A new approach for using genome scans to detect recent positive selection in the human genome

Genome-wide scanning for signals of recent positive selection is essential for a comprehensive and systematic understanding of human adaptation. Here, we present a genomic survey of recent local selective sweeps, especially aimed at those nearly or recently completed. A novel approach was developed for such signals, based on contrasting the extended haplotype homozygosity (EHH) profiles between populations. We applied this method to the genome single nucleotide polymorphism (SNP) data of both the International HapMap Project and Perlegen Sciences, and detected widespread signals of recent local selection across the genome, consisting of both complete and partial sweeps. A challenging problem of genomic scans of recent positive selection is to clearly distinguish selection from neutral effects, given the high sensitivity of the test statistics to departures from neutral demographic assumptions and the lack of a single, accurate neutral model of human history. We therefore developed a new procedure that is robust across a wide range of demographic and ascertainment models, one that indicates that certain portions of the genome clearly depart from neutrality. Simulations of positive selection showed that our tests have high power towards strong selection sweeps that have undergone fixation. Gene ontology analysis of the candidate regions revealed several new functional groups that might help explain some important interpopulation differences in phenotypic traits.     

Genome scans of DNA variability in humans reveal evidence for selective sweeps outside of Africa

The last 50,000-150,000 years of human history have been characterized by rapid demographic expansions and the colonization of novel environments outside of sub-Saharan Africa. Mass migrations outside the ancestral species range likely entailed many new selection pressures, suggesting that genetic adaptation to local environmental conditions may have been more prevalent in colonizing populations outside of sub-Saharan Africa. Here we report a test of this hypothesis using genome-wide patterns of DNA polymorphism. We conducted a multilocus scan of microsatellite variability to identify regions of the human genome that may have been subject to continent-specific hitchhiking events. Using published polymorphism data for a total of 624 autosomal loci in multiple populations of humans, we used coalescent simulations to identify candidate loci for geographically restricted selective sweeps. We identified a total of 13 loci that appeared as outliers in replicated population comparisons involving different reference samples for Africa. A disproportionate number of these loci exhibited reduced levels of relative variability in non-African populations alone, suggesting that recent episodes of positive selection have been more prevalent outside of sub-Saharan Africa.     

McSwan: A joint site frequency spectrum method to detect and date selective sweeps across multiple population genomes

Inferring the mode and tempo of natural selection helps further our understanding of adaptation to past environmental changes. Here, we introduce McSwan, a method to detect and date past and recent natural selection events in the case of a hard sweep. The method is based on the comparison of site frequency spectra obtained under various demographic models that include selection. McSwan demonstrated high power (high sensitivity and specificity) in capturing hard selective sweep events without requiring haplotype phasing. It performed slightly better than SweeD when the recent effective population size was low and the genomic region was small. We then applied our method to a European (CEU) and an African (LWK) human re‐sequencing data set. Most hard sweeps were detected in the CEU population (96%). Moreover, hard sweeps in the African population were estimated to have occurred further back in time (mode: 43,625 years BP) compared to those of Europeans (mode: 24,850 years BP). Most of the estimated ages of hard sweeps in Europeans were associated with the Last Glacial Maximum and were enriched in immunity‐associated genes.     

Demography and natural selection have shaped genetic variation in Drosophila melanogaster: a multi-locus approach

Demography and selection have been recognized for their important roles in shaping patterns of nucleotide variability. To investigate the relative effects of these forces in the genome of Drosophila melanogaster, we used a multi-locus scan (105 fragments) of X-linked DNA sequence variation in a putatively ancestral African and a derived European population. Surprisingly, we found evidence for a recent size expansion in the African population, i.e., a significant excess of singletons at a chromosome-wide level. In the European population, such an excess was not detected. In contrast to the African population, we found evidence for positive natural selection in the European sample: (i) a large number of loci with low levels of variation and (ii) a significant excess of derived variants at the low-variation loci that are fixed in the European sample but rare in the African population. These results are consistent with the hypothesis that the European population has experienced frequent selective sweeps in the recent past during its adaptation to new habitats. Our study shows the advantages of a genomic approach (over a locus-specific analysis) in disentangling demographic and selective forces.     

