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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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2
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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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3
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Lee CE. Genome architecture underlying salinity adaptation in the invasive copepod Eurytemora affinis species complex: A review. iScience 2023; 26:107851. [PMID: 37752947 PMCID: PMC10518491 DOI: 10.1016/j.isci.2023.107851] [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] [Indexed: 09/28/2023] Open
Abstract
With climate change, habitat salinity is shifting rapidly throughout the globe. In addition, many destructive freshwater invaders are recent immigrants from saline habitats. Recently, populations of the copepod Eurytemora affinis species complex have invaded freshwater habitats multiple times independently from saline estuaries on three continents. This review discusses features of this species complex that could enhance their evolutionary potential during rapid environmental change. Remarkably, across independent freshwater invasions, natural selection has repeatedly favored the same alleles far more than expected. This high degree of parallelism is surprising, given the expectation of nonparallel evolution for polygenic adaptation. Factors such as population structure and the genome architecture underlying critical traits under selection might help drive rapid adaptation and parallel evolution. Given the preponderance of saline-to-freshwater invasions and climate-induced salinity change, the principles found here could provide invaluable insights into mechanisms operating in other systems and the potential for adaptation in a changing planet.
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Affiliation(s)
- Carol Eunmi Lee
- Department of Integrative Biology, University of Wisconsin, 430 Lincoln Drive, Birge Hall, Madison, WI 53706, USA
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4
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Tavares H, Readshaw A, Kania U, de Jong M, Pasam RK, McCulloch H, Ward S, Shenhav L, Forsyth E, Leyser O. Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis. PLoS Genet 2023; 19:e1010863. [PMID: 37616321 PMCID: PMC10482290 DOI: 10.1371/journal.pgen.1010863] [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: 06/18/2022] [Revised: 09/06/2023] [Accepted: 07/08/2023] [Indexed: 08/26/2023] Open
Abstract
Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.
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Affiliation(s)
- Hugo Tavares
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Anne Readshaw
- Department of Biology, University of York, York, United Kingdom
| | - Urszula Kania
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Maaike de Jong
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Raj K. Pasam
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Hayley McCulloch
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Sally Ward
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
- Department of Biology, University of York, York, United Kingdom
| | - Liron Shenhav
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Elizabeth Forsyth
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Ottoline Leyser
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
- Department of Biology, University of York, York, United Kingdom
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5
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Steyn Y, Lawlor T, Masuda Y, Tsuruta S, Legarra A, Lourenco D, Misztal I. Nonparallel genome changes within subpopulations over time contributed to genetic diversity within the US Holstein population. J Dairy Sci 2023; 106:2551-2572. [PMID: 36797192 DOI: 10.3168/jds.2022-21914] [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: 02/01/2022] [Accepted: 10/03/2022] [Indexed: 02/16/2023]
Abstract
Maintaining genetic variation in a population is important for long-term genetic gain. The existence of subpopulations within a breed helps maintain genetic variation and diversity. The 20,990 genotyped animals, representing the breeding animals in the year 2014, were identified as the sires of animals born after 2010 with at least 25 progenies, and females measured for type traits within the last 2 yr of data. K-means clustering with 5 clusters (C1, C2, C3, C4, and C5) was applied to the genomic relationship matrix based on 58,990 SNP markers to stratify the selected candidates into subpopulations. The general higher inbreeding resulting from within-cluster mating than across-cluster mating suggests the successful stratification into genetically different groups. The largest cluster (C4) contained animals that were less related to each animal within and across clusters. The average fixation index was 0.03, indicating that the populations were differentiated, and allele differences across the subpopulations were not due to drift alone. Starting with the selected candidates within each cluster, a family unit was identified by tracing back through the pedigree, identifying the genotyped ancestors, and assigning them to a pseudogeneration. Each of the 5 families (F1, F2, F3, F4, and F5) was traced back for 10 generations, allowing for changes in frequency of individual SNPs over time to be observed, which we call allele frequencies change. Alternative procedures were used to identify SNPs changing in a parallel or nonparallel way across families. For example, markers that have changed the most in the whole population, markers that have changed differently across families, and genes previously identified as those that have changed in allele frequency. The genomic trajectory taken by each family involves selective sweeps, polygenic changes, hitchhiking, and epistasis. The replicate frequency spectrum was used to measure the similarity of change across families and showed that populations have changed differently. The proportion of markers that reversed direction in allele frequency change varied from 0.00 to 0.02 if the rate of change was greater than 0.02 per generation, or from 0.14 to 0.24 if the rate of change was greater than 0.005 per generation within each family. Cluster-specific SNP effects for stature were estimated using only females and applied to obtain indirect genomic predictions for males. Reranking occurs depending on SNP effects used. Additive genetic correlations between clusters show possible differences in populations. Further research is required to determine how this knowledge can be applied to maintain diversity and optimize selection decisions in the future.
