Detecting Signatures of Positive Selection along Defined Branches of a Population Tree Using LSD.

Identifying the genomic basis underlying local adaptation is paramount to evolutionary biology, and bears many applications in the fields of conservation biology, crop, and animal breeding, as well as personalized medicine. Although many approaches have been developed to detect signatures of positive selection within single populations and population pairs, the increasing wealth of high-throughput sequencing data requires improved methods capable of handling multiple, and ideally large number of, populations in a single analysis. In this study, we introduce LSD (levels of exclusively shared differences), a fast and flexible framework to perform genome-wide selection scans, along the internal and external branches of a given population tree. We use forward simulations to demonstrate that LSD can identify branches targeted by positive selection with remarkable sensitivity and specificity. We illustrate a range of potential applications by analyzing data from the 1000 Genomes Project and uncover a list of adaptive candidates accompanying the expansion of anatomically modern humans out of Africa and their spread to Europe.