1
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Gokhman D, Harris KD, Carmi S, Greenbaum G. Predicting the direction of phenotypic difference. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.22.581566. [PMID: 38895291 PMCID: PMC11185551 DOI: 10.1101/2024.02.22.581566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Predicting phenotypes from genomic data is a key goal in genetics, but for most complex phenotypes, predictions are hampered by incomplete genotype-to-phenotype mapping. Here, we describe a more attainable approach than quantitative predictions, which is aimed at qualitatively predicting phenotypic differences. Despite incomplete genotype-to-phenotype mapping, we show that it is relatively easy to determine which of two individuals has a greater phenotypic value. This question is central in many scenarios, e.g., comparing disease risk between individuals, the yield of crop strains, or the anatomy of extinct vs extant species. To evaluate prediction accuracy, i.e., the probability that the individual with the greater predicted phenotype indeed has a greater phenotypic value, we developed an estimator of the ratio between known and unknown effects on the phenotype. We evaluated prediction accuracy using human data from tens of thousands of individuals from either the same family or the same population, as well as data from different species. We found that, in many cases, even when only a small fraction of the loci affecting a phenotype is known, the individual with the greater phenotypic value can be identified with over 90% accuracy. Our approach also circumvents some of the limitations in transferring genetic association results across populations. Overall, we introduce an approach that enables accurate predictions of key information on phenotypes - the direction of phenotypic difference - and suggest that more phenotypic information can be extracted from genomic data than previously appreciated.
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2
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Glaser-Schmitt A, Ramnarine TJS, Parsch J. Rapid evolutionary change, constraints and the maintenance of polymorphism in natural populations of Drosophila melanogaster. Mol Ecol 2024; 33:e17024. [PMID: 37222070 DOI: 10.1111/mec.17024] [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: 10/30/2022] [Revised: 04/28/2023] [Accepted: 05/05/2023] [Indexed: 05/25/2023]
Abstract
Allele frequencies can shift rapidly within natural populations. Under certain conditions, repeated rapid allele frequency shifts can lead to the long-term maintenance of polymorphism. In recent years, studies of the model insect Drosophila melanogaster have suggested that this phenomenon is more common than previously believed and is often driven by some form of balancing selection, such as temporally fluctuating or sexually antagonistic selection. Here we discuss some of the general insights into rapid evolutionary change revealed by large-scale population genomic studies, as well as the functional and mechanistic causes of rapid adaptation uncovered by single-gene studies. As an example of the latter, we consider a regulatory polymorphism of the D. melanogaster fezzik gene. Polymorphism at this site has been maintained at intermediate frequency over an extended period of time. Regular observations from a single population over a period of 7 years revealed significant differences in the frequency of the derived allele and its variance across collections between the sexes. These patterns are highly unlikely to arise from genetic drift alone or from the action of sexually antagonistic or temporally fluctuating selection individually. Instead, the joint action of sexually antagonistic and temporally fluctuating selection can best explain the observed rapid and repeated allele frequency shifts. Temporal studies such as those reviewed here further our understanding of how rapid changes in selection can lead to the long-term maintenance of polymorphism as well as improve our knowledge of the forces driving and limiting adaptation in nature.
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Affiliation(s)
- Amanda Glaser-Schmitt
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Timothy J S Ramnarine
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - John Parsch
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany
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3
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O’Brien NLV, Holland B, Engelstädter J, Ortiz-Barrientos D. The distribution of fitness effects during adaptive walks using a simple genetic network. PLoS Genet 2024; 20:e1011289. [PMID: 38787919 PMCID: PMC11156440 DOI: 10.1371/journal.pgen.1011289] [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: 01/31/2024] [Revised: 06/06/2024] [Accepted: 05/04/2024] [Indexed: 05/26/2024] Open
Abstract
The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects.
