Summary: Sequencing pooled DNA samples (Pool-Seq) is the most cost-effective approach for the genome-wide comparison of population samples. Here, we introduce PoPoolation2, the first software tool specifically designed for the comparison of populations with Pool-Seq data. PoPoolation2 implements a range of commonly used measures of differentiation (F_ST, Fisher's exact test and Cochran-Mantel-Haenszel test) that can be applied on different scales (windows, genes, exons, SNPs). The result may be visualized with the widely used Integrated Genomics Viewer. Availability and Implementation: PoPoolation2 is implemented in Perl and R. It is freely available on http://code.google.com/p/popoolation2/ Contact:christian.schloetterer@vetmeduni.ac.at Supplementary Information: Manual: http://code.google.com/p/popoolation2/wiki/Manual Test data and tutorial: http://code.google.com/p/popoolation2/wiki/Tutorial Validation: http://code.google.com/p/popoolation2/wiki/Validation

The analysis of slippage synthesis of simple sequence DNA in vitro sheds some light on the question of how simple sequences arise in vivo. We show that it is possible to synthesize all types of repetitious di- and trinucleotide motifs starting from short primers and a polymerase in vitro. The rate of this synthesis depends on a sequence specific slippage rate, but is independent of the length of the fragments being synthesized. This indicates that only the ends of the DNA fragments are involved in determining this rate and that slippage is accordingly a short range effect. Slippage synthesis occurs also on a fixed template where only one strand is free to move, a situation which resembles chromosome replication in vivo. It seems therefore likely that slippage during replication is the cause of the observed length polymorphism of simple sequence stretches between individuals of a population.

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.