Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.

ABSTRACT: Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Sp

SUBMITTER: Kessner D 

PROVIDER: S-EPMC4391575 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature