1
|
Korfmann K, Temple-Boyer M, Sellinger T, Tellier A. Determinants of rapid adaptation in species with large variance in offspring production. Mol Ecol 2024; 33:e16982. [PMID: 37199145 DOI: 10.1111/mec.16982] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/26/2023] [Accepted: 05/02/2023] [Indexed: 05/19/2023]
Abstract
The speed of population adaptation to changing biotic and abiotic environments is determined by the interaction between genetic drift, positive selection and linkage effects. Many marine species (fish, crustaceans), invertebrates and pathogens of humans and crops, exhibit sweepstakes reproduction characterized by the production of a very large amount of offspring (fecundity phase) from which only a small fraction may survive to the next generation (viability phase). Using stochastic simulations, we investigate whether the occurrence of sweepstakes reproduction affects the efficiency of a positively selected unlinked locus, and thus, the speed of adaptation since fecundity and/or viability have distinguishable consequences on mutation rate, probability and fixation time of advantageous alleles. We observe that the mean number of mutations at the next generation is always the function of the population size, but the variance increases with stronger sweepstakes reproduction when mutations occur in the parents. On the one hand, stronger sweepstakes reproduction magnifies the effect of genetic drift thus increasing the probability of fixation of neutral allele and decreasing that of selected alleles. On the other hand, the time to fixation of advantageous (as well as neutral) alleles is shortened by stronger sweepstakes reproduction. Importantly, fecundity and viability selection exhibit different probabilities and times to fixation of advantageous alleles under intermediate and weak sweepstakes reproduction. Finally, alleles under both strong fecundity and viability selection display a synergistic efficiency of selection. We conclude that measuring and modelling accurately fecundity and/or viability selection are crucial to predict the adaptive potential of species with sweepstakes reproduction.
Collapse
Affiliation(s)
- Kevin Korfmann
- Professorship for Population Genetics, Department of Life Science Systems, Technical University of Munich, Freising, Germany
| | - Marie Temple-Boyer
- Professorship for Population Genetics, Department of Life Science Systems, Technical University of Munich, Freising, Germany
| | - Thibaut Sellinger
- Professorship for Population Genetics, Department of Life Science Systems, Technical University of Munich, Freising, Germany
- Department of Environment and Biodiversity, Paris Lodron University of Salzburg, Salzburg, Austria
| | - Aurélien Tellier
- Professorship for Population Genetics, Department of Life Science Systems, Technical University of Munich, Freising, Germany
| |
Collapse
|
2
|
Eldon B, Stephan W. Sweepstakes reproduction facilitates rapid adaptation in highly fecund populations. Mol Ecol 2024; 33:e16903. [PMID: 36896794 DOI: 10.1111/mec.16903] [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: 05/23/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 03/11/2023]
Abstract
Adaptation enables natural populations to survive in a changing environment. Understanding the mechanics of adaptation is therefore crucial for learning about the evolution and ecology of natural populations. We focus on the impact of random sweepstakes on selection in highly fecund haploid and diploid populations partitioned into two genetic types, with one type conferring selective advantage. For the diploid populations, we incorporate various dominance mechanisms. We assume that the populations may experience recurrent bottlenecks. In random sweepstakes, the distribution of individual recruitment success is highly skewed, resulting in a huge variance in the number of offspring contributed by the individuals present in any given generation. Using computer simulations, we investigate the joint effects of random sweepstakes, recurrent bottlenecks and dominance mechanisms on selection. In our framework, bottlenecks allow random sweepstakes to have an effect on the time to fixation, and in diploid populations, the effect of random sweepstakes depends on the dominance mechanism. We describe selective sweepstakes that are approximated by recurrent sweeps of strongly beneficial allelic types arising by mutation. We demonstrate that both types of sweepstakes reproduction may facilitate rapid adaptation (as defined based on the average time to fixation of a type conferring selective advantage conditioned on fixation of the type). However, whether random sweepstakes cause rapid adaptation depends also on their interactions with bottlenecks and dominance mechanisms. Finally, we review a case study in which a model of recurrent sweeps is shown to essentially explain population genomic data from Atlantic cod.
