4-year period. RESULTS This study reports the children who attended 95 per cent of all scanning sessions (Finland 48 out of 60; Latvia 104 out of 107; Wales 50 out of 96). Considerable facial variation is seen for all countries and sexes. There are clear patterns of growth that show different magnitudes at different age groups for the different country groups, sexes, and facial parameters. The greatest single yearly growth rate (5.4 mm) was seen for Welsh males for men-pogonion distance at 13.6 years of age. Males exhibit greater rates of growth compared to females. These variations in magnitude and timings are likely to be influenced by genetic ancestry as a result of population migration. CONCLUSION The midline points are a simple and valid method to assess the relative spatial positions of facial surface landmarks. This study confirms previous reports on the subtle differences in facial shapes and sizes of male and female children in different populations and also highlights the magnitudes and timings of growth for various midline landmark distances to the men point.
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Affiliation(s)
- Stephen Richmond
- Orthodontic Department, Applied Clinical Research and Public Health, School of Dentistry, College of Biomedical and Life Sciences, Heath Park, Cardiff, UK
| | - Alexei I Zhurov
- Orthodontic Department, Applied Clinical Research and Public Health, School of Dentistry, College of Biomedical and Life Sciences, Heath Park, Cardiff, UK
| | - Azrul Bin Mohd Ali
- Orthodontic Department, Applied Clinical Research and Public Health, School of Dentistry, College of Biomedical and Life Sciences, Heath Park, Cardiff, UK
| | - Pertti Pirttiniemi
- Oral Development and Orthodontics, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Tuomo Heikkinen
- Oral Development and Orthodontics, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Virpi Harila
- Oral Development and Orthodontics, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Signe Silinevica
- Orthodontic Department, RSU Institute of Stomatology, Rīga, Latvia
| | | | - Ilga Urtane
- Orthodontic Department, RSU Institute of Stomatology, Rīga, Latvia
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Savary P, Foltête J, Moal H, Vuidel G, Garnier S. graph4lg: A package for constructing and analysing graphs for landscape genetics in R. Methods Ecol Evol 2020. [DOI: 10.1111/2041-210x.13530] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Paul Savary
- ARP‐Astrance Paris France
- ThéMA UMR 6049 CNRSUniversité Bourgogne‐Franche‐Comté Besançon Cedex France
- Biogéosciences UMR 6282 CNRSUniversité Bourgogne‐Franche‐Comté Dijon France
| | | | | | - Gilles Vuidel
- ThéMA UMR 6049 CNRSUniversité Bourgogne‐Franche‐Comté Besançon Cedex France
| | - Stéphane Garnier
- Biogéosciences UMR 6282 CNRSUniversité Bourgogne‐Franche‐Comté Dijon France
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Genome variation and population structure among 1142 mosquitoes of the African malaria vector species Anopheles gambiae and Anopheles coluzzii. Genome Res 2020; 30:1533-1546. [PMID: 32989001 PMCID: PMC7605271 DOI: 10.1101/gr.262790.120] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 08/27/2020] [Indexed: 01/03/2023]
Abstract
Mosquito control remains a central pillar of efforts to reduce malaria burden in sub-Saharan Africa. However, insecticide resistance is entrenched in malaria vector populations, and countries with a high malaria burden face a daunting challenge to sustain malaria control with a limited set of surveillance and intervention tools. Here we report on the second phase of a project to build an open resource of high-quality data on genome variation among natural populations of the major African malaria vector species Anopheles gambiae and Anopheles coluzzii We analyzed whole genomes of 1142 individual mosquitoes sampled from the wild in 13 African countries, as well as a further 234 individuals comprising parents and progeny of 11 laboratory crosses. The data resource includes high-confidence single-nucleotide polymorphism (SNP) calls at 57 million variable sites, genome-wide copy number variation (CNV) calls, and haplotypes phased at biallelic SNPs. We use these data to analyze genetic population structure and characterize genetic diversity within and between populations. We illustrate the utility of these data by investigating species differences in isolation by distance, genetic variation within proposed gene drive target sequences, and patterns of resistance to pyrethroid insecticides. This data resource provides a foundation for developing new operational systems for molecular surveillance and for accelerating research and development of new vector control tools. It also provides a unique resource for the study of population genomics and evolutionary biology in eukaryotic species with high levels of genetic diversity under strong anthropogenic evolutionary pressures.
