1
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Camus L, Gautier M, Boitard S. Predicting species invasiveness with genomic data: Is genomic offset related to establishment probability? Evol Appl 2024; 17:e13709. [PMID: 38884022 PMCID: PMC11178484 DOI: 10.1111/eva.13709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/30/2024] [Accepted: 05/04/2024] [Indexed: 06/18/2024] Open
Abstract
Predicting the risk of establishment and spread of populations outside their native range represents a major challenge in evolutionary biology. Various methods have recently been developed to estimate population (mal)adaptation to a new environment with genomic data via so-called Genomic Offset (GO) statistics. These approaches are particularly promising for studying invasive species but have still rarely been used in this context. Here, we evaluated the relationship between GO and the establishment probability of a population in a new environment using both in silico and empirical data. First, we designed invasion simulations to evaluate the ability to predict establishment probability of two GO computation methods (Geometric GO and Gradient Forest) under several conditions. Additionally, we aimed to evaluate the interpretability of absolute Geometric GO values, which theoretically represent the adaptive genetic distance between populations from distinct environments. Second, utilizing public empirical data from the crop pest species Bactrocera tryoni, a fruit fly native from Northern Australia, we computed GO between "source" populations and a diverse range of locations within invaded areas. This practical application of GO within the context of a biological invasion underscores its potential in providing insights and guiding recommendations for future invasion risk assessment. Overall, our results suggest that GO statistics represent good predictors of the establishment probability and may thus inform invasion risk, although the influence of several factors on prediction performance (e.g., propagule pressure or admixture) will need further investigation.
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Affiliation(s)
- Louise Camus
- CBGP, INRAE, CIRAD, IRD, L'institut Agro, Université de Montpellier Montpellier France
| | - Mathieu Gautier
- CBGP, INRAE, CIRAD, IRD, L'institut Agro, Université de Montpellier Montpellier France
| | - Simon Boitard
- CBGP, INRAE, CIRAD, IRD, L'institut Agro, Université de Montpellier Montpellier France
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2
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Nunez JCB, Lenhart BA, Bangerter A, Murray CS, Mazzeo GR, Yu Y, Nystrom TL, Tern C, Erickson PA, Bergland AO. A cosmopolitan inversion facilitates seasonal adaptation in overwintering Drosophila. Genetics 2024; 226:iyad207. [PMID: 38051996 PMCID: PMC10847723 DOI: 10.1093/genetics/iyad207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 11/28/2023] [Indexed: 12/07/2023] Open
Abstract
Fluctuations in the strength and direction of natural selection through time are a ubiquitous feature of life on Earth. One evolutionary outcome of such fluctuations is adaptive tracking, wherein populations rapidly adapt from standing genetic variation. In certain circumstances, adaptive tracking can lead to the long-term maintenance of functional polymorphism despite allele frequency change due to selection. Although adaptive tracking is likely a common process, we still have a limited understanding of aspects of its genetic architecture and its strength relative to other evolutionary forces such as drift. Drosophila melanogaster living in temperate regions evolve to track seasonal fluctuations and are an excellent system to tackle these gaps in knowledge. By sequencing orchard populations collected across multiple years, we characterized the genomic signal of seasonal demography and identified that the cosmopolitan inversion In(2L)t facilitates seasonal adaptive tracking and shows molecular footprints of selection. A meta-analysis of phenotypic studies shows that seasonal loci within In(2L)t are associated with behavior, life history, physiology, and morphological traits. We identify candidate loci and experimentally link them to phenotype. Our work contributes to our general understanding of fluctuating selection and highlights the evolutionary outcome and dynamics of contemporary selection on inversions.