An analysis of signatures of selective sweeps in natural populations of the house mouse

Population and locus-specific reduction of variability of polymorphic loci could be an indication of positive selection at a linked site (selective sweep) and therefore point toward genes that have been involved in recent adaptations. Analysis of microsatellite variability offers a way to identify such regions and to ask whether they occur more often than expected by chance. We studied four populations of the house mouse (Mus musculus) to assess the frequency of such signatures of selective sweeps under natural conditions. Three samples represent the subspecies Mus m. dometicus [corrected] and came from Germany, France, and Cameroon. One sample came from Kazakhstan and constitutes a population of the subspecies Mus m. [corrected] musculus. Mitochondrial D-loop sequences from all animals confirm their respective assignments. Approximately 200 microsatellite loci were typed for up to 60 unrelated individuals from each population and evaluated for signs of selective sweeps on the basis of Schl?tterer's ln RV and ln RH statistics. Our data suggest that there are slightly more signs of selective sweeps than would have been expected by chance alone in each of the populations and also highlights some of the statistical challenges faced in genome scans for detecting selection. Single-nucleotide polymorphism typing of one sweep signature in the M. m. domesticus populations around the beta-defensin 6 locus confirms a lowered nucleotide diversity in this region and limits the potential sweep region to about 20 kb. However, no amino acid exchange has occurred in the coding region when compared to M. m. musculus. If this sweep signature is due to a recent adaptation, it is expected that a regulatory change would have caused it. Our data provide a framework for conducting a systematic whole genome scan for signatures of selective sweeps in the mouse genome.     

A hierarchical Bayesian model for next-generation population genomics

The demography of populations and natural selection shape genetic variation across the genome and understanding the genomic consequences of these evolutionary processes is a fundamental aim of population genetics. We have developed a hierarchical Bayesian model to quantify genome-wide population structure and identify candidate genetic regions affected by selection. This model improves on existing methods by accounting for stochastic sampling of sequences inherent in next-generation sequencing (with pooled or indexed individual samples) and by incorporating genetic distances among haplotypes in measures of genetic differentiation. Using simulations we demonstrate that this model has a low false-positive rate for classifying neutral genetic regions as selected genes (i.e., Φ(ST) outliers), but can detect recent selective sweeps, particularly when genetic regions in multiple populations are affected by selection. Nonetheless, selection affecting just a single population was difficult to detect and resulted in a high false-negative rate under certain conditions. We applied the Bayesian model to two large sets of human population genetic data. We found evidence of widespread positive and balancing selection among worldwide human populations, including many genetic regions previously thought to be under selection. Additionally, we identified novel candidate genes for selection, several of which have been linked to human diseases. This model will facilitate the population genetic analysis of a wide range of organisms on the basis of next-generation sequence data.     

Controlling the false-positive rate in multilocus genome scans for selection

Rapid typing of genetic variation at many regions of the genome is an efficient way to survey variability in natural populations in an effort to identify segments of the genome that have experienced recent natural selection. Following such a genome scan, individual regions may be chosen for further sequencing and a more detailed analysis of patterns of variability, often to perform a parametric test for selection and to estimate the strength of a recent selective sweep. We show here that not accounting for the ascertainment of loci in such analyses leads to false inference of natural selection when the true model is selective neutrality, because the procedure of choosing unusual loci (in comparison to the rest of the genome-scan data) selects regions of the genome with genealogies similar to those expected under models of recent directional selection. We describe a simple and efficient correction for this ascertainment bias, which restores the false-positive rate to near-nominal levels. For the parameters considered here, we find that obtaining a test with the expected distribution of P-values depends on accurately accounting both for ascertainment of regions and for demography. Finally, we use simulations to explore the utility of relying on outlier loci to detect recent selective sweeps. We find that measures of diversity and of population differentiation are more effective than summaries of the site-frequency spectrum and that sequencing larger regions (2.5 kbp) in genome-scan studies leads to more power to detect recent selective sweeps.     