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Affiliation(s)
- Y Steyn
- Department of Animal and Dairy Science, University of Georgia, 425 River Road, Athens 30602.
| | - T Lawlor
- Holstein Association USA Inc., Brattleboro, VT 05302
| | - Y Masuda
- Department of Animal and Dairy Science, University of Georgia, 425 River Road, Athens 30602
| | - S Tsuruta
- Department of Animal and Dairy Science, University of Georgia, 425 River Road, Athens 30602
| | - A Legarra
- GenPhySE, INRA, INPT, ENVT, Université de Toulouse, Castanet-Tolosan 31520, France
| | - D Lourenco
- Department of Animal and Dairy Science, University of Georgia, 425 River Road, Athens 30602
| | - I Misztal
- Department of Animal and Dairy Science, University of Georgia, 425 River Road, Athens 30602
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6
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Genome-wide signatures of synergistic epistasis during parallel adaptation in a Baltic Sea copepod. Nat Commun 2022; 13:4024. [PMID: 35821220 PMCID: PMC9276764 DOI: 10.1038/s41467-022-31622-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 06/27/2022] [Indexed: 01/01/2023] Open
Abstract
The role of epistasis in driving adaptation has remained an unresolved problem dating back to the Evolutionary Synthesis. In particular, whether epistatic interactions among genes could promote parallel evolution remains unexplored. To address this problem, we employ an Evolve and Resequence (E&R) experiment, using the copepod Eurytemora affinis, to elucidate the evolutionary genomic response to rapid salinity decline. Rapid declines in coastal salinity at high latitudes are a predicted consequence of global climate change. Based on time-resolved pooled whole-genome sequencing, we uncover a remarkably parallel, polygenic response across ten replicate selection lines, with 79.4% of selected alleles shared between lines by the tenth generation of natural selection. Using extensive computer simulations of our experiment conditions, we find that this polygenic parallelism is consistent with positive synergistic epistasis among alleles, far more so than other mechanisms tested. Our study provides experimental and theoretical support for a novel mechanism promoting repeatable polygenic adaptation, a phenomenon that may be common for selection on complex physiological traits. Using time-series whole-genome sequencing data from a laboratory evolution experiment, along with extensive computer simulations, the authors show that synergistic epistasis could drive rapid parallel freshwater adaptation in a saline copepod.
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7
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Saleh D, Chen J, Leplé J, Leroy T, Truffaut L, Dencausse B, Lalanne C, Labadie K, Lesur I, Bert D, Lagane F, Morneau F, Aury J, Plomion C, Lascoux M, Kremer A. Genome-wide evolutionary response of European oaks during the Anthropocene. Evol Lett 2022; 6:4-20. [PMID: 35127134 PMCID: PMC8802238 DOI: 10.1002/evl3.269] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 11/26/2021] [Accepted: 12/02/2021] [Indexed: 12/23/2022] Open
Abstract
The pace of tree microevolution during Anthropocene warming is largely unknown. We used a retrospective approach to monitor genomic changes in oak trees since the Little Ice Age (LIA). Allelic frequency changes were assessed from whole-genome pooled sequences for four age-structured cohorts of sessile oak (Quercus petraea) dating back to 1680, in each of three different oak forests in France. The genetic covariances of allelic frequency changes increased between successive time periods, highlighting genome-wide effects of linked selection. We found imprints of parallel linked selection in the three forests during the late LIA, and a shift of selection during more recent time periods of the Anthropocene. The changes in allelic covariances within and between forests mirrored the documented changes in the occurrence of extreme events (droughts and frosts) over the last 300 years. The genomic regions with the highest covariances were enriched in genes involved in plant responses to pathogens and abiotic stresses (temperature and drought). These responses are consistent with the reported sequence of frost (or drought) and disease damage ultimately leading to the oak dieback after extreme events. They provide support for adaptive evolution of long-lived species during recent climatic changes. Although we acknowledge that other sources (e.g., gene flow, generation overlap) may have contributed to temporal covariances of allelic frequency changes, the consistent and correlated response across the three forests lends support to the existence of a systematic driving force such as natural selection.
