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Genomic Scans of Zygotic Disequilibrium and Epistatic SNPs in HapMap Phase III Populations
Authors:Xin-Sheng Hu  Yang Hu
Affiliation:1. Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX13RB, United Kingdom.; 2. Department of Computing Science, University of Alberta, Edmonton, AB T6G 2S4, Canada.; Pennsylvania State University, UNITED STATES,
Abstract:Previous theory indicates that zygotic linkage disequilibrium (LD) is more informative than gametic or composite digenic LD in revealing natural population history. Further, the difference between the composite digenic and maximum zygotic LDs can be used to detect epistatic selection for fitness. Here we corroborate the theory by investigating genome-wide zygotic LDs in HapMap phase III human populations. Results show that non-Africa populations have much more significant zygotic LDs than do Africa populations. Africa populations (ASW, LWK, MKK, and YRI) possess more significant zygotic LDs for the double-homozygotes (DAABB) than any other significant zygotic LDs (DAABb, DAaBB, and DAaBb), while non-Africa populations generally have more significant DAaBb’s than any other significant zygotic LDs (DAABB, DAABb, and DAaBB). Average r-squares for any significant zygotic LDs increase generally in an order of populations YRI, MKK, CEU, CHB, LWK, JPT, CHD, TSI, GIH, ASW, and MEX. Average r-squares are greater for DAABB and DAaBb than for DAaBB and DAABb in each population. YRI and MKK can be separated from LWK and ASW in terms of the pattern of average r-squares. All population divergences in zygotic LDs can be interpreted with the model of Out of Africa for modern human origins. We have also detected 19735-95921 SNP pairs exhibiting strong signals of epistatic selection in different populations. Gene-gene interactions for some epistatic SNP pairs are evident from empirical findings, but many more epistatic SNP pairs await evidence. Common epistatic SNP pairs rarely exist among all populations, but exist in distinct regions (Africa, Europe, and East Asia), which helps to understand geographical genomic medicine.
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