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Affiliation(s)
- Nicholas L. V. O’Brien
- School of the Environment, The University of Queensland, Brisbane, Queensland, Australia
- ARC Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, Brisbane, QLD, Australia
| | - Barbara Holland
- School of Natural Sciences, University of Tasmania, Hobart, Tasmania, Australia
- ARC Centre of Excellence for Plant Success in Nature and Agriculture, University of Tasmania, Hobart, Tasmania, Australia
| | - Jan Engelstädter
- School of the Environment, The University of Queensland, Brisbane, Queensland, Australia
- ARC Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, Brisbane, QLD, Australia
| | - Daniel Ortiz-Barrientos
- School of the Environment, The University of Queensland, Brisbane, Queensland, Australia
- ARC Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, Brisbane, QLD, Australia
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4
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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] [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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5
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Lai WY, Nolte V, Jakšić AM, Schlötterer C. Evolution of Phenotypic Variance Provides Insights into the Genetic Basis of Adaptation. Genome Biol Evol 2024; 16:evae077. [PMID: 38620076 PMCID: PMC11057206 DOI: 10.1093/gbe/evae077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 03/27/2024] [Accepted: 04/02/2024] [Indexed: 04/17/2024] Open
Abstract
Most traits are polygenic, and the contributing loci can be identified by genome-wide association studies. The genetic basis of adaptation (adaptive architecture) is, however, difficult to characterize. Here, we propose to study the adaptive architecture of traits by monitoring the evolution of their phenotypic variance during adaptation to a new environment in well-defined laboratory conditions. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting can distinguish between oligogenic and polygenic adaptive architectures. We compared gene expression variance in male Drosophila simulans before and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We suggest that the majority of adaptive gene expression evolution can be explained by a polygenic architecture. We propose that tracking the evolution of phenotypic variance across generations can provide an approach to characterize the adaptive architecture.
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Affiliation(s)
- Wei-Yun Lai
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - Ana Marija Jakšić
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
- Present address: École polytechnique fédérale de Lausanne, Lausanne, Switzerland
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6
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Parsons TL, Ralph PL. Large effects and the infinitesimal model. Theor Popul Biol 2024; 156:117-129. [PMID: 38423480 DOI: 10.1016/j.tpb.2024.02.009] [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: 07/08/2023] [Revised: 02/20/2024] [Accepted: 02/24/2024] [Indexed: 03/02/2024]
Abstract
The infinitesimal model of quantitative genetics relies on the Central Limit Theorem to stipulate that under additive models of quantitative traits determined by many loci having similar effect size, the difference between an offspring's genetic trait component and the average of their two parents' genetic trait components is Normally distributed and independent of the parents' values. Here, we investigate how the assumption of similar effect sizes affects the model: if, alternatively, the tail of the effect size distribution is polynomial with exponent α<2, then a different Central Limit Theorem implies that sums of effects should be well-approximated by a "stable distribution", for which single large effects are often still important. Empirically, we first find tail exponents between 1 and 2 in effect sizes estimated by genome-wide association studies of many human disease-related traits. We then show that the independence of offspring trait deviations from parental averages in many cases implies the Gaussian aspect of the infinitesimal model, suggesting that non-Gaussian models of trait evolution must explicitly track the underlying genetics, at least for loci of large effect. We also characterize possible limiting trait distributions of the infinitesimal model with infinitely divisible noise distributions, and compare our results to simulations.
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Affiliation(s)
- Todd L Parsons
- LPSM, Sorbonne Université, CNRS UMR 8001, Paris, 75005, France
| | - Peter L Ralph
- Institute of Ecology & Evolution, University of Oregon, Eugene, OR, 97405, USA.
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7
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Veller C, Coop GM. Interpreting population- and family-based genome-wide association studies in the presence of confounding. PLoS Biol 2024; 22:e3002511. [PMID: 38603516 PMCID: PMC11008796 DOI: 10.1371/journal.pbio.3002511] [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: 03/22/2023] [Accepted: 01/19/2024] [Indexed: 04/13/2024] Open
Abstract
A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding and can also absorb the "indirect" genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect-size estimates are used in polygenic scores (PGSs). We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding.
