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- Title
A unified mixed-model method for association mapping that accounts for multiple levels of relatedness.
- Authors
Jianming Yu; Pressoir, Gael; Briggs, William H.; Irie Vroh Bi; Yamasaki, Masanori; Doebley, John F.; McMullen, Michael D.; Gaut, Brandon S.; Nielsen, Dahlia M.; Holland, James B.; Kresovich, Stephen; Buckler, Edward S.
- Abstract
As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples: a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping.
- Subjects
GENE mapping; GENETIC techniques; HUMAN genetics; GENETICS; HUMAN biology; PLANT genetics; GENETIC markers; BIOMARKERS; HUMAN beings; PLANTS
- Publication
Nature Genetics, 2006, Vol 38, Issue 2, p203
- ISSN
1061-4036
- Publication type
Article
- DOI
10.1038/ng1702