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.

Effective population size (Ne) is a key population genetic parameter that describes the amount of genetic drift in a population. Estimating Ne has been subject to much research over the last 80 years. Methods to estimate Ne from linkage disequilibrium (LD) were developed ~40 years ago but depend on the availability of large amounts of genetic marker data that only the most recent advances in DNA technology have made available. Here we introduce SNeP, a multithreaded tool to perform the estimate of Ne using LD using the standard PLINK input file format (.ped and .map files) or by using LD values calculated using other software. Through SNeP the user can apply several corrections to take account of sample size, mutation, phasing and recombination rate. Each variable involved in the computation such as the binning parameters or the chromosomes to include in the analysis can be modified. When applied to published datasets, SNeP produced results closely comparable with those obtained in the original studies. The use of SNeP to estimate Ne trends can improve understanding of population demography in the recent past, provided a sufficient number of SNPs and their physical position in the genome are available. Binaries for the most common operating systems are available at https://sourceforge.net/projects/snepnetrends/.

The evolutionary basis of domestication has been a longstanding question and its genetic architecture is becoming more tractable as more domestic species become genome-enabled. Before becoming established worldwide, sheep and goats were domesticated in the fertile crescent 10,500 years before present (YBP) where their wild relatives remain. Here we sequence the genomes of wild Asiatic mouflon and Bezoar ibex in the sheep and goat domestication center and compare their genomes with that of domestics from local, traditional, and improved breeds. Among the genomic regions carrying selective sweeps differentiating domestic breeds from wild populations, which are associated among others to genes involved in nervous system, immunity and productivity traits, 20 are common toCapraandOvis. The patterns of selection vary between species, suggesting that while common targets of selection related to domestication and improvement exist, different solutions have arisen to achieve similar phenotypic end-points within these closely related livestock species.

Climate oscillation may have a profound effect on species distributions, gene flow patterns and population demography. In response to environmental change, those species restricted to montane habitats experienced expansions and contractions along elevation gradients, which can drive differentiation among sky islands. The Shangcheng stout salamander (Pachyhynobius shangchengensis) is a cool stream amphibian restricted to high-elevation areas in the Dabie Mountains, East China. In the present study, we used mtDNA genes (Cyt b and ND2) of 193 individuals and 12 nuclear microsatellite loci genotyped on 370 individuals, representing 6 populations (JTX, KHJ, MW, TTZ, BYM and KJY) across the taxon’s distribution area, to investigate their genetic variation and evolutionary history of P. shangchengensis. Most populations showed unusually high levels of genetic diversity. Phylogenetic analyses revealed five monophyletic clades with divergence times ranging from 3.96 to 1.4 Mya. Accordingly, significant genetic differentiation was present between these populations. Bayesian skyline plot analyses provided that all populations underwent long-term population expansions since the last inter-glacial (0.13 Mya ~ 0.12 Mya). Msvar analyses found recent signals of population decline for two northern populations (JTX and KHJ) reflecting a strong bottleneck (approximately 15-fold decrease) during the mid-Holocene (about 6000 years ago). Ecological niche modelling has shown a discontinuity in suitable habitats for P. shangchengensis under different historical climatic conditions. Our results suggest that the niche conservatism of P. shangchengensis and sky island effects may have led to long-term isolation between populations. In sky island refuges, the mid-latitude Dabie Mountains have provided a long-term stable environment for P. shangchengensis, which has led to the accumulation of genetic diversity and has promoted genetic divergence.

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.