Progress and prospects in mapping recent selection in the genome

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modelled by a realistic mutation rate and as part of a realistic distribution of fitness effects (DFE), as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modelled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false positive rates are in excess of true positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Teaser Text

Outlier-based genomic scans have proven a popular approach for identifying loci that have potentially experienced recent positive selection. However, it has previously been shown that an evolutionarily appropriate baseline model that incorporates non-equilibrium population histories, purifying and background selection, and variation in mutation and recombination rates is necessary to reduce often extreme false positive rates when performing genomic scans. Here we evaluate the power to detect recurrent selective sweeps using common SFS-based and haplotype-based methods under these increasingly realistic models. We find that while these appropriate evolutionary baselines are essential to reduce false positive rates, the power to accurately detect recurrent selective sweeps is generally low across much of the biologically relevant parameter space.

Global population genetic structure and demographic trajectories of the black soldier fly, Hermetia illucens

Background

The black soldier fly (Hermetia illucens) is the most promising insect candidate for nutrient-recycling through bioconversion of organic waste into biomass, thereby improving sustainability of protein supplies for animal feed and facilitating transition to a circular economy. Contrary to conventional livestock, genetic resources of farmed insects remain poorly characterised. We present the first comprehensive population genetic characterisation of H. illucens. Based on 15 novel microsatellite markers, we genotyped and analysed 2862 individuals from 150 wild and captive populations originating from 57 countries on seven subcontinents.

Results

We identified 16 well-distinguished genetic clusters indicating substantial global population structure. The data revealed genetic hotspots in central South America and successive northwards range expansions within the indigenous ranges of the Americas. Colonisations and naturalisations of largely unique genetic profiles occurred on all non-native continents, either preceded by demographically independent founder events from various single sources or involving admixture scenarios. A decisive primarily admixed Polynesian bridgehead population serially colonised the entire Australasian region and its secondarily admixed descendants successively mediated invasions into Africa and Europe. Conversely, captive populations from several continents traced back to a single North American origin and exhibit considerably reduced genetic diversity, although some farmed strains carry distinct genetic signatures. We highlight genetic footprints characteristic of progressing domestication due to increasing socio-economic importance of H. illucens, and ongoing introgression between domesticated strains globally traded for large-scale farming and wild populations in some regions.

Conclusions

We document the dynamic population genetic history of a cosmopolitan dipteran of South American origin shaped by striking geographic patterns. These reflect both ancient dispersal routes, and stochastic and heterogeneous anthropogenic introductions during the last century leading to pronounced diversification of worldwide structure of H. illucens. Upon the recent advent of its agronomic commercialisation, however, current human-mediated translocations of the black soldier fly largely involve genetically highly uniform domesticated strains, which meanwhile threaten the genetic integrity of differentiated unique local resources through introgression. Our in-depth reconstruction of the contemporary and historical demographic trajectories of H. illucens emphasises benchmarking potential for applied future research on this emerging model of the prospering insect-livestock sector.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01029-w.

Evaluating the contributions of purifying selection and progeny-skew in dictating within-host Mycobacterium tuberculosis evolution

The within-host evolutionary dynamics of tuberculosis (TB) remain unclear, and underlying biological characteristics render standard population genetic approaches based upon the Wright-Fisher model largely inappropriate. In addition, the compact genome combined with an absence of recombination is expected to result in strong purifying selection effects. Thus, it is imperative to establish a biologically relevant evolutionary framework incorporating these factors in order to enable an accurate study of this important human pathogen. Further, such a model is critical for inferring fundamental evolutionary parameters related to patient treatment, including mutation rates and the severity of infection bottlenecks. We here implement such a model and infer the underlying evolutionary parameters governing within-patient evolutionary dynamics. Results demonstrate that the progeny skew associated with the clonal nature of TB severely reduces genetic diversity and that the neglect of this parameter in previous studies has led to significant mis-inference of mutation rates. As such, our results suggest an underlying de novo mutation rate that is considerably faster than previously inferred, and a progeny distribution differing significantly from Wright-Fisher assumptions. This inference represents a more appropriate evolutionary null model, against which the periodic effects of positive selection, associated with drug-resistance for example, may be better assessed.

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

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

Genetic variation of HvXYN1 associated with endoxylanase activity and TAX content in barley (Hordeum vulgare L.)

BACKGROUND

Endo-β-1,4-xylanase1 (EA), the key endoxylanase in plants, is involved in the degradation of arabinoxylan during grain germination. In barley (Hordeum vulgare L.), one gene (HvXYN-1) that encode a endo-beta-1,4-xylanase, has been cloned. However, the single nucleotide polymorphisms (SNPs) that affect the endoxylanase activity and total arabinoxylan (TAX) content have yet to be characterized. The investigation of genetic variation in HvXYN1 may facilitate a better understanding of the relationship between TAX content and EA activity in barley.

RESULTS

In the current study, 56 polymorphisms were detected in HvXYN1 among 210 barley accessions collected from 34 countries, with 10 distinct haplotypes identified. The SNPs at positions 110, 305, 1045, 1417, 1504, 1597, 1880 bp in the genomic region of HvXYN1 were significantly associated with EA activity (P < 0.0001), and the sites 110, 305, and 1045 were highly significantly associated with TAX content. The amount of phenotypic variation in a given trait explained by each associated polymorphism ranged from 6.96 to 9.85%. Most notably, we found two variants at positions 1504 bp and 1880 bp in the second exon that significantly (P < 0.0001) affected EA activity; this result could be used in breeding programs to improve beer quality. In addition, African accessions had the highest EA activity and TAX content, and the richest germplasm resources were from Asia, indicating the high potential value of Asian barley.

CONCLUSION

This study provided insight into understanding the relationship, EA activity, TAX content with the SNPs of HvXYN1 in barley. These SNPs can be applied as DNA markers in breeding programs to improve the quality of barley for beer brewing after further validation.

Standing genetic variation as the predominant source for adaptation of a songbird

It is a tenet of modern biology that species adapt through natural selection to cope with the ever-changing environment. By comparing genetic variants between the island and mainland populations of a passerine, we inferred the related age of genetic variants across its entire genome and suggest that preexisting standing variants played the predominant role in local adaptation. Our findings not only resolve a long-standing fundamental problem in biology regarding the genetic sources of adaptation, but imply that the evolutionary potential of a population is highly associated with its preexisting genetic variation.

