Publication Date:
2010-01-09
Description:
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.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Grossman, Sharon R -- Shlyakhter, Ilya -- Karlsson, Elinor K -- Byrne, Elizabeth H -- Morales, Shannon -- Frieden, Gabriel -- Hostetter, Elizabeth -- Angelino, Elaine -- Garber, Manuel -- Zuk, Or -- Lander, Eric S -- Schaffner, Stephen F -- Sabeti, Pardis C -- New York, N.Y. -- Science. 2010 Feb 12;327(5967):883-6. doi: 10.1126/science.1183863. Epub 2010 Jan 7.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. shari.grossman@post.harvard.edu〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20056855" target="_blank"〉PubMed〈/a〉
Keywords:
Computational Biology/methods
;
DNA, Intergenic/genetics
;
Evolution, Molecular
;
Genetic Loci
;
*Genetic Variation
;
*Genome, Human
;
Haplotypes
;
Humans
;
Polymorphism, Genetic
;
Population Groups/genetics
;
Regulatory Sequences, Nucleic Acid/genetics
;
*Selection, Genetic
;
Software
Print ISSN:
0036-8075
Electronic ISSN:
1095-9203
Topics:
Biology
,
Chemistry and Pharmacology
,
Computer Science
,
Medicine
,
Natural Sciences in General
,
Physics
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