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Chen G, Shi G, Dai Y, Zhao R, Wu Q. Graph-Based Pan-Genome Reveals the Pattern of Deleterious Mutations during the Domestication of Saccharomyces cerevisiae. J Fungi (Basel) 2024; 10:575. [PMID: 39194902 DOI: 10.3390/jof10080575] [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: 04/29/2024] [Revised: 08/08/2024] [Accepted: 08/10/2024] [Indexed: 08/29/2024] Open
Abstract
The "cost of domestication" hypothesis suggests that the domestication of wild species increases the number, frequency, and/or proportion of deleterious genetic variants, potentially reducing their fitness in the wild. While extensively studied in domesticated species, this phenomenon remains understudied in fungi. Here, we used Saccharomyces cerevisiae, the world's oldest domesticated fungus, as a model to investigate the genomic characteristics of deleterious variants arising from fungal domestication. Employing a graph-based pan-genome approach, we identified 1,297,761 single nucleotide polymorphisms (SNPs), 278,147 insertion/deletion events (indels; <30 bp), and 19,967 non-redundant structural variants (SVs; ≥30 bp) across 687 S. cerevisiae isolates. Comparing these variants with synonymous SNPs (sSNPs) as neutral controls, we found that the majority of the derived nonsynonymous SNPs (nSNPs), indels, and SVs were deleterious. Heterozygosity was positively correlated with the impact of deleterious SNPs, suggesting a role of genetic diversity in mitigating their effects. The domesticated isolates exhibited a higher additive burden of deleterious SNPs (dSNPs) than the wild isolates, but a lower burden of indels and SVs. Moreover, the domesticated S. cerevisiae showed reduced rates of adaptive evolution relative to the wild S. cerevisiae. In summary, deleterious variants tend to be heterozygous, which may mitigate their harmful effects, but they also constrain breeding potential. Addressing deleterious alleles and minimizing the genetic load are crucial considerations for future S. cerevisiae breeding efforts.
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Affiliation(s)
- Guotao Chen
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Guohui Shi
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yi Dai
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Ruilin Zhao
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qi Wu
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
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Di C, Lohmueller KE. Revisiting Dominance in Population Genetics. Genome Biol Evol 2024; 16:evae147. [PMID: 39114967 PMCID: PMC11306932 DOI: 10.1093/gbe/evae147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/24/2024] [Indexed: 08/11/2024] Open
Abstract
Dominance refers to the effect of a heterozygous genotype relative to that of the two homozygous genotypes. The degree of dominance of mutations for fitness can have a profound impact on how deleterious and beneficial mutations change in frequency over time as well as on the patterns of linked neutral genetic variation surrounding such selected alleles. Since dominance is such a fundamental concept, it has received immense attention throughout the history of population genetics. Early work from Fisher, Wright, and Haldane focused on understanding the conceptual basis for why dominance exists. More recent work has attempted to test these theories and conceptual models by estimating dominance effects of mutations. However, estimating dominance coefficients has been notoriously challenging and has only been done in a few species in a limited number of studies. In this review, we first describe some of the early theoretical and conceptual models for understanding the mechanisms for the existence of dominance. Second, we discuss several approaches used to estimate dominance coefficients and summarize estimates of dominance coefficients. We note trends that have been observed across species, types of mutations, and functional categories of genes. By comparing estimates of dominance coefficients for different types of genes, we test several hypotheses for the existence of dominance. Lastly, we discuss how dominance influences the dynamics of beneficial and deleterious mutations in populations and how the degree of dominance of deleterious mutations influences the impact of inbreeding on fitness.
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Affiliation(s)
- Chenlu Di
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
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3
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Götsch H, Bürger R. Polygenic dynamics underlying the response of quantitative traits to directional selection. Theor Popul Biol 2024; 158:21-59. [PMID: 38677378 DOI: 10.1016/j.tpb.2024.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/14/2024] [Accepted: 04/19/2024] [Indexed: 04/29/2024]
Abstract
We study the response of a quantitative trait to exponential directional selection in a finite haploid population, both at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per generation in the population follows a Poisson distribution (with mean Θ) and each mutation occurs at a new, previously monomorphic site. Mutation effects are beneficial and drawn from a distribution. Sites are unlinked and contribute additively to the trait. Assuming that selection is stronger than random genetic drift, we model the initial phase of the dynamics by a supercritical Galton-Watson process. This enables us to obtain time-dependent results. We show that the copy-number distribution of the mutant in generation n, conditioned on non-extinction until n, is described accurately by the deterministic increase from an initial distribution with mean 1. This distribution is related to the absolutely continuous part W+ of the random variable, typically denoted W, that characterizes the stochasticity accumulating during the mutant's sweep. A suitable transformation yields the approximate dynamics of the mutant frequency distribution in a Wright-Fisher population of size N. Our expression provides a very accurate approximation except when mutant frequencies are close to 1. On this basis, we derive explicitly the (approximate) time dependence of the expected mean and variance of the trait and of the expected number of segregating sites. Unexpectedly, we obtain highly accurate approximations for all times, even for the quasi-stationary phase when the expected per-generation response and the trait variance have equilibrated. The latter refine classical results. In addition, we find that Θ is the main determinant of the pattern of adaptation at the genetic level, i.e., whether the initial allele-frequency dynamics are best described by sweep-like patterns at few loci or small allele-frequency shifts at many. The number of segregating sites is an appropriate indicator for these patterns. The selection strength determines primarily the rate of adaptation. The accuracy of our results is tested by comprehensive simulations in a Wright-Fisher framework. We argue that our results apply to more complex forms of directional selection.
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Affiliation(s)
- Hannah Götsch
- Faculty of Mathematics, University of Vienna, 1090 Vienna, Austria; Vienna Graduate School of Population Genetics, Austria.
| | - Reinhard Bürger
- Faculty of Mathematics, University of Vienna, 1090 Vienna, Austria
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4
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Ostridge HJ, Fontsere C, Lizano E, Soto DC, Schmidt JM, Saxena V, Alvarez-Estape M, Barratt CD, Gratton P, Bocksberger G, Lester JD, Dieguez P, Agbor A, Angedakin S, Assumang AK, Bailey E, Barubiyo D, Bessone M, Brazzola G, Chancellor R, Cohen H, Coupland C, Danquah E, Deschner T, Dotras L, Dupain J, Egbe VE, Granjon AC, Head J, Hedwig D, Hermans V, Hernandez-Aguilar RA, Jeffery KJ, Jones S, Junker J, Kadam P, Kaiser M, Kalan AK, Kambere M, Kienast I, Kujirakwinja D, Langergraber KE, Lapuente J, Larson B, Laudisoit A, Lee KC, Llana M, Maretti G, Martín R, Meier A, Morgan D, Neil E, Nicholl S, Nixon S, Normand E, Orbell C, Ormsby LJ, Orume R, Pacheco L, Preece J, Regnaut S, Robbins MM, Rundus A, Sanz C, Sciaky L, Sommer V, Stewart FA, Tagg N, Tédonzong LR, van Schijndel J, Vendras E, Wessling EG, Willie J, Wittig RM, Yuh YG, Yurkiw K, Vigilant L, Piel A, Boesch C, Kühl HS, Dennis MY, Marques-Bonet T, Arandjelovic M, Andrés AM. Local genetic adaptation to habitat in wild chimpanzees. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.09.601734. [PMID: 39026872 PMCID: PMC11257515 DOI: 10.1101/2024.07.09.601734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
How populations adapt to their environment is a fundamental question in biology. Yet we know surprisingly little about this process, especially for endangered species such as non-human great apes. Chimpanzees, our closest living relatives, are particularly interesting because they inhabit diverse habitats, from rainforest to woodland-savannah. Whether genetic adaptation facilitates such habitat diversity remains unknown, despite having wide implications for evolutionary biology and conservation. Using 828 newly generated exomes from wild chimpanzees, we find evidence of fine-scale genetic adaptation to habitat. Notably, adaptation to malaria in forest chimpanzees is mediated by the same genes underlying adaptation to malaria in humans. This work demonstrates the power of non-invasive samples to reveal genetic adaptations in endangered populations and highlights the importance of adaptive genetic diversity for chimpanzees.
