Genomic characteristics of cattle copy number variations

BMC Genomics

Research Article

Paul M VanRaden¹  Curt P Van Tassell²  George E Liu²  Eui-soo Kim²  Tad S Sonstegard²  Derek M Bickhart²  Lakshmi K Matukumalli³  Yali Hou⁴  Kai Wang⁵  Jiuzhou Song⁶  Maria Francesca Cardone⁷  Mario Ventura⁷ 

[1] Animal Improvement Programs Laboratory, ANRI, USDA-ARS, 20705, Beltsville, Maryland, USA;Bovine Functional Genomics Laboratory, ANRI, USDA-ARS, 20705, Beltsville, Maryland, USA;Bovine Functional Genomics Laboratory, ANRI, USDA-ARS, 20705, Beltsville, Maryland, USA;Bioinformatics and Computational Biology, George Mason University, 20110, Manassas, VA, USA;Bovine Functional Genomics Laboratory, ANRI, USDA-ARS, 20705, Beltsville, Maryland, USA;Department of Animal and Avian Sciences, University of Maryland, 20742, College Park, Maryland, USA;Center for Applied Genomics, Children's Hospital of Philadelphia, 19104, Philadelphia, PA, USA;Department of Animal and Avian Sciences, University of Maryland, 20742, College Park, Maryland, USA;Department of Genetics and Microbiology, University of Bari, 70126, Bari, Italy;

关键词: Copy Number Variation;    Single Nucleotide Polymorphism Marker;    Single Nucleotide Polymorphism Array;    Single Nucleotide Polymorphism Data;    Copy Number Variation Region;   

DOI  :  10.1186/1471-2164-12-127

 received in 2010-09-10, accepted in 2011-02-23,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundCopy 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.ResultsWe 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.ConclusionsWe 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.

【 授权许可】

Unknown   
© Hou et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.