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Affiliation(s)
- Dounia Saleh
- UMR BIOGECO, INRAEUniversité de BordeauxCestas33612France
| | - Jun Chen
- College of Life SciencesZhejiang UniversityHangzhou310058China
| | | | - Thibault Leroy
- Department of Botany and Biodiversity ResearchUniversity of ViennaVienna1010Austria
| | - Laura Truffaut
- UMR BIOGECO, INRAEUniversité de BordeauxCestas33612France
| | | | - Céline Lalanne
- UMR BIOGECO, INRAEUniversité de BordeauxCestas33612France
| | - Karine Labadie
- Genoscope, Institut de Biologie François Jacob, Commissariat à l’énergie atomique (CEA)Université de Paris‐SaclayEvry91057France
| | | | - Didier Bert
- UMR BIOGECO, INRAEUniversité de BordeauxCestas33612France
| | | | - François Morneau
- Département Recherche Développement InnovationOffice National des ForêtsBoigny‐Sur‐Bionne45760France,Current Address: Service de l'Information Statistique Forestière et EnvironnementaleInstitut National de l'Information géographique et ForestièreNogent‐sur‐Vernisson45290France
| | - Jean‐Marc Aury
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRSUniv Evry, Université Paris‐SaclayEvry91057France
| | | | - Martin Lascoux
- Department of Ecology and Genetics, Evolutionary Biology CentreUppsala UniversityUppsalaSE‐75236Sweden
| | - Antoine Kremer
- UMR BIOGECO, INRAEUniversité de BordeauxCestas33612France
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8
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Mazzucco R, Schlötterer C. Long-term gut microbiome dynamics in Drosophila melanogaster reveal environment-specific associations between bacterial taxa at the family level. Proc Biol Sci 2021; 288:20212193. [PMID: 34905708 PMCID: PMC8670958 DOI: 10.1098/rspb.2021.2193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The influence of the microbiome on its host is well-documented, but the interplay of its members is not yet well-understood. Even for simple microbiomes, the interaction among members of the microbiome is difficult to study. Longitudinal studies provide a promising approach to studying such interactions through the temporal covariation of different taxonomic units. By contrast to most longitudinal studies, which span only a single host generation, we here present a post hoc analysis of a whole-genome dataset of 81 samples that follows microbiome composition for up to 180 host generations, which cover nearly 10 years. The microbiome diversity remained rather stable in replicated Drosophila melanogaster populations exposed to two different temperature regimes. The composition changed, however, systematically across replicates of the two temperature regimes. Significant associations between families, mostly specific to one temperature regime, indicate functional interdependence of different microbiome components. These associations also involve moderately abundant families, which emphasizes their functional importance, and highlights the importance of looking beyond the common constituents of the Drosophila microbiome.
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Affiliation(s)
- Rupert Mazzucco
- Institut für Populationsgenetik, Veterinärmedizinische Universität Wien, Veterinärplatz 1, Wien 1210, Austria
| | - Christian Schlötterer
- Institut für Populationsgenetik, Veterinärmedizinische Universität Wien, Veterinärplatz 1, Wien 1210, Austria
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9
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Lai WY, Schlötterer C. Evolution of phenotypic variance in response to a novel hot environment. Mol Ecol 2021; 31:934-945. [PMID: 34775658 DOI: 10.1111/mec.16274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 10/21/2021] [Accepted: 11/05/2021] [Indexed: 12/13/2022]
Abstract
Shifts in trait means are widely considered as evidence for adaptive responses, but the impact on phenotypic variance remains largely unexplored. Classic quantitative genetics provides a theoretical framework to predict how selection on phenotypic mean affects the variance. In addition to this indirect effect, it is also possible that the variance of the trait is the direct target of selection, but experimentally characterized cases are rare. Here, we studied gene expression variance of Drosophila simulans males before and after 100 generations of adaptation to a novel hot laboratory environment. In each of the two independently evolved populations, the variance of 125 and 97 genes was significantly reduced. We propose that the drastic loss in environmental complexity from nature to the laboratory may have triggered selection for reduced variance. Our observation that selection could drive changes in the variance of gene expression could have important implications for studies of adaptation processes in natural and experimental populations.
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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
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10
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Burny C, Nolte V, Dolezal M, Schlötterer C. Highly Parallel Genomic Selection Response in Replicated Drosophila melanogaster Populations with Reduced Genetic Variation. Genome Biol Evol 2021; 13:6409861. [PMID: 34694407 PMCID: PMC8599828 DOI: 10.1093/gbe/evab239] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2021] [Indexed: 12/12/2022] Open
Abstract
Many adaptive traits are polygenic and frequently more loci contributing to the phenotype are segregating than needed to express the phenotypic optimum. Experimental evolution with replicated populations adapting to a new controlled environment provides a powerful approach to study polygenic adaptation. Because genetic redundancy often results in nonparallel selection responses among replicates, we propose a modified evolve and resequence (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred Drosophila melanogaster strains and expose them to a very extreme, hot temperature environment (29 °C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Because two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.
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Affiliation(s)
- Claire Burny
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria.,Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria
| | - Marlies Dolezal
- Plattform Bioinformatik und Biostatistik, Vetmeduni Vienna, Wien, Austria
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11
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Otte KA, Nolte V, Mallard F, Schlötterer C. The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime. Genome Biol 2021; 22:211. [PMID: 34271951 PMCID: PMC8285869 DOI: 10.1186/s13059-021-02425-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 06/29/2021] [Indexed: 12/28/2022] Open
Abstract
Background Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates. Results Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime. Conclusions These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02425-9.
