Patterns Of Genomic Variation Research Articles

Evolution of the correlated genomic variation landscape across a divergence continuum in the genus Castanopsis.

The heterogeneous landscape of genomic variation has been well documented in population genomic studies. However, disentangling the intricate interplay of evolutionary forces influencing the genetic variation landscape over time remains challenging. In this study, we assembled a chromosome-level genome for Castanopsis eyrei and sequenced the whole genomes of 276 individuals from 12 Castanopsis species, spanning a broad divergence continuum. We found highly correlated genomic variation landscapes across these species. Furthermore, variations in genetic diversity and differentiation along the genome were strongly associated with recombination rates and gene density. These results suggest that long-term linked selection and conserved genomic features have contributed to the formation of a common genomic variation landscape. By examining how correlations between population summary statistics change throughout the species divergence continuum, we determined that background selection alone does not fully explain the observed patterns of genomic variation; the effects of recurrent selective sweeps must be considered. We further revealed that extensive gene flow has significantly influenced patterns of genomic variation in Castanopsis species. The estimated admixture proportion correlated positively with recombination rate and negatively with gene density, supporting a scenario of selection against gene flow. Additionally, putative introgression regions exhibited strong signals of positive selection, an enrichment of functional genes, and reduced genetic burdens, indicating that adaptive introgression has played a role in shaping the genomes of hybridizing species. This study provides insights into how different evolutionary forces have interacted in driving the evolution of the genomic variation landscape.

Population genomics of four co-distributed frog species in a barrier island system

Abstract In nature, small populations are often of concern because of limited genetic diversity, which underlies adaptive potential in the face of environmental change. Assessing patterns of genetic variation within co-distributed species sampled across varied landscapes can therefore illuminate their capacity to persist over time. We sequenced new genome-wide sequence data (double-digest restriction site-associated DNA sequencing) for four frog species (Anaxyrus terrestris, Hyla cinerea, Hyla squirella, and Rana sphenocephala) sampled from two barrier islands and the adjacent mainland of northern Florida. We calculated genomic diversity metrics and analysed spatial patterns of genomic variation for each species. We found higher genomic diversity within mainland individuals compared to island individuals for all species, suggesting a consistent effect of small island area on diversity across species. Three species (all but A. terrestris) showed significant signatures of isolation by distance, and some clustering analyses indicated separation of island and mainland individuals within species. We identified subtle differences in the strength of these patterns among species, with the strongest genetic differentiation observed in R. sphenocephala. Finally, we found evidence of recent migration between island and mainland populations for all species, which likely explains the limited genetic structure observed and contributes to the persistence of these small populations.

Isolation by environment and its consequences for range shifts with global change: Landscape genomics of the invasive plant common tansy.

Invasive species are a growing global economic and ecological problem. However, it is not well understood how environmental factors mediate invasive range expansion. In this study, we investigated the recent and rapid range expansion of common tansy across environmental gradients in Minnesota, USA. We densely sampled individuals across the expanding range and performed reduced representation sequencing to generate a dataset of 3071 polymorphic loci for 176 individuals. We used non-spatial and spatially explicit analyses to determine the relative influences of geographic distance and environmental variation on patterns of genomic variation. We found no evidence for isolation by distance but strong evidence for isolation by environment, indicating that environmental factors may have modulated patterns of range expansion. Land use classification and soils were particularly important variables related to population structure although they operated on different spatial scales; land use classification was related to broad-scale patterns and soils were related to fine-scale patterns. All analyses indicated a distinctive genetic cluster in the most recently invaded portion of the range. Individuals from the far northwestern range margin were separated from the remainder of the range by reduced migration, which was associated with environmental resistance. This portion of the range was invaded primarily in the last 15 years. Ecological niche models also indicated that this cluster was associated with the expansion of the niche. While invasion is often assumed to be primarily influenced by dispersal limitation, our results suggest that ongoing invasion and range shifts with climate change may be strongly affected by environmental heterogeneity.

