Additive and multiplicative genome-wide association models identify genes associated with growth

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.