4. Disentangle selection signature from neutral processes within inversions
Q. He, L. L. Knowles. 2016. Identifying targets of selection in mosaic genomes with machine learning: applications in Anopheles gambiae for detecting sites within locally adapted chromosomal inversions. Mol. Ecol. DOI: 10.1111/mec.13619
Chromosomal inversions are important structural changes that may facilitate divergent selection when they capture co-adaptive loci in the face of gene flow. The number one killer in human history, the mosquito Anopheles gambiae, adapts quickly to different environments through polymorphic inversions. Amazing, right?
However, due to high linkage disequilibrium, as well as the differences in demographic histories between regions within and outside inversions, it is challenging to detect selection targets within inversions. Here we develop a new approach that uses discriminant functions informed from inversion-specific expectations to classify loci that are under selection (or drift). We were able to identify two strongly selected regions within a particular inversion associated with dry habitat.