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Affiliation(s)
- Carl Veller
- Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America
| | - Graham M. Coop
- Department of Evolution and Ecology, and Center for Population Biology, University of California, Davis, California, United States of America
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8
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Muralidhar P, Coop G. Polygenic response of sex chromosomes to sexual antagonism. Evolution 2024; 78:539-554. [PMID: 38153370 PMCID: PMC10903542 DOI: 10.1093/evolut/qpad231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 11/30/2023] [Accepted: 12/22/2023] [Indexed: 12/29/2023]
Abstract
Sexual antagonism occurs when males and females differ in their phenotypic fitness optima but are constrained in their evolution to these optima because of their shared genome. The sex chromosomes, which have distinct evolutionary "interests" relative to the autosomes, are theorized to play an important role in sexually antagonistic conflict. However, the evolutionary responses of sex chromosomes and autosomes have usually been considered independently, that is, via contrasting the response of a gene located on either an X chromosome or an autosome. Here, we study the coevolutionary response of the X chromosome and autosomes to sexually antagonistic selection acting on a polygenic phenotype. We model a phenotype initially under stabilizing selection around a single optimum, followed by a sudden divergence of the male and female optima. We find that, in the absence of dosage compensation, the X chromosome promotes evolution toward the female optimum, inducing coevolutionary male-biased responses on the autosomes. Dosage compensation obscures the female-biased interests of the X, causing it to contribute equally to male and female phenotypic change. We further demonstrate that fluctuations in an adaptive landscape can generate prolonged intragenomic conflict and accentuate the differential responses of the X and autosomes to this conflict.
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Affiliation(s)
- Pavitra Muralidhar
- Center for Population Biology, University of California, Davis, CA, United States
- Department of Evolution and Ecology, University of California, Davis, CA, United States
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, United States
| | - Graham Coop
- Center for Population Biology, University of California, Davis, CA, United States
- Department of Evolution and Ecology, University of California, Davis, CA, United States
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9
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Christensen KE, Duarte A, Ma Z, Edwards JL, Brem RB. Dissecting an ancient stress resistance trait syndrome in the compost yeast Kluyveromyces marxianus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.21.572915. [PMID: 38187519 PMCID: PMC10769334 DOI: 10.1101/2023.12.21.572915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
In the search to understand how evolution builds new traits, ancient events are often the hardest to dissect. Species-unique traits pose a particular challenge for geneticists-cases in which a character arose long ago and, in the modern day, is conserved within a species, distinguishing it from reproductively isolated relatives. In this work, we have developed the budding yeast genus Kluyveromyces as a model for mechanistic dissection of trait variation across species boundaries. Phenotypic profiling revealed robust heat and chemical-stress tolerance phenotypes that distinguished the compost yeast K. marxianus from the rest of the clade. We used culture-based, transcriptomic, and genetic approaches to characterize the metabolic requirements of the K. marxianus trait syndrome. We then generated a population-genomic resource for K. marxianus and harnessed it in molecular-evolution analyses, which found hundreds of housekeeping genes with evidence for adaptive protein variation unique to this species. Our data support a model in which, in the distant past, K. marxianus underwent a vastly complex remodeling of its proteome to achieve stress resistance. Such a polygenic architecture, involving nucleotide-level allelic variation on a massive scale, is consistent with theoretical models of the mechanisms of long-term adaptation, and suggests principles of broad relevance for interspecies trait genetics.
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Affiliation(s)
- Kaylee E. Christensen
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, 94720
| | - Abel Duarte
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, 94720
| | - Zhenzhen Ma
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, 94720
- Current address: Department of Biology, Stanford University, Stanford, CA, 94305
| | - Judith L. Edwards
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, 94720
| | - Rachel B. Brem
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, 94720
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10
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Schlötterer C. Unraveling the Molecular Basis of Stabilizing Selection by Experimental Evolution. Genome Biol Evol 2023; 15:evad220. [PMID: 38092037 PMCID: PMC10718812 DOI: 10.1093/gbe/evad220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/23/2023] [Indexed: 12/17/2023] Open
Abstract
Stabilizing selection provides a challenge to molecular population genetics. Although stabilizing selection is ubiquitous, its genomic signature is difficult to distinguish from demographic signals. Experimental evolution provides a promising approach to characterize genomic regions exposed to stabilizing selection. A recent experimental evolution study of Aedes aegypti populations evolving either with or without sexual selection found a pattern of genetic differentiation suggestive of relaxed stabilizing selection. I argue that this study could not have detected the signal of relaxed stabilizing selection. I highlight why incorrect statistical methods resulted in a high number of false positive candidate single nucleotide polymorphism (SNPs) and discuss the fallacy of functional validation of candidate SNPs for polygenic traits by RNA-mediated knockdown.