Collapse
Affiliation(s)
- Bjarki Eldon
- Institute of Evolution and Biodiversity Science, Natural History Museum Berlin, Berlin, Germany
| | | |
Collapse
|
3
|
Fraimout A, Guillaume F, Li Z, Sillanpää MJ, Rastas P, Merilä J. Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing. Mol Ecol 2024; 33:e17299. [PMID: 38380534 DOI: 10.1111/mec.17299] [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: 07/28/2023] [Revised: 01/08/2024] [Accepted: 01/22/2024] [Indexed: 02/22/2024]
Abstract
Additive and dominance genetic variances underlying the expression of quantitative traits are important quantities for predicting short-term responses to selection, but they are notoriously challenging to estimate in most non-model wild populations. Specifically, large-sized or panmictic populations may be characterized by low variance in genetic relatedness among individuals which, in turn, can prevent accurate estimation of quantitative genetic parameters. We used estimates of genome-wide identity-by-descent (IBD) sharing from autosomal SNP loci to estimate quantitative genetic parameters for ecologically important traits in nine-spined sticklebacks (Pungitius pungitius) from a large, outbred population. Using empirical and simulated datasets, with varying sample sizes and pedigree complexity, we assessed the performance of different crossing schemes in estimating additive genetic variance and heritability for all traits. We found that low variance in relatedness characteristic of wild outbred populations with high migration rate can impair the estimation of quantitative genetic parameters and bias heritability estimates downwards. On the other hand, the use of a half-sib/full-sib design allowed precise estimation of genetic variance components and revealed significant additive variance and heritability for all measured traits, with negligible dominance contributions. Genome-partitioning and QTL mapping analyses revealed that most traits had a polygenic basis and were controlled by genes at multiple chromosomes. Furthermore, different QTL contributed to variation in the same traits in different populations suggesting heterogeneous underpinnings of parallel evolution at the phenotypic level. Our results provide important guidelines for future studies aimed at estimating adaptive potential in the wild, particularly for those conducted in outbred large-sized populations.
Collapse
Affiliation(s)
- Antoine Fraimout
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, FI-00014 University of Helsinki, Helsinki, Finland
| | - Frédéric Guillaume
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, FI-00014 University of Helsinki, Helsinki, Finland
| | - Zitong Li
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, FI-00014 University of Helsinki, Helsinki, Finland
| | - Mikko J Sillanpää
- Research Unit of Mathematical Sciences, FI-90014 University of Oulu, Oulu, Finland
| | - Pasi Rastas
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, FI-00014 University of Helsinki, Helsinki, Finland
- Institute of Biotechnology, FI-00014 University of Helsinki, Helsinki, Finland
| | - Juha Merilä
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, FI-00014 University of Helsinki, Helsinki, Finland
- Area of Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Hong Kong SAR, China
| |
Collapse
|
4
|
Ulmo‐Diaz G, Engman A, McLarney WO, Lasso Alcalá CA, Hendrickson D, Bezault E, Feunteun E, Prats‐Léon FL, Wiener J, Maxwell R, Mohammed RS, Kwak TJ, Benchetrit J, Bougas B, Babin C, Normandeau E, Djambazian HHV, Chen S, Reiling SJ, Ragoussis J, Bernatchez L. Panmixia in the American eel extends to its tropical range of distribution: Biological implications and policymaking challenges. Evol Appl 2023; 16:1872-1888. [PMID: 38143897 PMCID: PMC10739100 DOI: 10.1111/eva.13599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/25/2023] [Accepted: 09/06/2023] [Indexed: 12/26/2023] Open
Abstract
The American eel (Anguilla rostrata) has long been regarded as a panmictic fish and has been confirmed as such in the northern part of its range. In this paper, we tested for the first time whether panmixia extends to the tropical range of the species. To do so, we first assembled a reference genome (975 Mbp, 19 chromosomes) combining long (PacBio and Nanopore and short (Illumina paired-end) reads technologies to support both this study and future research. To test for population structure, we estimated genotype likelihoods from low-coverage whole-genome sequencing of 460 American eels, collected at 21 sampling sites (in seven geographic regions) ranging from Canada to Trinidad and Tobago. We estimated genetic distance between regions, performed ADMIXTURE-like clustering analysis and multivariate analysis, and found no evidence of population structure, thus confirming that panmixia extends to the tropical range of the species. In addition, two genomic regions with putative inversions were observed, both geographically widespread and present at similar frequencies in all regions. We discuss the implications of lack of genetic population structure for the species. Our results are key for the future genomic research in the American eel and the implementation of conservation measures throughout its geographic range. Additionally, our results can be applied to fisheries management and aquaculture of the species.
