QTL Detection using Genome Scans for Selection on Resequencing Data: Illustration in Cattle

Large scale genomic datasets allow to decipher the genetic determinism of quantitative traits. One of the possible approaches to tackle this question is to look for genome regions that have been subjected to selection on these traits in the past. Such regions are termed "selection signatures". Marker density is an important parameter affecting the power to detect these signatures. With the recent drastic reduction in sequencing costs, genotyping datasets on all polymorphisms in a species are becoming available, offering the highest possible density. For agricultural species, such data has been made available in cattle, where the 1000 bull genomes consortium has put together sequences of hundred of individuals in many populations (breeds). In this work, we will present the results of an analysis of this dataset. Besides the identification of new selection signatures in cattle, our results illustrate the advantages and limitations of genome scans for selection to unravel the genetic determinism of quantitative traits. Finally, we will discuss how these approaches can be combined with genome-wide association studies to decipher the evolutionary history of quantitative traits.