Background: Capra hircus is an important economic livestock animal, and therefore, it is necessary to discover transcriptome information about their reproductive performance. In this study, we performed de novo transcriptome sequencing to produce the first transcriptome dataset for the goat ovary using high-throughput sequencing technologies. The result will contribute to research on goat reproductive performance.
Method and results: RNA-seq analysis generated more than 38.8 million clean paired end (PE) reads, which were assembled into 80,069 unigenes (mean size = 619 bp). Based on sequence similarity searches, 64,824 (60.6%) genes were identified, among which 29,444 and 11,271 unigenes were assigned to Gene Ontology (GO) categories and Clusters of Orthologous Groups (COG), respectively. Searches in the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG) showed that 27,766 (63.4%) unigenes were mapped to 258 KEGG pathways. Furthermore, we investigated the transcriptome differences of goat ovaries at two different ages using a tag-based digital gene expression system. We obtained a sequencing depth of over 5.6 million and 5.8 million tags for the two ages and identified a large number of genes associated with reproductive hormones, ovulatory cycle and follicle. Moreover, many antisense transcripts and novel transcripts were found; clusters with similar differential expression patterns, enriched GO terms and metabolic pathways were revealed for the first time with regard to the differentially expressed genes.
Conclusions: The transcriptome provides invaluable new data for a functional genomic resource and future biological research in Capra hircus, and it is essential for the in-depth study of candidate genes in breeding programs.