Collapse
Affiliation(s)
- Gabriela Ulmo‐Diaz
- Département de BiologieInstitut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecCanada
| | - Augustin Engman
- University of Tennessee Institute of Agriculture, School of Natural ResourcesKnoxvilleTennesseeUSA
| | | | | | - Dean Hendrickson
- Department of Integrative Biology and Biodiversity CollectionsUniversity of Texas at AustinAustinTexasUSA
| | - Etienne Bezault
- UMR 8067 BOREA, Biologie Organismes Écosystèmes Aquatiques (MNHN, CNRS, SU, IRD, UCN, UA)Université des AntillesPointe‐à‐PitreGuadeloupe
- Caribaea Initiative, Département de BiologieUniversité Des Antilles‐Campus de FouillolePointe‐à‐PitreGuadeloupeFrance
| | - Eric Feunteun
- UMR 7208 BOREABiologie Organismes Écosystèmes Aquatiques (MNHN, CNRS, SU,IRD, UCN, UA)Station Marine de DinardRennesFrance
- EPHE‐PSLCGEL (Centre de Géoécologie Littorale)DinardFrance
| | | | - Jean Wiener
- Fondation pour la Protection de la Biodiversité Marine (FoProBiM)CaracolHaiti
| | - Robert Maxwell
- Inland Fisheries SectionLouisiana Department of Wildlife and FisheriesLouisianaUSA
| | - Ryan S. Mohammed
- The University of the West Indies (UWI)St. AugustineTrinidad and Tobago
- Present address:
Department of Biological SciencesAuburn UniversityAuburnAlabamaUSA
| | - Thomas J. Kwak
- US Geological SurveyNorth Carolina Cooperative Fish and Wildlife Research UnitDepartment of Applied EcologyNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | | | - Bérénice Bougas
- Département de BiologieInstitut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecCanada
| | - Charles Babin
- Département de BiologieInstitut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecCanada
| | - Eric Normandeau
- Département de BiologieInstitut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecCanada
| | - Haig H. V. Djambazian
- McGIll Genome Centre, Department of Human GeneticsVictor Phillip Dahdaleh Institute of Genomic MedicineMcGill UniversityMontrealQuebecCanada
| | - Shu‐Huang Chen
- McGIll Genome Centre, Department of Human GeneticsVictor Phillip Dahdaleh Institute of Genomic MedicineMcGill UniversityMontrealQuebecCanada
| | - Sarah J. Reiling
- McGIll Genome Centre, Department of Human GeneticsVictor Phillip Dahdaleh Institute of Genomic MedicineMcGill UniversityMontrealQuebecCanada
| | - Jiannis Ragoussis
- McGIll Genome Centre, Department of Human GeneticsVictor Phillip Dahdaleh Institute of Genomic MedicineMcGill UniversityMontrealQuebecCanada
| | - Louis Bernatchez
- Département de BiologieInstitut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecCanada
| |
Collapse
|
5
|
Clark MS, Hoffman JI, Peck LS, Bargelloni L, Gande D, Havermans C, Meyer B, Patarnello T, Phillips T, Stoof-Leichsenring KR, Vendrami DLJ, Beck A, Collins G, Friedrich MW, Halanych KM, Masello JF, Nagel R, Norén K, Printzen C, Ruiz MB, Wohlrab S, Becker B, Dumack K, Ghaderiardakani F, Glaser K, Heesch S, Held C, John U, Karsten U, Kempf S, Lucassen M, Paijmans A, Schimani K, Wallberg A, Wunder LC, Mock T. Multi-omics for studying and understanding polar life. Nat Commun 2023; 14:7451. [PMID: 37978186 PMCID: PMC10656552 DOI: 10.1038/s41467-023-43209-y] [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: 04/24/2023] [Accepted: 11/02/2023] [Indexed: 11/19/2023] Open
Abstract
Polar ecosystems are experiencing amongst the most rapid rates of regional warming on Earth. Here, we discuss 'omics' approaches to investigate polar biodiversity, including the current state of the art, future perspectives and recommendations. We propose a community road map to generate and more fully exploit multi-omics data from polar organisms. These data are needed for the comprehensive evaluation of polar biodiversity and to reveal how life evolved and adapted to permanently cold environments with extreme seasonality. We argue that concerted action is required to mitigate the impact of warming on polar ecosystems via conservation efforts, to sustainably manage these unique habitats and their ecosystem services, and for the sustainable bioprospecting of novel genes and compounds for societal gain.