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Affiliation(s)
- Joaquin C B Nunez
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
- Department of Biology, University of Vermont, 109 Carrigan Drive, Burlington, VT 05405, USA
| | - Benedict A Lenhart
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
| | - Alyssa Bangerter
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
| | - Connor S Murray
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
| | - Giovanni R Mazzeo
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
| | - Yang Yu
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
| | - Taylor L Nystrom
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
| | - Courtney Tern
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
| | - Priscilla A Erickson
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
- Department of Biology, University of Richmond, 138 UR Drive, Richmond, VA 23173, USA
| | - Alan O Bergland
- Department of Biology, University of Virginia, 90 Geldard Drive, Charlottesville, VA 22901, USA
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3
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Feng S, DeGrey SP, Guédot C, Schoville SD, Pool JE. Genomic Diversity Illuminates the Environmental Adaptation of Drosophila suzukii. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.03.547576. [PMID: 37461625 PMCID: PMC10349955 DOI: 10.1101/2023.07.03.547576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Biological invasions carry substantial practical and scientific importance, and represent natural evolutionary experiments on contemporary timescales. Here, we investigated genomic diversity and environmental adaptation of the crop pest Drosophila suzukii using whole-genome sequencing data and environmental metadata for 29 population samples from its native and invasive range. Through a multifaceted analysis of this population genomic data, we increase our understanding of the D. suzukii genome, its diversity and its evolution, and we identify an appropriate genotype-environment association pipeline for our data set. Using this approach, we detect genetic signals of local adaptation associated with nine distinct environmental factors related to altitude, wind speed, precipitation, temperature, and human land use. We uncover unique functional signatures for each environmental variable, such as a prevalence of cuticular genes associated with annual precipitation. We also infer biological commonalities in the adaptation to diverse selective pressures, particularly in terms of the apparent contribution of nervous system evolution to enriched processes (ranging from neuron development to circadian behavior) and to top genes associated with all nine environmental variables. Our findings therefore depict a finer-scale adaptive landscape underlying the rapid invasion success of this agronomically important species.
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Affiliation(s)
- Siyuan Feng
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA
| | - Samuel P. DeGrey
- Department of Entomology, University of Wisconsin-Madison, Madison, WI, USA
| | - Christelle Guédot
- Department of Entomology, University of Wisconsin-Madison, Madison, WI, USA
| | - Sean D. Schoville
- Department of Entomology, University of Wisconsin-Madison, Madison, WI, USA
| | - John E. Pool
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA
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4
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Horváth V, Guirao-Rico S, Salces-Ortiz J, Rech GE, Green L, Aprea E, Rodeghiero M, Anfora G, González J. Gene expression differences consistent with water loss reduction underlie desiccation tolerance of natural Drosophila populations. BMC Biol 2023; 21:35. [PMID: 36797754 PMCID: PMC9933328 DOI: 10.1186/s12915-023-01530-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 01/27/2023] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND Climate change is one of the main factors shaping the distribution and biodiversity of organisms, among others by greatly altering water availability, thus exposing species and ecosystems to harsh desiccation conditions. However, most of the studies so far have focused on the effects of increased temperature. Integrating transcriptomics and physiology is key to advancing our knowledge on how species cope with desiccation stress, and these studies are still best accomplished in model organisms. RESULTS Here, we characterized the natural variation of European D. melanogaster populations across climate zones and found that strains from arid regions were similar or more tolerant to desiccation compared with strains from temperate regions. Tolerant and sensitive strains differed not only in their transcriptomic response to stress but also in their basal expression levels. We further showed that gene expression changes in tolerant strains correlated with their physiological response to desiccation stress and with their cuticular hydrocarbon composition, and functionally validated three of the candidate genes identified. Transposable elements, which are known to influence stress response across organisms, were not found to be enriched nearby differentially expressed genes. Finally, we identified several tRNA-derived small RNA fragments that differentially targeted genes in response to desiccation stress. CONCLUSIONS Overall, our results showed that basal gene expression differences across individuals should be analyzed if we are to understand the genetic basis of differential stress survival. Moreover, tRNA-derived small RNA fragments appear to be relevant across stress responses and allow for the identification of stress-response genes not detected at the transcriptional level.