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11
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Marková S, Lanier HC, Escalante MA, da Cruz MOR, Horníková M, Konczal M, Weider LJ, Searle JB, Kotlík P. Local adaptation and future climate vulnerability in a wild rodent. Nat Commun 2023; 14:7840. [PMID: 38030627 PMCID: PMC10686993 DOI: 10.1038/s41467-023-43383-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 11/08/2023] [Indexed: 12/01/2023] Open
Abstract
As climate change continues, species pushed outside their physiological tolerance limits must adapt or face extinction. When change is rapid, adaptation will largely harness ancestral variation, making the availability and characteristics of that variation of critical importance. Here, we used whole-genome sequencing and genetic-environment association analyses to identify adaptive variation and its significance in the context of future climates in a small Palearctic mammal, the bank vole (Clethrionomys glareolus). We found that peripheral populations of bank vole in Britain are already at the extreme bounds of potential genetic adaptation and may require an influx of adaptive variation in order to respond. Analyses of adaptive loci suggest regional differences in climate variables select for variants that influence patterns of population adaptive resilience, including genes associated with antioxidant defense, and support a pattern of thermal/hypoxic cross-adaptation. Our findings indicate that understanding potential shifts in genomic composition in response to climate change may be key to predicting species' fate under future climates.
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Affiliation(s)
- Silvia Marková
- Laboratory of Molecular Ecology, Institute of Animal Physiology and Genetics of the Czech Academy of Sciences, Rumburská 89, 277 21, Liběchov, Czech Republic
| | - Hayley C Lanier
- School of Biological Sciences, University of Oklahoma, 730 Van Vleet Oval, Norman, OK, 73019, USA
- Sam Noble Museum, University of Oklahoma, 2401 Chautauqua Ave, Norman, OK, 73072, USA
| | - Marco A Escalante
- Laboratory of Molecular Ecology, Institute of Animal Physiology and Genetics of the Czech Academy of Sciences, Rumburská 89, 277 21, Liběchov, Czech Republic
| | - Marcos O R da Cruz
- School of Biological Sciences, University of Oklahoma, 730 Van Vleet Oval, Norman, OK, 73019, USA
- Sam Noble Museum, University of Oklahoma, 2401 Chautauqua Ave, Norman, OK, 73072, USA
| | - Michaela Horníková
- Laboratory of Molecular Ecology, Institute of Animal Physiology and Genetics of the Czech Academy of Sciences, Rumburská 89, 277 21, Liběchov, Czech Republic
| | - Mateusz Konczal
- Faculty of Biology, Evolutionary Biology Group, Adam Mickiewicz University, Poznań, Poland
| | - Lawrence J Weider
- School of Biological Sciences, University of Oklahoma, 730 Van Vleet Oval, Norman, OK, 73019, USA
| | - Jeremy B Searle
- Department of Ecology and Evolutionary Biology, Corson Hall, Cornell University, Ithaca, NY, 14853, USA
| | - Petr Kotlík
- Laboratory of Molecular Ecology, Institute of Animal Physiology and Genetics of the Czech Academy of Sciences, Rumburská 89, 277 21, Liběchov, Czech Republic.
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12
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Promy NT, Newberry M, Gulisija D. Rapid evolution of phenotypic plasticity in patchy habitats. Sci Rep 2023; 13:19158. [PMID: 37932330 PMCID: PMC10628295 DOI: 10.1038/s41598-023-45912-8] [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: 05/08/2023] [Accepted: 10/25/2023] [Indexed: 11/08/2023] Open
Abstract
Phenotypic plasticity may evolve rapidly, enabling a population's persistence in the face of sudden environmental change. Rapid evolution can occur when there is considerable genetic polymorphism at selected loci. We propose that balancing selection could be one of the mechanisms that sustain such polymorphism for plasticity. We use stochastic Monte Carlo simulations and deterministic analysis to investigate the evolution of a plasticity modifier locus in structured populations inhabiting favorable and adverse environments, i.e. patchy habitats. We survey a wide range of parameters including selective pressures on a target (structural) locus, plasticity effects, population sizes, and migration patterns between demes including periodic or continuous bidirectional and source-sink dynamics. We find that polymorphism in phenotypic plasticity can be maintained under a wide range of environmental scenarios in both favorable and adverse environments due to the balancing effect of population structure in patchy habitats. This effect offers a new plausible explanation for the rapid evolution of plasticity in nature: Phenotypic plasticity may rapidly evolve from genetic variation maintained by balancing selection if the population has experienced immigration from populations under different selection regimes.
