Genomic characteristics of cattle copy number variations

• Published in: BMC genomics 2011-02, Vol.12 (1), p.127-127, Article 127
• Main Authors: 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
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Animals; Arrays; Breeding; Cattle; Cattle - genetics; Comparative Genomic Hybridization; Data collection; Experiments; Gene Dosage; Gene expression; Genes; Genetic aspects; Genetic Markers; Genetic research; Genetic variation; Genetics; Genome; Genomes; Genomics; Genomics - methods; Genotype; Green chemistry; Pedigree; Polymorphism, Single Nucleotide; R&D; Research & development; Sequence Analysis, DNA; Single nucleotide polymorphisms
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/1471-2164-12-127

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.