Genomic characteristics of cattle copy number variations

• Published in: BMC genomics Vol. 12; no. 1; pp. 127 - 11
• 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: Journal Article
• Language: English
• Published: London BioMed Central 23.02.2011; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Algorithms; Analysis; Animal Genetics and Genomics; Animals; Arrays; artificial selection; Bovine: the companion papers for the publication of the bovine genome sequence; Breeding; Cattle; Cattle - genetics; cattle breeds; chromosome mapping; Comparative Genomic Hybridization; Dairy industry; Data collection; Domestic animals; Experiments; Gene Dosage; Gene expression; Genes; Genetic aspects; Genetic diversity; Genetic improvement; Genetic Markers; Genetic research; Genetic variation; Genetics; Genome; Genomes; Genomics; Genomics - methods; Genotype; genotyping; Green chemistry; haplotypes; Human and rodent genomics; lactation; Life Sciences; Microarrays; Microbial Genetics and Genomics; molecular systematics; Pedigree; Plant Genetics and Genomics; Polymorphism, Single Nucleotide; Proteomics; R&D; Research & development; Research Article; rumination; Sequence Analysis, DNA; single nucleotide polymorphism; Single nucleotide polymorphisms; tandem repeat sequences; United States; Copy Number Variation Region; Single Nucleotide Polymorphism Array; Single Nucleotide Polymorphism Data; Single Nucleotide Polymorphism Marker; Copy Number Variation
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/1471-2164-12-127

Background 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. Results 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. Conclusions 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.