Environmental variation predicts patterns of genomic variation in an African tropical forest frog

Central African rainforests are predicted to be disproportionately affected by future climate change. How species will cope with these changes is unclear, but rapid environmental changes will likely impose strong selection pressures. Here we examined environmental drivers of genomic variation in the central African puddle frog (Phrynobatrachus auritus) to identify areas of elevated environmentally-associated turnover. We also compared current and future climate models to pinpoint areas of high genomic vulnerability where allele frequencies will have to shift the most in order to keep pace with future climate change. Neither physical landscape barriers nor the effects of past Pleistocene refugia influenced genomic differentiation. Alternatively, geographic distance and seasonal aspects of precipitation are the most important drivers of SNP allele frequency variation. Patterns of genomic differentiation coincided with key ecological gradients across the forest-savanna ecotone, montane areas, and a coastal to interior rainfall gradient. Areas of greatest vulnerability were found in the lower Sanaga basin, the southeastern region of Cameroon, and southwest Gabon. In contrast with past conservation efforts that have focused on hotspots of species richness or endemism, our findings highlight the importance of maintaining environmentally heterogeneous landscapes to preserve genomic variation and ongoing evolutionary processes in the face of climate change.

Population genomics analysis reveals footprints of selective breeding in a rapid-growth variety of Paulownia fortunei with apical dominance

Paulownia fortunei is an ecologically and economically valuable tree cultivated for its rapid growth and high-quality timber. To enhance Paulownia germplasm, we have developed the elite variety QingT with patented advantages in growth rate and apical dominance. To illuminate the genetic basis of QingT's superior traits, here we harness comparative population genomics to analyze genomic variation patterns between QingT and common Paulownia. We performed whole-genome re-sequencing of 30 QingT and 30 common samples, detecting 15.6 million SNPs and 2.6 million indels. Phylogeny and population structure analyses robustly partitioned common and QingT into distinct groups which indicate robust genome stabilization. QingT exhibited reduced heterozygosity and linkage disequilibrium decay compared to common Paulownia, reflecting high recombination, indicating hybridizing effects with common white-flowered string is the source of its patented advantages. Genome selection scans uncovered 25 regions of 169 genes with elevated nucleotide diversity, indicating selection sweeps among groups. Functional analysis of sweep genes revealed upregulation of ribosomal, biosynthesis, and growth pathways in QingT, implicating enhanced protein production and developmental processes in its rapid growth phenotype. This study's insights comprehensively chart genomic variation during Paulownia breeding, localizing candidate loci governing agronomic traits, and underpinnings of future molecular breeding efforts to boost productivity.

Resequencing Analyses Revealed Genetic Diversity and Selection Signatures during Rabbit Breeding and Improvement.

Domestication has shaped the diverse characteristics of rabbits, including coat color, fur structure, body size, and various physiological traits. Utilizing whole-genome resequencing (DNBSEQ-T7), we analyzed the genetic diversity, population structure, and genomic selection across 180 rabbits from 17 distinct breeds to uncover the genetic basis of these traits. We conducted whole-genome sequencing on 17 rabbit breeds, identifying 17,430,184 high-quality SNPs and analyzing genomic diversity, patterns of genomic variation, population structure, and selection signatures related to coat color, coat structure, long hair, body size, reproductive capacity, and disease resistance. Through PCA and NJ tree analyses, distinct clusters emerged among Chinese indigenous rabbits, suggesting varied origins and domestication histories. Selective sweep testing pinpointed regions and genes linked to domestication and key morphological and economic traits, including those affecting coat color (TYR, ASIP), structure (LIPH), body size (INSIG2, GLI3), fertility (EDNRA, SRD5A2), heat stress adaptation (PLCB1), and immune response (SEC31A, CD86, LAP3). Our study identified key genomic signatures of selection related to traits such as coat color, fur structure, body size, and fertility; these findings highlight the genetic basis underlying phenotypic diversification in rabbits and have implications for breeding programs aiming to improve productive, reproductive, and adaptive traits. The detected genomic signatures of selection also provide insights into rabbit domestication and can aid conservation efforts for indigenous breeds.