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Dutch population structure across space, time and GWAS design. Nat Commun 2020; 11:4556. [PMID: 32917883 PMCID: PMC7486932 DOI: 10.1038/s41467-020-18418-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 08/21/2020] [Indexed: 11/09/2022] Open
Abstract
Previous genetic studies have identified local population structure within the Netherlands; however their resolution is limited by use of unlinked markers and absence of external reference data. Here we apply advanced haplotype sharing methods (ChromoPainter/fineSTRUCTURE) to study fine-grained population genetic structure and demographic change across the Netherlands using genome-wide single nucleotide polymorphism data (1,626 individuals) with associated geography (1,422 individuals). We identify 40 haplotypic clusters exhibiting strong north/south variation and fine-scale differentiation within provinces. Clustering is tied to country-wide ancestry gradients from neighbouring lands and to locally restricted gene flow across major Dutch rivers. North-south structure is temporally stable, with west-east differentiation more transient, potentially influenced by migrations during the middle ages. Despite superexponential population growth, regional demographic estimates reveal population crashes contemporaneous with the Black Death. Within Dutch and international data, GWAS incorporating fine-grained haplotypic covariates are less confounded than standard methods.
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Differences in local population history at the finest level: the case of the Estonian population. Eur J Hum Genet 2020; 28:1580-1591. [PMID: 32712624 PMCID: PMC7575549 DOI: 10.1038/s41431-020-0699-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 06/24/2020] [Accepted: 07/14/2020] [Indexed: 12/16/2022] Open
Abstract
Several recent studies detected fine-scale genetic structure in human populations. Hence, groups conventionally treated as single populations harbour significant variation in terms of allele frequencies and patterns of haplotype sharing. It has been shown that these findings should be considered when performing studies of genetic associations and natural selection, especially when dealing with polygenic phenotypes. However, there is little understanding of the practical effects of such genetic structure on demography reconstructions and selection scans when focusing on recent population history. Here we tested the impact of population structure on such inferences using high-coverage (~30×) genome sequences of 2305 Estonians. We show that different regions of Estonia differ in both effective population size dynamics and signatures of natural selection. By analyzing identity-by-descent segments we also reveal that some Estonian regions exhibit evidence of a bottleneck 10-15 generations ago reflecting sequential episodes of wars, plague and famine, although this signal is virtually undetected when treating Estonia as a single population. Besides that, we provide a framework for relating effective population size estimated from genetic data to actual census size and validate it on the Estonian population. This approach may be widely used both to cross-check estimates based on historical sources as well as to get insight into times and/or regions with no other information available. Our results suggest that the history of human populations within the last few millennia can be highly region specific and cannot be properly studied without taking local genetic structure into account.
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Battey CJ, Ralph PL, Kern AD. Space is the Place: Effects of Continuous Spatial Structure on Analysis of Population Genetic Data. Genetics 2020; 215:193-214. [PMID: 32209569 PMCID: PMC7198281 DOI: 10.1534/genetics.120.303143] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 03/12/2020] [Indexed: 12/14/2022] Open
Abstract
Real geography is continuous, but standard models in population genetics are based on discrete, well-mixed populations. As a result, many methods of analyzing genetic data assume that samples are a random draw from a well-mixed population, but are applied to clustered samples from populations that are structured clinally over space. Here, we use simulations of populations living in continuous geography to study the impacts of dispersal and sampling strategy on population genetic summary statistics, demographic inference, and genome-wide association studies (GWAS). We find that most common summary statistics have distributions that differ substantially from those seen in well-mixed populations, especially when Wright's neighborhood size is < 100 and sampling is spatially clustered. "Stepping-stone" models reproduce some of these effects, but discretizing the landscape introduces artifacts that in some cases are exacerbated at higher resolutions. The combination of low dispersal and clustered sampling causes demographic inference from the site frequency spectrum to infer more turbulent demographic histories, but averaged results across multiple simulations revealed surprisingly little systematic bias. We also show that the combination of spatially autocorrelated environments and limited dispersal causes GWAS to identify spurious signals of genetic association with purely environmentally determined phenotypes, and that this bias is only partially corrected by regressing out principal components of ancestry. Last, we discuss the relevance of our simulation results for inference from genetic variation in real organisms.
