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Joseph J. Increased Positive Selection in Highly Recombining Genes Does not Necessarily Reflect an Evolutionary Advantage of Recombination. Mol Biol Evol 2024; 41:msae107. [PMID: 38829800 PMCID: PMC11173204 DOI: 10.1093/molbev/msae107] [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: 01/30/2024] [Revised: 04/08/2024] [Accepted: 05/28/2024] [Indexed: 06/05/2024] Open
Abstract
It is commonly thought that the long-term advantage of meiotic recombination is to dissipate genetic linkage, allowing natural selection to act independently on different loci. It is thus theoretically expected that genes with higher recombination rates evolve under more effective selection. On the other hand, recombination is often associated with GC-biased gene conversion (gBGC), which theoretically interferes with selection by promoting the fixation of deleterious GC alleles. To test these predictions, several studies assessed whether selection was more effective in highly recombining genes (due to dissipation of genetic linkage) or less effective (due to gBGC), assuming a fixed distribution of fitness effects (DFE) for all genes. In this study, I directly derive the DFE from a gene's evolutionary history (shaped by mutation, selection, drift, and gBGC) under empirical fitness landscapes. I show that genes that have experienced high levels of gBGC are less fit and thus have more opportunities for beneficial mutations. Only a small decrease in the genome-wide intensity of gBGC leads to the fixation of these beneficial mutations, particularly in highly recombining genes. This results in increased positive selection in highly recombining genes that is not caused by more effective selection. Additionally, I show that the death of a recombination hotspot can lead to a higher dN/dS than its birth, but with substitution patterns biased towards AT, and only at selected positions. This shows that controlling for a substitution bias towards GC is therefore not sufficient to rule out the contribution of gBGC to signatures of accelerated evolution. Finally, although gBGC does not affect the fixation probability of GC-conservative mutations, I show that by altering the DFE, gBGC can also significantly affect nonsynonymous GC-conservative substitution patterns.
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Affiliation(s)
- Julien Joseph
- Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, CNRS, UMR 5558, Villeurbanne, France
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2
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Rodrigues MF, Kern AD, Ralph PL. Shared evolutionary processes shape landscapes of genomic variation in the great apes. Genetics 2024; 226:iyae006. [PMID: 38242701 PMCID: PMC10990428 DOI: 10.1093/genetics/iyae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 10/26/2023] [Accepted: 01/03/2024] [Indexed: 01/21/2024] Open
Abstract
For at least the past 5 decades, population genetics, as a field, has worked to describe the precise balance of forces that shape patterns of variation in genomes. The problem is challenging because modeling the interactions between evolutionary processes is difficult, and different processes can impact genetic variation in similar ways. In this paper, we describe how diversity and divergence between closely related species change with time, using correlations between landscapes of genetic variation as a tool to understand the interplay between evolutionary processes. We find strong correlations between landscapes of diversity and divergence in a well-sampled set of great ape genomes, and explore how various processes such as incomplete lineage sorting, mutation rate variation, GC-biased gene conversion and selection contribute to these correlations. Through highly realistic, chromosome-scale, forward-in-time simulations, we show that the landscapes of diversity and divergence in the great apes are too well correlated to be explained via strictly neutral processes alone. Our best fitting simulation includes both deleterious and beneficial mutations in functional portions of the genome, in which 9% of fixations within those regions is driven by positive selection. This study provides a framework for modeling genetic variation in closely related species, an approach which can shed light on the complex balance of forces that have shaped genetic variation.