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Affiliation(s)
- Nawsheen T Promy
- Department of Computer Science, University of New Mexico, Albuquerque, USA
| | - Mitchell Newberry
- Center for the Study of Complex Systems, University of Michigan, Ann Arbor, USA
- Department of Biology, University of New Mexico, 219 Yale Boulevard NE, 3566 Castetter Hall, Albuquerque, NM, 87131, USA
| | - Davorka Gulisija
- Department of Computer Science, University of New Mexico, Albuquerque, USA.
- Department of Biology, University of New Mexico, 219 Yale Boulevard NE, 3566 Castetter Hall, Albuquerque, NM, 87131, USA.
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13
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Höllinger I, Wölfl B, Hermisson J. A theory of oligogenic adaptation of a quantitative trait. Genetics 2023; 225:iyad139. [PMID: 37550847 PMCID: PMC10550320 DOI: 10.1093/genetics/iyad139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 04/20/2023] [Accepted: 07/13/2023] [Indexed: 08/09/2023] Open
Abstract
Rapid phenotypic adaptation is widespread in nature, but the underlying genetic dynamics remain controversial. Whereas population genetics envisages sequential beneficial substitutions, quantitative genetics assumes a collective response through subtle shifts in allele frequencies. This dichotomy of a monogenic and a highly polygenic view of adaptation raises the question of a middle ground, as well as the factors controlling the transition. Here, we consider an additive quantitative trait with equal locus effects under Gaussian stabilizing selection that adapts to a new trait optimum after an environmental change. We present an analytical framework based on Yule branching processes to describe how phenotypic adaptation is achieved by collective changes in allele frequencies at the underlying loci. In particular, we derive an approximation for the joint allele-frequency distribution conditioned on the trait mean as a comprehensive descriptor of the adaptive architecture. Depending on the model parameters, this architecture reproduces the well-known patterns of sequential, monogenic sweeps, or of subtle, polygenic frequency shifts. Between these endpoints, we observe oligogenic architecture types that exhibit characteristic patterns of partial sweeps. We find that a single compound parameter, the population-scaled background mutation rate Θbg, is the most important predictor of the type of adaptation, while selection strength, the number of loci in the genetic basis, and linkage only play a minor role.
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Affiliation(s)
- Ilse Höllinger
- Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
| | - Benjamin Wölfl
- Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
- Vienna Graduate School of Population Genetics, University of Vienna and Veterinary Medical University of Vienna, Vienna, Austria
- Vienna Doctoral School of Ecology and Evolution, University of Vienna, Vienna, Austria
| | - Joachim Hermisson
- Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
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14
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Gawra J, Valdivieso A, Roux F, Laporte M, de Lorgeril J, Gueguen Y, Saccas M, Escoubas JM, Montagnani C, Destoumieux-Garzόn D, Lagarde F, Leroy MA, Haffner P, Petton B, Cosseau C, Morga B, Dégremont L, Mitta G, Grunau C, Vidal-Dupiol J. Epigenetic variations are more substantial than genetic variations in rapid adaptation of oyster to Pacific oyster mortality syndrome. SCIENCE ADVANCES 2023; 9:eadh8990. [PMID: 37683000 PMCID: PMC10491289 DOI: 10.1126/sciadv.adh8990] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 08/09/2023] [Indexed: 09/10/2023]
Abstract
Disease emergence is accelerating with global changes. Understanding by which mechanisms host populations can rapidly adapt will be crucial for management practices. Pacific oyster mortality syndrome (POMS) imposes a substantial and recurrent selective pressure on oyster populations, and rapid adaptation may arise through genetics and epigenetics. In this study, we used (epi)genome-wide association mapping to show that oysters differentially exposed to POMS displayed genetic and epigenetic signatures of selection. Consistent with higher resistance to POMS, the genes targeted included many genes in several pathways related to immunity. By combining correlation, DNA methylation quantitative trait loci, and variance partitioning, we revealed that a third of phenotypic variation was explained by interactions between the genetic and epigenetic information, ~14% by the genome, and up to 25% by the epigenome alone. Similar to genetically based adaptation, epigenetic mechanisms notably governing immune responses can contribute substantially to the rapid adaptation of hosts to emerging infectious diseases.
