Biology subjects

Booker, T. R.

Publications and source records attributed to Booker, T. R..

17 recordsLinked to original sources

bioRxiv2026

Maintenance of quantitative genetic variation in regions of restricted recombination via associative overdominance

Mutation-selection balance is the most plausible general mechanism for the maintenance of additive genetic variance (VA) for quantitative traits in natural populations. It is well established that the genetic variants affecting traits (QTLs) are widely distributed across species' genomes. At the same time, unconditionally deleterious mutations are also expected to be common, with those with the largest fitness effects tending to be strongly recessive. Many genomes possess regions of restricted recombination that could result in tight linkage between largely recessive deleterious alleles, conditions which can lead to elevated heterozygosity via associative overdominance (AOD). Here we show that weakly selected QTLs linked to genomic regions exhibiting AOD can elevate VA above what is expected in the absence of unconditionally deleterious mutations. Selection on traits when VA is maintained by AOD, however, may expose recessive deleterious alleles as homozygotes, reducing fitness. Thus, while AOD may contribute to the maintenance of VA, variation maintained in this way may not be readily accessible by natural or artificial selection.

evolutionary biology↗

bioRxiv2026

The genetic architecture of local adaptation is historically contingent

Revealing the genetic basis of local adaptation is a common goal of evolutionary biology, but despite theoretical progress, general expectations for the genetic architecture of local adaptation are still unclear. Theoretical analyses usually model simplified ecologies or simplified genetic architectures of adaptive traits, so the interplay of these factors is missing from our understanding. In this study, we use simulations to explore how the interplay of ecological and genetic parameters influences the evolution and genetic architecture of local adaptation. With these simulations, we ask: i) What are the features of alleles that made the largest contribution to local adaptation, and how are they affected by polygenicity of adaptive traits, migration rates, demographic history, and the spatial pattern of the environment? And ii) does allele age moderate the confounding effect from population structure in genotype-environmental associations (GEA)? We find that the frequency, number, and phenotypic effect size of locally adaptive alleles are sensitive to trait polygenicity and demographic history, and that these factors shape the evolutionary dynamics of local adaptation. We find that population expansions can leave legacies in the genetic architecture of local adaptation, reducing the expected number of adaptive alleles relative to models with constant population size, and this effect is long-lasting. Compared to range expansion, other ecological variables known to affect the genetic basis of local adaptation had limited effects. Finally, allele age moderated the confounding effect of population structure and modified the causal effect of environmental variables on genotypes. Alleles that arose around the time of environmental changes often made large contributions to local adaptation, but young alleles often had the highest false positive rates and were the most common age category. We describe how incorporating allele age and its interactions with population structure and environmental variables may increase the sensitivity and specificity of GEA analysis. Overall, this work demonstrates the critical importance that a species demographic history can have on its genetic architecture of local adaptation.

genetics↗

bioRxiv2026

Polygenic and redundant architectures of climate-adaptive traits may complicate genomic predictions of maladaptation

