Abstract
BackgroundRecently, RNA sequencing (RNA-seq) has rapidly emerged as a major transcriptome profiling system. Elucidation of the bovine mammary gland transcriptome by RNA-seq is essential for identifying candidate genes that contribute to milk composition traits in dairy cattle.ResultsWe used massive, parallel, high-throughput, RNA-seq to generate the bovine transcriptome from the mammary glands of 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, which represented 15549 mRNA transcripts, across all the four mammary gland samples. Among them, 31 differentially expressed genes (p < 0.05, false discovery rate q < 0.05) between the high and low groups of cows were revealed. Gene ontology and pathway analysis demonstrated that the 31 differently expressed genes were enriched in specific biological processes with regard to protein metabolism, fat metabolism, and mammary gland development (p < 0.05). Integrated analysis of differential gene expression, previously reported quantitative trait loci, and genome-wide association studies indicated that TRIB3, SAA (SAA1, SAA3, and M-SAA3.2), VEGFA, PTHLH, and RPL23A were the most promising candidate genes affecting milk protein and fat percentage.ConclusionsThis study investigated the complexity of the mammary gland transcriptome in dairy cattle using RNA-seq. Integrated analysis of differential gene expression and the reported quantitative trait loci and genome-wide association study data permitted the identification of candidate key genes for milk composition traits.
Highlights
RNA sequencing (RNA-seq) has rapidly emerged as a major transcriptome profiling system
Alignment of the sequence reads against the bovine genome UMD3.1.66 yielded 90.6–91.9% of uniquely aligned reads across the four samples, of which 80–85% fell in annotated exons, 4–6% were located in introns, and the remaining 11–14% was assigned to intergenic regions
15549 mRNA transcripts were detected as expressed in the four mammary gland samples, among which there were certain well-known genes affecting milk traits; e.g., Κ-casein (CSN3), β-casein (CSN2), a-lactalbumin (LALBA), β-lactoglobulin (BLG), DGAT1, Growth hormone receptor (GHR), Signal transducer and activator of transcription5A (STAT5A), Signal transducer and activator of transcription5B (STAT5B), and Stearoyl-coenzyme A desaturase (SCD)
Summary
RNA sequencing (RNA-seq) has rapidly emerged as a major transcriptome profiling system. Elucidation of the bovine mammary gland transcriptome by RNA-seq is essential for identifying candidate genes that contribute to milk composition traits in dairy cattle. As compared with microarray technology, RNA-seq enables analysis of the complexity of whole eukaryotic transcriptomes with less bias, greater dynamic range, lower frequency of false-positive signals, and higher reproducibility [14,15]. Two studies on the transcriptome of the mammary gland of Holstein cows using an oligonucleotide microarray have been presented, one of which compared the gene expression profile before (dry) and after (milk) parturition, using an Affymetrix cDNA array [22]. We used RNA-seq technology to examine the genome-wide gene expression profile in mammary glands between two groups of Holstein cows with extremely high and low milk protein percentage (PP) and fat percentage (FP).
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