In anticipation of the imminent release of population samples of genomes, this project addresses the development of an integrated theoretical, statistical, and computational framework for the analysis of genome-wide variation. This project develops evolutionary models and statistical procedures for the analysis of genome- wide associations among single nucleotide polymorphism (SNP) loci. The methodology to be developed will provide a framework both for the description of genomic SNP variation and for inference of the demographic and evolutionary processes that generated those patterns. A major component entails the development of the sampling distribution of summary statistics of genome-scale variation under various forms of population structure, including regular systems of inbreeding and population subdivision. We will explicitly address the effect of linkage on associations among nucleotide positions. We will develop a novel method for detecting genomic tracts that appear to have had unusual evolutionary histories. A novel feature of this method is its use of ensembles of multilocus association measures. We will apply our methodologies to the population samples of genomes, which are just now beginning to appear. Of particular significance are the Drosophila Genetics Reference Panel, the 1000 Genomes Project, and yeast genomes presently being sequenced by our collaborators.

Public Health Relevance

This project undertakes the development of statistical procedures for the analysis of genome-wide patterns of variation observed in samples of genomes. This framework lays a basis for accounting for population structure in association mapping of factors contributing to disease and other important phenotypes. A comprehensive partitioning of genome-wide variation will be developed and used as a basis for the inference of historical demographical events and ongoing evolutionary processes.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Genetic Variation and Evolution Study Section (GVE)
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Eckstrand, Irene A
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Duke University
Schools of Arts and Sciences
United States
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Uyenoyama, Marcy K; Takebayashi, Naoki (2017) Evolution of the sex ratio and effective number under gynodioecy and androdioecy. Theor Popul Biol 118:27-45
Redelings, Benjamin D; Kumagai, Seiji; Tatarenkov, Andrey et al. (2015) A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation. Genetics 201:1171-88
Kumagai, Seiji; Uyenoyama, Marcy K (2015) Genealogical histories in structured populations. Theor Popul Biol 102:3-15
Ayres, Daniel L; Darling, Aaron; Zwickl, Derrick J et al. (2012) BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics. Syst Biol 61:170-3
Fusco, Diana; Uyenoyama, Marcy K (2011) Effects of polymorphism for locally adapted genes on rates of neutral introgression in structured populations. Theor Popul Biol 80:121-31
Fusco, Diana; Uyenoyama, Marcy K (2011) Sex-specific incompatibility generates locus-specific rates of introgression between species. Genetics 189:267-88
Ganapathy, Ganeshkumar; Uyenoyama, Marcy K (2009) Site frequency spectra from genomic SNP surveys. Theor Popul Biol 75:346-54