SignificanceUnderstanding the genetic basis of local adaptation is an important step to predict species responses to climate change. Current predictions of maladaptation to climate in trees, however, rely mostly on genotype-environment associations, which overlooks the complexity of genetic architectures underpinning climate-adaptive traits. Based on genotype-phenotype associations, we unveil key aspects of the polygenic architecture of drought tolerance and cold hardiness in two lineages of a widespread conifer. Our results suggest that predictions based solely on climate-associated alleles may mischaracterize maladaptation to future climates due to mismatches between the distribution of climate-associated alleles and alleles contributing to adaptive traits. We also show that cold hardiness and drought tolerance evolved largely independently in the two lineages, and with little pleiotropy between traits. Understanding the genetic architecture of climate-adaptive traits can help predict responses to climate change and inform management strategies that mitigate the effects of future climates. By characterizing the genetic basis of adaptation to spatially varying climate conditions, models can predict response to temporal change in climate by extrapolating from spatial patterns of variation. However, such methods are predicated upon a simple genetic basis, with a linear relationship between allele frequency, phenotype, and environment. Here, we explore the nature of the mapping between genotype, phenotype, and climate adaptation in Douglas-fir, an important North American conifer. Using two large common garden experiments combined with exome sequencing and case-control genome-wide association tests, we found that drought tolerance and cold hardiness in two Douglas-fir varieties (Pseudotsuga menziesii var. menziesii and var. glauca) are highly polygenic with little pleiotropy between the two traits. The two varieties showed little repeated evolution in the genetic basis of drought tolerance and none for cold hardiness. Allelic clines were observed along geographic and climatic gradients across 74 natural populations, but their direction of effect was often inconsistent with phenotypic clines. Our findings reveal that the genomic variation underlying climate-adaptive traits is remarkably complex, with redundancy likely playing a key role in the evolution of the divergent polygenetic architectures of abiotic stress tolerance. This suggests that predicting maladaptation to climate based solely on climate-associated alleles may misrepresent future adaptive responses. Genomic predictions and management practices should focus on individual lineages and consider the particularities of the genetic architecture of climate-adaptive traits.

evolutionary biology↗

bioRxiv2023

Spatial autocorrelation of the environment influences the patterns and genetics of local adaptation

Environmental heterogeneity can lead to spatially varying selection, which can, in turn, lead to local adaptation. Population genetic models have shown that the pattern of environmental variation in space can strongly influence the evolution of local adaptation. In particular, when environmental variation is highly autocorrelated in space local adaptation will more readily evolve. Despite this long-held prediction, the evolutionary genetic consequences of different patterns of environmental variation have not been thoroughly explored. In this study, simulations are used to model local adaptation to different patterns of environmental variation. The simulations confirm that local adaptation is expected to increase with the degree of spatial autocorrelation in the selective environment, but also show that highly heterogeneous environments are more likely to exhibit high variation in local adaptation, a result not previously described. Spatial autocorrelation in the environment also influences the evolution and genetic architecture of local adaptation, with different combinations of allele frequency and effect size arising under different patterns of environmental variation. These differences influence the ability to characterise the genetic basis of local adaptation in different environments. Finally, I analyse a large-scale provenance trial conducted on lodgepole pine and find suggestive evidence that spatially autocorrelated environmental variation leads to stronger local adaptation in natural populations of lodgepole pine. Overall, this work emphasizes the profound importance that the spatial pattern of selection can have on the evolution of local adaptation and how spatial autocorrelation should be considered when formulating hypotheses in ecological and genetic studies. Lay SummaryMany species exhibit local adaptation to environmental variation across their ranges. Theoretical population genetics predicts that the evolution of local adaptation and patterns of genetic variation underlying it will be influenced by the spatial pattern of variation across a species range. However, this prediction has not been thoroughly explored for cases of complex heterogeneous landscapes. In this paper, I analyse simulations and empirical data to characterise the effects that the spatial pattern of environmental variation can have on the evolution of local adaptation and the genetics underlying it. From these analyses, I show that the pattern of environmental variation influences the average level of local adaptation, variation in local adaptation as well as the genetics underlying this important phenomenon.

evolutionary biology↗

bioRxiv2023

How useful is genomic data for predicting maladaptation to future climate?

Methods using genomic information to forecast potential population maladaptation to climate change are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods - Gradient Forests (GFoffset) and the Risk Of Non-Adaptedness (RONA) - using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against two-year and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GFoffset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use.

evolutionary biology↗

bioRxiv2023

Repeated adaptation to whole genome duplication in outcrossing Arabidopsis is mediated by mosaic adaptive haplotypes

