|Liu, Ge - George|
|Hou, Yali - University Of Maryland|
|Zhu, Bin - University Of Maryland|
|Cardone, Maria - University Of Bari|
|Jiang, Lu - University Of Maryland|
|Cellamare, Angelo - University Of Bari|
|Mitra, Apratim - University Of Maryland|
|Coutinho, Luiz - Luiz De Queiroz College Of Agriculture (ESALQ)|
|Gasbarre, Louis - Retired Ars Employee|
|Matukumalli, Lakshmi - George Mason University|
|Nonneman, Danny - Dan|
|De A Regitano, Luciana - Embrapa|
|Smith, Timothy - Tim|
|Song, Jiuzhou - University Of Maryland|
|Van Tassell, Curtis - Curt|
|Eichler, Evan - University Of Washington|
Submitted to: Genome Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/4/2010
Publication Date: 3/8/2010
Publication URL: http://hdl.handle.net/10113/44598
Citation: Liu, G., Hou, Y., Zhu, B., Cardone, M.F., Jiang, L., Cellamare, A., Mitra, A., Alexander, L.J., Coutinho, L.L., Gasbarre, L.C., Heaton, M.P., Li, R.W., Matukumalli, L.K., Nonneman, D.J., De A Regitano, L.C., Smith, T.P., Song, J., Sonstegard, T.S., Van Tassell, C.P., Eichler, E.E., Mcdaneld, T.G., Keele, J.W. 2010. Analysis of copy number variations among cattle breeds. Genome Research. 20:693-703.
Interpretive Summary: In this study, we used 3 methodologies to describe the first systematic and genome-wide analysis of copy number variations (CNV) in modern domesticated cattle. We identified 177 high-confidence CNV covering 28.1 mega bases, which is about 1% of the cattle genome. We detected and confirmed marked variation in copy number across diverse breeds. Our combined findings revealed that many cattle CNV may be associated with cattle domestication and breed formation. Results of this study provide a valuable resource beyond traditional measures of genetic variation such as microsatellites and single nucleotide polymorphisms (SNP) to explore the full dimension of genetic variability in cattle. It provides insights into mechanisms of evolution of the cattle genome and generates a valuable knowledge base for accelerating genetic improvement for milk and beef production. It also provides the foundation for correlating structural variation in the genome with the molecular basis of economically-important adaptive traits of ruminants, such as milk production, metabolism, reproduction and disease resistance. This work will be an important complement to SNP-based genome-wide association studies.
Technical Abstract: Genomic structural variation is an important and abundant source of genetic and phenotypic variation. Here we describe the first systematic and genome-wide analysis of copy number variations (CNVs) in the modern domesticated cattle using array comparative genomic hybridization (array CGH) and quantitative PCR and fluorescent in situ hybridization (FISH). Our panel includes 90 animals from 11 Bos tarus, 3 Bos indicus and 3 composite breeds for beef, dairy or dual purposes. We identified over 200 candidate CNV regions (CNVRs) in total and 177 of which are within known chromosomes, which harbor or are adjacent to gains or losses. These 177 high-confidence CNVRs cover 28.1 mega bases, ~1.07% of the genome. Over 50% CNVRs (89/177) were found in multiple animals or breeds and analysis of them reveals breed-specific frequency differences and reflects aspects of the known ancestry of these cattle breeds. Selected CNVs were further successfully validated by independent methods using qPCR and FISH. About 67% CNVRs (119/177) completely or partially span cattle genes and 61% CNVRs (108/177) directly overlap with segmental duplications. CNVRs span about 400 annotated cattle genes that are significantly enriched for specific biological functions such as immunity, lactation, reproduction and rumination. For gene families like ULBP which have gone through ruminant lineage-specific gene amplification, we detected and confirmed marked differences in CNV frequencies across diverse breeds, demonstrating the evolutionary contributions of CNVs to cattle domestication and breed formation. Our results provide a valuable resource beyond microsatellites and single nucleotide polymorphisms to explore the full dimension of genetic variability for the future cattle genomic research.