Collapse
Affiliation(s)
- M S Clark
- British Antarctic Survey, UKRI-NERC, High Cross, Madingley Road, Cambridge, CB3 0ET, UK.
| | - J I Hoffman
- British Antarctic Survey, UKRI-NERC, High Cross, Madingley Road, Cambridge, CB3 0ET, UK.
- Universität Bielefeld, VHF, Konsequenz 45, 33615, Bielefeld, Germany.
| | - L S Peck
- British Antarctic Survey, UKRI-NERC, High Cross, Madingley Road, Cambridge, CB3 0ET, UK.
| | - L Bargelloni
- Department of Comparative Biomedicine and Food Science, Università degli Studi di Padova, Viale dell'Università 16, I-35020, Legnaro, Italy
| | - D Gande
- Microbial Ecophysiology Group, Faculty of Biology/Chemistry & MARUM, University of Bremen, Leobener Straße 3, 28359, Bremen, Germany
| | - C Havermans
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
| | - B Meyer
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
- Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Oldenburg, Germany
- Helmholtz Institute for Functional Marine Biodiversity at the University of Oldenburg (HIFMB), 23129, Oldenburg, Germany
| | - T Patarnello
- Department of Comparative Biomedicine and Food Science, Università degli Studi di Padova, Viale dell'Università 16, I-35020, Legnaro, Italy
| | - T Phillips
- British Antarctic Survey, UKRI-NERC, High Cross, Madingley Road, Cambridge, CB3 0ET, UK
| | - K R Stoof-Leichsenring
- Alfred-Wegener-Institute Helmholtz Centre for Polar and Marine Research, 14473, Potsdam, Germany
| | - D L J Vendrami
- Universität Bielefeld, VHF, Konsequenz 45, 33615, Bielefeld, Germany
| | - A Beck
- Staatliche Naturwissenschaftliche Sammlungen Bayerns, Botanische Staatssammlung München (SNSB-BSM), Menzinger Str. 67, 80638, München, Germany
| | - G Collins
- Senckenberg Biodiversity and Climate Research Centre & Loewe-Centre for Translational Biodiversity Genomics, Senckenberganlage 25, 60325, Frankfurt am Main, Germany
- Manaaki Whenua-Landcare Research, 231 Morrin Road St Johns, Auckland, 1072, New Zealand
| | - M W Friedrich
- Microbial Ecophysiology Group, Faculty of Biology/Chemistry & MARUM, University of Bremen, Leobener Straße 3, 28359, Bremen, Germany
| | - K M Halanych
- Center for Marine Science, University of North Carolina, 5600 Marvin K. Moss Lane, Wilmington, NC, 28409, USA
| | - J F Masello
- Universität Bielefeld, VHF, Konsequenz 45, 33615, Bielefeld, Germany
- Justus-Liebig-Universität Gießen, Giessen, Germany
| | - R Nagel
- Universität Bielefeld, VHF, Konsequenz 45, 33615, Bielefeld, Germany
- School of Biology, University of St Andrews, St Andrews, Fife, KY16 9TH, UK
| | - K Norén
- Department of Zoology, Stockholm University, 106 91, Stockholm, Sweden
| | - C Printzen
- Senckenberg Biodiversity and Climate Research Centre & Loewe-Centre for Translational Biodiversity Genomics, Senckenberganlage 25, 60325, Frankfurt am Main, Germany
- Natural History Museum Frankfurt, Senckenberganlage 25, 60325, Frankfurt am Main, Germany
| | - M B Ruiz
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
- Universität Duisburg-Essen, Universitätstrasse 5, 45151, Essen, Germany
| | - S Wohlrab
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
- Helmholtz Institute for Functional Marine Biodiversity at the University of Oldenburg (HIFMB), 23129, Oldenburg, Germany
| | - B Becker
- Universität zu Köln, Institut für Pflanzenwissenschaften, Zülpicher Str. 47b, 60674, Köln, Germany
| | - K Dumack
- Universität zu Köln, Terrestrische Ökologie, Zülpicher Str. 47b, 60674, Köln, Germany
| | - F Ghaderiardakani
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Lessingstraße 8, 07743, Jena, Germany
| | - K Glaser
- Institute of Biological Sciences, Applied Ecology and Phycology, University of Rostock, Albert-Einstein-Straße 3, 18059, Rostock, Germany
