scholarly journals Combining Experimental Evolution and Genomics to Understand How Seed Beetles Adapt to a Marginal Host Plant

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 400 ◽  
Author(s):  
Alexandre Rêgo ◽  
Samridhi Chaturvedi ◽  
Amy Springer ◽  
Alexandra M. Lish ◽  
Caroline L. Barton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Allele Frequency ◽  
Development Time ◽  
Callosobruchus Maculatus ◽  
Parallel Evolution ◽  
Frequency Change ◽  
Multiple Traits ◽  
Population Genomic ◽  
Performance Traits ◽  
Frequency Changes

Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve-and-resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic datasets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus.

scholarly journals Combining Experimental Evolution and Genomics to Understand How Seed Beetles Adapt to a Marginal Host Plant

2020 ◽  
Author(s):  
Alex Rêgo ◽  
Samridhi Chaturvedi ◽  
Amy Springer ◽  
Alexandra M. Lish ◽  
Caroline L. Barton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Allele Frequency ◽  
Development Time ◽  
Callosobruchus Maculatus ◽  
Parallel Evolution ◽  
Frequency Change ◽  
Multiple Traits ◽  
Population Genomic ◽  
Performance Traits ◽  
Frequency Changes

Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve and resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap, and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic data sets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution, and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus.

scholarly journals AF-vapeR: A multivariate genome scan for detecting parallel evolution using allele frequency change vectors

2021 ◽  
Author(s):  
James R Whiting ◽  
Josephine R Paris ◽  
Mijke van der Zee ◽  
Bonnie A Fraser
Keyword(s):  
Allele Frequency ◽  
Local Adaptation ◽  
Parallel Evolution ◽  
False Negative ◽  
False Negative Rate ◽  
Null Distribution ◽  
Frequency Change ◽  
Frequency Changes ◽  
Highly Correlated ◽  
Eigen Decomposition

The repeatability of evolution at the genetic level has been demonstrated to vary along a continuum from complete parallelism to divergence. In order to better understand why this continuum exists within and among systems, hypotheses must be tested using high-confidence sets of candidate loci for repeatability. Despite this, few methods have been developed to scan SNP data for signatures specifically associated with repeatability, as opposed to local adaptation. Here we present AF-vapeR (Allele Frequency Vector Analysis of Parallel Evolutionary Responses), an approach designed to identify genome regions exhibiting highly correlated allele frequency changes within haplotypes and among replicated allele frequency change vectors. The method divides the genome into windows of an equivalent number of SNPs, and within each window performs eigen decomposition over normalised allele frequency change vectors (AFV), each derived from a replicated pair of populations/species. Properties of the resulting eigenvalue distribution can be used to compare regions of the genome for those exhibiting strong parallelism, and can also be compared against a null distribution derived from randomly permuted AFV. We demonstrate the utility of this approach to detect different modes of parallel evolution using simulations, and also demonstrate a reduction in error rate compared with intersecting FST outliers. Lastly, we apply AF-vapeR to three previously published datasets (stickleback, guppies, and Galapagos finches) which comprise a range of sampling and sequencing strategies, and lineage ages. We highlight known parallel regions whilst also identifying novel candidates. The main benefits of this approach include a reduced false-negative rate under many conditions, an emphasis on signals associated specifically with repeatable evolution as opposed to local adaptation, and an opportunity to identify different modes of parallel evolution at the first instance.

scholarly journals The promise and deceit of genomic selection component analyses

2021 ◽  
Vol 288 (1961) ◽  
Author(s):  
John K. Kelly
Keyword(s):  
Allele Frequency ◽  
Statistical Power ◽  
Field Experiments ◽  
Whole Genome Sequence ◽  
Frequency Change ◽  
Genome Wide ◽  
Pooled Sequencing ◽  
Frequency Changes ◽  
Selection Intensities ◽  
Combine Information

