Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima

ABSTRACTUnderstanding the genetic basis of phenotypic adaptation to changing environments is an essential goal of population and quantitative genetics. While technological advances now allow interrogation of genome-wide genotyping data in large panels, our understanding of the process of polygenic adaptation is still limited. To address this limitation, we use extensive forward-time simulation to explore the impacts of variation in demography, trait genetics, and selection on the rate and mode of adaptation and the resulting genetic architecture. We simulate a population adapting to an optimum shift, modeling sequence variation for 20 QTL for each of 12 different demographies for 100 different traits varying in the effect size distribution of new mutations, the strength of stabilizing selection, and the contribution of the genomic background. We then use random forest regression approaches to learn the relative importance of input parameters in determining a number of aspects of the process of adaptation including the speed of adaptation, the relative frequency of hard sweeps and sweeps from standing variation, or the final genetic architecture of the trait. We find that selective sweeps occur even for traits under relatively weak selection and where the genetic background explains most of the variation. Though most sweeps occur from variation segregating in the ancestral population, new mutations can be important for traits under strong stabilizing selection that undergo a large optimum shift. We also show that population bottlenecks and expansion impact overall genetic variation as well as the relative importance of sweeps from standing variation and the speed with which adaptation can occur. We then compare our results to two traits under selection during maize domestication, showing that our simulations qualitatively recapitulate differences between them. Overall, our results underscore the complex population genetics of individual loci in even relatively simple quantitative trait models, but provide a glimpse into the factors that drive this complexity and the potential of these approaches for understanding polygenic adaptation.Author summaryMany traits are controlled by a large number of genes, and environmental changes can lead to shifts in trait optima. How populations adapt to these shifts depends on a number of parameters including the genetic basis of the trait as well as population demography. We simulate a number of trait architectures and population histories to study the genetics of adaptation to distant trait optima. We find that selective sweeps occur even in traits under relatively weak selection and our machine learning analyses find that demography and the effect sizes of mutations have the largest influence on genetic variation after adaptation. Maize domestication is a well suited model for trait adaptation accompanied by demographic changes. We show how two example traits under a maize specific demography adapt to a distant optimum and demonstrate that polygenic adaptation is a well suited model for crop domestication even for traits with major effect loci.

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Polygenic Adaptation to an Environmental Shift: Temporal Dynamics of Variation Under Gaussian Stabilizing Selection and Additive Effects on a Single Trait

Genetics ◽

10.1534/genetics.119.302662 ◽

2019 ◽

Vol 213 (4) ◽

pp. 1513-1530 ◽

Cited By ~ 10

Author(s):

Kevin R. Thornton

Keyword(s):

Temporal Dynamics ◽

Mutation Rates ◽

Stabilizing Selection ◽

Standing Variation ◽

Polygenic Adaptation ◽

Standard Models ◽

The Times ◽

General Populations ◽

Mutational Variance ◽

New Mutations

Predictions about the effect of natural selection on patterns of linked neutral variation are largely based on models involving the rapid fixation of unconditionally beneficial mutations. However, when phenotypes adapt to a new optimum trait value, the strength of selection on individual mutations decreases as the population adapts. Here, I use explicit forward simulations of a single trait with additive-effect mutations adapting to an “optimum shift.” Detectable “hitchhiking” patterns are only apparent if (i) the optimum shifts are large with respect to equilibrium variation for the trait, (ii) mutation rates to large-effect mutations are low, and (iii) large-effect mutations rapidly increase in frequency and eventually reach fixation, which typically occurs after the population reaches the new optimum. For the parameters simulated here, partial sweeps do not appreciably affect patterns of linked variation, even when the mutations are strongly selected. The contribution of new mutations vs. standing variation to fixation depends on the mutation rate affecting trait values. Given the fixation of a strongly selected variant, patterns of hitchhiking are similar on average for the two classes of sweeps because sweeps from standing variation involving large-effect mutations are rare when the optimum shifts. The distribution of effect sizes of new mutations has little effect on the time to reach the new optimum, but reducing the mutational variance increases the magnitude of hitchhiking patterns. In general, populations reach the new optimum prior to the completion of any sweeps, and the times to fixation are longer for this model than for standard models of directional selection. The long fixation times are due to a combination of declining selection pressures during adaptation and the possibility of interference among weakly selected sites for traits with high mutation rates.