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Affiliation(s)
- Vivien Horváth
- Institute of Evolutionary Biology, CSIC, UPF, Barcelona, Spain
| | | | | | - Gabriel E Rech
- Institute of Evolutionary Biology, CSIC, UPF, Barcelona, Spain
| | - Llewellyn Green
- Institute of Evolutionary Biology, CSIC, UPF, Barcelona, Spain
| | - Eugenio Aprea
- Agriculture Food Environment Centre (C3A), University of Trento, San Michele All'adige (TN), Italy
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige (TN), Italy
| | - Mirco Rodeghiero
- Agriculture Food Environment Centre (C3A), University of Trento, San Michele All'adige (TN), Italy
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige (TN), Italy
| | - Gianfranco Anfora
- Agriculture Food Environment Centre (C3A), University of Trento, San Michele All'adige (TN), Italy
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige (TN), Italy
| | - Josefa González
- Institute of Evolutionary Biology, CSIC, UPF, Barcelona, Spain.
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5
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Önder BŞ, Aksoy CF. Seasonal variation in wing size and shape of Drosophila melanogaster reveals rapid adaptation to environmental changes. Sci Rep 2022; 12:14622. [PMID: 36028640 PMCID: PMC9418266 DOI: 10.1038/s41598-022-18891-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 08/22/2022] [Indexed: 11/10/2022] Open
Abstract
Populations in seasonal fluctuating environments receive multiple environmental cues and must deal with this heterogenic environment to survive and reproduce. An enlarged literature shows that this situation can be resolved through rapid adaptation in Drosophila melanogaster populations. Long-term monitoring of a population in its natural habitat and quantitative measurement of its responses to seasonal environmental changes are important for understanding the adaptive response of D. melanogaster to temporal variable selection. Here, we use inbred lines of a D. melanogaster population collected at monthly intervals between May to October over a temporal scale spanning three consecutive years to understand the variation in wing size and wing shape over these timepoints. The wing size and shape of this population changed significantly between months and a seasonal cycle of this traits is repeated for three years. Our results suggest that the effects of environmental variables that generated variation in body size between populations such as latitudinal clines, are a selective pressure in a different manner in terms of seasonal variation. Temperature related variable have a significant nonlinear relation to this fluctuating pattern in size and shape, whereas precipitation and humidity have a sex-specific effect which is more significant in males.
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Affiliation(s)
- Banu Şebnem Önder
- Genetic Variation and Adaptation Laboratory, Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey.
| | - Cansu Fidan Aksoy
- Genetic Variation and Adaptation Laboratory, Department of Biology, Faculty of Science, Hacettepe University, Ankara, Turkey
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6
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Abstract
The rediscovery of Mendel’s work showing that the heredity of phenotypes is controlled by discrete genes was followed by the reconciliation of Mendelian genetics with evolution by natural selection in the middle of the last century with the Modern Synthesis. In the past two decades, dramatic advances in genomic methods have facilitated the identification of the loci, genes, and even individual mutations that underlie phenotypic variants that are the putative targets of natural selection. Moreover, these methods have also changed how we can study adaptation by flipping the problem around, allowing us to first examine what loci show evidence of having been under selection, and then connecting these genetic variants to phenotypic variation. As a result, we now have an expanding list of actual genetic changes that underlie potentially adaptive phenotypic variation. Here, we synthesize how considering the effects of these adaptive loci in the context of cellular environments, genomes, organisms, and populations has provided new insights to the genetic architecture of adaptation.
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7
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Rech GE, Radío S, Guirao-Rico S, Aguilera L, Horvath V, Green L, Lindstadt H, Jamilloux V, Quesneville H, González J. Population-scale long-read sequencing uncovers transposable elements associated with gene expression variation and adaptive signatures in Drosophila. Nat Commun 2022; 13:1948. [PMID: 35413957 PMCID: PMC9005704 DOI: 10.1038/s41467-022-29518-8] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 03/15/2022] [Indexed: 12/16/2022] Open
Abstract
High quality reference genomes are crucial to understanding genome function, structure and evolution. The availability of reference genomes has allowed us to start inferring the role of genetic variation in biology, disease, and biodiversity conservation. However, analyses across organisms demonstrate that a single reference genome is not enough to capture the global genetic diversity present in populations. In this work, we generate 32 high-quality reference genomes for the well-known model species D. melanogaster and focus on the identification and analysis of transposable element variation as they are the most common type of structural variant. We show that integrating the genetic variation across natural populations from five climatic regions increases the number of detected insertions by 58%. Moreover, 26% to 57% of the insertions identified using long-reads were missed by short-reads methods. We also identify hundreds of transposable elements associated with gene expression variation and new TE variants likely to contribute to adaptive evolution in this species. Our results highlight the importance of incorporating the genetic variation present in natural populations to genomic studies, which is essential if we are to understand how genomes function and evolve. Even in well-studied species, there is still substantial natural genetic variation that has not been characterized. Here, the authors use long read sequencing to discover transposable elements in the Drosophila genome not detected by short read sequencing, and link them to gene expression.
