Resolving candidate genes of duck ovarian tissue transplantation via RNA-Seq and expression network analyses

Abstract

This study aims to identify candidate genes related to ovarian development after ovarian tissue transplantation through transcriptome sequencing (RNA-seq) and expression network analyses, as well as to provide a reference for determining the molecular mechanism of improving ovarian development following ovarian tissue transplantation. We collected ovarian tissues from 15 thirty-day-old ducks and split each ovary into 4 equal portions of comparable sizes before orthotopically transplanting them into 2-day-old ducks. Samples were collected on days 0 (untransplanted), 3, 6, and 9. The samples were paraffin sectioned and then subjected to Hematoxylin-Eosin (HE) staining and follicular counting. We extracted RNA from ovarian samples via the Trizol method to construct a transcriptome library, which was then sequenced by the Illumina Novaseq 6000 sequencing platform. The sequencing results were examined for differentially expressed genes (DEG) through gene ontology (GO) function and the Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses, gene set enrichment analysis (GSEA), weighted correlation network analysis (WGCNA), and protein-protein interaction (PPI) networks. Some of the candidate genes were selected for verification using real-time fluorescence quantitative PCR (qRT-PCR). Histological analysis revealed a significant reduction in the number of morphologically normal follicles at 3, 6, and 9 d after ovarian transplantation, along with significantly higher abnormality rates (P < 0.05). The transcriptome analysis results revealed 2,114, 2,224, and 2,257 upregulated DEGs and 2,647, 2,883, and 2,665 downregulated DEGs at 3, 6, and 9 d after ovarian transplantation, respectively. Enrichment analysis revealed the involvement multiple pathways in inflammatory signaling, signal transduction, and cellular processes. Furthermore, WGCNA yielded 13 modules, with 10, 4, and 6 candidate genes mined at 3, 6 and 9 d after ovarian transplantation, respectively. Transcription factor (TF) prediction showed that STAT1 was the most important TF. Finally, the qRT-PCR verification results revealed that 12 candidate genes exhibited an expression trend consistent with sequencing data. In summary, significant differences were observed in the number of follicles in duck ovaries following ovarian transplantation. Candidate genes involved in ovarian vascular remodeling and proliferation were screened using RNA-Seq and WGCNA.