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Affiliation(s)
- Harrison J Ostridge
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Claudia Fontsere
- Center for Evolutionary Hologenomics, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Esther Lizano
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Daniela C Soto
- University of California, Davis, Genome Center, MIND Institute, Department of Biochemistry & Molecular Medicine, One Shields Drive, Davis, CA, 95616, USA
| | - Joshua M Schmidt
- Flinders Health and Medical Research Institute (FHMRI), Department of Ophthalmology, Flinders University Sturt Rd, Bedford Park South Australia 5042 Australia
| | - Vrishti Saxena
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Marina Alvarez-Estape
- University of California, Davis, Genome Center, MIND Institute, Department of Biochemistry & Molecular Medicine, One Shields Drive, Davis, CA, 95616, USA
| | - Christopher D Barratt
- Naturalis Biodiversity Center, Darwinweg 2, 2333 CR Leiden, the Netherlands
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Paolo Gratton
- University of Rome "Tor Vergata" Department of Biology Via Cracovia, 1, Roma, Italia
| | - Gaëlle Bocksberger
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Senckenberganlage, 60325 Frankfurt am Main, Germany
| | - Jack D Lester
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Paula Dieguez
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Anthony Agbor
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Samuel Angedakin
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Alfred Kwabena Assumang
- Department of Wildlife and Range Management, Faculty of Renewable Natural Resources, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Emma Bailey
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Donatienne Barubiyo
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Mattia Bessone
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- University of Konstanz, Centre for the Advanced Study of Collective Behaviour, Universitätsstraße 10, 78464, Konstanz, Germany
| | - Gregory Brazzola
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Rebecca Chancellor
- West Chester University, Depts of Anthropology & Sociology and Psychology, West Chester, PA, 19382 USA
| | - Heather Cohen
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Charlotte Coupland
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Emmanuel Danquah
- Department of Wildlife and Range Management, Faculty of Renewable Natural Resources, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Tobias Deschner
- Institute of Cognitive Science, University of Osnabrück, Artilleriestrasse 34, 49076 Osnabrück, Germany
| | - Laia Dotras
- Jane Goodall Institute Spain and Senegal, Dindefelo Biological Station, Dindefelo, Kedougou, Senegal
- Department of Social Psychology and Quantitative Psychology, Serra Hunter Programme, University of Barcelona, Barcelona, Spain
| | - Jef Dupain
- Antwerp Zoo Foundation, RZSA, Kon.Astridplein 26, 2018 Antwerp, Belgium
| | - Villard Ebot Egbe
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Anne-Céline Granjon
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Josephine Head
- The Biodiversity Consultancy, 3E Kings Parade, Cambridge, CB2 1SJ, UK
| | - Daniela Hedwig
- Elephant Listening Project, K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Road, Ithaca, NY 14850, USA
| | - Veerle Hermans
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
| | - R Adriana Hernandez-Aguilar
- Jane Goodall Institute Spain and Senegal, Dindefelo Biological Station, Dindefelo, Kedougou, Senegal
- Department of Social Psychology and Quantitative Psychology, Serra Hunter Programme, University of Barcelona, Barcelona, Spain
| | - Kathryn J Jeffery
- School of Natural Sciences, University of Stirling, UK
- Agence National des Parcs Nationaux (ANPN) Batterie 4, BP20379, Libreville, Gabon
| | - Sorrel Jones
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Jessica Junker
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Leipzig-Jena, Puschstrasse 4, 04103 Leipzig, Germany
| | - Parag Kadam
- Greater Mahale Ecosystem Research and Conservation Project
| | - Michael Kaiser
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Ammie K Kalan
- Department of Anthropology, University of Victoria, 3800 Finnerty Rd, Victoria, BC V8P 5C2, Canada
| | - Mbangi Kambere
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Ivonne Kienast
- Department of Natural Resources and the Environment, Cornell University, Ithaca, NY 14850, USA
- K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY 14850, USA
| | - Deo Kujirakwinja
- Wildlife Conservation Society (WCS), 2300 Southern Boulevard. Bronx, New York 10460, USA
| | - Kevin E Langergraber
- School of Human Evolution and Social Change, Institute of Human Origins, Arizona State University, 777 East University Drive, Tempe, AZ 85287 Arizona State University, PO Box 872402, Tempe, AZ 85287-2402 USA
- Institute of Human Origins, Arizona State University, 900 Cady Mall, Tempe, AZ 85287 Arizona State University, PO Box 872402, Tempe, AZ 85287-2402 USA
| | - Juan Lapuente
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | | | | | - Kevin C Lee
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- K. Lisa Yang Center for Conservation Bioacoustics, Cornell Lab of Ornithology, Cornell University, Ithaca, NY 14850, USA
| | - Manuel Llana
- Jane Goodall Institute Spain and Senegal, Dindefelo Biological Station, Dindefelo, Kedougou, Senegal
| | - Giovanna Maretti
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Rumen Martín
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Amelia Meier
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
- Hawai'i Insititute of Marine Biology, University of Hawai'i at Manoa, 46-007 Lilipuna Place, Kaneohe, HI, 96744, USA
| | - David Morgan
- Lester E. Fisher Center for the Study and Conservation of Apes, Lincoln Park Zoo, 2001 North Clark Street, Chicago, Illinois 60614 USA
| | - Emily Neil
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Sonia Nicholl
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Stuart Nixon
- North of England Zoological Society, Chester Zoo, Upton by Chester, CH2 1LH, United Kingdom
| | | | - Christopher Orbell
- Panthera, 8 W 40TH ST, New York, NY 10018, USA
- School of Natural Sciences, University of Stirling, UK
| | - Lucy Jayne Ormsby
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Robinson Orume
- Korup Rainforest Conservation Society, c/o Korup National Park, P.O. Box 36 Mundemba, South West Region, Cameroon
| | - Liliana Pacheco
- Save the Dogs and Other Animals, DJ 223 Km 3, 905200 Cernavoda CT, Romania
| | - Jodie Preece
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | | | - Martha M Robbins
- Max Planck Institute for Evolutionary Anthropology, Department of Primate Behavior and Evolution, Deutscher Platz 6, 04103 Leipzig
| | - Aaron Rundus
- West Chester University, Depts of Anthropology & Sociology and Psychology, West Chester, PA, 19382 USA
| | - Crickette Sanz
- Washington University in Saint Louis, Department of Anthropology, One Brookings Drive, St. Louis, MO 63130, USA
- Congo Program, Wildlife Conservation Society, 151 Avenue Charles de Gaulle, Brazzaville, Republic of Congo
| | - Lilah Sciaky
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Volker Sommer
- University College London, Department of Anthropology, 14 Taviton Street, London WC1H 0BW, UK
| | - Fiona A Stewart
- University College London, Department of Anthropology, 14 Taviton Street, London WC1H 0BW, UK
- Department of Human Origins, Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Nikki Tagg
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
- Born Free Foundation, Floor 2 Frazer House, 14 Carfax, Horsham, RH12 1ER, UK
| | - Luc Roscelin Tédonzong
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
| | - Joost van Schijndel
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Elleni Vendras
- Frankfurt Zoological Society, Bernhard-Grzimek-Allee 1, 60316 Frankfurt, Germany
| | - Erin G Wessling
- Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, Georg-August-University Göttingen,Göttingen, Germany
- German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
| | - Jacob Willie
- KMDA, Centre for Research and Conservation, Royal Zoological Society of Antwerp, Koningin Astridplein 20-26, B-2018 Antwerp, Belgium
- Terrestrial Ecology Unit (TEREC), Department of Biology, Ghent University (UGent), K.L. Ledeganckstraat 35, 9000 Ghent, Belgium
| | - Roman M Wittig
- Ape Social Mind Lab, Institute for Cognitive Sciences Marc Jeannerod, CNRS UMR 5229 CNRS, 67 bd Pinel, 69675 Bron CEDEX, France
- Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques, BP 1301, Abidjan 01, CI
| | - Yisa Ginath Yuh
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Kyle Yurkiw
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Linda Vigilant
- Max Planck Institute for Evolutionary Anthropology (MPI EVAN), Deutscher Platz 6, 04103 Leipzig
| | - Alex Piel
- University College London, Department of Anthropology, 14 Taviton Street, London WC1H 0BW, UK
| | | | - Hjalmar S Kühl
- Senckenberg Museum for Natural History Görlitz, Senckenberg - Member of the Leibniz Association Am Museum 1, 02826 Görlitz, Germany
- International Institute Zittau, Technische Universität Dresden, Markt 23, 02763 Zittau, Germany
| | - Megan Y Dennis
- University of California, Davis, Genome Center, MIND Institute, Department of Biochemistry & Molecular Medicine, One Shields Drive, Davis, CA, 95616, USA
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Passeig de Lluís Companys, 23, 08010, Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Edifici ICTA-ICP, c/ Columnes s/n, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Mimi Arandjelovic
- Max Planck Institute for Evolutionary Anthropology, Department of Primate Behavior and Evolution, Deutscher Platz 6, 04103 Leipzig
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103
| | - Aida M Andrés
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
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5
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Daigle A, Johri P. Hill-Robertson interference may bias the inference of fitness effects of new mutations in highly selfing species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.06.579142. [PMID: 38370745 PMCID: PMC10871249 DOI: 10.1101/2024.02.06.579142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The accurate estimation of the distribution of fitness effects (DFE) of new mutations is critical for population genetic inference but remains a challenging task. While various methods have been developed for DFE inference using the site frequency spectrum of putatively neutral and selected sites, their applicability in species with diverse life history traits and complex demographic scenarios is not well understood. Selfing is common among eukaryotic species and can lead to decreased effective recombination rates, increasing the effects of selection at linked sites, including interference between selected alleles. We employ forward simulations to investigate the limitations of current DFE estimation approaches in the presence of selfing and other model violations, such as linkage, departures from semidominance, population structure, and uneven sampling. We find that distortions of the site frequency spectrum due to Hill-Robertson interference in highly selfing populations lead to mis-inference of the deleterious DFE of new mutations. Specifically, while accounting for the decrease in the effective population size due to linked effects of selection allows an accurate estimation of selection coefficients in moderately selfing populations, this correction is unable to accurately estimate selection coefficients in highly selfing populations when interference between selected alleles is pervasive. In addition, the presence of cryptic population structure with low rates of migration and uneven sampling across subpopulations leads to the false inference of a deleterious DFE skewed towards effectively neutral/mildly deleterious mutations. Finally, the proportion of adaptive substitutions estimated at high rates of selfing is substantially overestimated. Our observations apply broadly to species and genomic regions with little/no recombination and where interference might be pervasive.
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6
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Gutiérrez-Valencia J, Zervakis PI, Postel Z, Fracassetti M, Losvik A, Mehrabi S, Bunikis I, Soler L, Hughes PW, Désamoré A, Laenen B, Abdelaziz M, Pettersson OV, Arroyo J, Slotte T. Genetic Causes and Genomic Consequences of Breakdown of Distyly in Linum trigynum. Mol Biol Evol 2024; 41:msae087. [PMID: 38709782 PMCID: PMC11114476 DOI: 10.1093/molbev/msae087] [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: 11/17/2023] [Revised: 03/22/2024] [Accepted: 04/29/2024] [Indexed: 05/08/2024] Open
Abstract
Distyly is an iconic floral polymorphism governed by a supergene, which promotes efficient pollen transfer and outcrossing through reciprocal differences in the position of sexual organs in flowers, often coupled with heteromorphic self-incompatibility. Distyly has evolved convergently in multiple flowering plant lineages, but has also broken down repeatedly, often resulting in homostylous, self-compatible populations with elevated rates of self-fertilization. Here, we aimed to study the genetic causes and genomic consequences of the shift to homostyly in Linum trigynum, which is closely related to distylous Linum tenue. Building on a high-quality genome assembly, we show that L. trigynum harbors a genomic region homologous to the dominant haplotype of the distyly supergene conferring long stamens and short styles in L. tenue, suggesting that loss of distyly first occurred in a short-styled individual. In contrast to homostylous Primula and Fagopyrum, L. trigynum harbors no fixed loss-of-function mutations in coding sequences of S-linked distyly candidate genes. Instead, floral gene expression analyses and controlled crosses suggest that mutations downregulating the S-linked LtWDR-44 candidate gene for male self-incompatibility and/or anther height could underlie homostyly and self-compatibility in L. trigynum. Population genomic analyses of 224 whole-genome sequences further demonstrate that L. trigynum is highly self-fertilizing, exhibits significantly lower genetic diversity genome-wide, and is experiencing relaxed purifying selection and less frequent positive selection on nonsynonymous mutations relative to L. tenue. Our analyses shed light on the loss of distyly in L. trigynum, and advance our understanding of a common evolutionary transition in flowering plants.