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Affiliation(s)
- Janan Gawra
- IHPE, Université de Perpignan Via Domitia, CNRS, Ifremer, Université de Montpellier, Perpignan, France
| | - Alejandro Valdivieso
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
| | - Fabrice Roux
- LIPME, INRAE, CNRS, Université de Toulouse, Castanet-Tolosan, France
| | - Martin Laporte
- Division de l'expertise sur la faune Aquatique, Ministère des Forêts, de la Faune et des Parcs (MFFP), 880 chemin Sainte-Foy, G1S 4X4 Québec, Québec, Canada
| | - Julien de Lorgeril
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
- Ifremer, IRD, Université de la Nouvelle-Calédonie, Université de La Réunion, ENTROPIE, Nouméa, Nouvelle-Calédonie, France
| | - Yannick Gueguen
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
- MARBEC, Université de Montpellier, CNRS, Ifremer, IRD, Sète, France
| | - Mathilde Saccas
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
| | - Jean-Michel Escoubas
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
| | - Caroline Montagnani
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
| | | | - Franck Lagarde
- MARBEC, Université de Montpellier, CNRS, Ifremer, IRD, Sète, France
| | - Marc A. Leroy
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
| | - Philippe Haffner
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
| | - Bruno Petton
- Université de Brest, Ifremer, CNRS, IRD, LEMAR, F-29280 Plouzané, France
| | - Céline Cosseau
- IHPE, Université de Perpignan Via Domitia, CNRS, Ifremer, Université de Montpellier, Perpignan, France
| | - Benjamin Morga
- Ifremer, ASIM, Adaptation Santé des Invertébrés Marins, La Tremblade, France
| | - Lionel Dégremont
- Ifremer, ASIM, Adaptation Santé des Invertébrés Marins, La Tremblade, France
| | - Guillaume Mitta
- IHPE, Université de Perpignan Via Domitia, CNRS, Ifremer, Université de Montpellier, Perpignan, France
- Université de la Polynésie Française, ILM, IRD, Ifremer, F-98719 Tahiti, French Polynesia, France
| | - Christoph Grunau
- IHPE, Université de Perpignan Via Domitia, CNRS, Ifremer, Université de Montpellier, Perpignan, France
| | - Jeremie Vidal-Dupiol
- IHPE, Université de Montpellier, CNRS, Ifremer, Université de Perpignan Via Domitia, Montpellier, France
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15
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Neto C, Hancock A. Genetic Architecture of Flowering Time Differs Between Populations With Contrasting Demographic and Selective Histories. Mol Biol Evol 2023; 40:msad185. [PMID: 37603463 PMCID: PMC10461413 DOI: 10.1093/molbev/msad185] [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: 03/29/2023] [Revised: 08/09/2023] [Accepted: 08/10/2023] [Indexed: 08/23/2023] Open
Abstract
Understanding the evolutionary factors that impact the genetic architecture of traits is a central goal of evolutionary genetics. Here, we investigate how quantitative trait variation accumulated over time in populations that colonized a novel environment. We compare the genetic architecture of flowering time in Arabidopsis populations from the drought-prone Cape Verde Islands and their closest outgroup population from North Africa. We find that trait polygenicity is severely reduced in the island populations compared to the continental North African population. Further, trait architectures and reconstructed allelic histories best fit a model of strong directional selection in the islands in accord with a Fisher-Orr adaptive walk. Consistent with this, we find that large-effect variants that disrupt major flowering time genes (FRI and FLC) arose first, followed by smaller effect variants, including ATX2 L125F, which is associated with a 4-day reduction in flowering time. The most recently arising flowering time-associated loci are not known to be directly involved in flowering time, consistent with an omnigenic signature developing as the population approaches its trait optimum. Surprisingly, we find no effect in the natural population of EDI-Cvi-0 (CRY2 V367M), an allele for which an effect was previously validated by introgression into a Eurasian line. Instead, our results suggest the previously observed effect of the EDI-Cvi-0 allele on flowering time likely depends on genetic background, due to an epistatic interaction. Altogether, our results provide an empirical example of the effects demographic history and selection has on trait architecture.