What kind of genetic variation contributes the most to adaptation is a fundamental question in evolutionary biology. By resequencing genomes of 80 individuals, we inferred the origin of genomic variants associated with a complex adaptive syndrome involving multiple quantitative traits, namely, adaptation between high and low altitudes, in the vinous-throated parrotbill (Sinosuthora webbiana) in Taiwan. By comparing these variants with those in the Asian mainland population, we revealed standing variation in 24 noncoding genomic regions to be the predominant genetic source of adaptation. Parrotbills at both high and low altitudes exhibited signatures of recent selection, suggesting that not only the front but also the trailing edges of postglacial expanding populations could be subjected to environmental stresses. This study verifies and quantifies the importance of standing variation in adaptation in a cohort of genes, illustrating that the evolutionary potential of a population depends significantly on its preexisting genetic diversity. These findings provide important context for understanding adaptation and conservation of species in the Anthropocene.

Quantifying Selection with Pool-Seq Time Series Data

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (N_e) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies.

Estimating the parameters of background selection and selective sweeps in Drosophila in the presence of gene conversion

We used whole-genome resequencing data from a population of Drosophila melanogaster to investigate the causes of the negative correlation between the within-population synonymous nucleotide site diversity (π_S ) of a gene and its degree of divergence from related species at nonsynonymous nucleotide sites (K_A ). By using the estimated distributions of mutational effects on fitness at nonsynonymous and UTR sites, we predicted the effects of background selection at sites within a gene on π_S and found that these could account for only part of the observed correlation between π_S and K_A We developed a model of the effects of selective sweeps that included gene conversion as well as crossing over. We used this model to estimate the average strength of selection on positively selected mutations in coding sequences and in UTRs, as well as the proportions of new mutations that are selectively advantageous. Genes with high levels of selective constraint on nonsynonymous sites were found to have lower strengths of positive selection and lower proportions of advantageous mutations than genes with low levels of constraint. Overall, background selection and selective sweeps within a typical gene reduce its synonymous diversity to ∼75% of its value in the absence of selection, with larger reductions for genes with high K_A Gene conversion has a major effect on the estimates of the parameters of positive selection, such that the estimated strength of selection on favorable mutations is greatly reduced if it is ignored.

New views on the selection acting on genetic polymorphism in central metabolic genes

Studies of the polymorphism of central metabolic genes as a source of fitness variation in natural populations date back to the discovery of allozymes in the 1960s. The unique features of these genes and their enzymes and our knowledge base greatly facilitates the systems-level study of this group. The expectation that pathway flux control is central to understanding the molecular evolution of genes is discussed, as well as studies that attempt to place gene-specific molecular evolution and polymorphism into a context of pathway and network architecture. There is an increasingly complex picture of the metabolic genes assuming additional roles beyond their textbook anabolic and catabolic reactions. In particular, this review emphasizes the potential role of these genes as part of the energy-sensing machinery. It is underscored that the concentrations of key cellular metabolites are the reflections of cellular energy status and nutritional input. These metabolites are the top-down signaling messengers that set signaling through signaling pathways that are involved in energy economy. I propose that the polymorphisms in central metabolic genes shift metabolite concentrations and in that fashion act as genetic modifiers of the energy-state coupling to the transcriptional networks that affect physiological trade-offs with significant fitness consequences.

SNPs across time and space: population genomic signatures of founder events and epizootics in the House Finch (Haemorhous mexicanus)

Identifying genomic signatures of natural selection can be challenging against a background of demographic changes such as bottlenecks and population expansions. Here, we disentangle the effects of demography from selection in the House Finch (Haemorhous mexicanus) using samples collected before and after a pathogen‐induced selection event. Using ddRADseq, we genotyped over 18,000 SNPs across the genome in native pre‐epizootic western US birds, introduced birds from Hawaii and the eastern United States, post‐epizootic eastern birds, and western birds sampled across a similar time span. We found 14% and 7% reductions in nucleotide diversity, respectively, in Hawaiian and pre‐epizootic eastern birds relative to pre‐epizootic western birds, as well as elevated levels of linkage disequilibrium and other signatures of founder events. Despite finding numerous significant frequency shifts (outlier loci) between pre‐epizootic native and introduced populations, we found no signal of reduced genetic diversity, elevated linkage disequilibrium, or outlier loci as a result of the epizootic. Simulations demonstrate that the proportion of outliers associated with founder events could be explained by genetic drift. This rare view of genetic evolution across time in an invasive species provides direct evidence that demographic shifts like founder events have genetic consequences more widespread across the genome than natural selection.

A Meta-Assembly of Selection Signatures in Cattle

Since domestication, significant genetic improvement has been achieved for many traits of commercial importance in cattle, including adaptation, appearance and production. In response to such intense selection pressures, the bovine genome has undergone changes at the underlying regions of functional genetic variants, which are termed “selection signatures”. This article reviews 64 recent (2009–2015) investigations testing genomic diversity for departure from neutrality in worldwide cattle populations. In particular, we constructed a meta-assembly of 16,158 selection signatures for individual breeds and their archetype groups (European, African, Zebu and composite) from 56 genome-wide scans representing 70,743 animals of 90 pure and crossbred cattle breeds. Meta-selection-scores (MSS) were computed by combining published results at every given locus, within a sliding window span. MSS were adjusted for common samples across studies and were weighted for significance thresholds across and within studies. Published selection signatures show extensive coverage across the bovine genome, however, the meta-assembly provides a consensus profile of 263 genomic regions of which 141 were unique (113 were breed-specific) and 122 were shared across cattle archetypes. The most prominent peaks of MSS represent regions under selection across multiple populations and harboured genes of known major effects (coat color, polledness and muscle hypertrophy) and genes known to influence polygenic traits (stature, adaptation, feed efficiency, immunity, behaviour, reproduction, beef and dairy production). As the first meta-assembly of selection signatures, it offers novel insights about the hotspots of selective sweeps in the bovine genome, and this method could equally be applied to other species.