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Affiliation(s)
- Juanita Gutiérrez-Valencia
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Panagiotis-Ioannis Zervakis
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Zoé Postel
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Marco Fracassetti
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Aleksandra Losvik
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Sara Mehrabi
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Ignas Bunikis
- Department of Immunology, Genetics and Pathology, Uppsala Genome Center, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lucile Soler
- Department of Medical Biochemistry and Microbiology, Uppsala University, National Bioinformatics Infrastructure Sweden (NBIS), Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - P William Hughes
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Aurélie Désamoré
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Benjamin Laenen
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | | | - Olga Vinnere Pettersson
- Department of Immunology, Genetics and Pathology, Uppsala Genome Center, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Juan Arroyo
- Department of Plant Biology and Ecology, University of Seville, Seville, Spain
| | - Tanja Slotte
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
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7
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Sendrowski J, Bataillon T. fastDFE: Fast and Flexible Inference of the Distribution of Fitness Effects. Mol Biol Evol 2024; 41:msae070. [PMID: 38577958 PMCID: PMC11140822 DOI: 10.1093/molbev/msae070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/19/2024] [Accepted: 03/25/2024] [Indexed: 04/06/2024] Open
Abstract
Estimating the distribution of fitness effects (DFE) of new mutations is of fundamental importance in evolutionary biology, ecology, and conservation. However, existing methods for DFE estimation suffer from limitations, such as slow computation speed and limited scalability. To address these issues, we introduce fastDFE, a Python-based software package, offering fast, and flexible DFE inference from site-frequency spectrum (SFS) data. Apart from providing efficient joint inference of multiple DFEs that share parameters, it offers the feature of introducing genomic covariates that influence the DFEs and testing their significance. To further simplify usage, fastDFE is equipped with comprehensive VCF-to-SFS parsing utilities. These include options for site filtering and stratification, as well as site-degeneracy annotation and probabilistic ancestral-allele inference. fastDFE thereby covers the entire workflow of DFE inference from the moment of acquiring a raw VCF file. Despite its Python foundation, fastDFE incorporates a full R interface, including native R visualization capabilities. The package is comprehensively tested and documented at fastdfe.readthedocs.io.
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Affiliation(s)
- Janek Sendrowski
- Bioinformatics Research Center, Aarhus University, Aarhus, Denmark
| | - Thomas Bataillon
- Bioinformatics Research Center, Aarhus University, Aarhus, Denmark
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8
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Raas MWD, Dutheil JY. The rate of adaptive molecular evolution in wild and domesticated Saccharomyces cerevisiae populations. Mol Ecol 2024; 33:e16980. [PMID: 37157166 DOI: 10.1111/mec.16980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/22/2023] [Accepted: 04/26/2023] [Indexed: 05/10/2023]
Abstract
Through its fermentative capacities, Saccharomyces cerevisiae was central in the development of civilisation during the Neolithic period, and the yeast remains of importance in industry and biotechnology, giving rise to bona fide domesticated populations. Here, we conduct a population genomic study of domesticated and wild populations of S. cerevisiae. Using coalescent analyses, we report that the effective population size of yeast populations decreased since the divergence with S. paradoxus. We fitted models of distributions of fitness effects to infer the rate of adaptive (ω a ) and non-adaptive (ω na ) non-synonymous substitutions in protein-coding genes. We report an overall limited contribution of positive selection to S. cerevisiae protein evolution, albeit with higher rates of adaptive evolution in wild compared to domesticated populations. Our analyses revealed the signature of background selection and possibly Hill-Robertson interference, as recombination was found to be negatively correlated withω na and positively correlated withω a . However, the effect of recombination onω a was found to be labile, as it is only apparent after removing the impact of codon usage bias on the synonymous site frequency spectrum and disappears if we control for the correlation withω na , suggesting that it could be an artefact of the decreasing population size. Furthermore, the rate of adaptive non-synonymous substitutions is significantly correlated with the residue solvent exposure, a relation that cannot be explained by the population's demography. Together, our results provide a detailed characterisation of adaptive mutations in protein-coding genes across S. cerevisiae populations.
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Affiliation(s)
- Maximilian W D Raas
- Research Group Molecular Systems Evolution, Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Julien Y Dutheil
- Research Group Molecular Systems Evolution, Max Planck Institute for Evolutionary Biology, Plön, Germany
- Unité Mixte de Recherche 5554 Institut des Sciences de l'Evolution, CNRS, IRD, EPHE, Université de Montpellier, Montpellier, France
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9
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Hancock ZB, Cardinale DS. Back to the fundamentals: a reply to Basener and Sanford 2018. J Math Biol 2024; 88:54. [PMID: 38568223 DOI: 10.1007/s00285-024-02077-w] [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: 10/30/2023] [Revised: 11/24/2023] [Accepted: 03/05/2024] [Indexed: 04/05/2024]
Abstract
Fisher's fundamental theorem of natural selection has haunted theoretical population genetic literature since it was proposed in 1930, leading to numerous interpretations. Most of the confusion stemmed from Fisher's own obscure presentation. By the 1970s, a clearer view of Fisher's theorem had been achieved and it was found that, regardless of its utility or significance, it represents a general theorem of evolutionary biology. Basener and Sanford (J Math Biol 76:1589-1622, 2018) writing in JOMB, however, paint a different picture of the fundamental theorem as one hindered by its assumptions and incomplete due to its failure to explicitly incorporate mutational effects. They argue that Fisher saw his theorem as a "mathematical proof of Darwinian evolution". In this reply, we show that, contrary to Basener and Sanford, Fisher's theorem is a general theorem that applies to any evolving population, and that, far from their assertion that it needed to be expanded, the theorem already implicitly incorporates ancestor-descendant variation. We also show that their numerical simulations produce unrealistic results. Lastly, we argue that Basener and Sanford's motivations were in undermining not merely Fisher's theorem, but the concept of universal common descent itself.
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Affiliation(s)
- Zachary B Hancock
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48103, USA.
| | - Daniel Stern Cardinale
- Division of Life Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, 08854, USA
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10
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Murga-Moreno J, Casillas S, Barbadilla A, Uricchio L, Enard D. An efficient and robust ABC approach to infer the rate and strength of adaptation. G3 (BETHESDA, MD.) 2024; 14:jkae031. [PMID: 38365205 PMCID: PMC11090462 DOI: 10.1093/g3journal/jkae031] [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: 10/10/2023] [Revised: 10/10/2023] [Accepted: 01/29/2024] [Indexed: 02/18/2024]
Abstract
Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in nonmodel species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to nonmodel genomes. We apply ABC-MK to the human proteome and a set of known virus interacting proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.
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Affiliation(s)
- Jesús Murga-Moreno
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85719, USA
| | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | | | - David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85719, USA
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11
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Kyriazis CC, Lohmueller KE. Constraining models of dominance for nonsynonymous mutations in the human genome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.25.582010. [PMID: 38463985 PMCID: PMC10925099 DOI: 10.1101/2024.02.25.582010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h=0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.
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Affiliation(s)
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, USA
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, USA
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, USA
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12
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Soni V, Pfeifer SP, Jensen JD. The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects. Genome Biol Evol 2024; 16:evae004. [PMID: 38207127 PMCID: PMC10834165 DOI: 10.1093/gbe/evae004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/12/2023] [Accepted: 01/07/2024] [Indexed: 01/13/2024] Open
Abstract
Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA
| | - Susanne P Pfeifer
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA
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13
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Fu YB, Peterson GW, Horbach C. Deleterious and Adaptive Mutations in Plant Germplasm Conserved Ex Situ. Mol Biol Evol 2023; 40:msad238. [PMID: 37931158 PMCID: PMC10724023 DOI: 10.1093/molbev/msad238] [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: 08/23/2023] [Revised: 10/20/2023] [Accepted: 10/26/2023] [Indexed: 11/08/2023] Open
Abstract
Conserving more than 7 million plant germplasm accessions in 1,750 genebanks worldwide raises the hope of securing the food supply for humanity for future generations. However, there is a genetic cost for such long-term germplasm conservation, which has been largely unaccounted for before. We investigated the extent and variation of deleterious and adaptive mutations in 490 individual plants representing barley, wheat, oat, soybean, maize, rapa, and sunflower collections in a seed genebank using RNA-Seq technology. These collections were found to have a range of deleterious mutations detected from 125 (maize) to 83,695 (oat) with a mean of 13,537 and of the averaged sample-wise mutation burden per deleterious locus from 0.069 to 0.357 with a mean of 0.200. Soybean and sunflower collections showed that accessions acquired earlier had increased mutation burdens. The germplasm with more years of storage in several collections carried more deleterious and fewer adaptive mutations. The samples with more cycles of germplasm regeneration revealed fewer deleterious and more adaptive mutations. These findings are significant for understanding mutational dynamics and genetic cost in conserved germplasm and have implications for long-term germplasm management and conservation.
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Affiliation(s)
- Yong-Bi Fu
- Plant Gene Resources of Canada, Saskatoon Research and Development Centre, Agriculture and Agri-Food Canada, Saskatoon, SK S7N 0X2, Canada
| | - Gregory W Peterson
- Plant Gene Resources of Canada, Saskatoon Research and Development Centre, Agriculture and Agri-Food Canada, Saskatoon, SK S7N 0X2, Canada
| | - Carolee Horbach
- Plant Gene Resources of Canada, Saskatoon Research and Development Centre, Agriculture and Agri-Food Canada, Saskatoon, SK S7N 0X2, Canada
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14
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Kyriazis CC, Robinson JA, Lohmueller KE. Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations. Am Nat 2023; 202:737-752. [PMID: 38033186 PMCID: PMC10897732 DOI: 10.1086/726736] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).
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15
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Soni V, Pfeifer SP, Jensen JD. The effects of mutation and recombination rate heterogeneity on the inference of demography and the distribution of fitness effects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.11.566703. [PMID: 38014252 PMCID: PMC10680612 DOI: 10.1101/2023.11.11.566703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavour; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modelled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination prior to utilizing population genomic data to quantify the effects of genetic drift (i.e., as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modelled in downstream inference.
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Affiliation(s)
- Vivak Soni
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine
| | - Susanne P. Pfeifer
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine
| | - Jeffrey D. Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine
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16
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James J, Kastally C, Budde KB, González-Martínez SC, Milesi P, Pyhäjärvi T, Lascoux M. Between but Not Within-Species Variation in the Distribution of Fitness Effects. Mol Biol Evol 2023; 40:msad228. [PMID: 37832225 PMCID: PMC10630145 DOI: 10.1093/molbev/msad228] [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: 05/17/2023] [Revised: 09/04/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
New mutations provide the raw material for evolution and adaptation. The distribution of fitness effects (DFE) describes the spectrum of effects of new mutations that can occur along a genome, and is, therefore, of vital interest in evolutionary biology. Recent work has uncovered striking similarities in the DFE between closely related species, prompting us to ask whether there is variation in the DFE among populations of the same species, or among species with different degrees of divergence, that is whether there is variation in the DFE at different levels of evolution. Using exome capture data from six tree species sampled across Europe we characterized the DFE for multiple species, and for each species, multiple populations, and investigated the factors potentially influencing the DFE, such as demography, population divergence, and genetic background. We find statistical support for the presence of variation in the DFE at the species level, even among relatively closely related species. However, we find very little difference at the population level, suggesting that differences in the DFE are primarily driven by deep features of species biology, and those evolutionarily recent events, such as demographic changes and local adaptation, have little impact.
