|XU, LINGYANG - University Of Maryland
|HOU, YALI - Chinese Academy Of Sciences
|SONG, JIUZHOU - University Of Maryland
|Van Tassell, Curtis - Curt
|Liu, Ge - George
Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/9/2014
Publication Date: 4/10/2014
Citation: Xu, L., Cole, J.B., Bickhart, D.M., Hou, Y., Song, J., Van Raden, P.M., Sonstegard, T.S., Van Tassell, C.P., Liu, G. 2014. Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins. BARC Poster Day. BARC Poster Day.p.67, abstract 54.
Technical Abstract: Milk production is an economically important sector of global agriculture. Much attention has been paid to the identification of quantitative trait loci (QTL) associated with milk, fat, and protein yield and the genetic and molecular mechanisms underlying them. Copy number variation (CNV) is an emerging class of variants which may be associated with complex traits. In this study, we performed a genome-wide association between CNVs and milk production traits in 26,362 Holstein bulls and cows. A total of 99 candidate CNVs were identified using Illumina BovineSNP50 array data, and association tests for each production trait were performed using a linear regression analysis with PCA correlation. A total of 34 CNVs on 22 chromosomes were significantly associated with at least one milk production trait after false discovery rate (FDR) correction. Some of those CNVs were located within or near known QTL for milk production traits. We further investigated the relationship between associated CNVs with neighboring SNPs. For all 82 combinations of traits and CNVs (less than 400 kb in length), we found 17 cases where CNVs directly overlapped with tag SNPs and 40 cases where CNVs were adjacent to tag SNPs. In 5 cases, CNVs located were in strong linkage disequilibrium with tag SNPs, either within or adjacent to the same haplotype block. There were an additional 20 cases where CNVs did not have a significant association with SNPs, suggesting that the effects of those CNVs were probably not captured by tag SNPs. We conclude that combining CNV with SNP analyses reveals more genetic variations underlying milk production traits than those revealed by SNPs alone.