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Affiliation(s)
- Murillo F Rodrigues
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403, USA
- Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Andrew D Kern
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403, USA
- Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Peter L Ralph
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403, USA
- Department of Biology, University of Oregon, Eugene, OR 97403, USA
- Department of Mathematics, University of Oregon, Eugene, OR 97403, USA
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3
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Cousins T, Tabin D, Patterson N, Reich D, Durvasula A. Accurate inference of population history in the presence of background selection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.18.576291. [PMID: 38313273 PMCID: PMC10838404 DOI: 10.1101/2024.01.18.576291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
All published methods for learning about demographic history make the simplifying assumption that the genome evolves neutrally, and do not seek to account for the effects of natural selection on patterns of variation. This is a major concern, as ample work has demonstrated the pervasive effects of natural selection and in particular background selection (BGS) on patterns of genetic variation in diverse species. Simulations and theoretical work have shown that methods to infer changes in effective population size over time (Ne(t)) become increasingly inaccurate as the strength of linked selection increases. Here, we introduce an extension to the Pairwise Sequentially Markovian Coalescent (PSMC) algorithm, PSMC+, which explicitly co-models demographic history and natural selection. We benchmark our method using forward-in-time simulations with BGS and find that our approach improves the accuracy of effective population size inference. Leveraging a high resolution map of BGS in humans, we infer considerable changes in the magnitude of inferred effective population size relative to previous reports. Finally, we separately infer Ne(t) on the X chromosome and on the autosomes in diverse great apes without making a correction for selection, and find that the inferred ratio fluctuates substantially through time in a way that differs across species, showing that uncorrected selection may be an important driver of signals of genetic difference on the X chromosome and autosomes.
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Affiliation(s)
- Trevor Cousins
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Daniel Tabin
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Nick Patterson
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - David Reich
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Boston, MA, USA
| | - Arun Durvasula
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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4
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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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5
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Sandler G, Agrawal AF, Wright SI. Population Genomics of the Facultatively Sexual Liverwort Marchantia polymorpha. Genome Biol Evol 2023; 15:evad196. [PMID: 37883717 PMCID: PMC10667032 DOI: 10.1093/gbe/evad196] [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: 12/16/2022] [Revised: 10/15/2023] [Accepted: 10/18/2023] [Indexed: 10/28/2023] Open
Abstract
The population genomics of facultatively sexual organisms are understudied compared with their abundance across the tree of life. We explore patterns of genetic diversity in two subspecies of the facultatively sexual liverwort Marchantia polymorpha using samples from across Southern Ontario, Canada. Despite the ease with which M. polymorpha should be able to propagate asexually, we find no evidence of strictly clonal descent among our samples and little to no signal of isolation by distance. Patterns of identity-by-descent tract sharing further showed evidence of recent recombination and close relatedness between geographically distant isolates, suggesting long distance gene flow and at least a modest frequency of sexual reproduction. However, the M. polymorpha genome contains overall very low levels of nucleotide diversity and signs of inefficient selection evidenced by a relatively high fraction of segregating deleterious variants. We interpret these patterns as possible evidence of the action of linked selection and a small effective population size due to past generations of asexual propagation. Overall, the M. polymorpha genome harbors signals of a complex history of both sexual and asexual reproduction.
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Affiliation(s)
- George Sandler
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
| | - Aneil F Agrawal
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
- Center for Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario, Canada
| | - Stephen I Wright
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
- Center for Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario, Canada
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6
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Alamil M, Thébaud G, Berthier K, Soubeyrand S. Characterizing viral within-host diversity in fast and non-equilibrium demo-genetic dynamics. Front Microbiol 2022; 13:983938. [PMID: 36274731 PMCID: PMC9581327 DOI: 10.3389/fmicb.2022.983938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
High-throughput sequencing has opened the route for a deep assessment of within-host genetic diversity that can be used, e.g., to characterize microbial communities and to infer transmission links in infectious disease outbreaks. The performance of such characterizations and inferences cannot be analytically assessed in general and are often grounded on computer-intensive evaluations. Then, being able to simulate within-host genetic diversity across time under various demo-genetic assumptions is paramount to assess the performance of the approaches of interest. In this context, we built an original model that can be simulated to investigate the temporal evolution of genotypes and their frequencies under various demo-genetic assumptions. The model describes the growth and the mutation of genotypes at the nucleotide resolution conditional on an overall within-host viral kinetics, and can be tuned to generate fast non-equilibrium demo-genetic dynamics. We ran simulations of this model and computed classic diversity indices to characterize the temporal variation of within-host genetic diversity (from high-throughput amplicon sequences) of virus populations under three demographic kinetic models of viral infection. Our results highlight how demographic (viral load) and genetic (mutation, selection, or drift) factors drive variations in within-host diversity during the course of an infection. In particular, we observed a non-monotonic relationship between pathogen population size and genetic diversity, and a reduction of the impact of mutation on diversity when a non-specific host immune response is activated. The large variation in the diversity patterns generated in our simulations suggests that the underlying model provides a flexible basis to produce very diverse demo-genetic scenarios and test, for instance, methods for the inference of transmission links during outbreaks.