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Affiliation(s)
- Jennifer James
- Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
- Swedish Collegium of Advanced Study, Uppsala University, Uppsala, Sweden
| | - Chedly Kastally
- Department of Forest Sciences, University of Helsinki, Helsinki, Finland
- Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland
| | - Katharina B Budde
- Department of Forest Genetics and Forest Tree Breeding, Georg-August-University Goettingen, Goettingen, Germany
- Center of Biodiversity and Sustainable Land Use (CBL), University of Goettingen, Goettingen, Germany
| | - Santiago C González-Martínez
- National Research Institute for Agriculture, Food and the Environment (INRAE), University of Bordeaux, BIOGECO, Cestas, France
| | - Pascal Milesi
- Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
- Science for Life Laboratory (SciLifeLab), Uppsala University, Uppsala, Sweden
| | - Tanja Pyhäjärvi
- Department of Forest Sciences, University of Helsinki, Helsinki, Finland
- Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland
| | - Martin Lascoux
- Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
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17
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Savageau MA. Phenotype Design Space Provides a Mechanistic Framework Relating Molecular Parameters to Phenotype Diversity Available for Selection. J Mol Evol 2023; 91:687-710. [PMID: 37620617 PMCID: PMC10598110 DOI: 10.1007/s00239-023-10127-y] [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: 03/13/2023] [Accepted: 07/27/2023] [Indexed: 08/26/2023]
Abstract
Two long-standing challenges in theoretical population genetics and evolution are predicting the distribution of phenotype diversity generated by mutation and available for selection, and determining the interaction of mutation, selection and drift to characterize evolutionary equilibria and dynamics. More fundamental for enabling such predictions is the current inability to causally link genotype to phenotype. There are three major mechanistic mappings required for such a linking - genetic sequence to kinetic parameters of the molecular processes, kinetic parameters to biochemical system phenotypes, and biochemical phenotypes to organismal phenotypes. This article introduces a theoretical framework, the Phenotype Design Space (PDS) framework, for addressing these challenges by focusing on the mapping of kinetic parameters to biochemical system phenotypes. It provides a quantitative theory whose key features include (1) a mathematically rigorous definition of phenotype based on biochemical kinetics, (2) enumeration of the full phenotypic repertoire, and (3) functional characterization of each phenotype independent of its context-dependent selection or fitness contributions. This framework is built on Design Space methods that relate system phenotypes to genetically determined parameters and environmentally determined variables. It also has the potential to automate prediction of phenotype-specific mutation rate constants and equilibrium distributions of phenotype diversity in microbial populations undergoing steady-state exponential growth, which provides an ideal reference to which more realistic cases can be compared. Although the framework is quite general and flexible, the details will undoubtedly differ for different functions, organisms and contexts. Here a hypothetical case study involving a small molecular system, a primordial circadian clock, is used to introduce this framework and to illustrate its use in a particular case. The framework is built on fundamental biochemical kinetics. Thus, the foundation is based on linear algebra and reasonable physical assumptions, which provide numerous opportunities for experimental testing and further elaboration to deal with complex multicellular organisms that are currently beyond its scope. The discussion provides a comparison of results from the PDS framework with those from other approaches in theoretical population genetics.
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Affiliation(s)
- Michael A Savageau
- Department of Microbiology & Molecular Genetics, University of California, 228 Briggs, Davis, CA, 95616, USA.
- Department of Biomedical Engineering, University of California, One Shields Avenue, Davis, CA, 95616, USA.
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18
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Dussex N, Morales HE, Grossen C, Dalén L, van Oosterhout C. Purging and accumulation of genetic load in conservation. Trends Ecol Evol 2023; 38:961-969. [PMID: 37344276 DOI: 10.1016/j.tree.2023.05.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/11/2023] [Accepted: 05/12/2023] [Indexed: 06/23/2023]
Abstract
Our ability to assess the threat posed by the genetic load to small and declining populations has been greatly improved by advances in genome sequencing and computational approaches. Yet, considerable confusion remains around the definitions of the genetic load and its dynamics, and how they impact individual fitness and population viability. We illustrate how both selective purging and drift affect the distribution of deleterious mutations during population size decline and recovery. We show how this impacts the composition of the genetic load, and how this affects the extinction risk and recovery potential of populations. We propose a framework to examine load dynamics and advocate for the introduction of load estimates in the management of endangered populations.
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Affiliation(s)
- Nicolas Dussex
- Department of Natural History, NTNU University Museum, Erling Skakkes Gate 47A, 7012 Trondheim, Norway.
| | - Hernán E Morales
- Center for Evolutionary Hologenomics, Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Christine Grossen
- WSL Swiss Federal Research Institute, CH-8903 Birmensdorf, Switzerland
| | - Love Dalén
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, SE-106 91 Stockholm, Sweden
| | - Cock van Oosterhout
- School of Environmental Sciences, University of East Anglia, Norwich Research Park, NR4 7TJ Norwich, UK
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19
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Murga-Moreno J, Casillas S, Barbadilla A, Uricchio L, Enard D. An efficient and robust ABC approach to infer the rate and strength of adaptation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.29.555322. [PMID: 37693550 PMCID: PMC10491248 DOI: 10.1101/2023.08.29.555322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in non-model species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to non-model genomes. We apply ABC-MK to the human proteome and a set of known Virus Interacting Proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.
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Affiliation(s)
- Jesús Murga-Moreno
- University of Arizona Department of Ecology and Evolutionary Biology, Tucson, USA
| | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | | | - David Enard
- University of Arizona Department of Ecology and Evolutionary Biology, Tucson, USA
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20
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Charmouh AP, Bocedi G, Hartfield M. Inferring the distributions of fitness effects and proportions of strongly deleterious mutations. G3 (BETHESDA, MD.) 2023; 13:jkad140. [PMID: 37337692 PMCID: PMC10468728 DOI: 10.1093/g3journal/jkad140] [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: 11/18/2022] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 06/21/2023]
Abstract
The distribution of fitness effects is a key property in evolutionary genetics as it has implications for several evolutionary phenomena including the evolution of sex and mating systems, the rate of adaptive evolution, and the prevalence of deleterious mutations. Despite the distribution of fitness effects being extensively studied, the effects of strongly deleterious mutations are difficult to infer since such mutations are unlikely to be present in a sample of haplotypes, so genetic data may contain very little information about them. Recent work has attempted to correct for this issue by expanding the classic gamma-distributed model to explicitly account for strongly deleterious mutations. Here, we use simulations to investigate one such method, adding a parameter (plth) to capture the proportion of strongly deleterious mutations. We show that plth can improve the model fit when applied to individual species but underestimates the true proportion of strongly deleterious mutations. The parameter can also artificially maximize the likelihood when used to jointly infer a distribution of fitness effects from multiple species. As plth and related parameters are used in current inference algorithms, our results are relevant with respect to avoiding model artifacts and improving future tools for inferring the distribution of fitness effects.
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Affiliation(s)
- Anders P Charmouh
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
- Bioinformatics Research Centre Aarhus University, University City 81, building 1872, 3rd floor. DK-8000 Aarhus C, Denmark
| | - Greta Bocedi
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - Matthew Hartfield
- Institute of Ecology and Evolution, The University of Edinburgh, Edinburgh EH9 3FL, UK
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21
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Miller SE, Sheehan MJ. Sex differences in deleterious genetic variants in a haplodiploid social insect. Mol Ecol 2023; 32:4546-4556. [PMID: 37350360 PMCID: PMC10528523 DOI: 10.1111/mec.17057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 06/01/2023] [Accepted: 06/12/2023] [Indexed: 06/24/2023]
Abstract
Deleterious variants are selected against but can linger in populations at low frequencies for long periods of time, decreasing fitness and contributing to disease burden in humans and other species. Deleterious variants occur at low frequency but distinguishing deleterious variants from low-frequency neutral variation is challenging based on population genomics data alone. As a result, we have little sense of the number and identity of deleterious variants in wild populations. For haplodiploid species, it has been hypothesised that deleterious alleles will be directly exposed to selection in haploid males, but selection can be masked in diploid females when deleterious variants are recessive, resulting in more efficient purging of deleterious mutations in males. Therefore, comparisons of the differences between haploid and diploid genomes from the same population may be a useful method for inferring rare deleterious variants. This study provides the first formal test of this hypothesis. Using wild populations of Northern paper wasps (Polistes fuscatus), we find that males have fewer missense and nonsense variants per generation than females from the same population. Allele frequency differences are especially pronounced for rare missense and nonsense variants and these differences lead to a lower mutational load in males than females. Based on these data we infer that many highly deleterious mutations are segregating in the paper wasp population. Stronger selection against deleterious alleles in haploid males may have implications for adaptation in other haplodiploid insects and provides evidence that wild populations harbour abundant deleterious variants.
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Affiliation(s)
- Sara E. Miller
- Laboratory for Animal Social Evolution and Recognition, Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA
- Department of Biology, University of Missouri St. Louis, St. Louis, MO, USA
| | - Michael J. Sheehan
- Laboratory for Animal Social Evolution and Recognition, Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA
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22
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Wade EE, Kyriazis CC, Cavassim MIA, Lohmueller KE. Quantifying the fraction of new mutations that are recessive lethal. Evolution 2023; 77:1539-1549. [PMID: 37074880 PMCID: PMC10309970 DOI: 10.1093/evolut/qpad061] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 03/21/2023] [Accepted: 04/14/2023] [Indexed: 04/20/2023]
Abstract
The presence and impact of recessive lethal mutations have been widely documented in diploid outcrossing species. However, precise estimates of the proportion of new mutations that are recessive lethal remain limited. Here, we evaluate the performance of Fit∂a∂i, a commonly used method for inferring the distribution of fitness effects (DFE), in the presence of lethal mutations. Using simulations, we demonstrate that in both additive and recessive cases, inference of the deleterious nonlethal portion of the DFE is minimally affected by a small proportion (<10%) of lethal mutations. Additionally, we demonstrate that while Fit∂a∂i cannot estimate the fraction of recessive lethal mutations, Fit∂a∂i can accurately infer the fraction of additive lethal mutations. Finally, as an alternative approach to estimate the proportion of mutations that are recessive lethal, we employ models of mutation-selection-drift balance using existing genomic parameters and estimates of segregating recessive lethals for humans and Drosophila melanogaster. In both species, the segregating recessive lethal load can be explained by a very small fraction (<1%) of new nonsynonymous mutations being recessive lethal. Our results refute recent assertions of a much higher proportion of mutations being recessive lethal (4%-5%), while highlighting the need for additional information on the joint distribution of selection and dominance coefficients.