Soft Selective Sweeps in Complex Demographic Scenarios

Adaptation from de novo mutation can produce so-called soft selective sweeps, where adaptive alleles of independent mutational origin sweep through the population at the same time. Population genetic theory predicts that such soft sweeps should be likely if the product of the population size and the mutation rate toward the adaptive allele is sufficiently large, such that multiple adaptive mutations can establish before one has reached fixation; however, it remains unclear how demographic processes affect the probability of observing soft sweeps. Here we extend the theory of soft selective sweeps to realistic demographic scenarios that allow for changes in population size over time. We first show that population bottlenecks can lead to the removal of all but one adaptive lineage from an initially soft selective sweep. The parameter regime under which such “hardening” of soft selective sweeps is likely is determined by a simple heuristic condition. We further develop a generalized analytical framework, based on an extension of the coalescent process, for calculating the probability of soft sweeps under arbitrary demographic scenarios. Two important limits emerge within this analytical framework: In the limit where population-size fluctuations are fast compared to the duration of the sweep, the likelihood of soft sweeps is determined by the harmonic mean of the variance effective population size estimated over the duration of the sweep; in the opposing slow fluctuation limit, the likelihood of soft sweeps is determined by the instantaneous variance effective population size at the onset of the sweep. We show that as a consequence of this finding the probability of observing soft sweeps becomes a function of the strength of selection. Specifically, in species with sharply fluctuating population size, strong selection is more likely to produce soft sweeps than weak selection. Our results highlight the importance of accurate demographic estimates over short evolutionary timescales for understanding the population genetics of adaptation from de novo mutation.     

Whole‐genome sequencing of two North American Drosophila melanogaster populations reveals genetic differentiation and positive selection

The prevailing demographic model for Drosophila melanogaster suggests that the colonization of North America occurred very recently from a subset of European flies that rapidly expanded across the continent. This model implies a sudden population growth and range expansion consistent with very low or no population subdivision. As flies adapt to new environments, local adaptation events may be expected. To describe demographic and selective events during North American colonization, we have generated a data set of 35 individual whole‐genome sequences from inbred lines of D. melanogaster from a west coast US population (Winters, California, USA) and compared them with a public genome data set from Raleigh (Raleigh, North Carolina, USA). We analysed nuclear and mitochondrial genomes and described levels of variation and divergence within and between these two North American D. melanogaster populations. Both populations exhibit negative values of Tajima's D across the genome, a common signature of demographic expansion. We also detected a low but significant level of genome‐wide differentiation between the two populations, as well as multiple allele surfing events, which can be the result of gene drift in local subpopulations on the edge of an expansion wave. In contrast to this genome‐wide pattern, we uncovered a 50‐kilobase segment in chromosome arm 3L that showed all the hallmarks of a soft selective sweep in both populations. A comparison of allele frequencies within this divergent region among six populations from three continents allowed us to cluster these populations in two differentiated groups, providing evidence for the action of natural selection on a global scale.     

Disentangling the effects of demography and selection in human history

Demographic events affect all genes in a genome, whereas natural selection has only local effects. Using publicly available data from 151 loci sequenced in both European-American and African-American populations, we attempt to distinguish the effects of demography and selection. To analyze large sets of population genetic data such as this one, we introduce "Perlymorphism," a Unix-based suite of analysis tools. Our analyses show that the demographic histories of human populations can account for a large proportion of effects on the level and frequency of variation across the genome. The African-American population shows both a higher level of nucleotide diversity and more negative values of Tajima's D statistic than does a European-American population. Using coalescent simulations, we show that the significantly negative values of the D statistic in African-Americans and the positive values in European-Americans are well explained by relatively simple models of population admixture and bottleneck, respectively. Working within these nonequilibrium frameworks, we are still able to show deviations from neutral expectations at a number of loci, including ABO and TRPV6. In addition, we show that the frequency spectrum of mutations--corrected for levels of polymorphism--is correlated with recombination rate only in European-Americans. These results are consistent with repeated selective sweeps in non-African populations, in agreement with recent reports using microsatellite data.     

A practical genome scan for population-specific strong selective sweeps that have reached fixation

Phenotypic divergences between modern human populations have developed as a result of genetic adaptation to local environments over the past 100,000 years. To identify genes involved in population-specific phenotypes, it is necessary to detect signatures of recent positive selection in the human genome. Although detection of elongated linkage disequilibrium (LD) has been a powerful tool in the field of evolutionary genetics, current LD-based approaches are not applicable to already fixed loci. Here, we report a method of scanning for population-specific strong selective sweeps that have reached fixation. In this method, genome-wide SNP data is used to analyze differences in the haplotype frequency, nucleotide diversity, and LD between populations, using the ratio of haplotype homozygosity between populations. To estimate the detection power of the statistics used in this study, we performed computer simulations and found that these tests are relatively robust against the density of typed SNPs and demographic parameters if the advantageous allele has reached fixation. Therefore, we could determine the threshold for maintaining high detection power, regardless of SNP density and demographic history. When this method was applied to the HapMap data, it was able to identify the candidates of population-specific strong selective sweeps more efficiently than the outlier approach that depends on the empirical distribution. This study, confirming strong positive selection on genes previously reported to be associated with specific phenotypes, also identifies other candidates that are likely to contribute to phenotypic differences between human populations.     

