Computational identification and characterization of novel microRNA in the mammary gland of dairy goat (Capra hircus).

Abstract

Many studies have indicated that microRNAs (miRNAs) influence the development of the mammary gland by posttranscriptionally affecting their target genes. The objective of this research was to identify novel miRNAs in the mammary gland of dairy goats with a bioinformatics approach that was based on expressed sequence tag (EST) and genome survey sequence (GSS) analyses. We applied all known major mammals, miRNAs to search against the goat EST and GSS databases for the first time to identify new miRNAs. We, then, validated these newly predicted miRNAs with stem-loop reverse transcription followed by a SYBR Green polymerase chain reaction assay. Finally, 29 mature miRNAs were identified and verified, and of these, 14 were grouped into 13 families based on seed sequence identity and 85 potential target genes of newly verified miRNAs were subsequently predicted, most of which seemed to encode the proteins participating in regulation of metabolism, signal transduction, growth and development. The predicting accuracy of the new miRNAs was 70.37%, which confirmed that the methods used in this study were efficient and reliable. Detailed analyses of the sequence characteristics of the novel miRNAs of the goat mammary gland were performed. In conclusion, these results provide a reference for further identification of miRNAs in animals without a complete genome and thus improve the understanding of miRNAs in the caprine mammary gland.