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Polygenic adaptation to an environmental shift: temporal dynamics of variation under Gaussian stabilizing selection and additive effects on a single trait

10.1101/505750 ◽

2018 ◽

Cited By ~ 6

Author(s):

Kevin R. Thornton

Keyword(s):

Temporal Dynamics ◽

Mutation Rates ◽

Stabilizing Selection ◽

Standing Variation ◽

Polygenic Adaptation ◽

Standard Models ◽

The Times ◽

General Populations ◽

Mutational Variance ◽

New Mutations

AbstractPredictions about the effect of natural selection on patterns of linked neutral variation are largely based on models involving the rapid fixation of unconditionally beneficial mutations. However, when phenotypes adapt to a new optimum trait value, the strength of selection on individual mutations decreases as the population adapts. Here, I use explicit forward simulations of a single trait with additive-effect mutations adapting to an optimum shift. Detectable “hitch-hiking” patterns are only apparent if i. the optimum shifts are large with respect to equilibrium variation for the trait, ii. mutation rates to large-effect mutations are low, and iii., large-effect mutations rapidly increase in frequency and eventually reach fixation, which typically occurs after the population reaches the new optimum. For the parameters simulated here, partial sweeps do not appreciably affect patterns of linked variation, even when the mutations are strongly selected. The contribution of new mutations versus standing variation to fixation depends on the mutation rate affecting trait values. Given the fixation of a strongly-selected variant, patterns of hitch-hiking are similar on average for the two classes of sweeps because sweeps from standing variation involving large-effect mutations are rare when the optimum shifts. The distribution of effect sizes of new mutations has little effect on the time to reach the new optimum, but reducing the mutational variance increases the magnitude of hitch-hiking patterns. In general, populations reach the new optimum prior to the completion of any sweeps, and the times to fixation are longer for this model than for standard models of directional selection. The long fixation times are due to a combination of declining selection pressures during adaptation and the possibility of interference among weakly selected sites for traits with high mutation rates.

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The genetic architecture and genomic context of glyphosate resistance

10.1101/2020.08.19.257972 ◽

2020 ◽

Author(s):

J.M. Kreiner ◽

P.J. Tranel ◽

D. Weigel ◽

J.R. Stinchcombe ◽

S.I. Wright

Keyword(s):

Herbicide Resistance ◽

Genetic Architecture ◽

Genetic Basis ◽

Glyphosate Resistance ◽

Target Site ◽

Plant Performance ◽

Comparable Amount ◽

Standing Variation ◽

Genome Wide ◽

Target Site Resistance

AbstractAlthough much of what we know about the genetic basis of herbicide resistance has come from detailed investigations of monogenic adaptation at known target-sites, the importance of polygenic resistance has been increasingly recognized. Despite this, little work has been done to characterize the genomic basis of herbicide resistance, including the number and distribution of involved genes, their effect sizes, allele frequencies, and signatures of selection. Here we implement genome-wide association (GWA) and population genomic approaches to examine the genetic architecture of glyphosate resistance in the problematic agricultural weed, Amaranthus tuberculatus. GWA correctly identifies the gene targeted by glyphosate, and additionally finds more than 100 genes across all 16 chromosomes associated with resistance. The encoded proteins have relevant non-target-site resistance and stress-related functions, with potential for pleiotropic roles in resistance to other herbicides and diverse life history traits. Resistance-related alleles are enriched for large effects and intermediate frequencies, implying that strong selection has shaped the genetic architecture of resistance despite potential pleiotropic costs. The range of common and rare allele involvement implies a partially shared genetic basis of non-target-site resistance across populations, complemented by population-specific alleles. Resistance-related alleles show evidence of balancing selection, and suggest a long-term maintenance of standing variation at stress-response loci that have implications for plant performance under herbicide pressure. By our estimates, genome-wide SNPs explain a comparable amount of the total variation in glyphosate resistance to monogenic mechanisms, indicating the potential for an underappreciated polygenic contribution to the evolution of herbicide resistance in weed populations.