Limited Evidence for Classic Selective Sweeps in African Populations

While hundreds of loci have been identified as reflecting strong-positive selection in human populations, connections between candidate loci and specific selective pressures often remain obscure. This study investigates broader patterns of selection in African populations, which are underrepresented despite their potential to offer key insights into human adaptation. We scan for hard selective sweeps using several haplotype and allele-frequency statistics with a data set of nearly 500,000 genome-wide single-nucleotide polymorphisms in 12 highly diverged African populations that span a range of environments and subsistence strategies. We find that positive selection does not appear to be a strong determinant of allele-frequency differentiation among these African populations. Haplotype statistics do identify putatively selected regions that are shared across African populations. However, as assessed by extensive simulations, patterns of haplotype sharing between African populations follow neutral expectations and suggest that tails of the empirical distributions contain false-positive signals. After highlighting several genomic regions where positive selection can be inferred with higher confidence, we use a novel method to identify biological functions enriched among populations’ empirical tail genomic windows, such as immune response in agricultural groups. In general, however, it seems that current methods for selection scans are poorly suited to populations that, like the African populations in this study, are affected by ascertainment bias and have low levels of linkage disequilibrium, possibly old selective sweeps, and potentially reduced phasing accuracy. Additionally, population history can confound the interpretation of selection statistics, suggesting that greater care is needed in attributing broad genetic patterns to human adaptation.     

Recent Selective Sweeps in North American Drosophila melanogaster Show Signatures of Soft Sweeps

Adaptation from standing genetic variation or recurrent de novo mutation in large populations should commonly generate soft rather than hard selective sweeps. In contrast to a hard selective sweep, in which a single adaptive haplotype rises to high population frequency, in a soft selective sweep multiple adaptive haplotypes sweep through the population simultaneously, producing distinct patterns of genetic variation in the vicinity of the adaptive site. Current statistical methods were expressly designed to detect hard sweeps and most lack power to detect soft sweeps. This is particularly unfortunate for the study of adaptation in species such as Drosophila melanogaster, where all three confirmed cases of recent adaptation resulted in soft selective sweeps and where there is evidence that the effective population size relevant for recent and strong adaptation is large enough to generate soft sweeps even when adaptation requires mutation at a specific single site at a locus. Here, we develop a statistical test based on a measure of haplotype homozygosity (H12) that is capable of detecting both hard and soft sweeps with similar power. We use H12 to identify multiple genomic regions that have undergone recent and strong adaptation in a large population sample of fully sequenced Drosophila melanogaster strains from the Drosophila Genetic Reference Panel (DGRP). Visual inspection of the top 50 candidates reveals that in all cases multiple haplotypes are present at high frequencies, consistent with signatures of soft sweeps. We further develop a second haplotype homozygosity statistic (H2/H1) that, in combination with H12, is capable of differentiating hard from soft sweeps. Surprisingly, we find that the H12 and H2/H1 values for all top 50 peaks are much more easily generated by soft rather than hard sweeps. We discuss the implications of these results for the study of adaptation in Drosophila and in species with large census population sizes.     

Extreme population structure and high interspecific divergence of the Silene Y chromosome

Previous studies have demonstrated that the diversity of Y-linked genes is substantially lower than that of their X-linked homologs in the plant Silene latifolia. This difference has been attributed to selective sweeps, Muller's ratchet, and background selection, processes that are predicted to severely affect the evolution of the nonrecombining Y chromosome. We studied the DNA diversity of a noncoding region of the homologous genes DD44Y and DD44X, sampling S. latifolia populations from a wide geographical area and also including the closely related species S. dioica, S. diclinis, and S. heuffelii. On the Y chromosome of S. latifolia, we found substantial DNA diversity. Geographical population structure was far higher than on the X chromosome and differentiation between the species was also higher for the Y than for the X chromosome. Our findings indicate that the loss of genetic diversity on the Y chromosome in Silene occurs within local populations rather than within entire species. These results are compatible with background selection, Muller's ratchet, and local selective sweeps, but not with species-wide selective sweeps. The higher interspecific divergence of DD44Y, compared to DD44X, supports the hypothesis that Y chromosome differentiation between incipient species precedes reproductive isolation of the entire genome, forming an early stage in the process of speciation.     