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Affiliation(s)
- Emma E Wade
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
- Department of Computer Science and Engineering, Mississippi State University, Starkville, MS, United States
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
| | - Maria Izabel A Cavassim
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
- Interdepartmental Program in Bioinformatics, University of California–Los Angeles, Los Angeles, CA, United States
- Department of Human Genetics, David Geffen School of Medicine, University of California–Los Angeles, Los Angeles, CA, United States
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23
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Kyriazis CC, Robinson JA, Nigenda-Morales SF, Beichman AC, Rojas-Bracho L, Robertson KM, Fontaine MC, Wayne RK, Taylor BL, Lohmueller KE, Morin PA. Models based on best-available information support a low inbreeding load and potential for recovery in the vaquita. Heredity (Edinb) 2023; 130:183-187. [PMID: 36941409 PMCID: PMC10076335 DOI: 10.1038/s41437-023-00608-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 03/01/2023] [Accepted: 03/02/2023] [Indexed: 03/23/2023] Open
Affiliation(s)
- Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Jacqueline A Robinson
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
| | - Sergio F Nigenda-Morales
- Advanced Genomics Unit, National Laboratory of Genomics for Biodiversity (Langebio), Center for Research and Advanced Studies (Cinvestav); Irapuato, Guanajuato, Mexico
| | - Annabel C Beichman
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Kelly M Robertson
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, La Jolla, CA, USA
| | - Michael C Fontaine
- MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France
- Centre de Recherche en Écologie et Évolution de la Santé (CREES), Montpellier, France
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, The Netherlands
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Barbara L Taylor
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, La Jolla, CA, USA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Phillip A Morin
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, La Jolla, CA, USA.
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24
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Barroso GV, Lohmueller KE. Inferring the mode and strength of ongoing selection. Genome Res 2023; 33:632-643. [PMID: 37055196 PMCID: PMC10234300 DOI: 10.1101/gr.276386.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 03/29/2023] [Indexed: 04/15/2023]
Abstract
Genome sequence data are no longer scarce. The UK Biobank alone comprises 200,000 individual genomes, with more on the way, leading the field of human genetics toward sequencing entire populations. Within the next decades, other model organisms will follow suit, especially domesticated species such as crops and livestock. Having sequences from most individuals in a population will present new challenges for using these data to improve health and agriculture in the pursuit of a sustainable future. Existing population genetic methods are designed to model hundreds of randomly sampled sequences but are not optimized for extracting the information contained in the larger and richer data sets that are beginning to emerge, with thousands of closely related individuals. Here we develop a new method called trio-based inference of dominance and selection (TIDES) that uses data from tens of thousands of family trios to make inferences about natural selection acting in a single generation. TIDES further improves on the state of the art by making no assumptions regarding demography, linkage, or dominance. We discuss how our method paves the way for studying natural selection from new angles.
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Affiliation(s)
- Gustavo V Barroso
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095-1606, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095-1606, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA
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25
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The use of evolutionary analyses to predict functionally relevant traits in filamentous plant pathogens. Curr Opin Microbiol 2023; 73:102244. [PMID: 36889024 DOI: 10.1016/j.mib.2022.102244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 10/27/2022] [Accepted: 11/03/2022] [Indexed: 03/08/2023]
Abstract
Identifying traits involved in plant-pathogen interactions is one of the major objectives in molecular plant pathology. Evolutionary analyses may assist in the identification of genes encoding traits that are involved in virulence and local adaptation, including adaptation to agricultural intervention strategies. In the past decades, the number of available genome sequences of fungal plant pathogens has rapidly increased, providing a rich source for the discovery of functionally important genes as well as inference of species histories. Positive selection in the form of diversifying or directional selection leaves particular signatures in genome alignments and can be identified with statistical genetics methods. This review summarises the concepts and approaches used in evolutionary genomics and lists major discoveries related to plant-pathogen adaptative evolution. We underline the significant contribution of evolutionary genomics in discovering virulence-related traits and the study of plant-pathogen ecology and adaptive evolution.
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26
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Robinson J, Kyriazis CC, Yuan SC, Lohmueller KE. Deleterious Variation in Natural Populations and Implications for Conservation Genetics. Annu Rev Anim Biosci 2023; 11:93-114. [PMID: 36332644 PMCID: PMC9933137 DOI: 10.1146/annurev-animal-080522-093311] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Deleterious mutations decrease reproductive fitness and are ubiquitous in genomes. Given that many organisms face ongoing threats of extinction, there is interest in elucidating the impact of deleterious variation on extinction risk and optimizing management strategies accounting for such mutations. Quantifying deleterious variation and understanding the effects of population history on deleterious variation are complex endeavors because we do not know the strength of selection acting on each mutation. Further, the effect of demographic history on deleterious mutations depends on the strength of selection against the mutation and the degree of dominance. Here we clarify how deleterious variation can be quantified and studied in natural populations. We then discuss how different demographic factors, such as small population size, nonequilibrium population size changes, inbreeding, and gene flow, affect deleterious variation. Lastly, we provide guidance on studying deleterious variation in nonmodel populations of conservation concern.
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Affiliation(s)
- Jacqueline Robinson
- Institute for Human Genetics, University of California, San Francisco, California, USA;
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , ,
| | - Stella C Yuan
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , ,
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , , .,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, USA
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27
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Yi H, Wang J, Wang J, Rausher M, Kang M. Genomic insights into inter- and intraspecific mating system shifts in Primulina. Mol Ecol 2022; 31:5699-5713. [PMID: 36178058 DOI: 10.1111/mec.16706] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 08/17/2022] [Accepted: 09/21/2022] [Indexed: 01/13/2023]
Abstract
The mating system shift from outcrossing to selfing is one of the most frequent evolutionary trends in flowering plants. However, the genomic consequences of this shift remain poorly understood. Specifically, the relative importance of the demographic and genetic processes causing changes in genetic variation and selection efficacy associated with the evolution of selfing is unclear. Here we sequenced the genomes of two Primulina species with contrasting mating systems: P. eburnea (outcrossing) versus P. tabacum (outcrossing, mixed-mating and selfing populations). Whole-genome resequencing data were used to investigate the genomic consequences of mating system shifts within and between species. We found that highly selfing populations of P. tabacum display loss of genetic diversity, increased deleterious mutations, higher genomic burden and fewer adaptive substitutions. However, compared with outcrossing populations, mixed-mating populations did not display loss of genetic diversity and accumulation of genetic load. We find no evidence of population bottlenecks associated with the shift to selfing, which suggests that the genetic effects of selfing on Ne and possibly linked selection, rather than demographic history, are the primary drivers of diversity reduction in highly selfing populations. Our results highlight the importance of distinguishing the relative contribution of mating system and demography on the genomic consequences associated with mating system evolution in plants.
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Affiliation(s)
- Huiqin Yi
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Jieyu Wang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Jing Wang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Mark Rausher
- Department of Biology, Duke University, Durham, North Carolina, USA
| | - Ming Kang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China.,Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Guangzhou, China
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28
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Murga-Moreno J, Coronado-Zamora M, Casillas S, Barbadilla A. impMKT: the imputed McDonald and Kreitman test, a straightforward correction that significantly increases the evidence of positive selection of the McDonald and Kreitman test at the gene level. G3 GENES|GENOMES|GENETICS 2022; 12:6670623. [PMID: 35976111 PMCID: PMC9526038 DOI: 10.1093/g3journal/jkac206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 07/28/2022] [Indexed: 11/14/2022]
Abstract
The McDonald and Kreitman test is one of the most powerful and widely used methods to detect and quantify recurrent natural selection in DNA sequence data. One of its main limitations is the underestimation of positive selection due to the presence of slightly deleterious variants segregating at low frequencies. Although several approaches have been developed to overcome this limitation, most of them work on gene pooled analyses. Here, we present the imputed McDonald and Kreitman test (impMKT), a new straightforward approach for the detection of positive selection and other selection components of the distribution of fitness effects at the gene level. We compare imputed McDonald and Kreitman test with other widely used McDonald and Kreitman test approaches considering both simulated and empirical data. By applying imputed McDonald and Kreitman test to humans and Drosophila data at the gene level, we substantially increase the statistical evidence of positive selection with respect to previous approaches (e.g. by 50% and 157% compared with the McDonald and Kreitman test in Drosophila and humans, respectively). Finally, we review the minimum number of genes required to obtain a reliable estimation of the proportion of adaptive substitution (α) in gene pooled analyses by using the imputed McDonald and Kreitman test compared with other McDonald and Kreitman test implementations. Because of its simplicity and increased power to detect recurrent positive selection on genes, we propose the imputed McDonald and Kreitman test as the first straightforward approach for testing specific evolutionary hypotheses at the gene level. The software implementation and population genomics data are available at the web-server imkt.uab.cat.
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Affiliation(s)
- Jesús Murga-Moreno
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
| | - Marta Coronado-Zamora
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
| | - Sònia Casillas
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
| | - Antonio Barbadilla
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona , Barcelona 08193, Spain
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29
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Mavreas K, Gossmann TI, Waxman D. Loss and fixation of strongly favoured new variants: Understanding and extending Haldane's result via the Wright-Fisher model. Biosystems 2022; 221:104759. [PMID: 35998748 DOI: 10.1016/j.biosystems.2022.104759] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 08/04/2022] [Accepted: 08/05/2022] [Indexed: 11/02/2022]
Abstract
The implications of Haldane's analysis for the fixation of beneficial alleles lies at the heart of much of 'population genetic thinking' and underlies many approaches that have been tailored to the detection of positive selection. Within the framework of a branching process, Haldane gave an approximation for the probability that fixation ultimately occurs when the selective advantage of a beneficial allele is small (≪1). Here, we make no use of branching processes. Rather, we work solely within a finite-population Wright-Fisher framework. We use this framework to analyse where Haldane's result applies, and extend Haldane's analysis. In particular, we present results for: (i) the domain of applicability of Haldane's analysis; (ii) the probability that loss occurs up to a given time; (iii) the probabilities that loss and fixation ultimately occur; (iv) an analytic approximation associated with the probability of loss and fixation ultimately occurring; (v) quantification of the crossover from weak to strong selection; (vi) determination of the number of invasive alleles that have a significant probability (>0.95) of invading a novel population. We note that the results obtained for (ii), (iii) and (iv) hold for an arbitrary initial number of mutations, and for selection that can be arbitrarily strong. Our results have fundamental implications for population and conservation genetics, and open up new avenues to identify traces of historically beneficial alleles through comparative genomics.
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Affiliation(s)
- K Mavreas
- Centre for Computational Systems Biology, ISTBI, Fudan University, 220 Handan Road, Shanghai 200433, China
| | - T I Gossmann
- Department of Evolutionary, Genetics (Animal Behaviour), Bielefeld University, Morgenbreede 45, D-33615 Bielefeld, Germany
| | - D Waxman
- Centre for Computational Systems Biology, ISTBI, Fudan University, 220 Handan Road, Shanghai 200433, China.
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30
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Johri P, Eyre-Walker A, Gutenkunst RN, Lohmueller KE, Jensen JD. On the prospect of achieving accurate joint estimation of selection with population history. Genome Biol Evol 2022; 14:evac088. [PMID: 35675379 PMCID: PMC9254643 DOI: 10.1093/gbe/evac088] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/02/2022] [Indexed: 11/15/2022] Open
Abstract
As both natural selection and population history can affect genome-wide patterns of variation, disentangling the contributions of each has remained as a major challenge in population genetics. We here discuss historical and recent progress towards this goal-highlighting theoretical and computational challenges that remain to be addressed, as well as inherent difficulties in dealing with model complexity and model violations-and offer thoughts on potentially fruitful next steps.