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Ethanol resistance in Drosophila melanogaster has increased in parallel cold-adapted populations and shows a variable genetic architecture within and between populations

10.22541/au.161064161.14860829/v1 ◽

2021 ◽

Author(s):

Quentin Sprengelmeyer ◽

John E Pool

Keyword(s):

Drosophila Melanogaster ◽

Genetic Architecture ◽

Genetic Basis ◽

Biological Diversity ◽

European Population ◽

Membrane Composition ◽

Trait Evolution ◽

Adaptive Trait ◽

Standing Variation ◽

Ethanol Resistance

Understanding the genetic properties of adaptive trait evolution is a fundamental crux of biological inquiry that links molecular processes to biological diversity. Important uncertainties persist regarding the genetic predictability of adaptive trait change, the role of standing variation, and whether adaptation tends to result in the fixation of favored variants. Here, we use the recurrent evolution of enhanced ethanol resistance in Drosophila melanogaster during this species’ worldwide expansion as a promising system to add to our understanding of the genetics of adaptation. We find that elevated ethanol resistance has evolved at least three times in different cooler regions of the species’ modern range - not only at high latitude but also in two African high altitude regions - and that ethanol and cold resistance may have a partially shared genetic basis. Applying a bulk segregant mapping framework, we find that the genetic architecture of ethanol resistance evolution differs substantially not only between our three resistant populations, but also between two crosses involving the same European population. We then apply population genetic scans for local adaptation within our quantitative trait locus regions, and we find potential contributions of genes with annotated roles in spindle localization, membrane composition, sterol and alcohol metabolism, and other processes. We also apply simulation-based analyses that confirm the variable genetic basis of ethanol resistance and hint at a moderately polygenic architecture. However, these simulations indicate that larger-scale studies will be needed to more clearly quantify the genetic architecture of adaptive evolution, and to firmly connect trait evolution to specific causative loci.

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The genetic basis of adaptation through the evolution of self-fertilization

10.1101/2021.02.11.430833 ◽

2021 ◽

Author(s):

Kuangyi Xu

Keyword(s):

Genetic Basis ◽

Pollen Limitation ◽

Fixation Probability ◽

Selfing Rate ◽

Effective Population ◽

Plant Populations ◽

Individual Fitness ◽

Standing Variation ◽

Self Fertilization ◽

New Mutations

AbstractAlthough adaptation can be realized through the fixation of beneficial alleles that increase viability, many plant populations may adapt through the evolution of self-fertilization, especially when pollination becomes inefficient. However, the genetic basis of adaptation through the evolution of selfing remains unclear. Using population genetic models, I study adaptation through the fixation of alleles that increase the selfing rate (selfing modifiers) from new mutations or/and standing variation. For adaptive alleles unrelated to selfing, it is known that selfing promotes adaptation from a new mutation only when the beneficial alleles are recessive, and the probability of adaptation from standing variation is nearly independent of dominance, and always decreases with the selfing rate. In contrast, for adaptation through the evolution of selfing, when it occurs by fixation of a newly arisen mutation, a population that already has a high selfing rate may be more (less) likely to adapt than outcrossers even when the modifier is dominant (recessive) if the modifier is weakly (strongly) selected. Also, adaptation from standing variation is more likely through recessive modifier alleles, with the highest fixation probability found in partially selfing populations, but fixation is fastest when dominance is intermediate. When there are multiple modifiers, adaptation through new mutations is more likely when selfing is controlled by few large-effect rather than many slight-effect modifiers. This study suggests that to understand the genetic basis of adaptation, it is necessary to determine the ecological and genetic advantages of adaptive alleles.Significance statementThis study, by deriving the selective coefficient and effective population size, investigated the genetic basis of adaptation through fixation of modifier alleles that increase the selfing rate, which is shown to differ in several aspects from that through evolution of mating-unrelated alleles. Specifically, when adaptation is from new mutations, the dominance of a selfing modifier allele below which selfing increases the fixation probability depends on the strength of pollen limitation and pollen discounting. Adaptation from standing variation is more likely through recessive modifier alleles and in populations with an intermediate selfing rate. This work suggests it is important to have a mechanistic understanding of how adaptive alleles increase individual fitness in environment that is unfavorable to the population.