Population genomics of natural and experimental populations of guppies (Poecilia reticulata)

Convergent evolution represents one of the best lines of evidence for adaptation, but few cases of phenotypic convergence are understood at the genetic level. Guppies inhabiting the Northern Mountain Range of Trinidad provide a classic example of phenotypic convergent evolution, where adaptation to low or high predation environments has been found for a variety of traits. A major advantage of this system is the possibility of long‐term experimental studies in nature, including transplantation from high to low predation sites. We used genome scans of guppies from three natural high and low predation populations and from two experimentally established populations and their sources to examine whether phenotypic convergent evolution leaves footprints at the genome level. We used population‐genetic modelling approaches to reconstruct the demographic history and migration among sampled populations. Naturally colonized low predation populations had signatures of increased effective population size since colonization, while introduction populations had signatures of decreased effective population size. Only a small number of regions across the genome had signatures of selection in all natural populations. However, the two experimental populations shared many genomic regions under apparent selection, more than expected by chance. This overlap coupled with a population decrease since introduction provides evidence for convergent selection occurring in the two introduced populations. The lack of genetic convergence in the natural populations suggests that convergent evolution is lacking in these populations or that the effects of selection become difficult to detect after a long‐time period.     

Genomewide spatial correspondence between nonsynonymous divergence and neutral polymorphism reveals extensive adaptation in Drosophila

The effect of recurrent selective sweeps is a spatially heterogeneous reduction in neutral polymorphism throughout the genome. The pattern of reduction depends on the selective advantage and recurrence rate of the sweeps. Because many adaptive substitutions responsible for these sweeps also contribute to nonsynonymous divergence, the spatial distribution of nonsynonymous divergence also reflects the distribution of adaptive substitutions. Thus, the spatial correspondence between neutral polymorphism and nonsynonymous divergence may be especially informative about the process of adaptation. Here we study this correspondence using genomewide polymorphism data from Drosophila simulans and the divergence between D. simulans and D. melanogaster. Focusing on highly recombining portions of the autosomes, at a spatial scale appropriate to the study of selective sweeps, we find that neutral polymorphism is both lower and, as measured by a new statistic Q(S), less homogeneous where nonsynonymous divergence is higher and that the spatial structure of this correlation is best explained by the action of strong recurrent selective sweeps. We introduce a method to infer, from the spatial correspondence between polymorphism and divergence, the rate and selective strength of adaptation. Our results independently confirm a high rate of adaptive substitution (approximately 1/3000 generations) and newly suggest that many adaptations are of surprisingly great selective effect (approximately 1%), reducing the effective population size by approximately 15% even in highly recombining regions of the genome.     

Discovery of Ongoing Selective Sweeps within Anopheles Mosquito Populations Using Deep Learning

Identification of partial sweeps, which include both hard and soft sweeps that have not currently reached fixation, provides crucial information about ongoing evolutionary responses. To this end, we introduce partialS/HIC, a deep learning method to discover selective sweeps from population genomic data. partialS/HIC uses a convolutional neural network for image processing, which is trained with a large suite of summary statistics derived from coalescent simulations incorporating population-specific history, to distinguish between completed versus partial sweeps, hard versus soft sweeps, and regions directly affected by selection versus those merely linked to nearby selective sweeps. We perform several simulation experiments under various demographic scenarios to demonstrate partialS/HIC’s performance, which exhibits excellent resolution for detecting partial sweeps. We also apply our classifier to whole genomes from eight mosquito populations sampled across sub-Saharan Africa by the Anopheles gambiae 1000 Genomes Consortium, elucidating both continent-wide patterns as well as sweeps unique to specific geographic regions. These populations have experienced intense insecticide exposure over the past two decades, and we observe a strong overrepresentation of sweeps at insecticide resistance loci. Our analysis thus provides a list of candidate adaptive loci that may be relevant to mosquito control efforts. More broadly, our supervised machine learning approach introduces a method to distinguish between completed and partial sweeps, as well as between hard and soft sweeps, under a variety of demographic scenarios. As whole-genome data rapidly accumulate for a greater diversity of organisms, partialS/HIC addresses an increasing demand for useful selection scan tools that can track in-progress evolutionary dynamics.     