Selection component analyses (SCA) relate individual genotype to fitness components such as viability, fecundity and mating success. SCA are based on population genetic models and yield selection estimates directly in terms of predicted allele frequency change. This paper explores the statistical properties of gSCA: experiments that apply SCA to genome-wide scoring of SNPs in field sampled individuals. Computer simulations indicate that gSCA involving a few thousand genotyped samples can detect allele frequency changes of the magnitude that has been documented in field experiments on diverse taxa. To detect selection, imprecise genotyping from low-level sequencing of large samples of individuals provides much greater power than precise genotyping of smaller samples. The simulations also demonstrate the efficacy of ‘haplotype matching’, a method to combine information from a limited collection of whole genome sequence (the reference panel) with the much larger sample of field individuals that are measured for fitness. Pooled sequencing is demonstrated as another way to increase statistical power. Finally, I discuss the interpretation of selection estimates in relation to the Beavis effect, the overestimation of selection intensities at significant loci.

scholarly journals Allele frequency dynamics in a pedigreed natural population

2018 ◽  
Vol 116 (6) ◽  
pp. 2158-2164 ◽  
Author(s):  
Nancy Chen ◽  
Ivan Juric ◽  
Elissa J. Cosgrove ◽  
Reed Bowman ◽  
John W. Fitzpatrick ◽  
...  
Keyword(s):  
Gene Flow ◽  
Reproductive Success ◽  
Allele Frequency ◽  
Natural Population ◽  
Allele Frequencies ◽  
Frequency Change ◽  
Short Term ◽  
Individual Survival ◽  
Frequency Changes ◽  
Genetic Contributions

A central goal of population genetics is to understand how genetic drift, natural selection, and gene flow shape allele frequencies through time. However, the actual processes underlying these changes—variation in individual survival, reproductive success, and movement—are often difficult to quantify. Fully understanding these processes requires the population pedigree, the set of relationships among all individuals in the population through time. Here, we use extensive pedigree and genomic information from a long-studied natural population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of different evolutionary processes in shaping patterns of genetic variation through time. We performed gene dropping simulations to estimate individual genetic contributions to the population and model drift on the known pedigree. We found that observed allele frequency changes are generally well predicted by accounting for the different genetic contributions of founders. Our results show that the genetic contribution of recent immigrants is substantial, with some large allele frequency shifts that otherwise may have been attributed to selection actually due to gene flow. We identified a few SNPs under directional short-term selection after appropriately accounting for gene flow. Using models that account for changes in population size, we partitioned the proportion of variance in allele frequency change through time. Observed allele frequency changes are primarily due to variation in survival and reproductive success, with gene flow making a smaller contribution. This study provides one of the most complete descriptions of short-term evolutionary change in allele frequencies in a natural population to date.

scholarly journals Estimating the genome-wide contribution of selection to temporal allele frequency change

2019 ◽  
Author(s):  
Vince Buffalo ◽  
Graham Coop
Keyword(s):  
Allele Frequency ◽  
Genetic Drift ◽  
Genomic Data ◽  
Allele Frequencies ◽  
Frequency Change ◽  
Standing Variation ◽  
Genome Wide ◽  
Selection Experiments ◽  
Frequency Changes ◽  
Linked Selection

