Mapping copy number variants across the cattle genome

Abstract

Copy number variation across individuals is known to be associated with traits such as gene expression, disease resistance, and other phenotypic variations. Due to improvements in accurately detecting genotypic variation and the variety of impacts copy number variants have on phenotype, copy number variant (CNV) analyses have increased in frequency. In the agricultural industry, understanding where copy number variants occur and the impact they have could lead to a significant improvement in the efficiency of production for desired commodities. Although a variety of CNV detection tools have been created, accurately mapping genomic regions containing CNVs has been difficult. This is largely due to inadequate sample size. A comprehensive understanding of CNVR location and frequency may enable more accurate genomic selection, which will benefit cattle producers along with other animal production systems. Using the detection algorithm of the PennCNV software, this study evaluated the ability to accurately call CNVs. This was done by testing various quality control variables and setting thresholds to determine the highest efficiency in CNV detection. Using these findings, the study created a catalog of confident copy number variable regions (CNVRs) in cattle.