Title :
Additive and multiplicative genome-wide association models identify genes associated with growth
Author :
Zavala, C. ; Serao, N. ; Villamil, Maria B. ; Caetano-Anolles, Gustavo ; Rodriguez-Zas, Sandra L.
Author_Institution :
Dept. of Animal Sci., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
Standard genome-wide association studies evaluate the association between single nucleotide polymorphisms (SNPs or Genotype G) and phenotype (e.g. growth) conditional on non-SNP covariates including environmental factors (E, e.g. diet) or population stratification, on an additive fashion. For traits known to be the result of genotype-by-environment interactions (G×E), like growth, a multiplicative model could potentially uncover additional SNPs that influence growth on a context-dependent (e.g. diet or breed) fashion. The objective of this study was to assess and compare the performance of context-independent (additive, G+E) and context-dependent (multiplicative, G+E+G×E) models to identify polymorphisms and corresponding genes associated with growth that are context-independent and context-dependent. In addition to single-SNP analysis, a multi-SNP haplotype-based analysis that can increase the precision of the estimates was evaluated for the additive model.
Keywords :
additives; association; biochemistry; environmental factors; genetics; genomics; physiological models; polymorphism; additive fashion; context-dependent fashion; context-dependent models; environmental factors; genotype-environment interactions; multiplicative genome-wide association models; multiplicative model; population stratification; single nucleotide polymorphisms; standard genome-wide association model; Additives; Bioinformatics; Biological system modeling; Context modeling; Cows; Environmental factors; Genomics;
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4577-1612-6
DOI :
10.1109/BIBMW.2011.6112527