Main content area

Genomic characteristics of cattle copy number variations

Hou, Yali, Liu, George E., Bickhart, Derek M., Cardone, Maria Francesca, Wang, Kai, Kim, Eui-soo, Matukumalli, Lakshmi K., Ventura, Mario, Song, Jiuzhou, VanRaden, Paul M., Sonstegard, Tad S., Van Tassell, Curt P.
Biomed Central (BMC) Genomics 2011 v.12 pp. 1
artificial selection, cattle, cattle breeds, chromosome mapping, dairy industry, gene dosage, genetic improvement, genetic variation, genome, genomics, genotyping, haplotypes, lactation, molecular systematics, pedigree, reproduction, rumination, single nucleotide polymorphism, tandem repeat sequences
Copy number variation (CNV) represents another important source of genetic variation complementary to single nucleotide polymorphism (SNP). High-density SNP array data have been routinely used to detect human CNVs, many of which have significant functional effects on gene expression and human diseases. In the dairy industry, a large quantity of SNP genotyping results are becoming available and can be used for CNV discovery to understand and accelerate genetic improvement for complex traits. We performed a systematic analysis of CNV using the Bovine HapMap SNP genotyping data, including 539 animals of 21 modern cattle breeds and 6 outgroups. After correcting genomic waves and considering the pedigree information, we identified 682 candidate CNV regions, which represent 139.8 megabases (~4.60%) of the genome. Selected CNVs were further experimentally validated and we found that copy number "gain" CNVs were predominantly clustered in tandem rather than existing as interspersed duplications. Many CNV regions (~56%) overlap with cattle genes (1,263), which are significantly enriched for immunity, lactation, reproduction and rumination. The overlap of this new dataset and other published CNV studies was less than 40%; however, our discovery of large, high frequency (> 5% of animals surveyed) CNV regions showed 90% agreement with other studies. These results highlight the differences and commonalities between technical platforms. We present a comprehensive genomic analysis of cattle CNVs derived from SNP data which will be a valuable genomic variation resource. Combined with SNP detection assays, gene-containing CNV regions may help identify genes undergoing artificial selection in domesticated animals.