A quantitative genetic model of background selection in humans.

Across the human genome, there are large-scale fluctuations in genetic diversity caused by the indirect effects of selection. This "linked selection signal" reflects the impact of selection according to the physical placement of functional regions and recombination rates along chromosomes. Previous work has shown that purifying selection acting against the steady influx of new deleterious mutations at functional portions of the genome shapes patterns of genomic variation. To date, statistical efforts to estimate purifying selection parameters from linked selection models have relied on classic Background Selection theory, which is only applicable when new mutations are so deleterious that they cannot fix in the population. Here, we develop a statistical method based on a quantitative genetics view of linked selection, that models how polygenic additive fitness variance distributed along the genome increases the rate of stochastic allele frequency change. By jointly predicting the equilibrium fitness variance and substitution rate due to both strong and weakly deleterious mutations, we estimate the distribution of fitness effects (DFE) and mutation rate across three geographically distinct human samples. While our model can accommodate weaker selection, we find evidence of strong selection operating similarly across all human samples. Although our quantitative genetic model of linked selection fits better than previous models, substitution rates of the most constrained sites disagree with observed divergence levels. We find that a model incorporating selective interference better predicts observed divergence in conserved regions, but overall our results suggest uncertainty remains about the processes generating fitness variation in humans.

A genotyping array for the globally invasive vector mosquito, Aedes albopictus

BackgroundAlthough whole-genome sequencing (WGS) is the preferred genotyping method for most genomic analyses, limitations are often experienced when studying genomes characterized by a high percentage of repetitive elements, high linkage, and recombination deserts. The Asian tiger mosquito (Aedes albopictus), for example, has a genome comprising up to 72% repetitive elements, and therefore we set out to develop a single-nucleotide polymorphism (SNP) chip to be more cost-effective. Aedes albopictus is an invasive species originating from Southeast Asia that has recently spread around the world and is a vector for many human diseases. Developing an accessible genotyping platform is essential in advancing biological control methods and understanding the population dynamics of this pest species, with significant implications for public health.MethodsWe designed a SNP chip for Ae. albopictus (Aealbo chip) based on approximately 2.7 million SNPs identified using WGS data from 819 worldwide samples. We validated the chip using laboratory single-pair crosses, comparing technical replicates, and comparing genotypes of samples genotyped by WGS and the SNP chip. We then used the chip for a population genomic analysis of 237 samples from 28 sites in the native range to evaluate its usefulness in describing patterns of genomic variation and tracing the origins of invasions.ResultsProbes on the Aealbo chip targeted 175,396 SNPs in coding and non-coding regions across all three chromosomes, with a density of 102 SNPs per 1 Mb window, and at least one SNP in each of the 17,461 protein-coding genes. Overall, 70% of the probes captured the genetic variation. Segregation analysis found that 98% of the SNPs followed expectations of single-copy Mendelian genes. Comparisons with WGS indicated that sites with genotype disagreements were mostly heterozygotes at loci with WGS read depth < 20, while there was near complete agreement with WGS read depths > 20, indicating that the chip more accurately detects heterozygotes than low-coverage WGS. Sample sizes did not affect the accuracy of the SNP chip genotype calls. Ancestry analyses identified four to five genetic clusters in the native range with various levels of admixture.ConclusionsThe Aealbo chip is highly accurate, is concordant with genotypes from WGS with high sequence coverage, and may be more accurate than low-coverage WGS.Graphical

A statistical learning method for simultaneous copy number estimation and subclone clustering with single-cell sequencing data.