Inferring the age of a fixed beneficial allele

Estimating the age and strength of beneficial alleles is central to understanding how adaptation proceeds in response to changing environmental conditions. Several haplotype-based estimators exist for inferring the age of segregating beneficial mutations. Here, we develop an approximate Bayesian-based approach that rather estimates these parameters for fixed beneficial mutations in single populations. We integrate a range of existing diversity, site frequency spectrum, haplotype- and linkage disequilibrium-based summary statistics. We show that for strong selective sweeps on de novo mutations the method can estimate allele age and selection strength even in nonequilibrium demographic scenarios. We extend our approach to models of selection on standing variation, and co-infer the frequency at which selection began to act upon the mutation. Finally, we apply our method to estimate the age and selection strength of a previously identified mutation underpinning cryptic colour adaptation in a wild deer mouse population, and compare our findings with previously published estimates as well as with geological data pertaining to the presumed shift in selective pressure.

Seeking signatures of reinforcement at the genetic level: a hitchhiking mapping and candidate gene approach in the house mouse

Reinforcement is the process by which prezygotic isolation is strengthened as a response to selection against hybridization. Most empirical support for reinforcement comes from the observation of its possible phenotypic signature: an accentuated degree of prezygotic isolation in the hybrid zone as compared to allopatry. Here, we implemented a novel approach to this question by seeking for the signature of reinforcement at the genetic level. In the house mouse, selection against hybrids and enhanced olfactory-based assortative mate preferences are observed in a hybrid zone between the two European subspecies Mus musculus musculus and M. m. domesticus, suggesting a possible recent reinforcement event. To test for the genetic signature of reinforcing selection and identify genes involved in sexual isolation, we adopted a hitchhiking mapping approach targeting genomic regions containing candidate genes for assortative mating in mice. We densely scanned these genomic regions in hybrid zone and allopatric samples using a large number of fast evolving microsatellite loci that allow the detection of recent selection events. We found a handful of loci showing the expected pattern of significant reduction in variability in populations close to the hybrid zone, showing assortative odour preference in mate choice experiments as compared to populations further away and displaying no such preference. These loci lie close to genes that we pinpoint as testable candidates for further investigation.

A Genome Scan for Genes Underlying Microgeographic-Scale Local Adaptation in a Wild Arabidopsis Species

Adaptive divergence at the microgeographic scale has been generally disregarded because high gene flow is expected to disrupt local adaptation. Yet, growing number of studies reporting adaptive divergence at a small spatial scale highlight the importance of this process in evolutionary biology. To investigate the genetic basis of microgeographic local adaptation, we conducted a genome-wide scan among sets of continuously distributed populations of Arabidopsis halleri subsp. gemmifera that show altitudinal phenotypic divergence despite gene flow. Genomic comparisons were independently conducted in two distinct mountains where similar highland ecotypes are observed, presumably as a result of convergent evolution. Here, we established a de novo reference genome and employed an individual-based resequencing for a total of 56 individuals. Among 527,225 reliable SNP loci, we focused on those showing a unidirectional allele frequency shift across altitudes. Statistical tests on the screened genes showed that our microgeographic population genomic approach successfully retrieve genes with functional annotations that are in line with the known phenotypic and environmental differences between altitudes. Furthermore, comparison between the two distinct mountains enabled us to screen out those genes that are neutral or adaptive only in either mountain, and identify the genes involved in the convergent evolution. Our study demonstrates that the genomic comparison among a set of genetically connected populations, instead of the commonly-performed comparison between two isolated populations, can also offer an effective screening for the genetic basis of local adaptation.

Biological invasions, climate change and genomics

The rate of biological invasions is expected to increase as the effects of climate change on biological communities become widespread. Climate change enhances habitat disturbance which facilitates the establishment of invasive species, which in turn provides opportunities for hybridization and introgression. These effects influence local biodiversity that can be tracked through genetic and genomic approaches. Metabarcoding and metagenomic approaches provide a way of monitoring some types of communities under climate change for the appearance of invasives. Introgression and hybridization can be followed by the analysis of entire genomes so that rapidly changing areas of the genome are identified and instances of genetic pollution monitored. Genomic markers enable accurate tracking of invasive species' geographic origin well beyond what was previously possible. New genomic tools are promoting fresh insights into classic questions about invading organisms under climate change, such as the role of genetic variation, local adaptation and climate pre-adaptation in successful invasions. These tools are providing managers with often more effective means to identify potential threats, improve surveillance and assess impacts on communities. We provide a framework for the application of genomic techniques within a management context and also indicate some important limitations in what can be achieved.

Thinking too positive? Revisiting current methods of population genetic selection inference

In the age of next-generation sequencing, the availability of increasing amounts and improved quality of data at decreasing cost ought to allow for a better understanding of how natural selection is shaping the genome than ever before. However, alternative forces, such as demography and background selection (BGS), obscure the footprints of positive selection that we would like to identify. In this review, we illustrate recent developments in this area, and outline a roadmap for improved selection inference. We argue (i) that the development and obligatory use of advanced simulation tools is necessary for improved identification of selected loci, (ii) that genomic information from multiple time points will enhance the power of inference, and (iii) that results from experimental evolution should be utilized to better inform population genomic studies.

On the prospect of identifying adaptive loci in recently bottlenecked populations

Identifying adaptively important loci in recently bottlenecked populations – be it natural selection acting on a population following the colonization of novel habitats in the wild, or artificial selection during the domestication of a breed – remains a major challenge. Here we report the results of a simulation study examining the performance of available population-genetic tools for identifying genomic regions under selection. To illustrate our findings, we examined the interplay between selection and demography in two species of Peromyscus mice, for which we have independent evidence of selection acting on phenotype as well as functional evidence identifying the underlying genotype. With this unusual information, we tested whether population-genetic-based approaches could have been utilized to identify the adaptive locus. Contrary to published claims, we conclude that the use of the background site frequency spectrum as a null model is largely ineffective in bottlenecked populations. Results are quantified both for site frequency spectrum and linkage disequilibrium-based predictions, and are found to hold true across a large parameter space that encompasses many species and populations currently under study. These results suggest that the genomic footprint left by selection on both new and standing variation in strongly bottlenecked populations will be difficult, if not impossible, to find using current approaches.