AbstractRapid phenotypic adaptation is often observed in natural populations and selection experiments. However, detecting the genome-wide impact of this selection is difficult, since adaptation often proceeds from standing variation and selection on polygenic traits, both of which may leave faint genomic signals indistinguishable from a noisy background of genetic drift. One promising signal comes from the genome-wide covariance between allele frequency changes observable from temporal genomic data, e.g. evolve-and-resequence studies. These temporal covariances reflect how heritable fitness variation in the population leads changes in allele frequencies at one timepoint to be predictive of the changes at later timepoints, as alleles are indirectly selected due to remaining associations with selected alleles. Since genetic drift does not lead to temporal covariance, we can use these covariances to estimate what fraction of the variation in allele frequency change through time is driven by linked selection. Here, we reanalyze three selection experiments to quantify the effects of linked selection over short timescales using covariance among time-points and across replicates. We estimate that at least 17% to 37% of allele frequency change is driven by selection in these experiments. Against this background of positive genome-wide temporal covariances we also identify signals of negative temporal covariance corresponding to reversals in the direction of selection for a reasonable proportion of loci over the time course of a selection experiment. Overall, we find that in the three studies we analyzed, linked selection has a large impact on short-term allele frequency dynamics that is readily distinguishable from genetic drift.Significance StatementA long-standing problem in evolutionary biology is to understand the processes that shape the genetic composition of populations. In a population without migration, the two processes that change allele frequencies are selection, which increases beneficial alleles and removes deleterious ones, and genetic drift which randomly changes frequencies as some parents contribute more or less alleles to the next generation. Previous efforts to disentangle these processes have used genomic samples from a single timepoint and models of how selection affects neighboring sites (linked selection). Here, we use genomic data taken through time to quantify the contributions of selection and drift to genome-wide frequency changes. We show selection acts over short timescales in three evolve-and-resequence studies and has a sizable genome-wide impact.

scholarly journals The Linked Selection Signature of Rapid Adaptation in Temporal Genomic Data

2019 ◽  
Author(s):  
Vince Buffalo ◽  
Graham Coop
Keyword(s):  
Genetic Variation ◽  
Allele Frequency ◽  
Genomic Data ◽  
Frequency Change ◽  
Rapid Adaptation ◽  
Effective Population ◽  
Additive Genetic Variation ◽  
Analytic Expressions ◽  
Frequency Changes ◽  
Linked Selection

AbstractPopulations can adapt over short, ecological timescales via standing genetic variation. Genomic data collected over tens of generations in both natural and lab populations is increasingly used to find selected loci underpinning such rapid adaptation. Although selection on large effect loci may be detectable in such data, often the fitness differences between individuals have a polygenic architecture, such that selection at any one locus leads to allele frequency changes that are too subtle to distinguish from genetic drift. However, one promising signal comes from the fact that selection on polygenic traits leads to heritable fitness backgrounds that neutral alleles can become stochastically associated with. These associations perturb neutral allele frequency trajectories, creating autocovariance across generations that can be directly measured from temporal genomic data. We develop theory that predicts the magnitude of these temporal autocovariances, showing that it 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 one can estimate the additive genetic variation for fitness and the drift-effective population size from temporal genomic data. Finally, we also show how the proportion of total variation in allele frequency change due to linked selection can be estimated from temporal data. Temporal genomic data offers strong opportunities to identify the role linked selection has on genome-wide diversity over short timescales, and can help bridge population genetic and quantitative genetic studies of adaptation.

scholarly journals Allele frequency dynamics under sex-biased demography and sex-specific inheritance in a pedigreed population

2021 ◽  
Author(s):  
Rose M.H. Driscoll ◽  
Felix E.G. Beaudry ◽  
Elissa J Cosgrove ◽  
Reed Bowman ◽  
John W Fitzpatrick ◽  
...  
Keyword(s):  
Allele Frequency ◽  
Evolutionary Dynamics ◽  
Z Chromosome ◽  
Frequency Change ◽  
Effective Population ◽  
Genome Wide ◽  
Males And Females ◽  
Frequency Changes ◽  
Genetic Contributions ◽  
The Impact

Sex-biased demography, including sex-biased survival or migration, can impact allele frequency changes across the genome. In particular, we can expect different patterns of genetic variation on autosomes and sex chromosomes due to sex-specific differences in life histories, as well as differences in effective population size, transmission modes, and the strength and mode of selection. Here, we demonstrate the role that sex differences in life history played in shaping short-term evolutionary dynamics across the genome. We used a 25-year pedigree and genomic dataset from a long-studied population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of sex-biased demography and inheritance in shaping genome-wide allele frequency trajectories. We used gene dropping simulations to estimate individual genetic contributions to future generations and to model drift and immigration on the known pedigree. We quantified differential expected genetic contributions of males and females over time, showing the impact of sex-biased dispersal in a monogamous system. Due to female-biased dispersal, more autosomal variation is introduced by female immigrants. However, due to male-biased transmission, more Z variation is introduced by male immigrants. Finally, we partitioned the proportion of variance in allele frequency change through time due to male and female contributions. Overall, most allele frequency change is due to variance in survival and births. Males and females have similar contributions to autosomal allele frequency change, but males have higher contributions to allele frequency change on the Z chromosome. Our work shows the importance of understanding sex-specific demographic processes in accounting for genome-wide allele frequency change in wild populations.

