title: Genomic characteristics of cattle copy number variations.
abstract: 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.
authors.affiliation: Bovine Functional Genomics Laboratory, ANRI, USDA-ARS, Beltsville, Maryland 20705, USA.
authors.forename: Yali
authors.initials: Y
authors.lastname: Hou
authors.forename: George E
authors.initials: GE
authors.lastname: Liu
authors.forename: Derek M
authors.initials: DM
authors.lastname: Bickhart
authors.forename: Maria Francesca
authors.initials: MF
authors.lastname: Cardone
authors.forename: Kai
authors.initials: K
authors.lastname: Wang
authors.forename: Eui-Soo
authors.initials: ES
authors.lastname: Kim
authors.forename: Lakshmi K
authors.initials: LK
authors.lastname: Matukumalli
authors.forename: Mario
authors.initials: M
authors.lastname: Ventura
authors.forename: Jiuzhou
authors.initials: J
authors.lastname: Song
authors.forename: Paul M
authors.initials: PM
authors.lastname: VanRaden
authors.forename: Tad S
authors.initials: TS
authors.lastname: Sonstegard
authors.forename: Curt P
authors.initials: CP
authors.lastname: Van Tassell
mesh_terms: D000818:Animals; D001947:Breeding; D002417:Cattle / Q000235:genetics*; D055028:Comparative Genomic Hybridization; D018628:Gene Dosage; D005819:Genetic Markers; D016678:Genome; D023281:Genomics / Q000379:methods; D005838:Genotype; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D017422:Sequence Analysis, DNA
chemical_list: D005819:Genetic Markers