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Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | | | - Ryan N Gutenkunst
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
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31
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Böndel KB, Samuels T, Craig RJ, Ness RW, Colegrave N, Keightley PD. The distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii inferred using frequency changes under experimental evolution. PLoS Genet 2022; 18:e1009840. [PMID: 35704655 PMCID: PMC9239454 DOI: 10.1371/journal.pgen.1009840] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 06/28/2022] [Accepted: 04/13/2022] [Indexed: 12/23/2022] Open
Abstract
The distribution of fitness effects (DFE) for new mutations is fundamental for many aspects of population and quantitative genetics. In this study, we have inferred the DFE in the single-celled alga Chlamydomonas reinhardtii by estimating changes in the frequencies of 254 spontaneous mutations under experimental evolution and equating the frequency changes of linked mutations with their selection coefficients. We generated seven populations of recombinant haplotypes by crossing seven independently derived mutation accumulation lines carrying an average of 36 mutations in the haploid state to a mutation-free strain of the same genotype. We then allowed the populations to evolve under natural selection in the laboratory by serial transfer in liquid culture. We observed substantial and repeatable changes in the frequencies of many groups of linked mutations, and, surprisingly, as many mutations were observed to increase as decrease in frequency. Mutation frequencies were highly repeatable among replicates, suggesting that selection was the cause of the observed allele frequency changes. We developed a Bayesian Monte Carlo Markov Chain method to infer the DFE. This computes the likelihood of the observed distribution of changes of frequency, and obtains the posterior distribution of the selective effects of individual mutations, while assuming a two-sided gamma distribution of effects. We infer that the DFE is a highly leptokurtic distribution, and that approximately equal proportions of mutations have positive and negative effects on fitness. This result is consistent with what we have observed in previous work on a different C. reinhardtii strain, and suggests that a high fraction of new spontaneously arisen mutations are advantageous in a simple laboratory environment.
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Affiliation(s)
- Katharina B. Böndel
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Toby Samuels
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Rory J. Craig
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Rob W. Ness
- Department of Biology, William G. Davis Building, University of Toronto, Mississauga, Canada
| | - Nick Colegrave
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Peter D. Keightley
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail:
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32
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Fulgione A, Neto C, Elfarargi AF, Tergemina E, Ansari S, Göktay M, Dinis H, Döring N, Flood PJ, Rodriguez-Pacheco S, Walden N, Koch MA, Roux F, Hermisson J, Hancock AM. Parallel reduction in flowering time from de novo mutations enable evolutionary rescue in colonizing lineages. Nat Commun 2022; 13:1461. [PMID: 35304466 PMCID: PMC8933414 DOI: 10.1038/s41467-022-28800-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 02/07/2022] [Indexed: 12/11/2022] Open
Abstract
Understanding how populations adapt to abrupt environmental change is necessary to predict responses to future challenges, but identifying specific adaptive variants, quantifying their responses to selection and reconstructing their detailed histories is challenging in natural populations. Here, we use Arabidopsis from the Cape Verde Islands as a model to investigate the mechanisms of adaptation after a sudden shift to a more arid climate. We find genome-wide evidence of adaptation after a multivariate change in selection pressures. In particular, time to flowering is reduced in parallel across islands, substantially increasing fitness. This change is mediated by convergent de novo loss of function of two core flowering time genes: FRI on one island and FLC on the other. Evolutionary reconstructions reveal a case where expansion of the new populations coincided with the emergence and proliferation of these variants, consistent with models of rapid adaptation and evolutionary rescue. Detailing how populations adapted to environmental change is needed to predict future responses, but identifying adaptive variants and detailing their fitness effects is rare. Here, the authors show that parallel loss of FRI and FLC function reduces time to flowering and drives adaptation in a drought prone environment.
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Affiliation(s)
- Andrea Fulgione
- Max Planck Institute for Plant Breeding Research, Cologne, Germany.,Mathematics and Bioscience, Department of Mathematics and Max F. Perutz Labs, University of Vienna, Vienna, Austria.,Vienna Graduate School for Population Genetics, Vienna, Austria
| | - Célia Neto
- Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | | | | | - Shifa Ansari
- Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | - Mehmet Göktay
- Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | - Herculano Dinis
- Parque Natural do Fogo, Direção Nacional do Ambiente, Praia, Santiago, Cabo Verde.,Associação Projecto Vitó, São Filipe, Fogo, Cabo Verde
| | - Nina Döring
- Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | - Pádraic J Flood
- Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | | | - Nora Walden
- Centre for Organismal Studies (COS) Heidelberg, Biodiversity and Plant Systematics, Heidelberg University, Heidelberg, Germany.,Biosystematics, Wageningen University, Wageningen, The Netherlands
| | - Marcus A Koch
- Centre for Organismal Studies (COS) Heidelberg, Biodiversity and Plant Systematics, Heidelberg University, Heidelberg, Germany
| | - Fabrice Roux
- LIPME, Université de Toulouse, INRAE, CNRS, Castanet-Tolosan, France
| | - Joachim Hermisson
- Mathematics and Bioscience, Department of Mathematics and Max F. Perutz Labs, University of Vienna, Vienna, Austria
| | - Angela M Hancock
- Max Planck Institute for Plant Breeding Research, Cologne, Germany. .,Mathematics and Bioscience, Department of Mathematics and Max F. Perutz Labs, University of Vienna, Vienna, Austria.
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33
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Fields PD, McTaggart S, Reisser CMO, Haag C, Palmer WH, Little TJ, Ebert D, Obbard DJ. Population-genomic analysis identifies a low rate of global adaptive fixation in the proteins of the cyclical parthenogen Daphnia magna. Mol Biol Evol 2022; 39:6542319. [PMID: 35244177 PMCID: PMC8963301 DOI: 10.1093/molbev/msac048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Daphnia are well-established ecological and evolutionary models, and the interaction between D. magna and its microparasites is widely considered a paragon of the host-parasite coevolutionary process. Like other well-studied arthropods such as Drosophila melanogaster and Anopheles gambiae, D. magna is a small, widespread, and abundant species that is therefore expected to display a large long-term population size and high rates of adaptive protein evolution. However, unlike these other species, D. magna is cyclically asexual and lives in a highly structured environment (ponds and lakes) with moderate levels of dispersal, both of which are predicted to impact upon long-term effective population size and adaptive protein evolution. To investigate patterns of adaptive protein fixation, we produced the complete coding genomes of 36 D. magna clones sampled from across the European range (Western Palaearctic), along with draft sequences for the close relatives D. similis and D. lumholtzi, used as outgroups. We analyzed genome-wide patterns of adaptive fixation, with a particular focus on genes that have an a priori expectation of high rates, such as those likely to mediate immune responses, RNA interference against viruses and transposable elements, and those with a strongly male-biased expression pattern. We find that, as expected, D. magna displays high levels of diversity and that this is highly structured among populations. However, compared with Drosophila, we find that D. magna proteins appear to have a high proportion of weakly deleterious variants and do not show evidence of pervasive adaptive fixation across its entire range. This is true of the genome as a whole, and also of putative ‘arms race’ genes that often show elevated levels of adaptive substitution in other species. In addition to the likely impact of extensive, and previously documented, local adaptation, we speculate that these findings may reflect reduced efficacy of selection associated with cyclical asexual reproduction.
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Affiliation(s)
- Peter D Fields
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, Basel, CH-4051, Switzerland
| | - Seanna McTaggart
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
| | - Céline M O Reisser
- Centre d'Ecologie Fonctionnelle et Evolutive CEFE UMR 5175, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, campus CNRS, 1919, route de Mende, 34293 Montpellier Cedex 5, France.,MARBEC, Univ Montpellier, CNRS, IFREMER, IRD, Montpellier, France
| | - Christoph Haag
- Centre d'Ecologie Fonctionnelle et Evolutive CEFE UMR 5175, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, campus CNRS, 1919, route de Mende, 34293 Montpellier Cedex 5, France
| | - William H Palmer
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
| | - Tom J Little
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
| | - Dieter Ebert
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, Basel, CH-4051, Switzerland
| | - Darren J Obbard
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
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34
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Abstract
How do mutational biases influence the process of adaptation? A common assumption is that selection alone determines the course of adaptation from abundant preexisting variation. Yet, theoretical work shows broad conditions under which the mutation rate to a given type of variant strongly influences its probability of contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation. Using large datasets from three different species, we show that the mutation spectrum has a proportional influence on the types of changes fixed in adaptation. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions reflects the spectrum of variants introduced by mutation. Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis. Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply (Nμ) and that predictive power is strongly affected by the number and diversity of beneficial mutations.
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35
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Pontz M, Bürger R. The effects of epistasis and linkage on the invasion of locally beneficial mutations and the evolution of genomic islands. Theor Popul Biol 2022; 144:49-69. [DOI: 10.1016/j.tpb.2022.01.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 01/04/2022] [Accepted: 01/07/2022] [Indexed: 11/26/2022]
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36
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Morales-Arce AY, Johri P, Jensen JD. Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies. Heredity (Edinb) 2022; 128:79-87. [PMID: 34987185 PMCID: PMC8728706 DOI: 10.1038/s41437-021-00493-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 11/19/2022] Open
Abstract
We here propose an analysis pipeline for inferring the distribution of fitness effects (DFE) from either patient-sampled or experimentally-evolved viral populations, that explicitly accounts for non-Wright-Fisher and non-equilibrium population dynamics inherent to pathogens. We examine the performance of this approach via extensive power and performance analyses, and highlight two illustrative applications - one from an experimentally-passaged RNA virus, and the other from a clinically-sampled DNA virus. Finally, we discuss how such DFE inference may shed light on major research questions in virus evolution, ranging from a quantification of the population genetic processes governing genome size, to the role of Hill-Robertson interference in dictating adaptive outcomes, to the potential design of novel therapeutic approaches to eradicate within-patient viral populations via induced mutational meltdown.
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Affiliation(s)
- Ana Y Morales-Arce
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Parul Johri
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Jeffrey D Jensen
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA.
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37
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Chen J, Bataillon T, Glémin S, Lascoux M. What does the distribution of fitness effects of new mutations reflect? Insights from plants. THE NEW PHYTOLOGIST 2022; 233:1613-1619. [PMID: 34704271 DOI: 10.1111/nph.17826] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 09/28/2021] [Indexed: 06/13/2023]
Abstract
The distribution of fitness effects (DFE) of new mutations plays a central role in molecular evolution. It is therefore crucial to be able to estimate it accurately from genomic data and to understand the factors that shape it. After a rapid overview of available methods to characterize the fitness effects of mutations, we review what is known on the factors affecting them in plants. Available data indicate that life history traits (e.g. mating system and longevity) have a major effect on the DFE. By contrast, the impact of demography within species appears to be more limited. These results remain to be confirmed, and methods to estimate the joint evolution of demography, life history traits, and the DFE need to be developed.