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Affiliation(s)
- Célia Neto
- Molecular Basis of Adaptation Research Group, Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | - Angela Hancock
- Molecular Basis of Adaptation Research Group, Max Planck Institute for Plant Breeding Research, Cologne, Germany
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16
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Veller C, Coop G. Interpreting population and family-based genome-wide association studies in the presence of confounding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.26.530052. [PMID: 36909521 PMCID: PMC10002712 DOI: 10.1101/2023.02.26.530052] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding, and can also absorb the 'indirect' genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of Mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect size estimates are used in polygenic scores. We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. In addition to known biases that can arise in family-based GWASs when interactions between family members are ignored, we show that biases can also arise from gene-by-environment (G×E) interactions when parental genotypes are not distributed identically across interacting environmental and genetic backgrounds. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding and interactions.
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Affiliation(s)
- Carl Veller
- Department of Evolution and Ecology, and Center for Population Biology, University of California, Davis, CA 95616
| | - Graham Coop
- Department of Evolution and Ecology, and Center for Population Biology, University of California, Davis, CA 95616
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17
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Devi A, Jain K. Polygenic adaptation dynamics in large, finite populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.525607. [PMID: 36747829 PMCID: PMC9901025 DOI: 10.1101/2023.01.25.525607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Although many phenotypic traits are determined by a large number of genetic variants, how a polygenic trait adapts in response to a change in the environment is not completely understood. In the framework of diffusion theory, we study the steady state and the adaptation dynamics of a large but finite population evolving under stabilizing selection and symmetric mutations when selection and mutation are moderately large. We find that in the stationary state, the allele frequency distribution at a locus is unimodal if its effect size is below a threshold effect and bimodal otherwise; these results are the stochastic analog of the deterministic ones where the stable allele frequency becomes bistable when the effect size exceeds a threshold. It is known that following a sudden shift in the phenotypic optimum, in an infinitely large population, selective sweeps at a large-effect locus are prevented and adaptation proceeds exclusively via subtle changes in the allele frequency; in contrast, we find that the chance of sweep is substantially enhanced in large, finite populations and the allele frequency at a large-effect locus can reach a high frequency at short times even for small shifts in the phenotypic optimum.
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Affiliation(s)
- Archana Devi
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA
| | - Kavita Jain
- Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore 560064, India
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18
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Hämälä T, Ning W, Kuittinen H, Aryamanesh N, Savolainen O. Environmental response in gene expression and DNA methylation reveals factors influencing the adaptive potential of Arabidopsis lyrata. eLife 2022; 11:83115. [PMID: 36306157 PMCID: PMC9616567 DOI: 10.7554/elife.83115] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 10/12/2022] [Indexed: 11/13/2022] Open
Abstract
Understanding what factors influence plastic and genetic variation is valuable for predicting how organisms respond to changes in the selective environment. Here, using gene expression and DNA methylation as molecular phenotypes, we study environmentally induced variation among Arabidopsis lyrata plants grown at lowland and alpine field sites. Our results show that gene expression is highly plastic, as many more genes are differentially expressed between the field sites than between populations. These environmentally responsive genes evolve under strong selective constraint – the strength of purifying selection on the coding sequence is high, while the rate of adaptive evolution is low. We find, however, that positive selection on cis-regulatory variants has likely contributed to the maintenance of genetically variable environmental responses, but such variants segregate only between distantly related populations. In contrast to gene expression, DNA methylation at genic regions is largely insensitive to the environment, and plastic methylation changes are not associated with differential gene expression. Besides genes, we detect environmental effects at transposable elements (TEs): TEs at the high-altitude field site have higher expression and methylation levels, suggestive of a broad-scale TE activation. Compared to the lowland population, plants native to the alpine environment harbor an excess of recent TE insertions, and we observe that specific TE families are enriched within environmentally responsive genes. Our findings provide insight into selective forces shaping plastic and genetic variation. We also highlight how plastic responses at TEs can rapidly create novel heritable variation in stressful conditions.
