Mapping Quantitative and Complex Traits Using Phenotype-based Selection and Introgression with Next-Gen Sequencing

Finding the genes underlying complex traits is difficult. We show that new sequencing technology combined with traditional genetic techniques can be used to efficiently identify genetic regions underlying a complex and quantitative behavioral trait. As a proof of concept we introduce through phenotype-based introgression and backcrossing loci controlling innate food preference found in Drosophila simulans into the genomic background of D. sechellia, which expresses the opposite preference. We successfully mapped D. simulans introgression regions in a small mapping population (30 flies) with whole-genome resequencing using light coverage (~1x). We found six loci contributing to D. simulans food preference, some of which overlap previously discovered alleles. This approach is applicable to many systems, does not rely on laborious marker development or genotyping and does not require existing high quality reference genomes. It is scalable in both space and time. To our knowledge, this is the first application of next-generation sequencing toward mapping quantitative traits without a priori knowledge of locus number or effect size.