Polyploidy, the result of whole genome duplication (WGD), is widespread across the tree of life and is often associated with speciation or adaptability. It is thought that adaptation in autopolyploids (within-species polyploids) may be facilitated by increased access to genetic variation. This variation may be sourced from gene flow with sister diploids and new access to other tetraploid lineages, as well as from increased mutational targets provided by doubled DNA content. Here we deconstruct the origins of haplotype blocks displaying the strongest selection signals in established, successful autopolyploids, Arabidopsis lyrata and Arabidopsis arenosa. We see strong signatures of selection in 17 genes implied in meiosis, cell cycle, and transcription across all four autotetraploid lineages present in our expanded sampling of 983 sequenced genomes. Most prominent in our results is the finding that the tetraploid-characteristic haplotype blocks with the most robust signals of selection were completely absent in diploid sisters. In contrast, the fine-scaled variant mosaics in the tetraploids originated from highly diverse evolutionary sources. These include novel reassortments of trans-specific polymorphism from diploids, new mutations, and tetraploid-specific inter-species hybridization. We speculate that this broad-scale allele acquisition and re-shuffling enabled the autotetraploids to rapidly adapt to the challenges inherent to WGD, and may further promote their adaptation to environmental challenges. Lay summaryPolyploidy, the result of whole genome duplication, is associated with speciation and adaptation. To fuel their often remarkable adaptations, polyploids may access and maintain adaptive alleles more readily than diploids. Here we identify repeated signals of selection on genes that are thought to mediate adaptation to whole genome duplication in two Arabidopsis species. We found that the tetraploid-characteristic haplotype blocks, found in genes exhibiting the most robust signals of selection, were never present in their diploid relatives. Instead, these blocks were made of mosaics forged from multiple allelic sources. We hypothesize that this increased variation helped polyploids to adapt to the process that caused this increase - genome duplication - and may also help them adapt to novel environments.

evolutionary biology↗

bioRxiv2022

Using genome scans to identify genes used repeatedly for adaptation

Adaptation occurring in similar genes or genomic regions in distinct lineages provides evolutionary biologists with a glimpse at the fundamental opportunities for and constraints to diversification. With the widespread availability of high throughput sequencing technologies and the development of population genetic methods to identify the genetic basis of adaptation, studies have begun to compare the evidence for adaptation at the molecular level among distinct lineages. However, methods to study repeated adaptation are often oriented towards genome-wide testing to identify a set of genes with signatures of repeated use, rather than evaluating the significance at the level of an individual gene. In this study, we propose PicMin, a novel statistical method derived from the theory of order statistics that can test for repeated molecular evolution to estimate significance at the level of an individual gene, using the results of genome scans. This method is generalizable to any number of lineages and indeed, statistical power to detect repeated adaptation increases with the number of lineages that have signals of repeated adaptation of a given gene in multiple lineages. An implementation of the method written for R can be downloaded from https://github.com/TBooker/PicMin.

evolutionary biology↗

bioRxiv2021

Background selection under evolving recombination rates

Background selection (BGS), the effect that purifying selection exerts on sites linked to deleterious alleles, is expected to be ubiquitous across eukaryotic genomes. The effects of BGS reflect the interplay of the rates and fitness effects of deleterious mutations with recombination. A fundamental assumption of BGS models is that recombination rates are invariant over time. However, in some lineages recombination rates evolve rapidly, violating this central assumption. Here, we investigate how recombination rate evolution affects genetic variation under BGS. We show that recombination rate evolution modifies the effects of BGS in a manner similar to a localised change in the effective population size, potentially leading to an underestimation of the genome-wide effects of selection. Furthermore, we find evidence that recombination rate evolution in the ancestors of modern house mice may have impacted inferences of the genome-wide effects of selection in that species.

evolutionary biology↗

bioRxiv2021

The WZA: A window-based method for characterizing genotype-environment association