| | - S Heesch
- Institute of Biological Sciences, Applied Ecology and Phycology, University of Rostock, Albert-Einstein-Straße 3, 18059, Rostock, Germany
| | - C Held
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
| | - U John
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
| | - U Karsten
- Institute of Biological Sciences, Applied Ecology and Phycology, University of Rostock, Albert-Einstein-Straße 3, 18059, Rostock, Germany
| | - S Kempf
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
| | - M Lucassen
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570, Bremerhaven, Germany
| | - A Paijmans
- Universität Bielefeld, VHF, Konsequenz 45, 33615, Bielefeld, Germany
| | - K Schimani
- Botanischer Garten und Botanisches Museum Berlin, Freie Universität Berlin, Königin-Luise-Straße 6-8, 14195, Berlin, Germany
| | - A Wallberg
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden
| | - L C Wunder
- Microbial Ecophysiology Group, Faculty of Biology/Chemistry & MARUM, University of Bremen, Leobener Straße 3, 28359, Bremen, Germany
| | - T Mock
- School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
| |
Collapse
|
6
|
Haye PA, Segovia NI. Shedding light on variation in reproductive success through studies of population genetic structure in a Southeast Pacific Coast mussel. Heredity (Edinb) 2023; 130:402-413. [PMID: 37024547 PMCID: PMC10238476 DOI: 10.1038/s41437-023-00615-8] [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: 11/13/2022] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 04/08/2023] Open
Abstract
Phylogeography often focuses on the spatial dimension of genetic diversity, rarely including the temporal dynamics occurring interannually among local populations, which can provide insight into past variations in reproductive success. Currently, there is an intense aquaculture industry of Mytilus spp. on the Southeast Pacific Coast which depends entirely on the spat released by natural populations forming a relevant and sensitive social-ecological system. Temporal and spatial spat variability from natural mussel beds could be related to interannual reproductive dynamics with variable reproductive success and recruitment, which leave genetic signatures. Temporal and spatial genetic structure was evaluated in six natural beds in the Southeast Pacific (from 39°25'S to 43°07'S) on the most abundant and widespread Mytilus lineage detected, Mytilus cf. chilensis, in 4 consecutive years. Analyses included data from >180 individuals per year, with a total of 751 (mitochondrial COI) and 747 (nuclear H1) individuals, respectively. Overall, both markers showed high haplotype diversity and low spatial and temporal genetic differentiation. Likely, the high dispersal capacity of Mytilus cf. chilensis maintains population homogeneity and prevents diversity erosion. The slight differences in genetic variance of COI were better explained by differences among sites (space), and conversely, the H1 genetic variance was better explained by interannual (temporal) comparisons, which could explain temporal variability in spat availability. This study highlights the important insights achieved with the evaluation of both temporal and spatial population genetic structures in marine species with high reproductive output, which can condition the success and sustainability of the relevant social-ecological system.
Collapse
Affiliation(s)
- Pilar A Haye
- Departamento de Biología Marina, Facultad de Ciencias del Mar, Universidad Católica del Norte, Coquimbo, Chile
- Instituto Milenio en Socio-Ecología Costera (SECOS), Santiago, Chile
| | - Nicolás I Segovia
- Departamento de Biología Marina, Facultad de Ciencias del Mar, Universidad Católica del Norte, Coquimbo, Chile.