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Affiliation(s)
- Kathrin A Otte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institute for Zoology, University of Cologne, Cologne, Germany
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - François Mallard
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institut de Biologie de l'École Normale Supérieure, CNRS UMR 8197, Inserm U1024, PSL Research University, F-75005, Paris, France
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12
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Blanckaert A, Payseur BA. Finding hybrid incompatibilities using genome sequences from hybrid populations. Mol Biol Evol 2021; 38:4616-4627. [PMID: 34097068 PMCID: PMC8476132 DOI: 10.1093/molbev/msab168] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Natural hybrid zones offer a powerful framework for understanding the genetic basis of speciation in progress because ongoing hybridization continually creates unfavorable gene combinations. Evidence indicates that postzygotic reproductive isolation is often caused by epistatic interactions between mutations in different genes that evolved independently of one another (hybrid incompatibilities). We examined the potential to detect epistatic selection against incompatibilities from genome sequence data using the site frequency spectrum (SFS) of polymorphisms by conducting individual-based simulations in SLiM. We found that the genome-wide SFS in hybrid populations assumes a diagnostic shape, with the continual input of fixed differences between source populations via migration inducing a mass at intermediate allele frequency. Epistatic selection locally distorts the SFS as non-incompatibility alleles rise in frequency in a manner analogous to a selective sweep. Building on these results, we present a statistical method to identify genomic regions containing incompatibility loci that locates departures in the local SFS compared with the genome-wide SFS. Cross-validation studies demonstrate that our method detects recessive and codominant incompatibilities across a range of scenarios varying in the strength of epistatic selection, migration rate, and hybrid zone age. Our approach takes advantage of whole genome sequence data, does not require knowledge of demographic history, and can be applied to any pair of nascent species that forms a hybrid zone.
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Affiliation(s)
- Alexandre Blanckaert
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, United States
| | - Bret A Payseur
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, United States
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13
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Tusso S, Nieuwenhuis BPS, Weissensteiner B, Immler S, Wolf JBW. Experimental evolution of adaptive divergence under varying degrees of gene flow. Nat Ecol Evol 2021; 5:338-349. [PMID: 33432131 DOI: 10.1038/s41559-020-01363-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 11/12/2020] [Indexed: 01/28/2023]
Abstract
Adaptive divergence is the key evolutionary process generating biodiversity by means of natural selection. Yet, the conditions under which it can arise in the presence of gene flow remain contentious. To address this question, we subjected 132 sexually reproducing fission yeast populations, sourced from two independent genetic backgrounds, to disruptive ecological selection and manipulated the level of migration between environments. Contrary to theoretical expectations, adaptive divergence was most pronounced when migration was either absent (allopatry) or maximal (sympatry), but was much reduced at intermediate rates (parapatry and local mating). This effect was apparent across central life-history components (survival, asexual growth and mating) but differed in magnitude between ancestral genetic backgrounds. The evolution of some fitness components was constrained by pervasive negative correlations (trade-off between asexual growth and mating), while others changed direction under the influence of migration (for example, survival and mating). In allopatry, adaptive divergence was mainly conferred by standing genetic variation and resulted in ecological specialization. In sympatry, divergence was mainly mediated by novel mutations enriched in a subset of genes and was characterized by the repeated emergence of two strategies: an ecological generalist and an asexual growth specialist. Multiple loci showed consistent evidence for antagonistic pleiotropy across migration treatments providing a conceptual link between adaptation and divergence. This evolve-and-resequence experiment shows that rapid ecological differentiation can arise even under high rates of gene flow. It further highlights that adaptive trajectories are governed by complex interactions of gene flow, ancestral variation and genetic correlations.
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Affiliation(s)
- Sergio Tusso
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany. .,Science for Life Laboratory, Uppsala University, Uppsala, Sweden. .,Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden.
| | - Bart P S Nieuwenhuis
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany
| | - Bernadette Weissensteiner
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany
| | - Simone Immler
- Science for Life Laboratory, Uppsala University, Uppsala, Sweden.,Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden.,School of Biological Sciences, University of East Anglia, Norwich, UK
| | - Jochen B W Wolf
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany. .,Science for Life Laboratory, Uppsala University, Uppsala, Sweden. .,Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden.
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14
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Burny C, Nolte V, Nouhaud P, Dolezal M, Schlötterer C. Secondary Evolve and Resequencing: An Experimental Confirmation of Putative Selection Targets without Phenotyping. Genome Biol Evol 2021; 12:151-159. [PMID: 32159748 PMCID: PMC7144549 DOI: 10.1093/gbe/evaa036] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Evolve and resequencing (E&R) studies investigate the genomic responses of adaptation during experimental evolution. Because replicate populations evolve in the same controlled environment, consistent responses to selection across replicates are frequently used to identify reliable candidate regions that underlie adaptation to a new environment. However, recent work demonstrated that selection signatures can be restricted to one or a few replicate(s) only. These selection signatures frequently have weak statistical support, and given the difficulties of functional validation, additional evidence is needed before considering them as candidates for functional analysis. Here, we introduce an experimental procedure to validate candidate loci with weak or replicate-specific selection signature(s). Crossing an evolved population from a primary E&R experiment to the ancestral founder population reduces the frequency of candidate alleles that have reached a high frequency. We hypothesize that genuine selection targets will experience a repeatable frequency increase after the mixing with the ancestral founders if they are exposed to the same environment (secondary E&R experiment). Using this approach, we successfully validate two overlapping selection targets, which showed a mutually exclusive selection signature in a primary E&R experiment of Drosophila simulans adapting to a novel temperature regime. We conclude that secondary E&R experiments provide a reliable confirmation of selection signatures that either are not replicated or show only a low statistical significance in a primary E&R experiment unless epistatic interactions predominate. Such experiments are particularly helpful to prioritize candidate loci for time-consuming functional follow-up investigations.