Fine-mapping and selective sweep analysis of QTL for cold tolerance in Drosophila melanogaster

There is a growing interest in investigating the relationship between genes with signatures of natural selection and genes identified in QTL mapping studies using combined population and quantitative genetics approaches. We dissected an X-linked interval of 6.2 Mb, which contains two QTL underlying variation in chill coma recovery time (CCRT) in Drosophila melanogaster from temperate (European) and tropical (African) regions. This resulted in two relatively small regions of 131 kb and 124 kb. The latter one co-localizes with a very strong selective sweep in the European population. We examined the genes within and near the sweep region individually using gene expression analysis and P-element insertion lines. Of the genes overlapping with the sweep, none appears to be related to CCRT. However, we have identified a new candidate gene of CCRT, brinker, which is located just outside the sweep region and is inducible by cold stress. We discuss these results in light of recent population genetics theories on quantitative traits.

Transcriptome population genomics reveals severe bottleneck and domestication cost in the African rice (Oryza glaberrima)

The African cultivated rice (Oryza glaberrima) was domesticated in West Africa 3000 years ago. Although less cultivated than the Asian rice (O. sativa), O. glaberrima landraces often display interesting adaptation to rustic environment (e.g. drought). Here, using RNA-seq technology, we were able to compare more than 12,000 transcripts between 9 O. glaberrima, 10 wild O. barthii and one O. meridionalis individuals. With a synonymous nucleotide diversity πs = 0.0006 per site, O. glaberrima appears as the least genetically diverse crop grass ever documented. Using approximate Bayesian computation, we estimated that O. glaberrima experienced a severe bottleneck during domestication. This demographic scenario almost fully accounts for the pattern of genetic diversity across O. glaberrima genome as we detected very few outliers regions where positive selection may have further impacted genetic diversity. Moreover, the large excess of derived nonsynonymous substitution that we detected suggests that the O. glaberrima population suffered from the 'cost of domestication'. In addition, we used this genome-scale data set to demonstrate that (i) O. barthii genetic diversity is positively correlated with recombination rate and negatively with gene density, (ii) expression level is negatively correlated with evolutionary constraint, and (iii) one region on chromosome 5 (position 4-6 Mb) exhibits a clear signature of introgression with a yet unidentified Oryza species. This work represents the first genome-wide survey of the African rice genetic diversity and paves the way for further comparison between the African and the Asian rice, notably regarding the genetics underlying domestication traits.

Differential strengths of positive selection revealed by hitchhiking effects at small physical scales in Drosophila melanogaster

The long time scale of adaptive evolution makes it difficult to directly observe the spread of most beneficial mutations through natural populations. Therefore, inferring attributes of beneficial mutations by studying the genomic signals left by directional selection is an important component of population genetics research. One kind of signal is a trough in nearby neutral genetic variation due to selective fixation of initially rare alleles, a phenomenon known as "genetic hitchhiking." Accumulated evidence suggests that a considerable fraction of substitutions in the Drosophila genome results from positive selection, most of which are expected to have small selection coefficients and influence the population genetics of sites in the immediate vicinity. Using Drosophila melanogaster population genomic data, we found that the heterogeneity in synonymous polymorphism surrounding different categories of coding fixations is readily observable even within 25 bp of focal substitutions, which we interpret as the result of small-scale hitchhiking effects. The strength of natural selection on different sites appears to be quite heterogeneous. Particularly, neighboring fixations that changed amino acid polarities in a way that maintained the overall polarities of a protein were under stronger selection than other categories of fixations. Interestingly, we found that substitutions in slow-evolving genes are associated with stronger hitchhiking effects. This is consistent with the idea that adaptive evolution may involve few substitutions with large effects or many substitutions with small effects. Because our approach only weakly depends on the numbers of recent nonsynonymous substitutions, it can provide a complimentary view to the adaptive evolution inferred by other divergence-based evolutionary genetic methods.

An ABC method for estimating the rate and distribution of effects of beneficial mutations

Determining the distribution of adaptive mutations available to natural selection is a difficult task. These are rare events and most of them are lost by chance. Some theoretical works propose that the distribution of newly arising beneficial mutations should be close to exponential. Empirical data are scarce and do not always support an exponential distribution. Analysis of the dynamics of adaptation in asexual populations of microorganisms has revealed that these can be summarized by two effective parameters, the effective mutation rate, U_e, and the effective selection coefficient of a beneficial mutation, S_e. Here, we show that these effective parameters will not always reflect the rate and mean effect of beneficial mutations, especially when the distribution of arising mutations has high variance, and the mutation rate is high. We propose a method to estimate the distribution of arising beneficial mutations, which is motivated by a common experimental setup. The method, which we call One Biallelic Marker Approximate Bayesian Computation, makes use of experimental data consisting of periodic measures of neutral marker frequencies and mean population fitness. Using simulations, we find that this method allows the discrimination of the shape of the distribution of arising mutations and that it provides reasonable estimates of their rates and mean effects in ranges of the parameter space that may be of biological relevance.

The impact of equilibrium assumptions on tests of selection

With the increasing availability and quality of whole genome population data, various methodologies of population genetic inference are being utilized in order to identify and quantify recent population-level selective events. Though there has been a great proliferation of such methodology, the type-I and type-II error rates of many proposed statistics have not been well-described. Moreover, the performance of these statistics is often not evaluated for different biologically relevant scenarios (e.g., population size change, population structure), nor for the effect of differing data sizes (i.e., genomic vs. sub-genomic). The absence of the above information makes it difficult to evaluate newly available statistics relative to one another, and thus, difficult to choose the proper toolset for a given empirical analysis. Thus, we here describe and compare the performance of four widely used tests of selection: SweepFinder, SweeD, OmegaPlus, and iHS. In order to consider the above questions, we utilize simulated data spanning a variety of selection coefficients and beneficial mutation rates. We demonstrate that the LD-based OmegaPlus performs best in terms of power to reject the neutral model under both equilibrium and non-equilibrium conditions-an important result regarding the relative effectiveness of linkage disequilibrium relative to site frequency spectrum based statics. The results presented here ought to serve as a useful guide for future empirical studies, and provides a guide for statistical choice depending on the history of the population under consideration. Moreover, the parameter space investigated and the Type-I and Type-II error rates calculated, represent a natural benchmark by which future statistics may be assessed.