The availability of single-cell sequencing (SCS) enables us to assess intra-tumor heterogeneity and identify cellular subclones without the confounding effect of mixed cells. Copy number aberrations (CNAs) have been commonly used to identify subclones in SCS data using various clustering methods, as cells comprising a subpopulation are found to share a genetic profile. However, currently available methods may generate spurious results (e.g., falsely identified variants) in the procedure of CNA detection, thereby diminishing the accuracy of subclone identification within a large, complex cell population. In this study, we developed a subclone clustering method based on a fused lasso model, referred to as FLCNA, which can simultaneously detect CNAs in single-cell DNA sequencing (scDNA-seq) data. Spike-in simulations were conducted to evaluate the clustering and CNA detection performance of FLCNA, benchmarking it against existing copy number estimation methods (SCOPE, HMMcopy) in combination with commonly used clustering methods. Application of FLCNA to a scDNA-seq data set of breast cancer revealed different genomic variation patterns in neoadjuvant chemotherapy-treated samples and pretreated samples. We show that FLCNA is a practical and powerful method for subclone identification and CNA detection with scDNA-seq data.

Whole-genome sequencing identified candidate genes associated with high and low litter size in Chuanzhong black goats.

The reproductive performance of goats significantly influences breeding efficiency and economic returns, with litter size serving as a comprehensive indicator. Despite this, research on the genetic control of litter size remains limited. Therefore, we aimed to explore the candidate genes affecting fecundity and compared the whole-genome sequences (WGS) of 15 high-litter (HL) and 15 low-litter (LL) size in Chuanzhong black goats. Then genetic diversity and genomic variation patterns were analyzed by phylogenetic, principal component and population genetic structure analysis, it was found that HL and LL subpopulations diverged. Population evolutionary selection elimination analysis was performed by Fst and θπ resulted in 506 genes were annotated in HL and 528 genes in LL. These genes were mainly related to Hippo signaling pathway, G protein-coupled signaling pathway, G protein-coupled receptor activity, cell surface receptor signaling pathway, gonadal and reproductive structure development. According to the significantly selected genomic regions and important pathways, we found that the g.89172108T > G variant locus in the exon of the AMH gene was significantly associated with litter size (P < 0.05), which could be used as an auxiliary selection gene for the high fertility of Chuanzhong black Goat.

Genomic Signatures of Local Adaptation under High Gene Flow in Lumpfish-Implications for Broodstock Provenance Sourcing and Larval Production.

Aquaculture of the lumpfish (Cyclopterus lumpus L.) has become a large, lucrative industry owing to the escalating demand for "cleaner fish" to minimise sea lice infestations in Atlantic salmon mariculture farms. We used over 10K genome-wide single nucleotide polymorphisms (SNPs) to investigate the spatial patterns of genomic variation in the lumpfish along the coast of Norway and across the North Atlantic. Moreover, we applied three genome scans for outliers and two genotype-environment association tests to assess the signatures and patterns of local adaptation under extensive gene flow. With our 'global' sampling regime, we found two major genetic groups of lumpfish, i.e., the western and eastern Atlantic. Regionally in Norway, we found marginal evidence of population structure, where the population genomic analysis revealed a small portion of individuals with a different genetic ancestry. Nevertheless, we found strong support for local adaption under high gene flow in the Norwegian lumpfish and identified over 380 high-confidence environment-associated loci linked to gene sets with a key role in biological processes associated with environmental pressures and embryonic development. Our results bridge population genetic/genomics studies with seascape genomics studies and will facilitate genome-enabled monitoring of the genetic impacts of escapees and allow for genetic-informed broodstock selection and management in Norway.

Ancient DNA reveals genetic admixture in China during tiger evolution.