- Instituto Milenio en Socio-Ecología Costera (SECOS), Santiago, Chile.
| |
Collapse
|
7
|
Freund F, Kerdoncuff E, Matuszewski S, Lapierre M, Hildebrandt M, Jensen JD, Ferretti L, Lambert A, Sackton TB, Achaz G. Interpreting the pervasive observation of U-shaped Site Frequency Spectra. PLoS Genet 2023; 19:e1010677. [PMID: 36952570 PMCID: PMC10072462 DOI: 10.1371/journal.pgen.1010677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 04/04/2023] [Accepted: 02/22/2023] [Indexed: 03/25/2023] Open
Abstract
The standard neutral model of molecular evolution has traditionally been used as the null model for population genomics. We gathered a collection of 45 genome-wide site frequency spectra from a diverse set of species, most of which display an excess of low and high frequency variants compared to the expectation of the standard neutral model, resulting in U-shaped spectra. We show that multiple merger coalescent models often provide a better fit to these observations than the standard Kingman coalescent. Hence, in many circumstances these under-utilized models may serve as the more appropriate reference for genomic analyses. We further discuss the underlying evolutionary processes that may result in the widespread U-shape of frequency spectra.
Collapse
Affiliation(s)
- Fabian Freund
- Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany
- Department of Genetics and Genome Biology, University of Leicester, Leicester, United Kingdom
| | - Elise Kerdoncuff
- Department of Genetics, University of California, Berkeley, California, United States of America
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
| | | | - Marguerite Lapierre
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
| | | | - Jeffrey D Jensen
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | - Luca Ferretti
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Amaury Lambert
- Institut de Biologie de l'ENS (IBENS), École Normale Supérieure, Paris, France
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
| | - Timothy B Sackton
- Éco-anthropologie, Muséum National d'Histoire Naturelle, Université Paris-Cité, Paris, France
| | - Guillaume Achaz
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
- SMILE group, Center for Interdisciplinary Research in Biology (CIRB), Collège de France, Paris, France
| |
Collapse
|
8
|
Árnason E, Koskela J, Halldórsdóttir K, Eldon B. Sweepstakes reproductive success via pervasive and recurrent selective sweeps. eLife 2023; 12:80781. [PMID: 36806325 PMCID: PMC9940914 DOI: 10.7554/elife.80781] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 12/28/2022] [Indexed: 02/22/2023] Open
Abstract
Highly fecund natural populations characterized by high early mortality abound, yet our knowledge about their recruitment dynamics is somewhat rudimentary. This knowledge gap has implications for our understanding of genetic variation, population connectivity, local adaptation, and the resilience of highly fecund populations. The concept of sweepstakes reproductive success, which posits a considerable variance and skew in individual reproductive output, is key to understanding the distribution of individual reproductive success. However, it still needs to be determined whether highly fecund organisms reproduce through sweepstakes and, if they do, the relative roles of neutral and selective sweepstakes. Here, we use coalescent-based statistical analysis of population genomic data to show that selective sweepstakes likely explain recruitment dynamics in the highly fecund Atlantic cod. We show that the Kingman coalescent (modelling no sweepstakes) and the Xi-Beta coalescent (modelling random sweepstakes), including complex demography and background selection, do not provide an adequate fit for the data. The Durrett-Schweinsberg coalescent, in which selective sweepstakes result from recurrent and pervasive selective sweeps of new mutations, offers greater explanatory power. Our results show that models of sweepstakes reproduction and multiple-merger coalescents are relevant and necessary for understanding genetic diversity in highly fecund natural populations. These findings have fundamental implications for understanding the recruitment variation of fish stocks and general evolutionary genomics of high-fecundity organisms.
Collapse
Affiliation(s)
- Einar Árnason
- Institute of Life- and environmental Sciences, University of IcelandReykjavikIceland,Department of Organismal and Evolutionary Biology, Harvard UniversityCambridgeUnited States
| | - Jere Koskela
- Department of Statistics, University of WarwickCoventryUnited Kingdom
| | - Katrín Halldórsdóttir
- Institute of Life- and environmental Sciences, University of IcelandReykjavikIceland
| | - Bjarki Eldon
- Leibniz Institute for Evolution and Biodiversity Science, Museum für NaturkundeBerlinGermany
| |
Collapse
|
9
|
Willis SC, Hollenbeck CM, Puritz JB, Portnoy DS. Genetic recruitment patterns are patchy and spatiotemporally unpredictable in a deep-water snapper (Lutjanus vivanus) sampled in fished and protected areas of western Puerto Rico. CONSERV GENET 2022. [DOI: 10.1007/s10592-021-01426-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
|
10
|
Baumdicker F, Bisschop G, Goldstein D, Gower G, Ragsdale AP, Tsambos G, Zhu S, Eldon B, Ellerman EC, Galloway JG, Gladstein AL, Gorjanc G, Guo B, Jeffery B, Kretzschmar WW, Lohse K, Matschiner M, Nelson D, Pope NS, Quinto-Cortés CD, Rodrigues MF, Saunack K, Sellinger T, Thornton K, van Kemenade H, Wohns AW, Wong Y, Gravel S, Kern AD, Koskela J, Ralph PL, Kelleher J. Efficient ancestry and mutation simulation with msprime 1.0. Genetics 2021; 220:6460344. [PMID: 34897427 PMCID: PMC9176297 DOI: 10.1093/genetics/iyab229] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/03/2021] [Indexed: 11/13/2022] Open
Abstract
Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.