Rapid intrahost evolution of human cytomegalovirus is shaped by demography and positive selection

Populations of human cytomegalovirus (HCMV), a large DNA virus, are highly polymorphic in patient samples, which may allow for rapid evolution within human hosts. To understand HCMV evolution, longitudinally sampled genomic populations from the urine and plasma of 5 infants with symptomatic congenital HCMV infection were analyzed. Temporal and compartmental variability of viral populations were quantified using high throughput sequencing and population genetics approaches. HCMV populations were generally stable over time, with ~88% of SNPs displaying similar frequencies. However, samples collected from plasma and urine of the same patient at the same time were highly differentiated with approximately 1700 consensus sequence SNPs (1.2% of the genome) identified between compartments. This inter-compartment differentiation was comparable to the differentiation observed in unrelated hosts. Models of demography (i.e., changes in population size and structure) and positive selection were evaluated to explain the observed patterns of variation. Evidence for strong bottlenecks (>90% reduction in viral population size) was consistent among all patients. From the timing of the bottlenecks, we conclude that fetal infection occurred between 13-18 weeks gestational age in patients analyzed, while colonization of the urine compartment followed roughly 2 months later. The timing of these bottlenecks is consistent with the clinical histories of congenital HCMV infections. We next inferred that positive selection plays a small but measurable role in viral evolution within a single compartment. However, positive selection appears to be a strong and pervasive driver of evolution associated with compartmentalization, affecting ≥ 34 of the 167 open reading frames (~20%) of the genome. This work offers the most detailed map of HCMV in vivo evolution to date and provides evidence that viral populations can be stable or rapidly differentiate, depending on host environment. The application of population genetic methods to these data provides clinically useful information, such as the timing of infection and compartment colonization.

Detecting negative selection on recurrent mutations using gene genealogy

BACKGROUND

Whether or not a mutant allele in a population is under selection is an important issue in population genetics, and various neutrality tests have been invented so far to detect selection. However, detection of negative selection has been notoriously difficult, partly because negatively selected alleles are usually rare in the population and have little impact on either population dynamics or the shape of the gene genealogy. Recently, through studies of genetic disorders and genome-wide analyses, many structural variations were shown to occur recurrently in the population. Such "recurrent mutations" might be revealed as deleterious by exploiting the signal of negative selection in the gene genealogy enhanced by their recurrence.

RESULTS

Motivated by the above idea, we devised two new test statistics. One is the total number of mutants at a recurrently mutating locus among sampled sequences, which is tested conditionally on the number of forward mutations mapped on the sequence genealogy. The other is the size of the most common class of identical-by-descent mutants in the sample, again tested conditionally on the number of forward mutations mapped on the sequence genealogy. To examine the performance of these two tests, we simulated recurrently mutated loci each flanked by sites with neutral single nucleotide polymorphisms (SNPs), with no recombination. Using neutral recurrent mutations as null models, we attempted to detect deleterious recurrent mutations. Our analyses demonstrated high powers of our new tests under constant population size, as well as their moderate power to detect selection in expanding populations. We also devised a new maximum parsimony algorithm that, given the states of the sampled sequences at a recurrently mutating locus and an incompletely resolved genealogy, enumerates mutation histories with a minimum number of mutations while partially resolving genealogical relationships when necessary.

CONCLUSIONS

With their considerably high powers to detect negative selection, our new neutrality tests may open new venues for dealing with the population genetics of recurrent mutations as well as help identifying some types of genetic disorders that may have escaped identification by currently existing methods.

Genetic hitchhiking under heterogeneous spatial selection pressures

During adaptive evolutionary processes substantial heterogeneity in selective pressure might act across local habitats in sympatry. Examples are selection for drug resistance in malaria or herbicide resistance in weeds. In such setups standard population-genetic assumptions (homogeneous constant selection pressures, random mating etc.) are likely to be violated. To avoid misinferences on the strength and pattern of natural selection it is therefore necessary to adjust population-genetic theory to meet the specifics driving adaptive processes in particular organisms. We introduce a deterministic model in which selection acts heterogeneously on a population of haploid individuals across different patches over which the population randomly disperses every generation. A fixed proportion of individuals mates exclusively within patches, whereas the rest mates randomly across all patches. We study how the allele frequencies at neutral markers are affected by the spread of a beneficial mutation at a closely linked locus (genetic hitchhiking). We provide an analytical solution for the frequency change and the expected heterozygosity at the neutral locus after a single copy of a beneficial mutation became fixed. We furthermore provide approximations of these solutions which allow for more obvious interpretations. In addition, we validate the results by stochastic simulations. Our results show that the application of standard population-genetic theory is accurate as long as differences across selective environments are moderate. However, if selective differences are substantial, as for drug resistance in malaria, herbicide resistance in weeds, or insecticide resistance in agriculture, it is necessary to adapt available theory to the specifics of particular organisms.

Single nucleotide polymorphisms in HSP17.8 and their association with agronomic traits in barley

Small heat shock protein 17.8 (HSP17.8) is produced abundantly in plant cells under heat and other stress conditions and may play an important role in plant tolerance to stress environments. However, HSP17.8 may be differentially expressed in different accessions of a crop species exposed to identical stress conditions. The ability of different genotypes to adapt to various stress conditions resides in their genetic diversity. Allelic variations are the most common forms of genetic variation in natural populations. In this study, single nucleotide polymorphisms (SNPs) of the HSP17.8 gene were investigated across 210 barley accessions collected from 30 countries using EcoTILLING technology. Eleven SNPs including 10 from the coding region of HSP17.8 were detected, which form nine distinguishable haplotypes in the barley collection. Among the 10 SNPs in the coding region, six are missense mutations and four are synonymous nucleotide changes. Five of the six missense changes are predicted to be deleterious to HSP17.8 function. The accessions from Middle East Asia showed the higher nucleotide diversity of HSP17.8 than those from other regions and wild barley (H. spontaneum) accessions exhibited greater diversity than the cultivated barley (H. vulgare) accessions. Four SNPs in HSP17.8 were found associated with at least one of the agronomic traits evaluated except for spike length, namely number of grains per spike, thousand kernel weight, plant height, flag leaf area and leaf color. The association between SNP and these agronomic traits may provide new insight for study of the gene's potential contribution to drought tolerance of barley.

Polymorphism at genes involved in salt tolerance in Arabidopsis thaliana (Brassicaceae)

PREMISE OF THE STUDY

Genes involved in relevant functions for environmental adaptation can be considered primary candidates for their variation having been shaped by natural selection. Detecting recent selective events through their footprint on nucleotide variation constitutes a challenging task in species with a complex demographic history such as Arabidopsis thaliana. We have surveyed nucleotide variation in this species at nine genes involved in salt tolerance. The available genomewide information for this species has allowed us to contrast the levels and patterns of variation detected at the candidate genes with empirical distributions obtained from noncandidate regions.

