Transcriptome analysis of the uniparous and multiparous goats ovaries

Abstract

Transcriptome analysis of Inner Mongolia Cashmere goat and Dazu black goat generated 38,772,947 and 38,771,668 clean pair end reads, respectively, which were assembled into 72,422 and 80,069 unigenes by Trinity, respectively. For Inner Mongolia Cashmere goat, 26,051 and 10,100 unigenes were assigned to gene ontology (GO) categories and clusters of orthologous groups, respectively. A total of 32,772 unigenes can comment to SWISS-Prot database, and the Kyoto Encyclopedia of Genes and Genomes Pathway database (KEGG) mapped 24,420 unigenes. While annotating the unigenes about Dazu black goats, we found 29,444(45.42%), 11,271 (38.28%), 36,910(56.94%) and 27,766 (42.83%) unigenes were assigned to GO database, COG database, SWISS-Prot database and KEGG database, respectively. In addition, we performed the bioinformatics analysis of gene expression profiling aimed at the ovarian transcriptome difference between Inner Mongolia Cashmere goat and Dazu black goat. We obtained a sequencing depth of over 5.5 million and 5.8 million tags. There were 1,133 DEGs between two species, of which 632 genes upregulated in the Dazu black goat and 501 genes downregulated compared with which in Inner Mongolia Cashmere goat. By annotating the 1,133 DEGs into KEGG database, we found 525 DEGs. And there were 68 DEGs annotated in metabolic pathways, 31 DEGs annotated in ribosome, 28 DEGs annotated in focal adhesion, 27 DEGs annotated in phagosome, 26 DEGs annotated in pathways in cancer, 25 DEGs annotated in ECM-receptor interaction, 23 DEGs annotated in protein digestion and absorption, 20 DEGs annotated in oxidative phosphorylation, 17 DEGs annotated in lysosome, and 16 DEGs annotated in cell adhesion molecules.

Comparative analysis of ovarian transcriptomes between prolific and non‐prolific goat breeds via high‐throughput sequencing

“…Among them, cell parts and cells, binding and catalytic activity, metabolic processes, and cellular processes were predominant in each of the three main categories, respectively. These observations are consistent with previous studies regarding ovarian transcriptomes of goats (Ling et al, 2014;Miao et al, 2016;Wang et al, 2016;Zhao et al, 2015) and pigs . Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway significant enrichment analysis revealed that the DEGs participated in 331 pathways, of which 22 significantly enriched pathways were identified in the current study.…”

“…On average, a total of 15,719 and 15,738 genes were expressed in each TBG and JTG ovary, respectively. Previous transcriptome studies of ovaries used samples from multiple pooled ovary RNA for analysis (Ling et al., ; Miao et al., ; Wang et al., ; Zhao et al., ). Pooling methods would possibly mask individual ovary variability and gene expression heterogeneity.…”

“…In pigs, the 10 most significant DEGs between large and small litter size samples were mainly in the metabolic pathways, ovarian steroidogenesis, citrate cycle, pyruvate metabolism and the PPAR signalling pathway (Zhang et al., ). In goats, the most significant DEGs of high‐ and low‐fecundity samples were mainly in the metabolic pathways, ECM–receptor interaction, focal adhesion and amoebiasis (Miao et al., ; Wang et al., ; Zhao et al., ). Oocyte metabolism determines its developmental competence.…”

“…To develop a broader view of the gene expression in the pre-ovulatory ovary and identify the key genes involved in the regulation of goat ovulation rate, for the first time, the present study compared the (Ling et al, 2014;Miao et al, 2016;Wang et al, 2016;Zhao et al, 2015). Pooling methods would possibly mask individual ovary variability and gene expression heterogeneity.…”

“…The RNA‐Seq approach produces millions of short cDNA reads that are mapped to a reference genome to obtain a genome‐scale transcriptional map, which consists of the transcriptional structure and the expression level for each gene (Mortazavi, Williams, McCue, Schaeffer, & Wold, ). Transcriptomes of ovaries have been initially compared in some goats (Ling, Xiang, Li, Liu, & Zhang, ; Miao, Luo, & Qin, ; Wang et al., ; Zhao et al., ) and pigs (Zhang et al., ) with different prolificacy using RNA‐Seq technology, and a large number of differentially expressed genes (DEGs) have been identified, although the results are not consistent. The Jintang black goat (JTG) is an excellent local Chinese breed that has a high kidding rate (248% on average) and superior meat performance.…”