Collapse
Affiliation(s)
- Franz Baumdicker
- Cluster of Excellence "Controlling Microbes to Fight Infections", Mathematical and Computational Population Genetics, University of Tübingen, 72076 Tübingen, Germany
| | - Gertjan Bisschop
- Institute of Evolutionary Biology,The University of Edinburgh, EH9 3FL, UK
| | - Daniel Goldstein
- Khoury College of Computer Sciences, Northeastern University, MA 02115, USA.,No affiliation
| | - Graham Gower
- Lundbeck GeoGenetics Centre, Globe Institute, University of Copenhagen, 1350 Copenhagen K, Denmark
| | - Aaron P Ragsdale
- Department of Integrative Biology, University of Wisconsin-Madison, WI 53706, USA
| | - Georgia Tsambos
- Melbourne Integrative Genomics, School of Mathematics and Statistics, University of Melbourne, Victoria, 3010, Australia
| | - Sha Zhu
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, OX3 7LF, UK
| | - Bjarki Eldon
- Leibniz Institute for Evolution and Biodiversity Science,Museum für Naturkunde Berlin, 10115, Germany
| | | | - Jared G Galloway
- Institute of Ecology and Evolution, Department of Biology, University of Oregon, OR 97403-5289, USA.,Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98102, USA
| | - Ariella L Gladstein
- Department of Genetics, University of North Carolina at Chapel Hill, NC 27599-7264, USA.,Embark Veterinary, Inc., Boston, MA 02111, USA
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, EH25 9RG, UK
| | - Bing Guo
- Institute for Genome Sciences,University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Ben Jeffery
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, OX3 7LF, UK
| | - Warren W Kretzschmar
- Center for Hematology and Regenerative Medicine, Karolinska Institute, 141 83 Huddinge, Sweden
| | - Konrad Lohse
- Institute of Evolutionary Biology,The University of Edinburgh, EH9 3FL, UK
| | | | - Dominic Nelson
- Department of Human Genetics, McGill University, Montréal, QC H3A 0C7, Canada
| | - Nathaniel S Pope
- Department of Entomology, Pennsylvania State University, PA 16802, USA
| | - Consuelo D Quinto-Cortés
- National Laboratory of Genomics for Biodiversity (LANGEBIO), Unit of Advanced Genomics, CINVESTAV, Irapuato, Mexico
| | - Murillo F Rodrigues
- Institute of Ecology and Evolution, Department of Biology, University of Oregon, OR 97403-5289, USA
| | - Kumar Saunack
- IIT Bombay, Powai, Mumbai 400 076, Maharashtra, India
| | - Thibaut Sellinger
- Professorship for Population Genetics, Department of Life Science Systems, Technical University of Munich, 85354 Freising, Germany
| | - Kevin Thornton
- Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
| | | | - Anthony W Wohns
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, OX3 7LF, UK.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yan Wong
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, OX3 7LF, UK
| | - Simon Gravel
- Department of Human Genetics, McGill University, Montréal, QC H3A 0C7, Canada
| | - Andrew D Kern
- Institute of Ecology and Evolution, Department of Biology, University of Oregon, OR 97403-5289, USA
| | - Jere Koskela
- Department of Statistics, University of Warwick, CV4 7AL, UK
| | - Peter L Ralph
- Institute of Ecology and Evolution, Department of Biology, University of Oregon, OR 97403-5289, USA.,Department of Mathematics, University of Oregon, OR 97403-5289 USA
| | - Jerome Kelleher
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, OX3 7LF, UK
| |
Collapse
|