Transcriptome profiling of follicular development-related genes in 2-, 6-, and 12-month-old sheep ovaries

Published: 25-07-2018| Version 2 | DOI: 10.17632/dwjg5276gj.2
Contributors:
Bo Gu,
Liu Hang,
Yue Han,
Yang Chen,
Huaizhi Jiang

Description

Transcriptome profiling of follicular development-related genes in 2-, 6-, and 12-month-old sheep ovaries. The results showed that 98, 1478, and 974 differentially expressed genes(DEGs) were identified in 2- vs 6-month-old, 6- vs 12-month-old, and 2- vs 12-month-old ovaries, respectively. Gene Ontology(GO) analysis showed that the following: DEGs in 2- vs 6-month-old ovaries were mainly related to the GO terms apoptotic process and regulation of mitochondrial organization; in 6- vs 12-month-old ovaries, most of the GO terms involving DEGs were related to metabolism and translation processes; in 2- vs 12-month-old ovaries, most of the GO terms that involving DEGs were related to cell adhesion. In a KEGG analysis, in 2- vs 6-month-old and 6- vs 12-month-old ovaries, nucleotide excision repair was the most significantly enriched pathway; in 2- vs 12-month-old ovaries, the ribosome pathway was the most significantly enriched term.

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Animal sample preparation Animals were obtained from the Jilin Jiayuan Sheep Breeding Co. Ltd(Chang Ling, P. R. China). All sheep were raised under the same environment with natural light and free intake of food and water. Three healthy animals in each age group were selected to obtain the ovaries for this study. The tissue samples were immediately snap-frozen in liquid nitrogen for total RNA extraction. Library preparation for transcriptome sequencing Sequencing libraries were generated using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. Clustering and sequencing) The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Differential expression analysis Differential expression analysis of two conditions/groups was performed using the DEGSeq R package (1.18.0). GO and KEGG enrichment analysis of differentially expressed genes Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented by the GOseq R package, in which gene length bias was corrected. GO terms with corrected P values <0.05 were considered significantly enriched by in DEGs. Kyoto Encyclopedia of Genes and Genomes(KEGG) is a database resource for understanding high-level functions and utilities of biological systems, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-through put experimental technologies (http://www.genome.jp/kegg/). We used KOBAS software to test the statistical enrichment of differential expression genes in KEGG pathways. PPI analysis of differentially expressed genes Protein–protein interaction(PPI) analysis of differentially expressed genes was based on the STRING database, covering known and predicted interactions. For the species in the database, we constructed networks by extracting a target gene list; Otherwise, Blastx (v2.2.28) was used to align the target gene sequences to the selected reference protein sequences, and then the networks were built according to the known interaction of selected reference species. RNA-Seq data validation by RT-qPCR RT–qPCR was conducted to validate the reliability of the RNA-Seq data.