scholarly journals Estimating the genome-wide contribution of selection to temporal allele frequency change

2020 ◽  
Vol 117 (34) ◽  
pp. 20672-20680
Author(s):  
Vince Buffalo ◽  
Graham Coop
Keyword(s):  
Allele Frequency ◽  
Genetic Drift ◽  
Time Course ◽  
Frequency Change ◽  
Time Points ◽  
Standing Variation ◽  
Genome Wide ◽  
Selection Experiments ◽  
Frequency Changes ◽  
Linked Selection

Rapid phenotypic adaptation is often observed in natural populations and selection experiments. However, detecting the genome-wide impact of this selection is difficult since adaptation often proceeds from standing variation and selection on polygenic traits, both of which may leave faint genomic signals indistinguishable from a noisy background of genetic drift. One promising signal comes from the genome-wide covariance between allele frequency changes observable from temporal genomic data (e.g., evolve-and-resequence studies). These temporal covariances reflect how heritable fitness variation in the population leads changes in allele frequencies at one time point to be predictive of the changes at later time points, as alleles are indirectly selected due to remaining associations with selected alleles. Since genetic drift does not lead to temporal covariance, we can use these covariances to estimate what fraction of the variation in allele frequency change through time is driven by linked selection. Here, we reanalyze three selection experiments to quantify the effects of linked selection over short timescales using covariance among time points and across replicates. We estimate that at least 17 to 37% of allele frequency change is driven by selection in these experiments. Against this background of positive genome-wide temporal covariances, we also identify signals of negative temporal covariance corresponding to reversals in the direction of selection for a reasonable proportion of loci over the time course of a selection experiment. Overall, we find that in the three studies we analyzed, linked selection has a large impact on short-term allele frequency dynamics that is readily distinguishable from genetic drift.

scholarly journals Allele frequency dynamics in a pedigreed natural population

2018 ◽  
Author(s):  
Nancy Chen ◽  
Ivan Juric ◽  
Elissa J. Cosgrove ◽  
Reed Bowman ◽  
John W. Fitzpatrick ◽  
...  
Keyword(s):  
Gene Flow ◽  
Reproductive Success ◽  
Allele Frequency ◽  
Natural Population ◽  
Allele Frequencies ◽  
Frequency Change ◽  
Short Term ◽  
Individual Survival ◽  
Frequency Changes ◽  
Genetic Contributions

ABSTRACTA central goal of population genetics is to understand how genetic drift, natural selection, and gene flow shape allele frequencies through time. However, the actual processes underlying these changes - variation in individual survival, reproductive success, and movement - are often difficult to quantify. Fully understanding these processes requires the population pedigree, the set of relationships among all individuals in the population through time. Here, we use extensive pedigree and genomic information from a long-studied natural population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of different evolutionary processes in shaping patterns of genetic variation through time. We performed gene dropping simulations to estimate individual genetic contributions to the population and model drift on the known pedigree. We found that observed allele frequency changes are generally well predicted by accounting for the different genetic contributions of founders. Our results show that the genetic contribution of recent immigrants is substantial, with some large allele frequency shifts that otherwise may have been attributed to selection actually due to gene flow. We identified a few SNPs under directional short-term selection after appropriately accounting for gene flow. Using models that account for changes in population size, we partitioned the proportion of variance in allele frequency change through time. Observed allele frequency changes are primarily due to variation in survival and reproductive success, with gene flow making a smaller contribution. This study provides one of the most complete descriptions of short-term evolutionary change in allele frequencies in a natural population to date.

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