Genotype environment association (GEA) studies have the potential to elucidate the genetic basis of local adaptation in natural populations. Specifically, GEA approaches look for a correlation between allele frequencies and putatively selective features of the environment. Genetic markers with extreme evidence of correlation with the environment are presumed to be tagging the location of alleles that contribute to local adaptation. In this study, we propose a new method for GEA studies called the weighted-Z analysis (WZA) that combines information from closely linked sites into analysis windows in a way that was inspired by methods for calculating FST. We analyze simulations modelling local adaptation to heterogeneous environments either using a GEA method that controls for population structure or an uncorrected approach. In the majority of cases we tested, the WZA either outperformed single-SNP based approaches or performed similarly. The WZA outperformed individual SNP approaches when the measured environment is not perfectly correlated with the true selection pressure or when a small number of individuals or demes was sampled. We apply the WZA to previously published data from lodgepole pine and identified candidate loci that were not found in the original study.

evolutionary biology↗

bioRxiv2021

Selective sweeps influence diversity over large regions of the mouse genome

To what extent do substitutions in protein-coding versus gene-regulatory regions contribute to fitness change over time? Answering this question requires estimates of the extent of selection acting on beneficial mutations in the two classes of sites. New mutations that have advantageous or deleterious fitness effects can induce selective sweeps and background selection, respectively, causing variation in the level of neutral genetic diversity along the genome. In this study, we analyse the profiles of genetic variability around protein-coding and regulatory elements in the genomes of wild mice to estimate the parameters of positive selection. We find patterns of diversity consistent with the effects of selection at linked sites, which are similar across mouse taxa, despite differences in effective population size and demographic history. By fitting a model that combines the effects of selective sweeps and background selection, we estimate the strength of positive selection and the frequency of advantageous mutations. We find that strong positive selection is required to explain variation in genetic diversity across the murid genome. In particular, we estimate that beneficial mutations in protein-coding regions have stronger effects on fitness than do mutations in gene-regulatory regions, but that mutations in gene-regulatory regions are more common. Overall though, our parameter estimates suggest that the cumulative fitness changes brought about by beneficial mutations in protein-coding may be greater than those in gene-regulatory elements.

evolutionary biology↗

bioRxiv2021

The genetics of assisted gene flow: immediate costs and long-term benefits

Plant and animal populations are facing several novel risks such as human-mediated habitat fragmentation and climate change that threaten their long-term productivity and persistence. With the genetic health of many populations deteriorating due to climate change outpacing physiological adaptation, human interventions in the form of assisted gene flow (AGF) may provide genetic variation to adapt populations to predicted climate change scenarios and result in more robust and productive populations. We ran genetic simulations to mimic a variety of AGF scenarios and measured their outcomes on population-level fitness to answer the question: in which circumstances is it worthwhile to perform AGF? Based on the parameters we explored, AGF may be harmful in certain situations over the short term (e.g., the first [~]10-20 generations), due to outbreeding depression and introducing deleterious genetic variation. Moreover, under many parameter sets, the benefits of AGF were relatively weak or took many generations to accrue. In general, when the adaptive trait is controlled by many loci of small effect, the benefits of assisted gene flow take much longer to realize-potentially too long for most climate-related management decisions. We also show that when translocation effort is divided across several generations and outbreeding depression is strong, the recipient population experiences a smaller decrease in fitness as compared to moving all individuals in a single effort. Importantly, in most cases, we show that the genomic integrity of the recipient population remains relatively intact following AGF; the amount of genetic material from the donor population typically ends up constituting no more of the recipient populations genome than the fraction introduced. Our results will be useful for conservation practitioners and silviculturists, for instance, aiming to intervene and adaptively manage so that populations maintain a robust genetic health and maintain productivity into the future given anthropogenic climate change.

evolutionary biology↗

bioRxiv2020

Haploid, diploid, and pooled exome capture recapitulate features of biology and paralogy in two non-model tree species