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Affiliation(s)
- Claire Burny
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria.,Vienna Graduate school of Population Genetics, Vetmeduni Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria
| | - Pierre Nouhaud
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria
| | - Marlies Dolezal
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria.,Plattform Bioinformatik und Biostatistik, Vetmeduni Vienna, Austria
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15
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Otte KA, Schlötterer C. Detecting selected haplotype blocks in evolve and resequence experiments. Mol Ecol Resour 2020; 21:93-109. [PMID: 32810339 PMCID: PMC7754423 DOI: 10.1111/1755-0998.13244] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 07/30/2020] [Accepted: 08/04/2020] [Indexed: 12/15/2022]
Abstract
Shifting from the analysis of single nucleotide polymorphisms to the reconstruction of selected haplotypes greatly facilitates the interpretation of evolve and resequence (E&R) experiments. Merging highly correlated hitchhiker SNPs into haplotype blocks reduces thousands of candidates to few selected regions. Current methods of haplotype reconstruction from Pool‐seq data need a variety of data‐specific parameters that are typically defined ad hoc and require haplotype sequences for validation. Here, we introduce haplovalidate, a tool which detects selected haplotypes in Pool‐seq time series data without the need for sequenced haplotypes. Haplovalidate makes data‐driven choices of two key parameters for the clustering procedure, the minimum correlation between SNPs constituting a cluster and the window size. Applying haplovalidate to simulated E&R data reliably detects selected haplotype blocks with low false discovery rates. Importantly, our analyses identified a restriction of the haplotype block‐based approach to describe the genomic architecture of adaptation. We detected a substantial fraction of haplotypes containing multiple selection targets. These blocks were considered as one region of selection and therefore led to underestimation of the number of selection targets. We demonstrate that the separate analysis of earlier time points can significantly increase the separation of selection targets into individual haplotype blocks. We conclude that the analysis of selected haplotype blocks has great potential for the characterization of the adaptive architecture with E&R experiments.
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Affiliation(s)
- Kathrin A Otte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
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16
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The Effects of Quantitative Trait Architecture on Detection Power in Short-Term Artificial Selection Experiments. G3-GENES GENOMES GENETICS 2020; 10:3213-3227. [PMID: 32646912 PMCID: PMC7466968 DOI: 10.1534/g3.120.401287] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Evolve and resequence (E&R) experiments, in which artificial selection is imposed on organisms in a controlled environment, are becoming an increasingly accessible tool for studying the genetic basis of adaptation. Previous work has assessed how different experimental design parameters affect the power to detect the quantitative trait loci (QTL) that underlie adaptive responses in such experiments, but so far there has been little exploration of how this power varies with the genetic architecture of the evolving traits. In this study, we use forward simulation to build a more realistic model of an E&R experiment in which a quantitative polygenic trait experiences a short, but strong, episode of truncation selection. We study the expected power for QTL detection in such an experiment and how this power is influenced by different aspects of trait architecture, including the number of QTL affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of these parameters can affect allele frequency dynamics at the QTL and linked loci in complex and often unintuitive ways, and thus influence our power to detect them. One consequence of this is that existing detection methods based on models of independent selective sweeps at individual QTL often have lower detection power than a simple measurement of allele frequency differences before and after selection. Our findings highlight the importance of taking trait architecture into account when designing and interpreting studies of molecular adaptation with temporal data. We provide a customizable modeling framework that will enable researchers to easily simulate E&R experiments with different trait architectures and parameters tuned to their specific study system, allowing for assessment of expected detection power and optimization of experimental design.
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17
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Polygenic adaptation: a unifying framework to understand positive selection. Nat Rev Genet 2020; 21:769-781. [DOI: 10.1038/s41576-020-0250-z] [Citation(s) in RCA: 144] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/12/2020] [Indexed: 12/20/2022]
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18
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Barghi N, Schlötterer C. Distinct Patterns of Selective Sweep and Polygenic Adaptation in Evolve and Resequence Studies. Genome Biol Evol 2020; 12:890-904. [PMID: 32282913 PMCID: PMC7313669 DOI: 10.1093/gbe/evaa073] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/07/2020] [Indexed: 12/15/2022] Open
Abstract
In molecular population genetics, adaptation is typically thought to occur via selective sweeps, where targets of selection have independent effects on the phenotype and rise to fixation, whereas in quantitative genetics, many loci contribute to the phenotype and subtle frequency changes occur at many loci during polygenic adaptation. The sweep model makes specific predictions about frequency changes of beneficial alleles and many test statistics have been developed to detect such selection signatures. Despite polygenic adaptation is probably the prevalent mode of adaptation, because of the traditional focus on the phenotype, we are lacking a solid understanding of the similarities and differences of selection signatures under the two models. Recent theoretical and empirical studies have shown that both selective sweep and polygenic adaptation models could result in a sweep-like genomic signature; therefore, additional criteria are needed to distinguish the two models. With replicated populations and time series data, experimental evolution studies have the potential to identify the underlying model of adaptation. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles for two models: 1) adaptation of a trait via independent beneficial mutations that are conditioned for fixation, that is, selective sweep model and 2) trait optimum model (polygenic adaptation), that is adaptation of a quantitative trait under stabilizing selection after a sudden shift in trait optimum. We identify several distinct patterns of selective sweep and trait optimum models in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two models.