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Affiliation(s)
- Jun Chen
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, C.F. Möllers Allé 8, Aarhus C, DK-8000, Denmark
| | - Sylvain Glémin
- Centre National de la Recherche Scientifique (CNRS), ECOBIO (Ecosystèmes, Biodiversité, Evolution) - Unité Mixte de Recherche (UMR) 6553, Université de Rennes, Rennes, F-35000, France
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, 75236, Sweden
| | - Martin Lascoux
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, 75236, Sweden
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38
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Vecchyo DOD, Lohmueller KE, Novembre J. Haplotype-based inference of the distribution of fitness effects. Genetics 2022; 220:6501446. [PMID: 35100400 PMCID: PMC8982047 DOI: 10.1093/genetics/iyac002] [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: 10/13/2021] [Accepted: 12/18/2021] [Indexed: 11/13/2022] Open
Abstract
Abstract
Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.
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Affiliation(s)
- Diego Ortega-Del Vecchyo
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, 76230, México
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - Kirk E Lohmueller
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, 90095, United States of America
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, Illinois, 60637, United States of America
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, 60637, United States of America
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39
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Gilbert KJ, Zdraljevic S, Cook DE, Cutter AD, Andersen EC, Baer CF. The distribution of mutational effects on fitness in Caenorhabditis elegans inferred from standing genetic variation. Genetics 2022; 220:iyab166. [PMID: 34791202 PMCID: PMC8733438 DOI: 10.1093/genetics/iyab166] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 09/27/2021] [Indexed: 11/14/2022] Open
Abstract
The distribution of fitness effects (DFE) for new mutations is one of the most theoretically important but difficult to estimate properties in population genetics. A crucial challenge to inferring the DFE from natural genetic variation is the sensitivity of the site frequency spectrum to factors like population size change, population substructure, genome structure, and nonrandom mating. Although inference methods aim to control for population size changes, the influence of nonrandom mating remains incompletely understood, despite being a common feature of many species. We report the DFE estimated from 326 genomes of Caenorhabditis elegans, a nematode roundworm with a high rate of self-fertilization. We evaluate the robustness of DFE inferences using simulated data that mimics the genomic structure and reproductive life history of C. elegans. Our observations demonstrate how the combined influence of self-fertilization, genome structure, and natural selection on linked sites can conspire to compromise estimates of the DFE from extant polymorphisms with existing methods. These factors together tend to bias inferences toward weakly deleterious mutations, making it challenging to have full confidence in the inferred DFE of new mutations as deduced from standing genetic variation in species like C. elegans. Improved methods for inferring the DFE are needed to appropriately handle strong linked selection and selfing. These results highlight the importance of understanding the combined effects of processes that can bias our interpretations of evolution in natural populations.
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Affiliation(s)
| | - Stefan Zdraljevic
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
- Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA
| | - Daniel E Cook
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
| | - Asher D Cutter
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON M5S 3B2, Canada
| | - Erik C Andersen
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
| | - Charles F Baer
- Department of Biology, University of Florida, Gainesville, FL 32611-8525, USA
- University of Florida Genetics Institute, Gainesville, FL 32611, USA
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40
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Liang YY, Shi Y, Yuan S, Zhou BF, Chen XY, An QQ, Ingvarsson PK, Plomion C, Wang B. Linked selection shapes the landscape of genomic variation in three oak species. THE NEW PHYTOLOGIST 2022; 233:555-568. [PMID: 34637540 DOI: 10.1111/nph.17793] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/27/2021] [Indexed: 06/13/2023]
Abstract
Natural selection shapes genome-wide patterns of diversity within species and divergence between species. However, quantifying the efficacy of selection and elucidating the relative importance of different types of selection in shaping genomic variation remain challenging. We sequenced whole genomes of 101 individuals of three closely related oak species to track the divergence history, and to dissect the impacts of selective sweeps and background selection on patterns of genomic variation. We estimated that the three species diverged around the late Neogene and experienced a bottleneck during the Pleistocene. We detected genomic regions with elevated relative differentiation ('FST -islands'). Population genetic inferences from the site frequency spectrum and ancestral recombination graph indicated that FST -islands were formed by selective sweeps. We also found extensive positive selection; the fixation of adaptive mutations and reduction neutral diversity around substitutions generated a signature of selective sweeps. Prevalent negative selection and background selection have reduced genetic diversity in both genic and intergenic regions, and contributed substantially to the baseline variation in genetic diversity. Our results demonstrate the importance of linked selection in shaping genomic variation, and illustrate how the extent and strength of different selection models vary across the genome.
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Affiliation(s)
- Yi-Ye Liang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Yong Shi
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Shuai Yuan
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Biao-Feng Zhou
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Xue-Yan Chen
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Qing-Qing An
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Pär K Ingvarsson
- Department of Plant Biology, Linnean Center for Plant Biology, Uppsala BioCenter, Swedish University of Agricultural Sciences, Uppsala, SE-75007, Sweden
| | | | - Baosheng Wang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
- Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Guangzhou, 510650, China
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41
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Soni V, Eyre-Walker A. OUP accepted manuscript. Genome Biol Evol 2022; 14:6528851. [PMID: 35166775 PMCID: PMC8882387 DOI: 10.1093/gbe/evac028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2022] [Indexed: 12/05/2022] Open
Abstract
The rate of amino acid substitution has been shown to be correlated to a number of factors including the rate of recombination, the age of the gene, the length of the protein, mean expression level, and gene function. However, the extent to which these correlations are due to adaptive and nonadaptive evolution has not been studied in detail, at least not in hominids. We find that the rate of adaptive evolution is significantly positively correlated to the rate of recombination, protein length and gene expression level, and negatively correlated to gene age. These correlations remain significant when each factor is controlled for in turn, except when controlling for expression in an analysis of protein length; and they also generally remain significant when biased gene conversion is taken into account. However, the positive correlations could be an artifact of population size contraction. We also find that the rate of nonadaptive evolution is negatively correlated to each factor, and all these correlations survive controlling for each other and biased gene conversion. Finally, we examine the effect of gene function on rates of adaptive and nonadaptive evolution; we confirm that virus-interacting proteins (VIPs) have higher rates of adaptive and lower rates of nonadaptive evolution, but we also demonstrate that there is significant variation in the rate of adaptive and nonadaptive evolution between GO categories when removing VIPs. We estimate that the VIP/non-VIP axis explains about 5–8 fold more of the variance in evolutionary rate than GO categories.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
| | - Adam Eyre-Walker
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
- Corresponding author: E-mail:
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42
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Horvath R, Menon M, Stitzer M, Ross-Ibarra J. OUP accepted manuscript. Genome Biol Evol 2022; 14:6519160. [PMID: 35104327 PMCID: PMC8872973 DOI: 10.1093/gbe/evac016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/22/2022] [Indexed: 11/23/2022] Open
Abstract
Recognition of the important role of transposable elements (TEs) in eukaryotic genomes quickly led to a burgeoning literature modeling and estimating the effects of selection on TEs. Much of the empirical work on selection has focused on analyzing the site frequency spectrum (SFS) of TEs. But TE evolution differs from standard models in a number of ways that can impact the power and interpretation of the SFS. For example, rather than mutating under a clock-like model, transposition often occurs in bursts which can inflate particular frequency categories compared with expectations under a standard neutral model. If a TE burst has been recent, the excess of low-frequency polymorphisms can mimic the effect of purifying selection. Here, we investigate how transposition bursts affect the frequency distribution of TEs and the correlation between age and allele frequency. Using information on the TE age distribution, we propose an age-adjusted SFS to compare TEs and neutral polymorphisms to more effectively evaluate whether TEs are under selective constraints. We show that our approach can minimize instances of false inference of selective constraint, remains robust to simple demographic changes, and allows for a correct identification of even weak selection affecting TEs which experienced a transposition burst. The results presented here will help researchers working on TEs to more reliably identify the effects of selection on TEs without having to rely on the assumption of a constant transposition rate.
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Affiliation(s)
- Robert Horvath
- Department of Evolution and Ecology, University of California, Davis, USA
- Corresponding authors: E-mails: ;
| | - Mitra Menon
- Department of Evolution and Ecology, University of California, Davis, USA
- Center for Population Biology, University of California, Davis, USA
| | - Michelle Stitzer
- Institute for Genomic Diversity and Department of Molecular Biology and Genetics, Cornell University, USA
| | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, University of California, Davis, USA
- Center for Population Biology, University of California, Davis, USA
- Genome Center, University of California, Davis, USA
- Corresponding authors: E-mails: ;
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43
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Horvath R, Josephs EB, Pesquet E, Stinchcombe JR, Wright SI, Scofield D, Slotte T. Selection on Accessible Chromatin Regions in Capsella grandiflora. Mol Biol Evol 2021; 38:5563-5575. [PMID: 34498072 PMCID: PMC8662636 DOI: 10.1093/molbev/msab270] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Accurate estimates of genome-wide rates and fitness effects of new mutations are essential for an improved understanding of molecular evolutionary processes. Although eukaryotic genomes generally contain a large noncoding fraction, functional noncoding regions and fitness effects of mutations in such regions are still incompletely characterized. A promising approach to characterize functional noncoding regions relies on identifying accessible chromatin regions (ACRs) tightly associated with regulatory DNA. Here, we applied this approach to identify and estimate selection on ACRs in Capsella grandiflora, a crucifer species ideal for population genomic quantification of selection due to its favorable population demography. We describe a population-wide ACR distribution based on ATAC-seq data for leaf samples of 16 individuals from a natural population. We use population genomic methods to estimate fitness effects and proportions of positively selected fixations (α) in ACRs and find that intergenic ACRs harbor a considerable fraction of weakly deleterious new mutations, as well as a significantly higher proportion of strongly deleterious mutations than comparable inaccessible intergenic regions. ACRs are enriched for expression quantitative trait loci (eQTL) and depleted of transposable element insertions, as expected if intergenic ACRs are under selection because they harbor regulatory regions. By integrating empirical identification of intergenic ACRs with analyses of eQTL and population genomic analyses of selection, we demonstrate that intergenic regulatory regions are an important source of nearly neutral mutations. These results improve our understanding of selection on noncoding regions and the role of nearly neutral mutations for evolutionary processes in outcrossing Brassicaceae species.
