Quantifying_Linkage_and_Selection_in_Artificially_Outbred_Populations

When selection is acting on a large, genetically diverse population, regions containing beneficial alleles increase in frequency. This idea can be used to map trait loci by deep sequencing the pooled DNA from the population under selection at consecutive time points, and observing allele frequency changes. We have developed population genetic methods for finding driver alleles and quantifying their fitness effects from such data. The testing of the tools has been done on data generated here at Sanger by the Durbin Group (for the experiment see (Parts et al Genome Res. 2011)). While we can quantify the selective advantage of the identified driver mutations from the existing data, at the same time, detection of epistatic interactions between the driver loci will greatly benefit from the measurements of pairwise linkages in the initial population. We will also map fine structure of recombination that took place in during the crossing. More generally, as the initial pool of variation is a resource facilitating selection experiments on various traits. All these future applications of the resource will substantially benefit from knowing the linkage structure within the initial F12 pool. A further application of 2 x 96 haploid segregants with full genome sequence is generating 96 x 96 diploid individuals with known genomes for QTL mapping studies.