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Affiliation(s)
- Neda Barghi
- Institut für Populationsgenetik, Vetmeduni, Vienna, Austria
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19
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Pfenninger M, Foucault Q. Genomic processes underlying rapid adaptation of a natural
Chironomus riparius
population to unintendedly applied experimental selection pressures. Mol Ecol 2020; 29:536-548. [DOI: 10.1111/mec.15347] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 12/13/2019] [Accepted: 12/24/2019] [Indexed: 12/15/2022]
Affiliation(s)
- Markus Pfenninger
- Department of Molecular Ecology Senckenberg Biodiversity and Climate Research Centre Frankfurt am Main Germany
- Institute for Molecular and Organismic Evolution Johannes Gutenberg University Mainz Germany
- LOEWE Centre for Translational Biodiversity Genomics Senckenberg Biodiversity and Climate Research Centre Frankfurt am Main Germany
| | - Quentin Foucault
- Department of Molecular Ecology Senckenberg Biodiversity and Climate Research Centre Frankfurt am Main Germany
- Institute for Molecular and Organismic Evolution Johannes Gutenberg University Mainz Germany
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20
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Abstract
Maize is an excellent model for the study of plant adaptation. Indeed, post domestication maize quickly adapted to a host of new environments across the globe. And work over the last decade has begun to highlight the role of the wild relatives of maize-the teosintes Zea mays ssp. parviglumis and ssp. mexicana-as excellent models for dissecting long-term local adaptation.Although human-driven selection associated with maize domestication has been extensively studied, the genetic basis of natural variation is still poorly understood. Here we review studies on the genetic basis of adaptation and plasticity in maize and its wild relatives. We highlight a range of different processes that contribute to adaptation and discuss evidence from natural, cultivated, and experimental populations. From an applied perspective, understanding the genetic bases of adaptation and the contribution of plasticity will provide us with new tools to both better understand and mitigate the effect of climate changes on natural and cultivated populations.
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21
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Buffalo V, Coop G. The Linked Selection Signature of Rapid Adaptation in Temporal Genomic Data. Genetics 2019; 213:1007-1045. [PMID: 31558582 PMCID: PMC6827383 DOI: 10.1534/genetics.119.302581] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 09/22/2019] [Indexed: 11/18/2022] Open
Abstract
The majority of empirical population genetic studies have tried to understand the evolutionary processes that have shaped genetic variation in a single sample taken from a present-day population. However, genomic data collected over tens of generations in both natural and laboratory populations are increasingly used to find selected loci underpinning adaptation over these short timescales. Although these studies have been quite successful in detecting selection on large-effect loci, the fitness differences between individuals are often polygenic, such that selection leads to allele frequency changes that are difficult to distinguish from genetic drift. However, one promising signal comes from polygenic selection's effect on neutral sites that become stochastically associated with the genetic backgrounds that lead to fitness differences between individuals. Previous theoretical work has established that the random associations between a neutral allele and heritable fitness backgrounds act to reduce the effective population size experienced by this neutral allele. These associations perturb neutral allele frequency trajectories, creating autocovariance in the allele frequency changes across generations. Here, we show how temporal genomic data allow us to measure the temporal autocovariance in allele frequency changes and characterize the genome-wide impact of polygenic selection. We develop expressions for these temporal autocovariances, showing that their magnitude is determined by the level of additive genetic variation, recombination, and linkage disequilibria in a region. Furthermore, by using analytic expressions for the temporal variances and autocovariances in allele frequency, we demonstrate that one can estimate the additive genetic variation for fitness and the drift-effective population size from temporal genomic data. We also show how the proportion of total variation in allele frequency change due to linked selection can be estimated from temporal data. Overall, we demonstrate that temporal genomic data offer opportunities to identify the role of linked selection on genome-wide diversity over short timescales, and can help bridge population genetic and quantitative genetic studies of adaptation.
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Affiliation(s)
- Vince Buffalo
- Population Biology Graduate Group, University of California, Davis, California 95616
- Center for Population Biology, Department of Evolution and Ecology, University of California, Davis, California 95616
| | - Graham Coop
- Center for Population Biology, Department of Evolution and Ecology, University of California, Davis, California 95616
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22
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Vlachos C, Burny C, Pelizzola M, Borges R, Futschik A, Kofler R, Schlötterer C. Benchmarking software tools for detecting and quantifying selection in evolve and resequencing studies. Genome Biol 2019; 20:169. [PMID: 31416462 PMCID: PMC6694636 DOI: 10.1186/s13059-019-1770-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 07/22/2019] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The combination of experimental evolution with whole-genome resequencing of pooled individuals, also called evolve and resequence (E&R) is a powerful approach to study the selection processes and to infer the architecture of adaptive variation. Given the large potential of this method, a range of software tools were developed to identify selected SNPs and to measure their selection coefficients. RESULTS In this benchmarking study, we compare 15 test statistics implemented in 10 software tools using three different scenarios. We demonstrate that the power of the methods differs among the scenarios, but some consistently outperform others. LRT-1, CLEAR, and the CMH test perform best despite LRT-1 and the CMH test not requiring time series data. CLEAR provides the most accurate estimates of selection coefficients. CONCLUSION This benchmark study will not only facilitate the analysis of already existing data, but also affect the design of future data collections.
