The promise and deceit of genomic selection component analyses

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.

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

10.1101/798595 ◽

2019 ◽

Cited By ~ 1

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.

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

10.1101/2021.10.28.466320 ◽

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.

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

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1919039117 ◽

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.

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Genome-Wide Detection of Allele Frequency Change and Quantitative Trait Loci for Respiratory Disease and Immune-Related Traits in Landrace Pigs Selected for Mycoplasmal Pneumonia of Swine Resistance

10.21203/rs.3.rs-133661/v1 ◽

2021 ◽

Author(s):

Yoshinobu Uemoto ◽

Kasumi Ichinoseki ◽

Toshimi Matsumoto ◽

Nozomi Oka ◽

Hironori Takamori ◽

...

Keyword(s):

Disease Resistance ◽

Allele Frequency ◽

Respiratory Disease ◽

Quantitative Trait ◽

Association Studies ◽

Frequency Change ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Mycoplasmal Pneumonia ◽

Frequency Changes

Abstract Background: The genetic improvement of disease resistance in pig has been well-received. Identification of a quantitative trait locus (QTL) related to a chronic respiratory disease such as Mycoplasmal pneumonia of swine (MPS) and immune-related traits is important for understanding the genomic background of disease resistance and to apply marker-assisted selection. The objective of this study was to understand the influence of genomic factors on respiratory disease and immune-related traits in MPS-selected pigs.Results: A total of 874 Landrace purebred pigs, which were selected based on MPS resistance, were genotyped using the Illumina PorcineSNP60 BeadChip, and were then used for genomic analyses. First, we performed genome-wide association studies (GWAS) to detect a novel QTL for a total of 22 performance, respiratory disease, and immune-related traits using additive and nonadditive genetic effects. Second, we evaluated the changes in allele frequency due to selection for MPS resistance and compared the putative selected regions with the detected QTL. GWAS detected a total of 11 genome-wide significant single nucleotide polymorphisms (SNPs) with an additive effect in five traits and a total of three significant SNPs with a nonadditive effect in three traits. Most of these detected QTL regions were novel regions with some candidate genes located in them. With regard to a pleiotropic region among traits, only five of these detected QTL regions overlapped among traits. Changes in allele frequencies at the many putative selected regions were spread across the whole genome and overlapped with the detected QTL. Some of these selected regions were the ones that contained the detected QTL for MPS score and other traits.Conclusion: These results suggest that a closed-line breeding population is a useful target population to refine and confirm QTL regions by integrating the results of GWAS and allele frequency changes. The study provides new insights into the genomic factors that affect respiratory disease and immune-related traits in pigs.

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

Genes ◽

10.3390/genes11040400 ◽

2020 ◽

Vol 11 (4) ◽

pp. 400 ◽

Cited By ~ 2

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.

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Increased virulence of Puccinia coronata f. sp.avenae populations through allele frequency changes at multiple putative Avr loci

PLoS Genetics ◽

10.1371/journal.pgen.1009291 ◽

2020 ◽

Vol 16 (12) ◽

pp. e1009291

Author(s):

Marisa E. Miller ◽

Eric S. Nazareno ◽

Susan M. Rottschaefer ◽

Jakob Riddle ◽

Danilo Dos Santos Pereira ◽

...

Keyword(s):

Allele Frequency ◽

Resistance Genes ◽

Genetic Recombination ◽

Genotypic Variation ◽

Puccinia Coronata ◽

Alternate Host ◽

Rust Disease ◽

Temporal Shift ◽

Genome Wide ◽

Frequency Changes

Pathogen populations are expected to evolve virulence traits in response to resistance deployed in agricultural settings. However, few temporal datasets have been available to characterize this process at the population level. Here, we examined two temporally separated populations of Puccinia coronata f. sp. avenae (Pca), which causes crown rust disease in oat (Avena sativa) sampled from 1990 to 2015. We show that a substantial increase in virulence occurred from 1990 to 2015 and this was associated with a genetic differentiation between populations detected by genome-wide sequencing. We found strong evidence for genetic recombination in these populations, showing the importance of the alternate host in generating genotypic variation through sexual reproduction. However, asexual expansion of some clonal lineages was also observed within years. Genome-wide association analysis identified seven Avr loci associated with virulence towards fifteen Pc resistance genes in oat and suggests that some groups of Pc genes recognize the same pathogen effectors. The temporal shift in virulence patterns in the Pca populations between 1990 and 2015 is associated with changes in allele frequency in these genomic regions. Nucleotide diversity patterns at a single Avr locus corresponding to Pc38, Pc39, Pc55, Pc63, Pc70, and Pc71 showed evidence of a selective sweep associated with the shift to virulence towards these resistance genes in all 2015 collected isolates.

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Allele frequency dynamics in a pedigreed natural population

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1813852116 ◽

2018 ◽

Vol 116 (6) ◽

pp. 2158-2164 ◽

Cited By ~ 14

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.

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Broad geographic sampling reveals the shared basis and environmental correlates of seasonal adaptation in Drosophila

eLife ◽

10.7554/elife.67577 ◽

2021 ◽

Vol 10 ◽

Author(s):

Heather E Machado ◽

Alan Bergland ◽

Ryan W Taylor ◽

Susanne Tilk ◽

Emily Behrman ◽

...

Keyword(s):

Allele Frequency ◽

Weather Conditions ◽

Frequency Change ◽

Fluctuating Selection ◽

Seasonal Adaptation ◽

Environmental Correlates ◽

Chromosomal Inversions ◽

Genome Wide ◽

Evolutionary Force ◽

Genomic Response

To advance our understanding of adaptation to temporally varying selection pressures, we identified signatures of seasonal adaptation occurring in parallel among Drosophila melanogaster populations. Specifically, we estimated allele frequencies genome-wide from flies sampled early and late in the growing season from 20 widely dispersed populations. We identified parallel seasonal allele frequency shifts across North America and Europe, demonstrating that seasonal adaptation is a general phenomenon of temperate fly populations. Seasonally fluctuating polymorphisms are enriched in large chromosomal inversions and we find a broad concordance between seasonal and spatial allele frequency change. The direction of allele frequency change at seasonally variable polymorphisms can be predicted by weather conditions in the weeks prior to sampling, linking the environment and the genomic response to selection. Our results suggest that fluctuating selection is an important evolutionary force affecting patterns of genetic variation in Drosophila.

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The Linked Selection Signature of Rapid Adaptation in Temporal Genomic Data

10.1101/559419 ◽

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.

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Allele frequency changes in artificial selection experiments: statistical power and precision of QTL mapping

Genetics Research ◽

10.1017/s0016672398003711 ◽

1999 ◽

Vol 73 (2) ◽

pp. 177-184 ◽

Cited By ~ 9

Author(s):

YUSEOB KIM ◽

WOLFGANG STEPHAN

Keyword(s):

Allele Frequency ◽

Artificial Selection ◽

Statistical Power ◽

Statistical Tests ◽

Marker Locus ◽

Marker Allele ◽

Selection Experiments ◽

Correct Location ◽

Trait Locus ◽

Frequency Changes

A simple mathematical model of genic directional selection is developed to study frequency changes of genetic marker alleles that are partially linked to a quantitative trait locus (QTL) under artificial selection. The effects of population size, number of generations of artificial selection, recombination between marker locus and QTL, and the strength of selection on the change in allele frequency are analysed by the diffusion equation approach and by stimulation. Using these results, we investigate the power of statistical tests for the detection of QTLs based on the observation of significant marker allele frequency changes in selection experiments. The probability of inferring the correct location of a QTL is also obtained.

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