SNP-Chip analysis for investigating genetic effects over a timeline

Abstract

High throughput methods have been recently developed to genotype individuals for 50,000 or more single nucleotide polymorphisms (SNPs) in a cost effective way. However, besides increasing the power of association studies by using dense marker maps the importance of the accurate selection of the phenotypic data should not be disregarded. The level of milk production differs between parities and shows a decrease for higher parities. Moreover, differences in milk yield can be observed between different lactations as well as within a single lactation. A lactation curve shows the peak production between day 35 and 50 after which production slowly decreases until the end of the lactation (Stanton et al. 1992, Dematawewa et al. 2007). This study aims to locate genetic effects underlying variation in milk production over time. In order to estimate genetic effects between lactations the average production level for each cow was considered. To estimate genetic effects within a lactation, lactation curve parameters were estimated.