The tiger (Panthera tigris) is a charismatic megafauna species that originated and diversified in Asia and probably experienced population contraction and expansion during the Pleistocene, resulting in low genetic diversity of modern tigers. However, little is known about patterns of genomic diversity in ancient populations. Here we generated whole-genome sequences from ancient or historical (100-10,000 yr old) specimens collected across mainland Asia, including a 10,600-yr-old Russian Far East specimen (RUSA21, 8× coverage) plus six ancient mitogenomes, 14 South China tigers (0.1-12×) and three Caspian tigers (4-8×). Admixture analysis showed that RUSA21 clustered within modern Northeast Asian phylogroups and partially derived from an extinct Late Pleistocene lineage. While some of the 8,000-10,000-yr-old Russian Far East mitogenomes are basal to all tigers, one 2,000-yr-old specimen resembles present Amur tigers. Phylogenomic analyses suggested that the Caspian tiger probably dispersed from an ancestral Northeast Asian population and experienced gene flow from southern Bengal tigers. Lastly, genome-wide monophyly supported the South China tiger as a distinct subspecies, albeit with mitochondrial paraphyly, hence resolving its longstanding taxonomic controversy. The distribution of mitochondrial haplogroups corroborated by biogeographical modelling suggested that Southwest China was a Late Pleistocene refugium for a relic basal lineage. As suitable habitat returned, admixture between divergent lineages of South China tigers took place in Eastern China, promoting the evolution of other northern subspecies. Altogether, our analysis of ancient genomes sheds light on the evolutionary history of tigers and supports the existence of nine modern subspecies.

A Comparison of Non-Destructive Visceral Swab and Tissue Biopsy Sampling Methods for Genotyping-by-Sequencing in the Freshwater Mussel Fusconaia askewi.

Limiting harm to organisms caused by genetic sampling is an important consideration for rare species, and a number of non-destructive sampling techniques have been developed to address this issue in freshwater mussels. Two methods, visceral swabbing and tissue biopsies, have proven to be effective for DNA sampling, though it is unclear as to which method is preferable for genotyping-by-sequencing (GBS). Tissue biopsies may cause undue stress and damage to organisms, while visceral swabbing potentially reduces the chance of such harm. Our study compared the efficacy of these two DNA sampling methods for generating GBS data for the unionid freshwater mussel, the Texas pigtoe (Fusconaia askewi). Our results find both methods generate quality sequence data, though some considerations are in order. Tissue biopsies produced significantly higher DNA concentrations and larger numbers of reads when compared with swabs, though there was no significant association between starting DNA concentration and number of reads generated. Swabbing produced greater sequence depth (more reads per sequence), while tissue biopsies revealed greater coverage across the genome (at lower sequence depth). Patterns of genomic variation as characterized in principal component analyses were similar regardless of the sampling method, suggesting that the less invasive swabbing is a viable option for producing quality GBS data in these organisms.

Balancing selection on an MYB transcription factor maintains the twig trichome color variation in Melastoma normale

BackgroundThe factors that maintain phenotypic and genetic variation within a population have received long-term attention in evolutionary biology. Here the genetic basis and evolution of the geographically widespread variation in twig trichome color (from red to white) in a shrub Melastoma normale was investigated using Pool-seq and evolutionary analyses.ResultsThe results show that the twig trichome coloration is under selection in different light environments and that a 6-kb region containing an R2R3 MYB transcription factor gene is the major region of divergence between the extreme red and white morphs. This gene has two highly divergent groups of alleles, one of which likely originated from introgression from another species in this genus and has risen to high frequency (> 0.6) within each of the three populations under investigation. In contrast, polymorphisms in other regions of the genome show no sign of differentiation between the two morphs, suggesting that genomic patterns of diversity have been shaped by homogenizing gene flow. Population genetics analysis reveals signals of balancing selection acting on this gene, and it is suggested that spatially varying selection is the most likely mechanism of balancing selection in this case.ConclusionsThis study demonstrate that polymorphisms on a single transcription factor gene largely confer the twig trichome color variation in M. normale, while also explaining how adaptive divergence can occur and be maintained in the face of gene flow.

Genomic insights into local adaptation in the Asiatic toad Bufo gargarizans, and its genomic offset to climate warming.

