Abstract
The human genome contains hundreds of regions whose patterns of genetic variation indicate recent positive natural selection, yet for most the underlying gene and the advantageous mutation remain unknown. We developed a method, composite of multiple signals (CMS), that combines tests for multiple signals of selection and increases resolution by up to 100-fold. By applying CMS to candidate regions from the International Haplotype Map, we localized population-specific selective signals to 55 kilobases (median), identifying known and novel causal variants. CMS can not just identify individual loci but implicates precise variants selected by evolution.
Highlights
Grossman, Sharon R., Ilya Shylakhter, Elinor K
Composite of Multiple Signals (CMS), that combines tests for multiple signals of selection and increases resolution by up to 100-fold
Numerous methods have been developed to exploit signatures left by positive natural selection to identify genomic regions in the human genome harboring recent local adaptations, presumably to such pressures as infectious disease, changes in diet, and new environments [1, 2] Hundreds of such regions have been identified, but they are typically large, 100s of kilobases to megabases, and contain many genes and thousands of polymorphisms
Summary
A composite of multiple signals distinguishes causal variants in regions of positive selection. A composite of multiple signals distinguishes causal variants in regions of positive selection Sharon R. The human genome contains hundreds of regions whose patterns of genetic variation indicate recent positive natural selection, yet for most the underlying gene and the advantageous mutation remain unknown.
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