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Affiliation(s)
- Robert Horvath
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Emily B Josephs
- Department of Plant Biology, Michigan State University, Lansing, MI, USA
| | - Edouard Pesquet
- Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden
| | - John R Stinchcombe
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
| | - Stephen I Wright
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
| | - Douglas Scofield
- Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
| | - Tanja Slotte
- Department of Ecology, Environment and Plant Sciences, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
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44
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Scharmann M, Rebelo AG, Pannell JR. High rates of evolution preceded shifts to sex-biased gene expression in Leucadendron, the most sexually dimorphic angiosperms. eLife 2021; 10:e67485. [PMID: 34726596 PMCID: PMC8635981 DOI: 10.7554/elife.67485] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 10/27/2021] [Indexed: 11/21/2022] Open
Abstract
Differences between males and females are usually more subtle in dioecious plants than animals, but strong sexual dimorphism has evolved convergently in the South African Cape plant genus Leucadendron. Such sexual dimorphism in leaf size is expected largely to be due to differential gene expression between the sexes. We compared patterns of gene expression in leaves among 10 Leucadendron species across the genus. Surprisingly, we found no positive association between sexual dimorphism in morphology and the number or the percentage of sex-biased genes (SBGs). Sex bias in most SBGs evolved recently and was species specific. We compared rates of evolutionary change in expression for genes that were sex biased in one species but unbiased in others and found that SBGs evolved faster in expression than unbiased genes. This greater rate of expression evolution of SBGs, also documented in animals, might suggest the possible role of sexual selection in the evolution of gene expression. However, our comparative analysis clearly indicates that the more rapid rate of expression evolution of SBGs predated the origin of bias, and shifts towards bias were depleted in signatures of adaptation. Our results are thus more consistent with the view that sex bias is simply freer to evolve in genes less subject to constraints in expression level.
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Affiliation(s)
- Mathias Scharmann
- Department of Ecology and Evolution, University of LausanneLausanneSwitzerland
| | - Anthony G Rebelo
- Applied Biodiversity Research Division, South African National Biodiversity InstituteCape TownSouth Africa
| | - John R Pannell
- Department of Ecology and Evolution, University of LausanneLausanneSwitzerland
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45
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Huang YF. Dissecting genomic determinants of positive selection with an evolution-guided regression model. Mol Biol Evol 2021; 39:6379733. [PMID: 34597406 PMCID: PMC8763110 DOI: 10.1093/molbev/msab291] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
In evolutionary genomics, it is fundamentally important to understand how characteristics of genomic sequences, such as gene expression level, determine the rate of adaptive evolution. While numerous statistical methods, such as the McDonald–Kreitman (MK) test, are available to examine the association between genomic features and the rate of adaptation, we currently lack a statistical approach to disentangle the independent effect of a genomic feature from the effects of other correlated genomic features. To address this problem, I present a novel statistical model, the MK regression, which augments the MK test with a generalized linear model. Analogous to the classical multiple regression model, the MK regression can analyze multiple genomic features simultaneously to infer the independent effect of a genomic feature, holding constant all other genomic features. Using the MK regression, I identify numerous genomic features driving positive selection in chimpanzees. These features include well-known ones, such as local mutation rate, residue exposure level, tissue specificity, and immune genes, as well as new features not previously reported, such as gene expression level and metabolic genes. In particular, I show that highly expressed genes may have a higher adaptation rate than their weakly expressed counterparts, even though a higher expression level may impose stronger negative selection. Also, I show that metabolic genes may have a higher adaptation rate than their nonmetabolic counterparts, possibly due to recent changes in diet in primate evolution. Overall, the MK regression is a powerful approach to elucidate the genomic basis of adaptation.
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Affiliation(s)
- Yi-Fei Huang
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA.,Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA
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46
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Jackson B, Charlesworth B. Evidence for a force favoring GC over AT at short intronic sites in Drosophila simulans and Drosophila melanogaster. G3 GENES|GENOMES|GENETICS 2021; 11:6321237. [PMID: 34544137 PMCID: PMC8496279 DOI: 10.1093/g3journal/jkab240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 07/06/2021] [Indexed: 11/13/2022]
Abstract
Population genetics studies often make use of a class of nucleotide site free from selective pressures, in order to make inferences about population size changes or natural selection at other sites. If such neutral sites can be identified, they offer the opportunity to avoid any confounding effects of selection. Here, we investigate evolution at putatively neutrally evolving short intronic sites in natural populations of Drosophila melanogaster and Drosophila simulans, in order to understand the properties of spontaneous mutations and the extent of GC-biased gene conversion in these species. Use of data on the genetics of natural populations is advantageous because it integrates information from large numbers of individuals over long timescales. In agreement with direct evidence from observations of spontaneous mutations in Drosophila, we find a bias in the spectrum of mutations toward AT basepairs. In addition, we find that this bias is stronger in the D. melanogaster lineage than in the D. simulans lineage. The evidence for GC-biased gene conversion in Drosophila has been equivocal. Here, we provide evidence for a weak force favoring GC in both species, which is correlated with the GC content of introns and is stronger in D. simulans than in D. melanogaster.
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Affiliation(s)
- Ben Jackson
- School of Biological Sciences, Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Brian Charlesworth
- School of Biological Sciences, Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
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Cavassim MIA, Andersen SU, Bataillon T, Schierup MH. Recombination facilitates adaptive evolution in rhizobial soil bacteria. Mol Biol Evol 2021; 38:5480-5490. [PMID: 34410427 PMCID: PMC8662638 DOI: 10.1093/molbev/msab247] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Homologous recombination is expected to increase natural selection efficacy by decoupling the fate of beneficial and deleterious mutations and by readily creating new combinations of beneficial alleles. Here, we investigate how the proportion of amino acid substitutions fixed by adaptive evolution (α) depends on the recombination rate in bacteria. We analyze 3,086 core protein-coding sequences from 196 genomes belonging to five closely related species of the genus Rhizobium. These genes are found in all species and do not display any signs of introgression between species. We estimate α using the site frequency spectrum (SFS) and divergence data for all pairs of species. We evaluate the impact of recombination within each species by dividing genes into three equally sized recombination classes based on their average level of intragenic linkage disequilibrium. We find that α varies from 0.07 to 0.39 across species and is positively correlated with the level of recombination. This is both due to a higher estimated rate of adaptive evolution and a lower estimated rate of nonadaptive evolution, suggesting that recombination both increases the fixation probability of advantageous variants and decreases the probability of fixation of deleterious variants. Our results demonstrate that homologous recombination facilitates adaptive evolution measured by α in the core genome of prokaryote species in agreement with studies in eukaryotes.
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Affiliation(s)
- Maria Izabel A Cavassim
- Bioinformatics Research Centre, Aarhus University, Aarhus, 8000, Denmark.,Department of Molecular Biology and Genetics, Aarhus University, Aarhus, 8000, Denmark
| | - Stig U Andersen
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, 8000, Denmark
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, Aarhus, 8000, Denmark
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Chen J, Bataillon T, Glémin S, Lascoux M. Hunting for beneficial mutations: conditioning on SIFT scores when estimating the distribution of fitness effect of new mutations. Genome Biol Evol 2021; 14:6310736. [PMID: 34180988 PMCID: PMC8743036 DOI: 10.1093/gbe/evab151] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/21/2021] [Indexed: 11/13/2022] Open
Abstract
The Distribution of Fitness Effects (DFE) of new mutations is a key parameter of molecular evolution. The DFE can in principle be estimated by comparing the Site Frequency Spectra (SFS) of putatively neutral and functional polymorphisms. Unfortunately the DFE is intrinsically hard to estimate, especially for beneficial mutations since these tend to be exceedingly rare. There is therefore a strong incentive to find out whether conditioning on properties of mutations that are independent of the SFS could provide additional information. In the present study, we developed a new measure based on SIFT scores. SIFT scores are assigned to nucleotide sites based on their level of conservation across a multi species alignment: the more conserved a site, the more likely mutations occurring at this site are deleterious and the lower the SIFT score. If one knows the ancestral state at a given site, one can assign a value to new mutations occurring at the site based on the change of SIFT score associated with the mutation. We called this new measure δ. We show that properties of the DFE as well as the flux of beneficial mutations across classes covary with δ and, hence, that SIFT scores are informative when estimating the fitness effect of new mutations. In particular, conditioning on SIFT scores can help to characterize beneficial mutations.
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Affiliation(s)
- J Chen
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - T Bataillon
- Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, Aarhus C, DK-8000, Denmark
| | - S Glémin
- Université de Rennes, Centre National de la Recherche Scientifique (CNRS), ECOBIO (Ecosystèmes, Biodiversité, Evolution) - Unité Mixte de Recherche (UMR) 6553, Rennes, F-35000, France.,Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, 75236, Sweden
| | - M Lascoux
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, 75236, Sweden
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Huang X, Fortier AL, Coffman AJ, Struck TJ, Irby MN, James JE, León-Burguete JE, Ragsdale AP, Gutenkunst RN. Inferring genome-wide correlations of mutation fitness effects between populations. Mol Biol Evol 2021; 38:4588-4602. [PMID: 34043790 PMCID: PMC8476148 DOI: 10.1093/molbev/msab162] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The effect of a mutation on fitness may differ between populations depending on environmental and genetic context, but little is known about the factors that underlie such differences. To quantify genome-wide correlations in mutation fitness effects, we developed a novel concept called a joint distribution of fitness effects (DFE) between populations. We then proposed a new statistic w to measure the DFE correlation between populations. Using simulation, we showed that inferring the DFE correlation from the joint allele frequency spectrum is statistically precise and robust. Using population genomic data, we inferred DFE correlations of populations in humans, Drosophila melanogaster, and wild tomatoes. In these species, we found that the overall correlation of the joint DFE was inversely related to genetic differentiation. In humans and D. melanogaster, deleterious mutations had a lower DFE correlation than tolerated mutations, indicating a complex joint DFE. Altogether, the DFE correlation can be reliably inferred, and it offers extensive insight into the genetics of population divergence.
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50
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Blischak PD, Barker MS, Gutenkunst RN. Inferring the Demographic History of Inbred Species from Genome-Wide SNP Frequency Data. Mol Biol Evol 2021; 37:2124-2136. [PMID: 32068861 DOI: 10.1093/molbev/msaa042] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 02/04/2020] [Accepted: 02/13/2020] [Indexed: 01/04/2023] Open
Abstract
Demographic inference using the site frequency spectrum (SFS) is a common way to understand historical events affecting genetic variation. However, most methods for estimating demography from the SFS assume random mating within populations, precluding these types of analyses in inbred populations. To address this issue, we developed a model for the expected SFS that includes inbreeding by parameterizing individual genotypes using beta-binomial distributions. We then take the convolution of these genotype probabilities to calculate the expected frequency of biallelic variants in the population. Using simulations, we evaluated the model's ability to coestimate demography and inbreeding using one- and two-population models across a range of inbreeding levels. We also applied our method to two empirical examples, American pumas (Puma concolor) and domesticated cabbage (Brassica oleracea var. capitata), inferring models both with and without inbreeding to compare parameter estimates and model fit. Our simulations showed that we are able to accurately coestimate demographic parameters and inbreeding even for highly inbred populations (F = 0.9). In contrast, failing to include inbreeding generally resulted in inaccurate parameter estimates in simulated data and led to poor model fit in our empirical analyses. These results show that inbreeding can have a strong effect on demographic inference, a pattern that was especially noticeable for parameters involving changes in population size. Given the importance of these estimates for informing practices in conservation, agriculture, and elsewhere, our method provides an important advancement for accurately estimating the demographic histories of these species.
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Affiliation(s)
- Paul D Blischak
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ.,Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ
| | - Michael S Barker
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ
| | - Ryan N Gutenkunst
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ
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