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Affiliation(s)
- Christos Vlachos
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Wien, 1210, Austria
- Vienna Graduate School of Population Genetics, Vienna, Austria
| | - Claire Burny
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Wien, 1210, Austria
- Vienna Graduate School of Population Genetics, Vienna, Austria
| | - Marta Pelizzola
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Wien, 1210, Austria
- Vienna Graduate School of Population Genetics, Vienna, Austria
| | - Rui Borges
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Wien, 1210, Austria
| | - Andreas Futschik
- Institute of Applied Statistics, Johannes Kepler University, Linz, 4040, Austria
- Plattform Bioinformatik und Biostatistik, Vetmeduni Vienna, Veterinärplatz 1, Wien, 1210, Austria
| | - Robert Kofler
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Wien, 1210, Austria.
| | - Christian Schlötterer
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, Wien, 1210, Austria.
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23
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Höllinger I, Pennings PS, Hermisson J. Polygenic adaptation: From sweeps to subtle frequency shifts. PLoS Genet 2019; 15:e1008035. [PMID: 30893299 PMCID: PMC6443195 DOI: 10.1371/journal.pgen.1008035] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 04/01/2019] [Accepted: 02/20/2019] [Indexed: 11/19/2022] Open
Abstract
Evolutionary theory has produced two conflicting paradigms for the adaptation of a polygenic trait. While population genetics views adaptation as a sequence of selective sweeps at single loci underlying the trait, quantitative genetics posits a collective response, where phenotypic adaptation results from subtle allele frequency shifts at many loci. Yet, a synthesis of these views is largely missing and the population genetic factors that favor each scenario are not well understood. Here, we study the architecture of adaptation of a binary polygenic trait (such as resistance) with negative epistasis among the loci of its basis. The genetic structure of this trait allows for a full range of potential architectures of adaptation, ranging from sweeps to small frequency shifts. By combining computer simulations and a newly devised analytical framework based on Yule branching processes, we gain a detailed understanding of the adaptation dynamics for this trait. Our key analytical result is an expression for the joint distribution of mutant alleles at the end of the adaptive phase. This distribution characterizes the polygenic pattern of adaptation at the underlying genotype when phenotypic adaptation has been accomplished. We find that a single compound parameter, the population-scaled background mutation rate Θbg, explains the main differences among these patterns. For a focal locus, Θbg measures the mutation rate at all redundant loci in its genetic background that offer alternative ways for adaptation. For adaptation starting from mutation-selection-drift balance, we observe different patterns in three parameter regions. Adaptation proceeds by sweeps for small Θbg ≲ 0.1, while small polygenic allele frequency shifts require large Θbg ≳ 100. In the large intermediate regime, we observe a heterogeneous pattern of partial sweeps at several interacting loci. It is still an open question how complex traits adapt to new selection pressures. While population genetics champions the search for selective sweeps, quantitative genetics proclaims adaptation via small concerted frequency shifts. To date the empirical evidence of clear sweep signals is more scarce than expected, while subtle shifts remain notoriously hard to detect. In the current study we develop a theoretical framework to predict the expected adaptive architecture of a simple polygenic trait, depending on parameters such as mutation rate, effective population size, size of the trait basis, and the available genetic variability at the onset of selection. For a population in mutation-selection-drift balance we find that adaptation proceeds via complete or partial sweeps for a large set of parameter values. We predict adaptation by small frequency shifts for two main cases. First, for traits with a large mutational target size and high levels of genetic redundancy among loci, and second if the starting frequencies of mutant alleles are more homogeneous than expected in mutation-selection-drift equilibrium, e.g. due to population structure or balancing selection.
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Affiliation(s)
- Ilse Höllinger
- Mathematics and BioSciences Group, Faculty of Mathematics and Max F. Perutz Laboratories, University of Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, University of Vienna, Vienna, Austria
- * E-mail: (IH); (JH)
| | - Pleuni S. Pennings
- Department of Biology, San Francisco State University, San Francisco, California, USA
| | - Joachim Hermisson
- Mathematics and BioSciences Group, Faculty of Mathematics and Max F. Perutz Laboratories, University of Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, University of Vienna, Vienna, Austria
- * E-mail: (IH); (JH)
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24
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Barghi N, Tobler R, Nolte V, Jakšić AM, Mallard F, Otte KA, Dolezal M, Taus T, Kofler R, Schlötterer C. Genetic redundancy fuels polygenic adaptation in Drosophila. PLoS Biol 2019; 17:e3000128. [PMID: 30716062 PMCID: PMC6375663 DOI: 10.1371/journal.pbio.3000128] [Citation(s) in RCA: 127] [Impact Index Per Article: 25.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 02/14/2019] [Accepted: 01/14/2019] [Indexed: 12/31/2022] Open
Abstract
The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic-i.e., result from selection on a large number of genetic loci-but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes-e.g., fitness, metabolic rate, and fat content-and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.
