A composite of multiple signals distinguishes causal variants in regions of positive selection

Sharon R. Grossman, Ilya Shylakhter, Elinor K. Karlsson, Elizabeth H. Byrne, Shannon Morales, Gabriel Frieden, Elizabeth Hostetter, Elaine Angelino, Manuel Garber, Or Zuk, Eric S. Lander, Stephen F. Schaffner, Pardis C. Sabeti

Research output: Contribution to journalArticlepeer-review

390 Scopus citations

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.

Original languageEnglish
Pages (from-to)883-886
Number of pages4
JournalScience
Volume327
Issue number5967
DOIs
StatePublished - 12 Feb 2010
Externally publishedYes

Fingerprint

Dive into the research topics of 'A composite of multiple signals distinguishes causal variants in regions of positive selection'. Together they form a unique fingerprint.

Cite this