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Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima

PLoS Genetics ◽

10.1371/journal.pgen.1007794 ◽

2018 ◽

Vol 14 (11) ◽

pp. e1007794 ◽

Cited By ~ 19

Author(s):

Markus G. Stetter ◽

Kevin Thornton ◽

Jeffrey Ross-Ibarra

Keyword(s):

Genetic Architecture ◽

Selective Sweeps ◽

Polygenic Adaptation

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The genetic architecture underlying prey-dependent performance in a microbial predator

Nature Communications ◽

10.1038/s41467-021-27844-x ◽

2022 ◽

Vol 13 (1) ◽

Author(s):

Balint Stewart ◽

Nicole Gruenheit ◽

Amy Baldwin ◽

Rex Chisholm ◽

Daniel Rozen ◽

...

Keyword(s):

Experimental Evolution ◽

Genetic Architecture ◽

Natural Variation ◽

Genetic Basis ◽

Prey Type ◽

Generalist Predators ◽

Generalist Predator ◽

Antagonistic Pleiotropy ◽

Relative Importance ◽

Specific Effects

AbstractNatural selection should favour generalist predators that outperform specialists across all prey types. Two genetic solutions could explain why intraspecific variation in predatory performance is, nonetheless, widespread: mutations beneficial on one prey type are costly on another (antagonistic pleiotropy), or mutational effects are prey-specific, which weakens selection, allowing variation to persist (relaxed selection). To understand the relative importance of these alternatives, we characterised natural variation in predatory performance in the microbial predator Dictyostelium discoideum. We found widespread nontransitive differences among strains in predatory success across different bacterial prey, which can facilitate stain coexistence in multi-prey environments. To understand the genetic basis, we developed methods for high throughput experimental evolution on different prey (REMI-seq). Most mutations (~77%) had prey-specific effects, with very few (~4%) showing antagonistic pleiotropy. This highlights the potential for prey-specific effects to dilute selection, which would inhibit the purging of variation and prevent the emergence of an optimal generalist predator.

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Not so local: the population genetics of convergent adaptation in maize and teosinte

10.1101/2021.09.09.459637 ◽

2021 ◽

Author(s):

Silas Tittes ◽

Anne Lorant ◽

Sean McGinty ◽

John F. Doebley ◽

James B. Holland ◽

...

Keyword(s):

Population Genetics ◽

Zea Mays ◽

Local Adaptation ◽

Genetic Architecture ◽

Wild Relative ◽

Selective Sweeps ◽

Sympatric Population ◽

Geographic Scale ◽

Standing Variation ◽

Maize Populations

ABSTRACTWhat is the genetic architecture of local adaptation and what is the geographic scale that it operates over? We investigated patterns of local and convergent adaptation in five sympatric population pairs of traditionally cultivated maize and its wild relative teosinte (Zea mays subsp. parviglumis). We found that signatures of local adaptation based on the inference of adaptive fixations and selective sweeps are frequently exclusive to individual populations, more so in teosinte compared to maize. However, for both maize and teosinte, selective sweeps are frequently shared by several populations, and often between the subspecies. We were further able to infer that selective sweeps were shared among populations most often via migration, though sharing via standing variation was also common. Our analyses suggest that teosinte has been a continued source of beneficial alleles for maize, post domestication, and that maize populations have facilitated adaptation in teosinte by moving beneficial alleles across the landscape. Taken together, out results suggest local adaptation in maize and teosinte has an intermediate geographic scale, one that is larger than individual populations, but smaller than the species range.

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