Genomic signatures of local adaptation have been identified in many species but remain sparsely studied in amphibians. Here, we explored genome-wide divergence within the Asiatic toad, Bufo gargarizans, to study local adaptation and genomic offset (i.e., the mismatch between current and future genotype-environment relationships) under climate warming scenarios. We obtained high-quality SNP data for 94 Asiatic toads from 21 populations in China to study spatial patterns of genomic variation, local adaptation, and genomic offset to warming in this wide-ranging species. Population structure and genetic diversity analysis based on high-quality SNPs revealed three clusters of B. gargarizans in the western, central-eastern, and northeastern portions of the species' range in China. Populations generally dispersed along two migration routes, one from the west to the central-east and one from the central-east to the northeast. Both genetic diversity and pairwise F ST were climatically correlated, and pairwise F ST was also correlated with geographic distance. Spatial genomic patterns in B. gargarizans were determined by the local environment and geographic distance. Global warming will increase the extirpation risk of B. gargarizans.

The landscape of nucleotide diversity in Drosophila melanogaster is shaped by mutation rate variation

What shapes the distribution of nucleotide diversity along the genome? Attempts to answer this question have sparked debate about the roles of neutral stochastic processes and natural selection in molecular evolution. However, the mechanisms of evolution do not act in isolation, and integrative models that simultaneously consider the influence of multiple factors on diversity are lacking; without them, confounding factors lurk in the estimates. Here we present a new statistical method that jointly infers the genomic landscapes of genealogies, recombination rates and mutation rates. In doing so, our model captures the effects of genetic drift, linked selection and local mutation rates on patterns of genomic variation. We then formalize a causal model of how these micro-evolutionary mechanisms interact, and cast it as a linear regression to estimate their individual contributions to levels of diversity along the genome. Our analyses reclaim the well-established signature of linked selection in Drosophila melanogaster, but we estimate that the mutation landscape is the major driver of the genome-wide distribution of diversity in this species. Furthermore, our simulation results suggest that in many evolutionary scenarios the mutation landscape will be a crucial factor shaping diversity, depending notably on the genomic window size. We argue that incorporating mutation rate variation into the null model of molecular evolution will lead to more realistic inferences in population genomics.

An unusual suspect: the mutation landscape as a determinant of local variation in nucleotide diversity

What shapes the distribution of nucleotide diversity along the genome? Attempts to answer this question have sparked debate about the roles of neutral stochastic processes and natural selection in molecular evolution. However, the mechanisms of evolution do not act in isolation, and integrative models that simultaneously consider the influence of multiple factors on diversity are lacking; without them, confounding factors lurk in the estimates. Here we present a new statistical method that jointly infers the genomic landscapes of genealogies, recombination rates and mutation rates. In doing so, our model captures the effects of genetic drift, linked selection and local mutation rates on patterns of genomic variation. We then formalise a causal model of how these micro-evolutionary forces interact, and cast it as a linear regression to estimate their individual contributions to levels of diversity along the genome. Our analyses reclaim the well-established signature of linked selection in Drosophila melanogaster, but we estimate that the mutation landscape is the major driver of the genome-wide distribution of diversity in this species. Furthermore, our simulation results suggest that in many evolutionary scenarios the mutation landscape will be a crucial factor shaping diversity, depending notably on the genomic window size. We argue that incorporating mutation rate variation into the null model of molecular evolution will lead to more robust inferences in population genomics.

Demographic and spatially-explicit landscape genomic analyses in a tropical oak reveal the impacts of late Quaternary climate change on Andean montane forests.

