A New Method for Exploring Genome-wide Associations Applied to Cattle Puberty

Abstract

Genome wide approaches are now commonly used to examine the genetics underlying complex phenotypes. These approaches yield a varying number of loci associated with the phenotype, depending on significance thresholds and interpretation of results is less than straightforward. There is a consequential need to develop new analytical approaches to maximise the value of genome wide association studies (GWAS). A systemic approach is fitted for complex phenotypes (Mackay, Stone et al. 2009). It allows a large number of associations by using relaxed significance thresholds, while simultaneously reducing the number of false positives. Here, we describe a new systemic approach applied to a GWAS conducted in Brahman cattle. We call the approach an association weight matrix (AWM). The use of AWM is two-fold: it estimates correlations between phenotypes and it explores gene to gene interactions across the genome. We demonstrate the application of AWM for complex phenotypes to examine the genetic drivers of puberty in Brahman cattle.