Despite their suitability for studying evolution, many conifer species have large and repetitive giga-genomes (16-31Gbp) that create hurdles to producing high coverage SNP datasets that captures diversity from across the entirety of the genome. Due in part to multiple ancient whole genome duplication events, gene family expansion and subsequent evolution within Pinaceae, false diversity from the misalignment of paralog copies create further challenges in accurately and reproducibly inferring evolutionary history from sequence data. Here, we leverage the cost-saving benefits of pool-seq and exome-capture to discover SNPs in two conifer species, Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco, Pinaceae) and jack pine (Pinus banksiana Lamb., Pinaceae). We show, using minimal baseline filtering, that allele frequencies estimated from pooled individuals show a strong positive correlation with those estimated by sequencing the same population as individuals (r > 0.948), on par with such comparisons made in model organisms. Further, we highlight the use of haploid megagametophyte tissue in identifying sites that are likely due to misaligned paralogs. Together with additional minor filtering, we show that it is possible to remove many of the loci with large frequency estimate discrepancies between individual and pooled sequencing approaches, improving the correlation further (r > 0.973). Our work addresses bioinformatic challenges in non-model organisms with large and complex genomes, highlights the use of megagametophyte tissue for the identification of paralog sites when sequencing large numbers of populations, and suggests the combination of pool-seq and exome capture to be robust for further evolutionary hypothesis testing in these systems.

genomics↗

bioRxiv2020

Variation in recombination rate affects detection of FST outliers under neutrality

Genome scans can potentially identify genetic loci involved in evolutionary processes such as local adaptation and gene flow. Here, we show that recombination rate variation across a neutrally evolving genome gives rise to mixed sampling distributions of mean FST[Formula], a common population genetic summary statistic. In particular, we show that in regions of low recombination the distribution of [Formula] estimates have more variance and a longer tail than in more highly recombining regions. Determining outliers from the genome-wide distribution without taking local recombination rate into consideration may therefore increase the frequency of false positives in low recombination regions and be overly conservative in more highly recombining ones. We perform genome-scans on simulated and empirical Drosophila melanogaster datasets and, in both cases, find patterns consistent with this neutral model. Similar patterns are observed for other summary statistics used to capture variation in the coalescent process. Linked selection, particularly background selection, is often invoked to explain heterogeneity in [Formula] across the genome, but here we point out that even under neutrality, statistical artefacts can arise due to variation in recombination rate. Our results highlight a flaw in the design of genome scan studies and suggest that without estimates of local recombination rate, interpreting the genomic landscape of any summary statistic that captures variation in the coalescent process will be very difficult.

evolutionary biology↗

bioRxiv2019

Inferring parameters of the distribution of fitness effects of new mutations when beneficial mutations are strongly advantageous and rare

Characterising the distribution of fitness effects (DFE) for new mutations is central in evolutionary genetics. Analysis of molecular data under the McDonald-Kreitman test has suggested that adaptive substitutions make a substantial contribution to between-species divergence. Methods have been proposed to estimate the parameters of the distribution of fitness effects for positively selected mutations from the unfolded site frequency spectrum (uSFS). However, when beneficial mutations are strongly selected and rare, they may make little contribution to standing variation and will thus be difficult to detect from the uSFS. In this study, I analyse uSFS data from simulated populations subject to advantageous mutations with effects on fitness ranging from mildly to strongly beneficial. When advantageous mutations are strongly selected and rare, there are very few segregating in populations at any one time. Fitting the uSFS in such cases leads to underestimates of the strength of positive selection and may lead researchers to false conclusions regarding the relative contribution adaptive mutations make to molecular evolution. Fortunately, the parameters for the distribution of fitness effects for harmful mutations are estimated with high accuracy and precision. The results from this study suggest that the parameters of positively selected mutations obtained by analysis of the uSFS should be treated with caution and that variability at linked sites should be used in conjunction with standing variability to estimate parameters of the distribution of fitness effects in the future.