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Affiliation(s)
- Gabriel E Rech
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Santiago Radío
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Sara Guirao-Rico
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Laura Aguilera
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Vivien Horvath
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Llewellyn Green
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Hannah Lindstadt
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | | | | | - Josefa González
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain.
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8
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Kapun M, Nunez JCB, Bogaerts-Márquez M, Murga-Moreno J, Paris M, Outten J, Coronado-Zamora M, Tern C, Rota-Stabelli O, Guerreiro MPG, Casillas S, Orengo DJ, Puerma E, Kankare M, Ometto L, Loeschcke V, Onder BS, Abbott JK, Schaeffer SW, Rajpurohit S, Behrman EL, Schou MF, Merritt TJS, Lazzaro BP, Glaser-Schmitt A, Argyridou E, Staubach F, Wang Y, Tauber E, Serga SV, Fabian DK, Dyer KA, Wheat CW, Parsch J, Grath S, Veselinovic MS, Stamenkovic-Radak M, Jelic M, Buendía-Ruíz AJ, Gómez-Julián MJ, Espinosa-Jimenez ML, Gallardo-Jiménez FD, Patenkovic A, Eric K, Tanaskovic M, Ullastres A, Guio L, Merenciano M, Guirao-Rico S, Horváth V, Obbard DJ, Pasyukova E, Alatortsev VE, Vieira CP, Vieira J, Torres JR, Kozeretska I, Maistrenko OM, Montchamp-Moreau C, Mukha DV, Machado HE, Lamb K, Paulo T, Yusuf L, Barbadilla A, Petrov D, Schmidt P, Gonzalez J, Flatt T, Bergland AO. Drosophila Evolution over Space and Time (DEST): A New Population Genomics Resource. Mol Biol Evol 2021; 38:5782-5805. [PMID: 34469576 PMCID: PMC8662648 DOI: 10.1093/molbev/msab259] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.
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Affiliation(s)
- Martin Kapun
- Department of Evolutionary Biology and Environmental Studies, University of
Zürich, Switzerland
- Department of Cell & Developmental Biology, Center of Anatomy and Cell
Biology, Medical University of Vienna, Vienna, Austria
| | - Joaquin C B Nunez
- Department of Biology, University of Virginia, Charlottesville,
VA, USA
| | | | - Jesús Murga-Moreno
- Department of Genetics and Microbiology, Universitat Autònoma de
Barcelona, Barcelona, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de
Barcelona, Barcelona, Spain
| | - Margot Paris
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | - Joseph Outten
- Department of Biology, University of Virginia, Charlottesville,
VA, USA
| | | | - Courtney Tern
- Department of Biology, University of Virginia, Charlottesville,
VA, USA
| | - Omar Rota-Stabelli
- Center Agriculture Food Environment, University of Trento, San Michele all'
Adige, Italy
| | | | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de
Barcelona, Barcelona, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de
Barcelona, Barcelona, Spain
| | - Dorcas J Orengo
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia,
Universitat de Barcelona, Barcelona, Spain
- Institut de Recerca de la Biodiversitat (IRBio), Universitat de
Barcelona, Barcelona, Spain
| | - Eva Puerma
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia,
Universitat de Barcelona, Barcelona, Spain
- Institut de Recerca de la Biodiversitat (IRBio), Universitat de
Barcelona, Barcelona, Spain
| | - Maaria Kankare
- Department of Biological and Environmental Science, University of
Jyväskylä, Jyväskylä, Finland
| | - Lino Ometto
- Department of Biology and Biotechnology, University of Pavia,
Pavia, Italy
| | | | - Banu S Onder
- Department of Biology, Hacettepe University, Ankara, Turkey
| | | | - Stephen W Schaeffer
- Department of Biology, The Pennsylvania State University,
University Park, PA, USA
| | - Subhash Rajpurohit
- Department of Biology, University of Pennsylvania, Philadelphia,
PA, USA
