|ZHOU, YANG - Collaborator|
|UTSUNOMIYA, YURI - Collaborator|
|XU, LINGYANG - University Of Maryland|
|Hay, El Hamidi|
|CARVALHEIRO, ROBERTO - Collaborator|
|NEVES, HAROLDO HENRIQU - Collaborator|
|SONSTEGARD, TAD - Former ARS Employee|
|Van Tassell, Curtis - Curt|
|GARCIA, JOSE FERNANDO - Collaborator|
|Liu, Ge - George|
Submitted to: Biomed Central (BMC) Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/11/2016
Publication Date: 6/1/2016
Citation: Zhou, Y., Utsunomiya, Y.T., Xu, L., Hay, E.A., Bickhart, D.M., Carvalheiro, R., Neves, H.E., Sonstegard, T., Van Tassell, C.P., Garcia, J., Liu, G. 2016. Genome-wide CNV analysis reveals variants associated with growth traits in Bos indicus. Biomed Central (BMC) Genomics. 17(1):419.2016.
Interpretive Summary: Beef production is an economically important sector of global agriculture. We performed the first CNV-based genome-wide association study of growth traits using high density SNP microarray data in cattle. We detected 17 Copy number variants significantly associated with seven growth traits and one of them may be involved in growth traits through the gene KCNJ12. Farmers, scientist, and policy planners who need to improve animal health and production based on genome-enable animal selection will benefit from this research report chapter.
Technical Abstract: Background: Apart from single nucleotide polymorphism (SNP), copy number variation (CNV) is another important type of genetic variation, which may affect growth traits and play key roles for the production of beef cattle. To date, no genome-wide association study (GWAS) for CNV and body traits in beef cattle has been reported, so the present study aimed to investigate this type of association in one of the most important cattle subspecies: Bos indicus (Nellore breed). Results: We have used intensity data from over 700,000 SNP probes across the bovine genome to detect common CNVs in a sample of 2,230 Nellore cattle, and performed GWAS between the detected CNVs and nine growth traits. After filtering for frequency and length, a total of 231 CNVs ranging from 894 bp to 4,855,088 bp were kept and tested as predictors for each growth trait using linear regression analysis with principal components correction. There were 49 significant associations identified among 17 CNVs and seven body traits after false discovery rate (FDR) correction (P<0.05). Among the 17 CNVs, three were significant or marginally significant for all the traits. We have compared the locations of associated CNVs with quantitative trait locus (QTL) and the RefGene database, and found two sets of 9 CNVs overlapping with either known QTLs or genes, respectively. The gene overlapping with CNV100, KCNJ12, is a functional candidate for muscle development and plays critical roles in muscling traits. Conclusion: This study presents the first CNV-based GWAS of growth traits using high density SNP microarray data in cattle. We detected 17 CNVs significantly associated with seven growth traits and one of them (CNV100) may be involved in growth traits through KCNJ12.