Tropical Andes are one of the most important biodiversity hotspots on earth, yet our understanding on how their biotas have responded to Quaternary climatic oscillations is extraordinarily limited and the alternative models proposed to explain their demographic dynamics have been seldom formally evaluated. Here, we test the hypothesis that the interplay between the spatial configuration of geographical barriers to dispersal and elevational displacements driven by Quaternary cooling-warming cycles have shaped the demographic trajectories of montane oak forests (Quercus humboldtii) from the Colombian Andes. Specifically, we integrate genomic data and environmental niche modelling at fine temporal resolution to test competing spatially-explicit demographic and coalescent models, including scenarios considering (i) isotropic gene flow through the landscape, (ii) the hypothetical impact of contemporary barriers to dispersal (i.e., inter-Andean valleys), and (ii) distributional shifts of montane oak forests from the Last Glacial Maximum to present. Although our data revealed a marked genetic fragmentation of montane oak forests, statistical support for isolation-with-migration models indicate that geographically separated populations from the different Andean Cordilleras regularly exchange gene flow. Accordingly, spatiotemporally-explicit demographic analyses supported a model of flickering connectivity, with scenarios considering isotropic gene flow or currently unsuitable habitats as persistent barriers to dispersal providing a comparatively worse fit to empirical genomic data. Overall, these results emphasize the role of landscape heterogeneity on shaping spatial patterns of genomic variation in montane oak forests, rejecting the hypothesis of genetic continuity and supporting a significant impact of Quaternary climatic oscillations on their demographic trajectories.

Genomic Underpinnings of Population Persistence in Isle Royale Moose.

Island ecosystems provide natural laboratories to assess the impacts of isolation on population persistence. However, most studies of persistence have focused on a single species, without comparisons to other organisms they interact with in the ecosystem. The case study of moose and gray wolves on Isle Royale allows for a direct contrast of genetic variation in isolated populations that have experienced dramatically differing population trajectories over the past decade. Whereas the Isle Royale wolf population recently declined nearly to extinction due to severe inbreeding depression, the moose population has thrived and continues to persist, despite having low genetic diversity and being isolated for ∼120 years. Here, we examine the patterns of genomic variation underlying the continued persistence of the Isle Royale moose population. We document high levels of inbreeding in the population, roughly as high as the wolf population at the time of its decline. However, inbreeding in the moose population manifests in the form of intermediate-length runs of homozygosity suggestive of historical inbreeding and purging, contrasting with the long runs of homozygosity observed in the smaller wolf population. Using simulations, we confirm that substantial purging has likely occurred in the moose population. However, we also document notable increases in genetic load, which could eventually threaten population viability over the long term. Overall, our results demonstrate a complex relationship between inbreeding, genetic diversity, and population viability that highlights the use of genomic datasets and computational simulation tools for understanding the factors enabling persistence in isolated populations.

Demography and linked selection interact to shape the genomic landscape of codistributed woodpeckers during the Ice Age.

The influence of genetic drift on population dynamics during Pleistocene glacial cycles is well understood, but the role of selection in shaping patterns of genomic variation during these events is less explored. We resequenced whole genomes to investigate how demography and natural selection interact to generate the genomic landscapes of Downy and Hairy Woodpecker, species codistributed in previously glaciated North America. First, we explored the spatial and temporal patterns of genomic diversity produced by neutral evolution. Next, we tested (i) whether levels of nucleotide diversity along the genome are correlated with intrinsic genomic properties, such as recombination rate and gene density, and (ii) whether different demographic trajectories impacted the efficacy of selection. Our results revealed cycles of bottleneck and expansion, and genetic structure associated with glacial refugia. Nucleotide diversity varied widely along the genome, but this variation was highly correlated between the species, suggesting the presence of conserved genomic features. In both taxa, nucleotide diversity was positively correlated with recombination rate and negatively correlated with gene density, suggesting that linked selection played a role in reducing diversity. Despite strong fluctuations in effective population size, the maintenance of relatively large populations during glaciations may have facilitated selection. Under these conditions, we found evidence that the individual demographic trajectory of populations modulated linked selection, with purifying selection being more efficient in removing deleterious alleles in large populations. These results highlight that while genome-wide variation reflects the expected signature of demographic change during climatic perturbations, the interaction of multiple processes produces a predictable and highly heterogeneous genomic landscape.