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Affiliation(s)
- Maryam Alamil
- INRAE, BioSP, Avignon, France
- Department of Mathematics and Computer Science, Alfaisal University, Riyadh, Saudi Arabia
- *Correspondence: Maryam Alamil ;
| | - Gaël Thébaud
- PHIM Plant Health Institute, INRAE, Univ Montpellier, CIRAD, Institut Agro, IRD, Montpellier, France
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7
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Boman J, Mugal CF, Backström N. The Effects of GC-Biased Gene Conversion on Patterns of Genetic Diversity among and across Butterfly Genomes. Genome Biol Evol 2021; 13:evab064. [PMID: 33760095 PMCID: PMC8175052 DOI: 10.1093/gbe/evab064] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2021] [Indexed: 12/28/2022] Open
Abstract
Recombination reshuffles the alleles of a population through crossover and gene conversion. These mechanisms have considerable consequences on the evolution and maintenance of genetic diversity. Crossover, for example, can increase genetic diversity by breaking the linkage between selected and nearby neutral variants. Bias in favor of G or C alleles during gene conversion may instead promote the fixation of one allele over the other, thus decreasing diversity. Mutation bias from G or C to A and T opposes GC-biased gene conversion (gBGC). Less recognized is that these two processes may-when balanced-promote genetic diversity. Here, we investigate how gBGC and mutation bias shape genetic diversity patterns in wood white butterflies (Leptidea sp.). This constitutes the first in-depth investigation of gBGC in butterflies. Using 60 resequenced genomes from six populations of three species, we find substantial variation in the strength of gBGC across lineages. When modeling the balance of gBGC and mutation bias and comparing analytical results with empirical data, we reject gBGC as the main determinant of genetic diversity in these butterfly species. As alternatives, we consider linked selection and GC content. We find evidence that high values of both reduce diversity. We also show that the joint effects of gBGC and mutation bias can give rise to a diversity pattern which resembles the signature of linked selection. Consequently, gBGC should be considered when interpreting the effects of linked selection on levels of genetic diversity.
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Affiliation(s)
- Jesper Boman
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, Sweden
| | - Carina F Mugal
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, Sweden
| | - Niclas Backström
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, Sweden
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8
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Evolution: Small populations, low recombination, big trouble? Curr Biol 2021; 31:R282-R284. [PMID: 33756137 DOI: 10.1016/j.cub.2021.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Small populations harbour less genetic diversity and more harmful mutations. They thus adapt more slowly. A new study supports these notions and suggests that reduced recombination exacerbates these effects, highlighting the impact of genome architecture on adaptability.
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9
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Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD. The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects. Mol Biol Evol 2021; 38:2986-3003. [PMID: 33591322 PMCID: PMC8233493 DOI: 10.1093/molbev/msab050] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
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Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Kellen Riall
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Hannes Becher
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Laurent Excoffier
- Institute of Ecology and Evolution, University of Berne, Berne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
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10
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Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD. The impact of purifying and background selection on the inference of population history: problems and prospects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021. [PMID: 33501439 PMCID: PMC7836109 DOI: 10.1101/2020.04.28.066365] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Current procedures for inferring population history generally assume complete neutrality - that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects (DFE) and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the DFE as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
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Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Kellen Riall
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Hannes Becher
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Laurent Excoffier
- Institute of Ecology and Evolution, University of Berne, Berne 3012, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
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11
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McGrath C. Human Genetics: A Look in the Mirror. Genome Biol Evol 2020. [DOI: 10.1093/gbe/evaa139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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12
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Castellano D, Macià MC, Tataru P, Bataillon T, Munch K. Comparison of the Full Distribution of Fitness Effects of New Amino Acid Mutations Across Great Apes. Genetics 2019; 213:953-966. [PMID: 31488516 PMCID: PMC6827385 DOI: 10.1534/genetics.119.302494] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 08/29/2019] [Indexed: 12/31/2022] Open
Abstract
The distribution of fitness effects (DFE) is central to many questions in evolutionary biology. However, little is known about the differences in DFE between closely related species. We use >9000 coding genes orthologous one-to-one across great apes, gibbons, and macaques to assess the stability of the DFE across great apes. We use the unfolded site frequency spectrum of polymorphic mutations (n = 8 haploid chromosomes per population) to estimate the DFE. We find that the shape of the deleterious DFE is strikingly similar across great apes. We confirm that effective population size (Ne ) is a strong predictor of the strength of negative selection, consistent with the nearly neutral theory. However, we also find that the strength of negative selection varies more than expected given the differences in Ne between species. Across species, mean fitness effects of new deleterious mutations covaries with Ne , consistent with positive epistasis among deleterious mutations. We find that the strength of negative selection for the smallest populations, bonobos and western chimpanzees, is higher than expected given their Ne This may result from a more efficient purging of strongly deleterious recessive variants in these populations. Forward simulations confirm that these findings are not artifacts of the way we are inferring Ne and DFE parameters. All findings are replicated using only GC-conservative mutations, thereby confirming that GC-biased gene conversion is not affecting our conclusions.
