A complex of forces determines the extent of linkage disequilibrium among a set of loci in a given population. As a general rule, the magnitude of disequilibrium between a pair of loci decays systematically in each generation due to recombination. However, the amount of disequilibrium at the founding of the population depends on numerous systematic and random factors. In this proposal, we focus on developing and applying methods to measure the degree of association among a set of linked loci. These measures will then be contrasted across chromosomal regions which are presumed to have different physical distance/recombination fraction relationship, as well as across populations with different histologies. These methods will be based on linear regression and nested analysis of variance. We intend to initially concentrate on pair wise measures of disequilibrium. With pair wise measures considered on all pairs of a set of linked loci, disequilibrium estimates are correlated, and we intend to evaluate the effect of this correlation. The methods that we develop will be tested using simulation programs that generate population haplotype data for a set of linked marker loci. These programs will also allow us to evaluate the effect of various biological/demographic forces, such as mutation at marker loci, gene flow, and genetic drift. Finally, these methods will be applied to the data collected in Projects 1, 2 and 3 by Drs. Kidd, Kidd and Ward. Given our experience from the simulation studies, we hope to understand the linkage disequilibrium relationships established in these projects.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Program Projects (P01)
Project #
5P01GM057672-03
Application #
6301796
Study Section
Project Start
2000-04-01
Project End
2001-03-31
Budget Start
1998-10-01
Budget End
1999-09-30
Support Year
3
Fiscal Year
2000
Total Cost
$187,650
Indirect Cost
Name
Yale University
Department
Type
DUNS #
082359691
City
New Haven
State
CT
Country
United States
Zip Code
06520
Heffelfinger, Christopher; Pakstis, Andrew J; Speed, William C et al. (2014) Haplotype structure and positive selection at TLR1. Eur J Hum Genet 22:551-7
Murdoch, John D; Speed, William C; Pakstis, Andrew J et al. (2013) Worldwide population variation and haplotype analysis at the serotonin transporter gene SLC6A4 and implications for association studies. Biol Psychiatry 74:879-89
Donnelly, Michael P; Paschou, Peristera; Grigorenko, Elena et al. (2012) A global view of the OCA2-HERC2 region and pigmentation. Hum Genet 131:683-96
Reich, David; Patterson, Nick; Campbell, Desmond et al. (2012) Reconstructing Native American population history. Nature 488:370-4
Pakstis, Andrew J; Fang, Rixun; Furtado, Manohar R et al. (2012) Mini-haplotypes as lineage informative SNPs and ancestry inference SNPs. Eur J Hum Genet 20:1148-54
Nakagome, Shigeki; Mano, Shuhei; Kozlowski, Lukasz et al. (2012) Crohn's disease risk alleles on the NOD2 locus have been maintained by natural selection on standing variation. Mol Biol Evol 29:1569-85
Godshalk, S E; Paranjape, T; Nallur, S et al. (2011) A Variant in a MicroRNA complementary site in the 3' UTR of the KIT oncogene increases risk of acral melanoma. Oncogene 30:1542-50
Pelletier, Cory; Speed, William C; Paranjape, Trupti et al. (2011) Rare BRCA1 haplotypes including 3'UTR SNPs associated with breast cancer risk. Cell Cycle 10:90-9
Liu, Nianjun; Zhao, Hongyu; Patki, Amit et al. (2011) Controlling Population Structure in Human Genetic Association Studies with Samples of Unrelated Individuals. Stat Interface 4:317-326
Kidd, Judith R; Friedlaender, Françoise; Pakstis, Andrew J et al. (2011) Single nucleotide polymorphisms and haplotypes in Native American populations. Am J Phys Anthropol 146:495-502

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