The analysis of polymorphism data is becoming increasingly important as a complementary tool to classical genetic analyses. Nevertheless, despite plunging sequencing costs, genomic sequencing of individuals at the population scale is still restricted to a few model species. Whole-genome sequencing of pools of individuals (Pool-seq) provides a cost-effective alternative to sequencing individuals separately. With the availability of custom-tailored software tools, Pool-seq is being increasingly used for population genomic research on both model and non-model organisms. In this Review, we not only demonstrate the breadth of questions that are being addressed by Pool-seq but also discuss its limitations and provide guidelines for users.

Recent statistical analyses suggest that sequencing of pooled samples provides a cost effective approach to determine genome-wide population genetic parameters. Here we introduce PoPoolation, a toolbox specifically designed for the population genetic analysis of sequence data from pooled individuals. PoPoolation calculates estimates of θ Watterson, θ π, and Tajima's D that account for the bias introduced by pooling and sequencing errors, as well as divergence between species. Results of genome-wide analyses can be graphically displayed in a sliding window plot. PoPoolation is written in Perl and R and it builds on commonly used data formats. Its source code can be downloaded from http://code.google.com/p/popoolation/. Furthermore, we evaluate the influence of mapping algorithms, sequencing errors, and read coverage on the accuracy of population genetic parameter estimates from pooled data.

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic—i.e., result from selection on a large number of genetic loci—but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes—e.g., fitness, metabolic rate, and fat content—and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D . simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.

Understanding the genetic underpinnings of adaptive change is a fundamental but largely unresolved problem in evolutionary biology. Drosophila melanogaster, an ancestrally tropical insect that has spread to temperate regions and become cosmopolitan, offers a powerful opportunity for identifying the molecular polymorphisms underlying clinal adaptation. Here, we use genome-wide next-generation sequencing of DNA pools ('pool-seq') from three populations collected along the North American east coast to examine patterns of latitudinal differentiation. Comparing the genomes of these populations is particularly interesting since they exhibit clinal variation in a number of important life history traits. We find extensive latitudinal differentiation, with many of the most strongly differentiated genes involved in major functional pathways such as the insulin/TOR, ecdysone, torso, EGFR, TGFβ/BMP, JAK/STAT, immunity and circadian rhythm pathways. We observe particularly strong differentiation on chromosome 3R, especially within the cosmopolitan inversion In(3R)Payne, which contains a large number of clinally varying genes. While much of the differentiation might be driven by clinal differences in the frequency of In(3R)P, we also identify genes that are likely independent of this inversion. Our results provide genome-wide evidence consistent with pervasive spatially variable selection acting on numerous loci and pathways along the well-known North American cline, with many candidates implicated in life history regulation and exhibiting parallel differentiation along the previously investigated Australian cline.

With the delivery of millions of sequence reads in a single experiment, next-generation sequencing (NGS) is currently revolutionizing surveys of microorganism diversity. In particular, when applied to Eukaryotes, we are still lacking a rigorous comparison of morphological and NGS-based diversity estimates. In this report, we studied the diversity and the seasonal community turnover of alveolates (Ciliophora and Dinophyceae) in an oligotrophic freshwater lake by SSU amplicon sequencing with NGS as well as by classical morphological analysis. We complemented the morphological analysis by single-cell PCR followed by Sanger sequencing to provide an unambiguous link to the NGS data. We show that NGS and morphological analyses generally capture frequency shifts of abundant taxa over our seasonal samples. The observed incongruencies are probably largely due to rDNA copy number variation among taxa and heterogeneity in the efficiency of cell lysis. Overall, NGS-based amplicon sequencing was superior in detecting rare species. We propose that in the absence of other nuclear markers less susceptible to copy number variation, rDNA-based diversity studies need to be adjusted for confounding effects of copy number variation.

Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS) to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs) segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.

Significance Despite ample knowledge of the genetics and physiology of host responses to parasites, little is known about the genetic basis of host adaptation to parasites. Moreover, adaptation to one parasite is likely to impact the outcome of different infections. Yet these correlated responses, seminal to the understanding of host evolution in multiparasite environments, remain poorly studied. We determined the genetic and phenotypic changes underlying adaptation upon experimental evolution of a Drosophila melanogaster population under viral infection [ Drosophila C virus (DCV)]. After 20 generations, selected flies showed increased survival upon infection with DCV and two other viruses. Using whole-genome sequencing and through RNAi, we identified and functionally validated three genes underlying the adaptive process and revealed their differential roles in the correlated responses observed.

Experimental evolution in combination with whole-genome sequencing (evolve and resequence [E&R]) is a promising approach to define the genotype–phenotype map and to understand adaptation in evolving populations. Many previous studies have identified a large number of putative selected sites (i.e., candidate loci), but it remains unclear to what extent these loci are genuine targets of selection or experimental noise. To address this question, we exposed the same founder population to two different selection regimes—a hot environment and a cold environment—and quantified the genomic response in each. We detected large numbers of putative selected loci in both environments, albeit with little overlap between the two sets of candidates, indicating that most resulted from habitat-specific selection. By quantifying changes across multiple independent biological replicates, we demonstrate that most of the candidate SNPs were false positives that were linked to selected sites over distances much larger than the typical linkage disequilibrium range of Drosophila melanogaster. We show that many of these mid- to long-range associations were attributable to large segregating inversions and confirm by computer simulations that such patterns could be readily replicated when strong selection acts on rare haplotypes. In light of our findings, we outline recommendations to improve the performance of future Drosophila E&R studies which include using species with negligible inversion loads, such as D. mauritiana and D. simulans, instead of D. melanogaster.