evolutionary biology↗

bioRxiv2019

Global adaptation confounds the search for local adaptation

Spatially varying selection promotes variance in allele frequencies, increasing genetic differentiation between the demes of a metapopulation. For that reason, outliers in the genome wide distribution of summary statistics measuring genetic differentiation, such as FST, are often interpreted as evidence for alleles which contribute to local adaptation. However, in spatially structured populations, the spread of beneficial mutations with spatially uniform effects can also induce transient genetic differentiation and numerous theoretical studies have suggested that species-wide, or global, adaptation makes a substantial contribution to molecular evolution. In this study, we ask whether such global adaptation affects the genome-wide distribution of FST and generates statistical outliers which could be mistaken for local adaptation. Using forward-in-time population genetic simulations assuming parameters for the rate and strength of beneficial mutations similar to those that have been estimated for natural populations, we show the spread of globally beneficial in parapatric populations can readily generate FST outliers, which may be misinterpreted as evidence for local adaptation. The spread of beneficial mutations causes selective sweeps at flanking sites, so the effects of global versus local adaptation may be distinguished by examining patterns of nucleotide diversity along with FST. Our study suggests that global adaptation should be considered in the interpretation of genome-scan results and the design of future studies aimed at understanding the genetic basis of local adaptation.

evolutionary biology↗

bioRxiv2018

Understanding the factors that shape patterns of nucleotide diversity in the house mouse genome

A major goal of population genetics has been to determine the extent to which selection at linked sites influences patterns of neutral nucleotide diversity in the genome. Multiple lines of evidence suggest that diversity is influenced by both positive and negative selection. For example, in many species there are troughs in diversity surrounding functional genomic elements, consistent with the action of either background selection (BGS) or selective sweeps. In this study, we investigated the causes of the diversity troughs that are observed in the wild house mouse genome. Using the unfolded site frequency spectrum (uSFS), we estimated the strength and frequencies of deleterious and advantageous mutations occurring in different functional elements in the genome. We then used these estimates to parameterize forward-in-time simulations of chromosomes, using realistic distributions of functional elements and recombination rate variation in order to determine if selection at linked sites can explain the observed patterns of nucleotide diversity. The simulations suggest that BGS alone cannot explain the dips in diversity around either exons or conserved non-coding elements (CNEs). A combination of BGS and selective sweeps, however, can explain the troughs in diversity around CNEs. This is not the case for protein-coding exons, where observed dips in diversity cannot be explained by parameter estimates obtained from the uSFS. We discuss the extent to which our results provide evidence of sweeps playing a role in shaping patterns of nucleotide diversity and the limitations of using the uSFS for obtaining inferences of the frequency and effects of advantageous mutations.\n\nAuthor SummaryWe present a study examining the causes of variation in nucleotide diversity across the mouse genome. The status of mice as a model organism in the life sciences makes them an excellent model system for studying molecular evolution in mammals. In our study, we analyse how natural selection acting on new mutations can affect levels of nucleotide diversity through the processes of background selection and selective sweeps. To perform our analyses, we first estimated the rate and strengths of selected mutations from a sample of wild mice and then use our estimates in realistic population genetic simulations. Analysing simulations, we find that both harmful and beneficial mutations are required to explain patterns of nucleotide diversity in regions of the genome close to gene regulatory elements. For protein-coding genes, however, our approach is not able to fully explain observed patterns and we think that this is because there are strongly advantageous mutations that occur in protein-coding genes that we were not able to detect.

evolutionary biology↗

bioRxiv2017

The recombination landscape in wild house mice inferred using population genomic data

Characterizing variation in the rate of recombination across the genome is important for understanding many evolutionary processes. The landscape of recombination has been studied previously in the house mouse, Mus musculus, and it is known that the different subspecies exhibit different suites of recombination hotspots. However, it is not established whether broad-scale variation in the rate of recombination is conserved between the subspecies. In this study, we construct a fine-scale recombination map for the Eastern house mouse subspecies, M. m. castaneus, using 10 individuals sampled from its ancestral range. After inferring phase, we use LDhelmet to construct recombination maps for each autosome. We find that the spatial distribution of recombination rate is strongly positively between our castaneus map and a map constructed using inbred lines of mice derived predominantly from M. m. domesticus. We also find that levels of genetic diversity in M. m. castaneus are positively correlated with the rate of recombination, consistent with pervasive natural selection acting in the genome. Our study suggests that recombination rate variation is conserved at broad scales between M. musculus subspecies.

evolutionary biology↗