- Division of Biological and Life Sciences, School of Arts and Sciences,
Ahmedabad University, Ahmedabad, India
| | - Emily L Behrman
- Department of Biology, University of Pennsylvania, Philadelphia,
PA, USA
- Janelia Research Campus, Ashburn, VA, USA
| | - Mads F Schou
- Department of Biology, Aarhus University, Aarhus, Denmark
- Department of Biology, Lund University, Lund, Sweden
| | - Thomas J S Merritt
- Department of Chemistry & Biochemistry, Laurentian
University, Sudbury, ON, Canada
| | - Brian P Lazzaro
- Department of Entomology, Cornell University, Ithaca, NY,
USA
| | - Amanda Glaser-Schmitt
- Division of Evolutionary Biology, Faculty of Biology,
Ludwig-Maximilians-Universität, Munich, Germany
| | - Eliza Argyridou
- Division of Evolutionary Biology, Faculty of Biology,
Ludwig-Maximilians-Universität, Munich, Germany
| | - Fabian Staubach
- Department of Evolution and Ecology, University of Freiburg,
Freiburg, Germany
| | - Yun Wang
- Department of Evolution and Ecology, University of Freiburg,
Freiburg, Germany
| | - Eran Tauber
- Department of Evolutionary and Environmental Biology, Institute of Evolution,
University of Haifa, Haifa, Israel
| | - Svitlana V Serga
- Department of General and Medical Genetics, Taras Shevchenko National
University of Kyiv, Kyiv, Ukraine
- State Institution National Antarctic Scientific Center, Ministry of Education
and Science of Ukraine, Kyiv, Ukraine
| | - Daniel K Fabian
- Department of Genetics, University of Cambridge, Cambridge,
United Kingdom
| | - Kelly A Dyer
- Department of Genetics, University of Georgia, Athens, GA,
USA
| | | | - John Parsch
- Division of Evolutionary Biology, Faculty of Biology,
Ludwig-Maximilians-Universität, Munich, Germany
| | - Sonja Grath
- Division of Evolutionary Biology, Faculty of Biology,
Ludwig-Maximilians-Universität, Munich, Germany
| | | | | | - Mihailo Jelic
- Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | | | | | | | | | - Aleksandra Patenkovic
- Institute for Biological Research “Siniša Stanković”, National Institute of
Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Katarina Eric
- Institute for Biological Research “Siniša Stanković”, National Institute of
Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Marija Tanaskovic
- Institute for Biological Research “Siniša Stanković”, National Institute of
Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Anna Ullastres
- Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra,
Barcelona, Spain
| | - Lain Guio
- Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra,
Barcelona, Spain
| | - Miriam Merenciano
- Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra,
Barcelona, Spain
| | - Sara Guirao-Rico
- Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra,
Barcelona, Spain
| | - Vivien Horváth
- Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra,
Barcelona, Spain
| | - Darren J Obbard
- Institute of Evolutionary Biology, University of Edinburgh,
Edinburgh, United Kingdom
| | - Elena Pasyukova
- Institute of Molecular Genetics of the National Research Centre “Kurchatov
Institute”, Moscow, Russia
| | - Vladimir E Alatortsev
- Institute of Molecular Genetics of the National Research Centre “Kurchatov
Institute”, Moscow, Russia
| | - Cristina P Vieira
- Instituto de Biologia Molecular e Celular (IBMC), Porto, Portugal
- Instituto de Investigação e Inovação em Saúde, Universidade do
Porto, Porto, Portugal
| | - Jorge Vieira
- Instituto de Biologia Molecular e Celular (IBMC), Porto, Portugal
- Instituto de Investigação e Inovação em Saúde, Universidade do
Porto, Porto, Portugal
| | | | - Iryna Kozeretska
- Department of General and Medical Genetics, Taras Shevchenko National
University of Kyiv, Kyiv, Ukraine
- State Institution National Antarctic Scientific Center, Ministry of Education
and Science of Ukraine, Kyiv, Ukraine
| | - Oleksandr M Maistrenko
- Department of General and Medical Genetics, Taras Shevchenko National