METHODS

We sequenced nine genes involved in salt tolerance (~32 kb) in 20 ecotypes of A. thaliana and analyzed polymorphism and divergence at the individual gene and multilocus levels.

KEY RESULTS

Variation at the nine genes studied was characterized by a generalized skew toward polymorphisms with low-frequency variants. Except for genes RCD1 and NHX8, this pattern was similar to that generally detected in the A. thaliana genome and could thus be primarily explained by the species demographic history. The more extreme deviation at the NHX8 gene and its excess of polymorphism relative to divergence points to the recent action of selection on this gene.

CONCLUSIONS

The analysis of nucleotide polymorphism and divergence at nine genes involved in salt tolerance provided little evidence for the recent action of positive selection. Only the signals detected at NHX8 from both polymorphism and divergence were suggestive of the putative contribution of this gene to local adaptation.

Inferring the demographic history of European Ficedula flycatcher populations

Background

Inference of population and species histories and population stratification using genetic data is important for discriminating between different speciation scenarios and for correct interpretation of genome scans for signs of adaptive evolution and trait association. Here we use data from 24 intronic loci re-sequenced in population samples of two closely related species, the pied flycatcher and the collared flycatcher.

Results

We applied Isolation-Migration models, assignment analyses and estimated the genetic differentiation and diversity between species and between populations within species. The data indicate a divergence time between the species of <1 million years, significantly shorter than previous estimates using mtDNA, point to a scenario with unidirectional gene-flow from the pied flycatcher into the collared flycatcher and imply that barriers to hybridisation are still permeable in a recently established hybrid zone. Furthermore, we detect significant population stratification, predominantly between the Spanish population and other pied flycatcher populations.

Conclusions

Our results provide further evidence for a divergence process where different genomic regions may be at different stages of speciation. We also conclude that forthcoming analyses of genotype-phenotype relations in these ecological model species should be designed to take population stratification into account.

Adaptation of Drosophila to a novel laboratory environment reveals temporally heterogeneous trajectories of selected alleles

The genomic basis of adaptation to novel environments is a fundamental problem in evolutionary biology that has gained additional importance in the light of the recent global change discussion. Here, we combined laboratory natural selection (experimental evolution) in Drosophila melanogaster with genome-wide next generation sequencing of DNA pools (Pool-Seq) to identify alleles that are favourable in a novel laboratory environment and traced their trajectories during the adaptive process. Already after 15 generations, we identified a pronounced genomic response to selection, with almost 5000 single nucleotide polymorphisms (SNP; genome-wide false discovery rates < 0.005%) deviating from neutral expectation. Importantly, the evolutionary trajectories of the selected alleles were heterogeneous, with the alleles falling into two distinct classes: (i) alleles that continuously rise in frequency; and (ii) alleles that at first increase rapidly but whose frequencies then reach a plateau. Our data thus suggest that the genomic response to selection can involve a large number of selected SNPs that show unexpectedly complex evolutionary trajectories, possibly due to nonadditive effects.

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.

Parallel and lineage-specific molecular adaptation to climate in boreal black spruce

In response to selective pressure, adaptation may follow different genetic pathways throughout the natural range of a species due to historical differentiation in standing genetic variation. Using 41 populations of black spruce (Picea mariana), the objectives of this study were to identify adaptive genetic polymorphisms related to temperature and precipitation variation across the transcontinental range of the species, and to evaluate the potential influence of historical events on their geographic distribution. Population structure was first inferred using 50 control nuclear markers. Then, 47 candidate gene SNPs identified in previous genome scans were tested for relationship with climatic factors using an F(ST) -based outlier method and regressions between allele frequencies and climatic variations. Two main intraspecific lineages related to glacial vicariance were detected at the transcontinental scale. Within-lineage analyses of allele frequencies allowed the identification of 23 candidate SNPs significantly related to precipitation and/or temperature variation, among which seven were common to both lineages, eight were specific to the eastern lineage and eight were specific to the western lineage. The implication of these candidate SNPs in adaptive processes was further supported by gene functional annotations. Multiple evidences indicated that the occurrence of lineage-specific adaptive SNPs was better explained by selection acting on historically differentiated gene pools rather than differential selection due to heterogeneity of interacting environmental factors and pleiotropic effects. Taken together, these findings suggest that standing genetic variation of potentially adaptive nature has been modified by historical events, hence affecting the outcome of recent selection and leading to different adaptive routes between intraspecific lineages.

Evidence of adaptation from ancestral variation in young populations of beach mice

To understand how organisms adapt to novel habitats, which involves both demographic and selective events, we require knowledge of the evolutionary history of populations and also selected alleles. There are still few cases in which the precise mutations (and hence, defined alleles) that contribute to adaptive change have been identified in nature; one exception is the genetic basis of camouflaging pigmentation of oldfield mice (Peromyscus polionotus) that have colonized the sandy dunes of Florida's Gulf Coast. To quantify the genomic impact of colonization as well as the signature of selection, we resequenced 5000 1.5-kb noncoding loci as well as a 160-kb genomic region surrounding the melanocortin-1 receptor (Mc1r), a gene that contributes to pigmentation differences, in beach and mainland populations. Using a genome-wide phylogenetic approach, we recovered a single monophyletic group comprised of beach mice, consistent with a single colonization event of the Gulf Coast. We also found evidence of a severe founder event, estimated to have occurred less than 3000 years ago. In this demographic context, we show that all beach subspecies share a single derived light Mc1r allele, which was likely selected from standing genetic variation that originated in the mainland. Surprisingly, we were unable to identify a clear signature of selection in the Mc1r region, despite independent evidence that this locus contributes to adaptive coloration. Nonetheless, these data allow us to reconstruct and compare the evolutionary history of populations and alleles to better understand how adaptive evolution, following the colonization of a novel habitat, proceeds in nature.