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Affiliation(s)
- Tuomas Hämälä
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Weixuan Ning
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Helmi Kuittinen
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Nader Aryamanesh
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Outi Savolainen
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
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19
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Arnqvist G, Sayadi A. A possible genomic footprint of polygenic adaptation on population divergence in seed beetles? Ecol Evol 2022; 12:e9440. [PMID: 36311399 PMCID: PMC9608792 DOI: 10.1002/ece3.9440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 09/14/2022] [Accepted: 09/29/2022] [Indexed: 11/25/2022] Open
Abstract
Efforts to unravel the genomic basis of incipient speciation are hampered by a mismatch between our toolkit and our understanding of the ecology and genetics of adaptation. While the former is focused on detecting selective sweeps involving few independently acting or linked speciation genes, the latter states that divergence typically occurs in polygenic traits under stabilizing selection. Here, we ask whether a role of stabilizing selection on polygenic traits in population divergence may be unveiled by using a phenotypically informed integrative approach, based on genome‐wide variation segregating in divergent populations. We compare three divergent populations of seed beetles (Callosobruchus maculatus) where previous work has demonstrated a prominent role for stabilizing selection on, and population divergence in, key life history traits that reflect rate‐dependent metabolic processes. We derive and assess predictions regarding the expected pattern of covariation between genetic variation segregating within populations and genetic differentiation between populations. Population differentiation was considerable (mean FST = 0.23–0.26) and was primarily built by genes showing high selective constraints and an imbalance in inferred selection in different populations (positive Tajima's DNS in one and negative in one), and this set of genes was enriched with genes with a metabolic function. Repeatability of relative population differentiation was low at the level of individual genes but higher at the level of broad functional classes, again spotlighting metabolic genes. Absolute differentiation (dXY) showed a very different general pattern at this scale of divergence, more consistent with an important role for genetic drift. Although our exploration is consistent with stabilizing selection on polygenic metabolic phenotypes as an important engine of genome‐wide relative population divergence and incipient speciation in our study system, we note that it is exceedingly difficult to firmly exclude other scenarios.
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Affiliation(s)
- Göran Arnqvist
- Animal Ecology, Department of Ecology and Genetics, EBCUppsala UniversityUppsalaSweden
| | - Ahmed Sayadi
- Animal Ecology, Department of Ecology and Genetics, EBCUppsala UniversityUppsalaSweden,Rheumatology, Department of Medical SciencesUppsala UniversityUppsalaSweden
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20
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Hayward LK, Sella G. Polygenic adaptation after a sudden change in environment. eLife 2022; 11:66697. [PMID: 36155653 PMCID: PMC9683794 DOI: 10.7554/elife.66697] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/18/2022] [Indexed: 11/13/2022] Open
Abstract
Polygenic adaptation is thought to be ubiquitous, yet remains poorly understood. Here, we model this process analytically, in the plausible setting of a highly polygenic, quantitative trait that experiences a sudden shift in the fitness optimum. We show how the mean phenotype changes over time, depending on the effect sizes of loci that contribute to variance in the trait, and characterize the allele dynamics at these loci. Notably, we describe the two phases of the allele dynamics: The first is a rapid phase, in which directional selection introduces small frequency differences between alleles whose effects are aligned with or opposed to the shift, ultimately leading to small differences in their probability of fixation during a second, longer phase, governed by stabilizing selection. As we discuss, key results should hold in more general settings and have important implications for efforts to identify the genetic basis of adaptation in humans and other species.
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Affiliation(s)
- Laura Katharine Hayward
- Department of Mathematics, Columbia UniversityNew YorkUnited States,Institute of Science and TechnologyMaria GuggingAustria
| | - Guy Sella
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States,Program for Mathematical Genomics, Columbia UniversityNew YorkUnited States
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