University of Kyiv, Kyiv, Ukraine
- Structural and Computational Biology Unit, European Molecular Biology
Laboratory, Heidelberg, Germany
| | | | - Dmitry V Mukha
- Vavilov Institute of General Genetics, Russian Academy of
Sciences, Moscow, Russia
| | - Heather E Machado
- Department of Biology, Stanford University, Stanford, CA,
USA
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Keric Lamb
- Department of Biology, University of Virginia, Charlottesville,
VA, USA
| | - Tânia Paulo
- Departamento de Biologia Animal, Instituto Gulbenkian de Ciência,
Oeiras, Portugal
| | - Leeban Yusuf
- Center for Biological Diversity, University of St. Andrews, St
Andrews, United Kingdom
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de
Barcelona, Barcelona, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de
Barcelona, Barcelona, Spain
| | - Dmitri Petrov
- Department of Biology, Stanford University, Stanford, CA,
USA
| | - Paul Schmidt
- Department of Biology, The Pennsylvania State University,
University Park, PA, USA
| | - Josefa Gonzalez
- Institute of Evolutionary Biology, CSIC-Universitat Pompeu Fabra,
Barcelona, Spain
| | - Thomas Flatt
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | - Alan O Bergland
- Department of Biology, University of Virginia, Charlottesville,
VA, USA
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9
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Alshwairikh YA, Kroeze SL, Olsson J, Stephens‐Cardenas SA, Swain WL, Waits LP, Horn RL, Narum SR, Seaborn T. Influence of environmental conditions at spawning sites and migration routes on adaptive variation and population connectivity in Chinook salmon. Ecol Evol 2021; 11:16890-16908. [PMID: 34938480 PMCID: PMC8668735 DOI: 10.1002/ece3.8324] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 10/05/2021] [Accepted: 10/18/2021] [Indexed: 11/25/2022] Open
Abstract
Many species that undergo long breeding migrations, such as anadromous fishes, face highly heterogeneous environments along their migration corridors and at their spawning sites. These environmental challenges encountered at different life stages may act as strong selective pressures and drive local adaptation. However, the relative influence of environmental conditions along the migration corridor compared with the conditions at spawning sites on driving selection is still unknown. In this study, we performed genome-environment associations (GEA) to understand the relationship between landscape and environmental conditions driving selection in seven populations of the anadromous Chinook salmon (Oncorhynchus tshawytscha)-a species of important economic, social, cultural, and ecological value-in the Columbia River basin. We extracted environmental variables for the shared migration corridors and at distinct spawning sites for each population, and used a Pool-seq approach to perform whole genome resequencing. Bayesian and univariate GEA tests with migration-specific and spawning site-specific environmental variables indicated many more candidate SNPs associated with environmental conditions at the migration corridor compared with spawning sites. Specifically, temperature, precipitation, terrain roughness, and elevation variables of the migration corridor were the most significant drivers of environmental selection. Additional analyses of neutral loci revealed two distinct clusters representing populations from different geographic regions of the drainage that also exhibit differences in adult migration timing (summer vs. fall). Tests for genomic regions under selection revealed a strong peak on chromosome 28, corresponding to the GREB1L/ROCK1 region that has been identified previously in salmonids as a region associated with adult migration timing. Our results show that environmental variation experienced throughout migration corridors imposed a greater selective pressure on Chinook salmon than environmental conditions at spawning sites.
