Academic journal article Genetics

Identifying Quantitative Trait Locus by Genetic Background Interactions in Association Studies

Academic journal article Genetics

Identifying Quantitative Trait Locus by Genetic Background Interactions in Association Studies

Article excerpt

ABSTRACT

Association studies are designed to identify main effects of alleles across a potentially wide range of genetic backgrounds. To control for spurious associations, effects of the genetic background itself are often incorporated into the linear model, either in the form of subpopulation effects in the case of structure or in the form of genetic relationship matrices in the case of complex pedigrees. In this context epistatic interactions between loci can be captured as an interaction effect between the associated locus and the genetic background. In this study I developed genetic and statistical models to tie the locus by genetic background interaction idea back to more standard concepts of epistasis when genetic background is modeled using an additive relationship matrix. I also simulated epistatic interactions in four-generation randomly mating pedigrees and evaluated the ability of the statistical models to identify when a biallelic associated locus was epistatic to other loci. Under additive-by-additive epistasis, when interaction effects of the associated locus were quite large (explaining 20% of the phenotypic variance), epistasis was detected in 79% of pedigrees containing 320 individuals. The epistatic model also predicted the genotypic value of progeny better than a standard additive model in 78% of simulations. When interaction effects were smaller (although still fairly large, explaining 5% of the phenotypic variance), epistasis was detected in only 9% of pedigrees containing 320 individuals and the epistatic and additive models were equally effective at predicting the genotypic values of progeny. Epistasis was detected with the same power whether the overall epistatic effect was the result of a single pairwise interaction or the sum of nine pairwise interactions, each generating one ninth of the epistatic variance. The power to detect epistasis was highest (94%) at low QTL minor allele frequency, fell to a minimum (60%) at minor allele frequency of about 0.2, and then plateaued at about 80% as alleles reached intermediate frequencies. The power to detect epistasis declined when the linkage disequilibrium between the DNA marker and the functional polymorphism was not complete.

(ProQuest-CSA LLC: ... denotes formulae omitted.)

THE existence of epistasis is supported by classic quantitative genetic studies (e.g., MATHER and JINKS 1982; LAMKEY et al. 1995) and has also been identified in quantitative trait locus (QTL) studies (e.g., SPICKETT and THODAY 1966; LARK et al. 1994; HOLLAND et al. 1997; BLANC et al. 2006; CARLBORG et al. 2006) and in near-isogenic line studies (ESHED and ZAMIR 1996; KROYMANN and MITCHELL-OLDS 2005). At the same time, QTL detection methods using population-wide linkage disequilibrium are beginning to demonstrate their potential to identify either mutations causing phenotypic variance or genetic polymorphisms in strong linkage disequilibrium and therefore, presumably, in tight linkage with those mutations. Application of these methods has occurred in large germplasm collections (THORNSBERRY et al. 2001) and in pedigreed populations (KRAAKMAN et al. 2004;PARISSEAUX and BERNARDO2004; ARBELBIDE and BERNARDO 2006; BRESEGHELLO and SORRELLS 2006). Association mapping models to date have assumed additive gene action in the loci analyzed (KENNEDY et al. 1992; YU et al. 2006). Statistical approaches to association mapping that account for epistasis are needed both to detect loci that display little main effect and to discern the extent to which identified additive effect loci also display epistasis.

A typical statistical model to detect association between a DNAmarker and the phenotype includes a term for the DNA marker itself and a term for the genetic background of the individual (KENNEDY et al. 1992; Thornsberry et al. 2001; Yu et al. 2006). In the absence of the latter term, associations between markers and the phenotype can arise even for markers unlinked to any causal QTL because of correlation between marker allelic states and the genetic background. …

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