Fast and robust detection of ancestral selective sweeps

There are few methods tailored for detecting signals of positive selection in populations directly ancestral to multiple descendent populations. We introduce the ancestral branch statistic (ABS), a four‐population summary statistic for identifying selective sweeps occurring in the direct ancestor of a pair of populations. Simulations show that ABS performs at least as well as, and often better under model violations, than the complementary likelihood approach of 3P‐CLR across diverse selection scenarios and parameter values. We first applied ABS to contemporary human genomic data to identify genes that may have been adaptive in ancestral East Asian populations, uncovering the well‐established candidate EDAR, as well as a novel candidate SLC35F3, which encodes a putative thiamine transporter that may have been involved in adaptation to eating polished grains. Next, we performed scans with ancient European genomic data to reexamine evidence of recent positive selection in ancestral Europeans. The MCM6/LCT cluster and the SLC45A2 and HERC2 genes are strong outliers, agreeing with previous studies. Novel candidates, such as SLC30A9 and CYP1A2, may have been involved in adaptation to local nutrient sufficiency and lifestyle changes. Finally, we provide open‐source software, CalcABS, which can perform genomic scans of ancestral sweeps with ABS from population allele frequency data.     

Genome‐wide evidence for divergent selection between populations of a major agricultural pathogen

The genetic and environmental homogeneity in agricultural ecosystems is thought to impose strong and uniform selection pressures. However, the impact of this selection on plant pathogen genomes remains largely unknown. We aimed to identify the proportion of the genome and the specific gene functions under positive selection in populations of the fungal wheat pathogen Zymoseptoria tritici. First, we performed genome scans in four field populations that were sampled from different continents and on distinct wheat cultivars to test which genomic regions are under recent selection. Based on extended haplotype homozygosity and composite likelihood ratio tests, we identified 384 and 81 selective sweeps affecting 4% and 0.5% of the 35 Mb core genome, respectively. We found differences both in the number and the position of selective sweeps across the genome between populations. Using a XtX‐based outlier detection approach, we identified 51 extremely divergent genomic regions between the allopatric populations, suggesting that divergent selection led to locally adapted pathogen populations. We performed an outlier detection analysis between two sympatric populations infecting two different wheat cultivars to identify evidence for host‐driven selection. Selective sweep regions harboured genes that are likely to play a role in successfully establishing host infections. We also identified secondary metabolite gene clusters and an enrichment in genes encoding transporter and protein localization functions. The latter gene functions mediate responses to environmental stress, including interactions with the host. The distinct gene functions under selection indicate that both local host genotypes and abiotic factors contributed to local adaptation.     

Whole‐genome resequencing uncovers molecular signatures of natural and sexual selection in wild bighorn sheep

The identification of genes influencing fitness is central to our understanding of the genetic basis of adaptation and how it shapes phenotypic variation in wild populations. Here, we used whole‐genome resequencing of wild Rocky Mountain bighorn sheep (Ovis canadensis) to >50‐fold coverage to identify 2.8 million single nucleotide polymorphisms (SNPs) and genomic regions bearing signatures of directional selection (i.e. selective sweeps). A comparison of SNP diversity between the X chromosome and the autosomes indicated that bighorn males had a dramatically reduced long‐term effective population size compared to females. This probably reflects a long history of intense sexual selection mediated by male–male competition for mates. Selective sweep scans based on heterozygosity and nucleotide diversity revealed evidence for a selective sweep shared across multiple populations at RXFP2, a gene that strongly affects horn size in domestic ungulates. The massive horns carried by bighorn rams appear to have evolved in part via strong positive selection at RXFP2. We identified evidence for selection within individual populations at genes affecting early body growth and cellular response to hypoxia; however, these must be interpreted more cautiously as genetic drift is strong within local populations and may have caused false positives. These results represent a rare example of strong genomic signatures of selection identified at genes with known function in wild populations of a nonmodel species. Our results also showcase the value of reference genome assemblies from agricultural or model species for studies of the genomic basis of adaptation in closely related wild taxa.