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Affiliation(s)
| | | | - Jenny Olsson
- Department of Ecology and Environmental ScienceUmeå UniversityUmeåSweden
| | | | - William L. Swain
- Wildlife Genomics and Disease LaboratoryProgram in EcologyDepartment of Veterinary SciencesUniversity of WyomingLaramieWyomingUSA
| | - Lisette P. Waits
- Department of Fish and Wildlife SciencesUniversity of IdahoMoscowIdahoUSA
| | | | - Shawn R. Narum
- Columbia River Inter‐Tribal Fish CommissionHagermanIdahoUSA
| | - Travis Seaborn
- Department of Fish and Wildlife SciencesUniversity of IdahoMoscowIdahoUSA
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Machado HE, Bergland AO, Taylor R, Tilk S, Behrman E, Dyer K, Fabian DK, Flatt T, González J, Karasov TL, Kim B, Kozeretska I, Lazzaro BP, Merritt TJS, Pool JE, O'Brien K, Rajpurohit S, Roy PR, Schaeffer SW, Serga S, Schmidt P, Petrov DA. Broad geographic sampling reveals the shared basis and environmental correlates of seasonal adaptation in Drosophila. eLife 2021; 10:e67577. [PMID: 34155971 PMCID: PMC8248982 DOI: 10.7554/elife.67577] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 06/21/2021] [Indexed: 11/16/2022] Open
Abstract
To advance our understanding of adaptation to temporally varying selection pressures, we identified signatures of seasonal adaptation occurring in parallel among Drosophila melanogaster populations. Specifically, we estimated allele frequencies genome-wide from flies sampled early and late in the growing season from 20 widely dispersed populations. We identified parallel seasonal allele frequency shifts across North America and Europe, demonstrating that seasonal adaptation is a general phenomenon of temperate fly populations. Seasonally fluctuating polymorphisms are enriched in large chromosomal inversions, and we find a broad concordance between seasonal and spatial allele frequency change. The direction of allele frequency change at seasonally variable polymorphisms can be predicted by weather conditions in the weeks prior to sampling, linking the environment and the genomic response to selection. Our results suggest that fluctuating selection is an important evolutionary force affecting patterns of genetic variation in Drosophila.
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Affiliation(s)
- Heather E Machado
- Department of Biology, Stanford UniversityStanfordUnited States
- Wellcome Sanger InstituteHinxtonUnited Kingdom
| | - Alan O Bergland
- Department of Biology, Stanford UniversityStanfordUnited States
- Department of Biology, University of VirginiaCharlottesvilleUnited States
| | - Ryan Taylor
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Susanne Tilk
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Emily Behrman
- Department of Biology, University of PennsylvaniaPhiladelphiaUnited States
| | - Kelly Dyer
- Department of Genetics, University of GeorgiaAthensUnited States
| | - Daniel K Fabian
- Institute of Population Genetics, Vetmeduni ViennaViennaAustria
- Centre for Pathogen Evolution, Department of Zoology, University of CambridgeCambridgeUnited Kingdom
| | - Thomas Flatt
- Institute of Population Genetics, Vetmeduni ViennaViennaAustria
- Department of Biology, University of FribourgFribourgSwitzerland
| | - Josefa González
- Institute of Evolutionary Biology, CSIC- Universitat Pompeu FabraBarcelonaSpain
| | - Talia L Karasov
- Department of Biology, University of UtahSalt Lake CityUnited States
| | - Bernard Kim
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Iryna Kozeretska
- Taras Shevchenko National University of KyivKyivUkraine
- National Antarctic Scientific Centre of Ukraine, Taras Shevchenko Blvd.KyivUkraine
| | - Brian P Lazzaro
- Department of Entomology, Cornell UniversityIthacaUnited States
| | - Thomas JS Merritt
- Department of Chemistry & Biochemistry, Laurentian UniversitySudburyCanada
| | - John E Pool
- Laboratory of Genetics, University of Wisconsin-MadisonMadisonUnited States
| | - Katherine O'Brien
- Department of Biology, University of PennsylvaniaPhiladelphiaUnited States
| | - Subhash Rajpurohit
- Department of Biology, University of PennsylvaniaPhiladelphiaUnited States
| | - Paula R Roy
- Department of Ecology and Evolutionary Biology, University of KansasLawrenceUnited States
| | - Stephen W Schaeffer
- Department of Biology, The Pennsylvania State UniversityUniversity ParkUnited States
| | - Svitlana Serga
- Taras Shevchenko National University of KyivKyivUkraine
- National Antarctic Scientific Centre of Ukraine, Taras Shevchenko Blvd.KyivUkraine
| | - Paul Schmidt
- Department of Biology, University of PennsylvaniaPhiladelphiaUnited States
| | - Dmitri A Petrov
- Department of Biology, Stanford UniversityStanfordUnited States
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