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Affiliation(s)
- C J Battey
- Institute of Ecology Evolution, Department of Biology, University of Oregon, Eugene, Oregon
| | - Peter L Ralph
- Institute of Ecology Evolution, Department of Biology, University of Oregon, Eugene, Oregon
| | - Andrew D Kern
- Institute of Ecology Evolution, Department of Biology, University of Oregon, Eugene, Oregon
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Li Y, Shetty AC, Lon C, Spring M, Saunders DL, Fukuda MM, Hien TT, Pukrittayakamee S, Fairhurst RM, Dondorp AM, Plowe CV, O’Connor TD, Takala-Harrison S, Stewart K. Detecting geospatial patterns of Plasmodium falciparum parasite migration in Cambodia using optimized estimated effective migration surfaces. Int J Health Geogr 2020; 19:13. [PMID: 32276636 PMCID: PMC7149848 DOI: 10.1186/s12942-020-00207-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 04/01/2020] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Understanding the genetic structure of natural populations provides insight into the demographic and adaptive processes that have affected those populations. Such information, particularly when integrated with geospatial data, can have translational applications for a variety of fields, including public health. Estimated effective migration surfaces (EEMS) is an approach that allows visualization of the spatial patterns in genomic data to understand population structure and migration. In this study, we developed a workflow to optimize the resolution of spatial grids used to generate EEMS migration maps and applied this optimized workflow to estimate migration of Plasmodium falciparum in Cambodia and bordering regions of Thailand and Vietnam. METHODS The optimal density of EEMS grids was determined based on a new workflow created using density clustering to define genomic clusters and the spatial distance between genomic clusters. Topological skeletons were used to capture the spatial distribution for each genomic cluster and to determine the EEMS grid density; i.e., both genomic and spatial clustering were used to guide the optimization of EEMS grids. Model accuracy for migration estimates using the optimized workflow was tested and compared to grid resolutions selected without the optimized workflow. As a test case, the optimized workflow was applied to genomic data generated from P. falciparum sampled in Cambodia and bordering regions, and migration maps were compared to estimates of malaria endemicity, as well as geographic properties of the study area, as a means of validating observed migration patterns. RESULTS Optimized grids displayed both high model accuracy and reduced computing time compared to grid densities selected in an unguided manner. In addition, EEMS migration maps generated for P. falciparum using the optimized grid corresponded to estimates of malaria endemicity and geographic properties of the study region that might be expected to impact malaria parasite migration, supporting the validity of the observed migration patterns. CONCLUSIONS Optimized grids reduce spatial uncertainty in the EEMS contours that can result from user-defined parameters, such as the resolution of the spatial grid used in the model. This workflow will be useful to a broad range of EEMS users as it can be applied to analyses involving other organisms of interest and geographic areas.
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Affiliation(s)
- Yao Li
- Center for Geospatial Information Science, Department of Geographical Sciences, University of Maryland, College Park, 20742 MD USA
| | - Amol C. Shetty
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, 21201 MD USA
| | - Chanthap Lon
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Michele Spring
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - David L. Saunders
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Mark M. Fukuda
- Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Tran Tinh Hien
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | | | | | - Arjen M. Dondorp
- Mahidol-Oxford Tropical Medicine Research Unit, Bangkok, Thailand
| | | | - Timothy D. O’Connor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, 21201 MD USA
| | - Shannon Takala-Harrison
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, 21201 MD USA
| | - Kathleen Stewart
- Center for Geospatial Information Science, Department of Geographical Sciences, University of Maryland, College Park, 20742 MD USA
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Thomaz AT, He Q. When are populations not connected like a circuit? Identifying biases in gene flow from coalescent times. Mol Ecol Resour 2020; 19:1381-1384. [PMID: 31657534 DOI: 10.1111/1755-0998.13075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 08/06/2019] [Accepted: 08/07/2019] [Indexed: 11/28/2022]
Abstract
Connectivity and movement patterns of populations are influenced by past and present environmental and biotic factors, which are reflected in genetic relatedness among populations. Methods that estimate the "commute time" between populations based on electrical resistance (i.e., isolation-by-resistance [IBR]) have been widely applied to either infer movement patterns directly from environmental factors or detect possible barriers to gene flow given empirical genetic relatedness. Yet, the commute time is only equivalent to the coalescence time between populations under symmetric migration with isotropic landscapes. Asymmetric gene flow is relatively common when populations are expanding, retreating, or with source-sink dynamics. In a From the Cover paper in this issue of Molecular Ecology Resources, Lundgren and Ralph (Molecular Ecology Resources, 19, 2019) describe a Bayesian method to infer bidirectional gene flow rates and population sizes without the assumption of symmetry. The method shows great accuracy in connectivity estimations under symmetric, as well as asymmetric gene flow scenarios where resistance methods fail. However, computational complexity limits the method to a few populations, preventing its application to finescale environmental maps. Also, as a discrete-deme static model, the inferred differences in gene flow rates are sensitive to population discretization and cannot be directly used to differentiate among processes (e.g., past expansion vs. current barrier). Here, we discuss scenarios where the new method can best be utilized and provide potential directions to identify the underlying processes causing deviations in gene flow patterns.
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Affiliation(s)
- Andréa T Thomaz
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada
| | - Qixin He
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
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