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Affiliation(s)
- Neda Barghi
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - Raymond Tobler
- 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
| | - François Mallard
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | | | - Marlies Dolezal
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Plattform Bioinformatik und Biostatistik, Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - Thomas Taus
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
| | - Robert Kofler
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
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25
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Mallard F, Nolte V, Tobler R, Kapun M, Schlötterer C. A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila. Genome Biol 2018; 19:119. [PMID: 30122150 PMCID: PMC6100727 DOI: 10.1186/s13059-018-1503-4] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 08/03/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large-effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation. RESULTS To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population. Transcriptome and respiration measurements reveal extensive metabolic rewiring after only approximately 60 generations in a hot environment. Analysis of genome-wide polymorphisms identifies two interacting selection targets, Sestrin and SNF4Aγ, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation. CONCLUSIONS Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because SNF4Aγ also exhibits clinal variation in various Drosophila species, we suggest that this large-effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.
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Affiliation(s)
- François Mallard
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - Ray Tobler
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
- Present address: Australian Centre for Ancient DNA, School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Martin Kapun
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
- Present address: Department of Ecology and Evolution, Université de Lausanne, Lausanne, Switzerland
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26
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27
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Seabra SG, Fragata I, Antunes MA, Faria GS, Santos MA, Sousa VC, Simões P, Matos M. Different Genomic Changes Underlie Adaptive Evolution in Populations of Contrasting History. Mol Biol Evol 2017; 35:549-563. [PMID: 29029198 DOI: 10.1093/molbev/msx247] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Experimental evolution is a powerful tool to understand the adaptive potential of populations under environmental change. Here, we study the importance of the historical genetic background in the outcome of evolution at the genome-wide level. Using the natural clinal variation of Drosophila subobscura, we sampled populations from two contrasting latitudes (Adraga, Portugal and Groningen, Netherlands) and introduced them in a new common environment in the laboratory. We characterized the genome-wide temporal changes underlying the evolutionary dynamics of these populations, which had previously shown fast convergence at the phenotypic level, but not at chromosomal inversion frequencies. We found that initially differentiated populations did not converge either at genome-wide level or at candidate SNPs with signs of selection. In contrast, populations from Portugal showed convergence to the control population that derived from the same geographical origin and had been long-established in the laboratory. Candidate SNPs showed a variety of different allele frequency change patterns across generations, indicative of an underlying polygenic basis. We did not detect strong linkage around candidate SNPs, but rather a small but long-ranging effect. In conclusion, we found that history played a major role in genomic variation and evolution, with initially differentiated populations reaching the same adaptive outcome through different genetic routes.
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Affiliation(s)
- Sofia G Seabra
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Inês Fragata
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.,Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Marta A Antunes
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Gonçalo S Faria
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.,School of Biology, University of St Andrews, St Andrews, United Kingdom
| | - Marta A Santos
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.,CEDOC - Centro de Estudos de Doenças Crónicas, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisboa, Portugal
| | - Vitor C Sousa
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Pedro Simões
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Margarida Matos
- cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
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28
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A Mixed Model Approach to Genome-Wide Association Studies for Selection Signatures, with Application to Mice Bred for Voluntary Exercise Behavior. Genetics 2017; 207:785-799. [PMID: 28774881 DOI: 10.1534/genetics.117.300102] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 07/31/2017] [Indexed: 01/08/2023] Open
Abstract
Selection experiments and experimental evolution provide unique opportunities to study the genetics of adaptation because the target and intensity of selection are known relatively precisely. In contrast to natural selection, where populations are never strictly "replicated," experimental evolution routinely includes replicate lines so that selection signatures-genomic regions showing excessive differentiation between treatments-can be separated from possible founder effects, genetic drift, and multiple adaptive solutions. We developed a mouse model with four lines within a high running (HR) selection treatment and four nonselected controls (C). At generation 61, we sampled 10 mice of each line and used the Mega Mouse Universal Genotyping Array to obtain single nucleotide polymorphism (SNP) data for 25,318 SNPs for each individual. Using an advanced mixed model procedure developed in this study, we identified 152 markers that were significantly different in frequency between the two selection treatments. They occurred on all chromosomes except 1, 2, 8, 13, and 19, and showed a variety of patterns in terms of fixation (or the lack thereof) in the four HR and four C lines. Importantly, none were fixed for alternative alleles between the two selection treatments. The current state-of-the-art regularized F test applied after pooling DNA samples for each line failed to detect any markers. We conclude that when SNP or sequence data are available from individuals, the mixed model methodology is recommended for selection signature detection. As sequencing at the individual level becomes increasingly feasible, the new methodology may be routinely applied for detection of selection.
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29
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Genetic variation, selection and evolution: special issue in celebration of the 50th anniversary of the population genetics group meeting. Heredity (Edinb) 2016; 118:1. [PMID: 27827388 DOI: 10.1038/hdy.2016.97] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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