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Local Score Based Method Applied On Pool-Sequenced Behavior-Divergent Lines Precisely Detected Selection Signatures Related To Autism In Quail
Detecting genomic footprints of selection is an important step in the understanding of evolution. Accounting for haplotype information in genome scans for selection allows increasing the detection power, but haplotype-based methods require individual genotypes and are not applicable when only allele frequencies are available. We propose here to take advantage of the local score approach to accumulate (possibly small) signals from single markers over a genomic segment, to clearly pinpoint a selection signal. This method gave results similar to haplotype-based methods on benchmark data sets with individual genotypes. Results obtained for a divergent selection experiment on behavior in quail, where two lines were sequenced in pools, are precise and biologically coherent. This local score approach is general and can be applied to other genome-wide analyzes such as GWAS or genome scans for selection.
Keywords:
Footprint of selection
Local score
Quail