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Affiliation(s)
- David Castellano
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Moisès Coll Macià
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Paula Tataru
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Thomas Bataillon
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Kasper Munch
- Bioinformatics Research Centre, Aarhus University, DK-8000 Aarhus C, Denmark
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13
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Talla V, Soler L, Kawakami T, Dincă V, Vila R, Friberg M, Wiklund C, Backström N. Dissecting the Effects of Selection and Mutation on Genetic Diversity in Three Wood White (Leptidea) Butterfly Species. Genome Biol Evol 2019; 11:2875-2886. [PMID: 31580421 PMCID: PMC6795238 DOI: 10.1093/gbe/evz212] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2019] [Indexed: 12/12/2022] Open
Abstract
The relative role of natural selection and genetic drift in evolution is a major topic of debate in evolutionary biology. Most knowledge spring from a small group of organisms and originate from before it was possible to generate genome-wide data on genetic variation. Hence, it is necessary to extend to a larger number of taxonomic groups, descriptive and hypothesis-based research aiming at understanding the proximate and ultimate mechanisms underlying both levels of genetic polymorphism and the efficiency of natural selection. In this study, we used data from 60 whole-genome resequenced individuals of three cryptic butterfly species (Leptidea sp.), together with novel gene annotation information and population recombination data. We characterized the overall prevalence of natural selection and investigated the effects of mutation and linked selection on regional variation in nucleotide diversity. Our analyses showed that genome-wide diversity and rate of adaptive substitutions were comparatively low, whereas nonsynonymous to synonymous polymorphism and substitution levels were comparatively high in Leptidea, suggesting small long-term effective population sizes. Still, negative selection on linked sites (background selection) has resulted in reduced nucleotide diversity in regions with relatively high gene density and low recombination rate. We also found a significant effect of mutation rate variation on levels of polymorphism. Finally, there were considerable population differences in levels of genetic diversity and pervasiveness of selection against slightly deleterious alleles, in line with expectations from differences in estimated effective population sizes.
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Affiliation(s)
- Venkat Talla
- Department of Evolutionary Biology, Evolutionary Biology Centre (EBC), Uppsala University, Sweden
| | - Lucile Soler
- Department of Medical Biochemistry and Microbiology, National Bioinformatics Infrastructure Sweden (NBIS), Science for Life Laboratory, Uppsala, Sweden
| | - Takeshi Kawakami
- Department of Evolutionary Biology, Evolutionary Biology Centre (EBC), Uppsala University, Sweden
| | - Vlad Dincă
- Department of Ecology and Genetics, University of Oulu, Finland
| | - Roger Vila
- Institut de Biologia Evolutiva (CSIC-UPF), Barcelona, Spain
| | - Magne Friberg
- Department of Biology, Biodiversity Unit, Lund University, Sweden
| | - Christer Wiklund
- Department of Zoology, Division of Ecology, Stockholm University, Sweden
| | - Niclas Backström
- Department of Evolutionary Biology, Evolutionary Biology Centre (EBC), Uppsala University, Sweden
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