Recent progress in polymorphism-based population genetic inference

The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. These approaches seek to estimate, for example, recently fixed or sweeping beneficial mutations, the rate of recurrent positive selection, the distribution of selection coefficients, and the demographic history of the population. Yet despite estimating similar parameters using similar data sets, results between methodologies are far from consistent. We here summarize the current state of the field, compare existing approaches, and attempt to reconcile emerging discrepancies. We also discuss the biases in selection estimators introduced by ignoring the demographic history of the population, discuss the biases in demographic estimators introduced by assuming neutrality, and highlight the important challenge to the field of achieving a true joint estimation procedure to circumvent these confounding effects.

On detecting selective sweeps using single genomes

Identifying the genetic basis of human adaptation has remained a central focal point of modern population genetics. One major area of interest has been the use of polymorphism data to detect so-called “footprints” of selective sweeps – patterns produced as a beneficial mutation arises and rapidly fixes in the population. Based on numerous simulation studies and power analyses, the necessary sample size for achieving appreciable power has been shown to vary from a few individuals to a few dozen, depending on the test statistic. And yet, the sequencing of multiple copies of a single region, or of multiple genomes as is now often the case, incurs considerable cost. Enard et al. (2010) have recently proposed a method to identify patterns of selective sweeps using a single genome – and apply this approach to human and non-human primates (chimpanzee, orangutan, and macaque). They employ essentially a modification of the Hudson, Kreitman, and Aguade test – using heterozygous single nucleotide polymorphisms from single individuals, and divergence data from two closely related species (human–chimpanzee, human–orangutan, and human–macaque). Given the potential importance of this finding, we here investigate the properties of this statistic. We demonstrate through simulation that this approach is neither robust to demography nor background selection; nor is it robust to variable recombination rates.

Molecular spandrels: tests of adaptation at the genetic level

Although much progress has been made in identifying the genes (and, in rare cases, mutations) that contribute to phenotypic variation, less is known about the effects that these genes have on fitness. Nonetheless, genes are commonly labelled as 'adaptive' if an allele has been shown to affect a phenotype with known or suspected functional importance or if patterns of nucleotide variation at the locus are consistent with positive selection. In these cases, the 'adaptive' designation may be premature and may lead to incorrect conclusions about the relationships between gene function and fitness. Experiments to test targets and agents of natural selection within a genomic context are necessary for identifying the adaptive consequences of individual alleles.

Deciphering the genetic basis of animal domestication

Genomic technologies for livestock and companion animal species have revolutionized the study of animal domestication, allowing an increasingly detailed description of the genetic changes accompanying domestication and breed development. This review describes important recent results derived from the application of population and quantitative genetic approaches to the study of genetic changes in the major domesticated species. These include findings of regions of the genome that show between-breed differentiation, evidence of selective sweeps within individual genomes and signatures of demographic events. Particular attention is focused on the study of the genetics of behavioural traits and the implications for domestication. Despite the operation of severe bottlenecks, high levels of inbreeding and intensive selection during the history of domestication, most domestic animal species are genetically diverse. Possible explanations for this phenomenon are discussed. The major insights from the surveyed studies are highlighted and directions for future study are suggested.

Hitchhiking effect of a beneficial mutation spreading in a subdivided population

A central problem in population genetics is to detect and analyze positive natural selection by which beneficial mutations are driven to fixation. The hitchhiking effect of a rapidly spreading beneficial mutation, which results in local removal of standing genetic variation, allows such an analysis using DNA sequence polymorphism. However, the current mathematical theory that predicts the pattern of genetic hitchhiking relies on the assumption that a beneficial mutation increases to a high frequency in a single random-mating population, which is certainly violated in reality. Individuals in natural populations are distributed over a geographic space. The spread of a beneficial allele can be delayed by limited migration of individuals over the space and its hitchhiking effect can also be affected. To study this effect of geographic structure on genetic hitchhiking, we analyze a simple model of directional selection in a subdivided population. In contrast to previous studies on hitchhiking in subdivided populations, we mainly investigate the range of sufficiently high migration rates that would homogenize genetic variation at neutral loci. We provide a heuristic mathematical analysis that describes how the genealogical structure at a neutral locus linked to the locus under selection is expected to change in a population divided into two demes. Our results indicate that the overall strength of genetic hitchhiking--the degree to which expected heterozygosity decreases--is diminished by population subdivision, mainly because opportunity for the breakdown of hitchhiking by recombination increases as the spread of the beneficial mutation across demes is delayed when migration rate is much smaller than the strength of selection. Furthermore, the amount of genetic variation after a selective sweep is expected to be unequal over demes: a greater reduction in expected heterozygosity occurs in the subpopulation from which the beneficial mutation originates than in its neighboring subpopulations. This raises a possibility of detecting a "hidden" geographic structure of population by carefully analyzing the pattern of a selective sweep.

Characterizing the influence of effective population size on the rate of adaptation: Gillespie's Darwin domain

Characterizing the role of effective population size in dictating the rate of adaptive evolution remains a major challenge in evolutionary biology. Depending on the underlying distribution of fitness effects of new mutations, populations of different sizes may differ vastly in their rate of adaptation. Here, we collect polymorphism data at over 100 loci for two closely related Drosophila species with different current effective population sizes (N_e), Drosophila miranda and D. pseudoobscura, to evaluate the prevalence of adaptive evolution versus genetic drift in molecular evolution. Utilizing these large and consistently sampled data sets, we obtain greatly improved estimates of the demographic histories of both species. Specifically, although current N_e differs between these species, their ancestral sizes were much more similar. We find that statistical approaches capturing recent adaptive evolution (using patterns of polymorphisms) detect higher rates of adaptive evolution in the larger D. pseudoobscura population. In contrast, methods aimed at detecting selection over longer time periods (i.e., those relying on divergence data) estimate more similar rates of adaptation between the two species. Thus, our results suggest an important role of effective population size in dictating rates of adaptation and highlight how complicated population histories—as is probably the case for most species—can effect rates of adaptation. Additionally, we also show how different methodologies to detect positive selection can reveal information about different timescales of adaptive evolution.

