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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #291174
Title: Gene expression profiles of bovine mammary epithelial cells and association with milk composition traits using RNA-seq

Author
item CUI, XIAOGANG - China Agricultural University
item HOU, YALI - Chinese Academy Of Sciences
item SUN, DONGXIAO - China Agricultural University
item ZHANG, SHENGLI - China Agricultural University
item LV, XUEMEI - Chinese Academy Of Sciences
item Liu, Ge - George
item ZHANG, YUAN - China Agricultural University
item ZHANG, QIN - China Agricultural University

Submitted to: BMC Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/8/2014
Publication Date: 3/24/2014
Citation: Cui, X., Hou, Y., Sun, D., Zhang, S., Lv, X., Liu, G., Zhang, Y., Zhang, Q. 2014. Gene expression profiles of bovine mammary epithelial cells and association with milk composition traits using RNA-seq. Biomed Central (BMC) Genomics 15:226.

Interpretive Summary: RNA sequencing (RNA-seq) is a state-of-the-art tool for measuring differential gene expression. Using RNA-seq and other analyses, we profiled global gene expression in the mammary epithelium obtained from four Holstein cows with high or low milk protein and fat percentages. We identified 34 genes and potential networks related to differences in milk composition traits. These genes and networks are involved in fat and protein metabolism and development of the mammary gland. Results of the study will assist in the identification of key genes contributing to milk composition traits. Farmers, scientists, and policy planners who desire improved animal health and production based on genome-enabled animal selection will benefit from this research.

Technical Abstract: In most recent years, RNA Sequencing is rapidly emerging as the major quantitative transcriptome profiling system. Elucidation of the bovine mammary gland transcriptome with RNA-seq is essential for identifying candidate genes for milk composition traits in dairy cattle. Here we used massive parallel high-throughput RNA sequencing to generate the bovine transcriptome in mammary epithelium from four lactating Holstein cows with extremely high and low phenotypic values of milk protein and fat percentage. In total, we obtained 48,967,376-75,572,578 uniquely mapped reads that covered 82.25% of the current annotated transcripts, among which were totally 24616 mRNA transcripts across all the four mammary epithelium samples. Out of them, 34 differentially expressed genes (p<0.05, FDR q<0.05) between the high and low groups of cows were revealed. Through Gene Ontology (GO) and pathway analysis, we found that significant biological processes for such 34 genes were enriched on fat and protein metabolism and mammary gland development (p<0.05). Integrated analysis of differential gene expression, previously reported quantitative trait locus (QTL) and genome-wide association study (GWAS) discoveries and biological functions showed that TRIB3, VEGFA, PTHLH and RPL23A could be the most promising candidate genes for milk fat and protein traits. This study presents the first investigation on the complexity of the mammary epithelium transcriptome in dairy cattle by RNA sequencing. Integrated analysis of the differential gene expression and the reported QTL and GWAS data allows us to find candidate key genes for milk composition traits.