Adaptation to drought in two wild tomato species: the evolution of the Asr gene family

Wild tomato species are a valuable system in which to study local adaptation to drought: they grow in diverse environments ranging from mesic to extremely arid conditions. Here, we investigate the evolution of members of the Asr (ABA/water stress/ripening induced) gene family, which have been reported to be involved in the water stress response. We analysed molecular variation in the Asr gene family in populations of two closely related species, Solanum chilense and Solanum peruvianum. We concluded that Asr1 has evolved under strong purifying selection. In contrast to previous reports, we did not detect evidence for positive selection at Asr2. However, Asr4 shows patterns consistent with local adaptation in an S. chilense population that lives in an extremely dry environment. We also discovered a new member of the gene family, Asr5. Our results show that the Asr genes constitute a dynamic gene family and provide an excellent example of tandemly arrayed genes that are of importance in adaptation. Taking the potential distribution of the species into account, it appears that S. peruvianum can cope with a great variety of environmental conditions without undergoing local adaptation, whereas S. chilense undergoes local adaptation more frequently.

A regression-based approach to selection mapping

Selection mapping applies the population genetics theory of hitchhiking to the localization of genomic regions containing genes under selection. This approach predicts that neutral loci linked to genes under positive selection will have reduced diversity due to their shared history with a selected locus, and thus, genome scans of diversity levels can be used to identify regions containing selected loci. Most previous approaches to this problem ignore the spatial genomic pattern of diversity expected under selection. The regression-based approach advocated in this paper takes into account the expected pattern of decreasing genetic diversity with increased proximity to a selected locus. Simulated data are used to examine the patterns of diversity under different scenarios, in order to assess the power of a regression-based approach to the identification of regions under selection. Application of this method to both simulated and empirical data demonstrates its potential to detect selection. In contrast to some other methods, the regression approach described in this paper can be applied to any marker type. Results also suggest that this approach may give more precise estimates of the location of the selected locus than alternative methods, although the power is slightly lower in some cases.

Characterization of a divergent chromosome region in the willow warbler Phylloscopus trochilus using avian genomic resources

Genome scans have made it possible to find outlier markers thought to have been influenced by divergent selection in almost any wild population. However, the lack of genomic information in nonmodel species often makes it difficult to associate these markers with certain genes or chromosome regions. Furthermore, the extent of linkage disequilibrium (LD) in the genome will determine the density of markers required to identify the genes under selection. In this study, we investigated a chromosome region in the willow warbler Phylloscopus trochilus surrounding a single marker previously identified in a genome scan. We first located the marker in the assembled genome of another species, the zebra finch Taeniopygia guttata, and amplified surrounding sequences in Fennoscandian willow warblers. Within an investigated chromosome region of 7.3 Mb as mapped to the zebra finch genome, we observed elevated genetic differentiation between a southern and a northern population across a 2.5-Mb interval comprising numerous coding genes. Within the southern and northern populations, higher values of LD were mostly found between SNPs within the same locus, but extended across distantly situated loci when the analyses were restricted to sampling sites showing intermediate allele frequencies of southern and northern alleles. Our study shows that cross-species genome information is a useful resource to obtain candidate sequences adjacent to outlier markers in nonmodel species.

Scanning the genome for gene SNPs related to climate adaptation and estimating selection at the molecular level in boreal black spruce

Outlier detection methods were used to scan the genome of the boreal conifer black spruce (Picea mariana [Mill.] B.S.P.) for gene single-nucleotide polymorphisms (SNPs) potentially involved in adaptations to temperature and precipitation variations. The scan involved 583 SNPs from 313 genes potentially playing adaptive roles. Differentiation estimates among population groups defined following variation in temperature and precipitation were moderately high for adaptive quantitative characters such as the timing of budset or tree height (Q(ST) = 0.189-0.314). Average differentiation estimates for gene SNPs were null, with F(ST) values of 0.005 and 0.006, respectively, among temperature and precipitation population groups. Using two detection approaches, a total of 26 SNPs from 25 genes distributed among 11 of the 12 linkage groups of black spruce were detected as outliers with F(ST) as high as 0.078. Nearly half of the outlier SNPs were located in exons and half of those were nonsynonymous. The functional annotations of genes carrying outlier SNPs and regression analyses between the frequencies of these SNPs and climatic variables supported their implication in adaptive processes. Several genes carrying outlier SNPs belonged to gene families previously found to harbour outlier SNPs in a reproductively isolated but largely sympatric congeneric species, suggesting differential subfunctionalization of gene duplicates. Selection coefficient estimates (S) were moderate but well above the magnitude of drift (>>1/N(e)), indicating that the signature of natural selection could be detected at the nucleotide level despite the recent establishment of these populations during the Holocene.

Integrating evolutionary and functional approaches to infer adaptation at specific loci

Inferences about adaptation at specific loci are often exclusively based on the static analysis of DNA sequence variation. Ideally,population-genetic evidence for positive selection serves as a stepping-off point for experimental studies to elucidate the functional significance of the putatively adaptive variation. We argue that inferences about adaptation at specific loci are best achieved by integrating the indirect, retrospective insights provided by population-genetic analyses with the more direct, mechanistic insights provided by functional experiments. Integrative studies of adaptive genetic variation may sometimes be motivated by experimental insights into molecular function, which then provide the impetus to perform population genetic tests to evaluate whether the functional variation is of adaptive significance. In other cases, studies may be initiated by genome scans of DNA variation to identify candidate loci for recent adaptation. Results of such analyses can then motivate experimental efforts to test whether the identified candidate loci do in fact contribute to functional variation in some fitness-related phenotype. Functional studies can provide corroborative evidence for positive selection at particular loci, and can potentially reveal specific molecular mechanisms of adaptation.

Structural genomics: correlation blocks, population structure, and genome architecture

An integration of the pattern of genome-wide inter-site associations with evolutionary forces is important for gaining insights into the genomic evolution in natural or artificial populations. Here, we assess the inter-site correlation blocks and their distributions along chromosomes. A correlation block is broadly termed as the DNA segment within which strong correlations exist between genetic diversities at any two sites. We bring together the population genetic structure and the genomic diversity structure that have been independently built on different scales and synthesize the existing theories and methods for characterizing genomic structure at the population level. We discuss how population structure could shape correlation blocks and their patterns within and between populations. Effects of evolutionary forces (selection, migration, genetic drift, and mutation) on the pattern of genome-wide correlation blocks are discussed. In eukaryote organisms, we briefly discuss the associations between the pattern of correlation blocks and genome assembly features in eukaryote organisms, including the impacts of multigene family, the perturbation of transposable elements, and the repetitive nongenic sequences and GC-rich isochores. Our reviews suggest that the observable pattern of correlation blocks can refine our understanding of the ecological and evolutionary processes underlying the genomic evolution at the population level.