Construction of Competing Endogenous RNA Networks Incorporating Transcription Factors to Reveal Differences in Granulosa Cells from Patients with Endometriosis.
Rongfeng WuJunzui LiJingjing LiNingqing ZhangWeidong ZhouLulu RenQionghua ChenYouzhu LiPublished in: Genetic testing and molecular biomarkers (2021)
Purpose: This study aimed to reveal the molecular differences in granulosa cells (GCs) from patients with endometriosis (EM). Methods: RNA sequencing was performed on GCs from patients with EM-related infertility (n = 3) and controls (n = 3). Differentially expressed long noncoding RNAs [differentially expressed lncRNAs (DELs), |log2 FC|>4, false discovery rate (FDR) <0.05] and genes [differentially expressed genes (DEGs), |log2 FC|>1.4, FDR <0.05] in patients with EM-related infertility and controls were screened. Protein-protein interaction (PPI) networks of the DEGs were constructed. Then, mRNA-miRNA-lncRNA pairs based on DEGs and DELs were constructed by comprehensive bioinformatics analyses. In addition, overlapping genes identified from both the PPI and mRNA-miRNA-lncRNA pairs were selected. Finally, a competing endogenous RNA (ceRNA) network incorporating transcription factors (TFs) was constructed. Results: A total of 25,806 lncRNAs and 19,684 mRNAs were detected, and 7 DELs and 46 DEGs were identified. Five hub genes from the PPI network were also identified. A single overlapping gene, NR4A2, from both the PPI network and mRNA-miRNA-lncRNA pairs was identified. Finally, a ceRNA network incorporating TFs, including one mRNA (NR4A2), one miRNA (hsa-miR-217), three lncRNAs (XIST, MCM3AP-AS1, and C17orf51), and five TFs (SRF, POLR2A, NRF1, MNT, and TCF7L2), was successfully constructed. Conclusions: The proposed ceRNA network and the prediction of TFs in GCs from EM-related infertility revealed differences in GCs from patients with EM. Importantly, the novel TFs, lncRNAs, miRNAs, and mRNAs involved in the ceRNA network might provide new insights into the underlying molecular mechanisms of EM-related infertility.
Keyphrases
- genome wide identification
- long non coding rna
- protein protein
- genome wide analysis
- transcription factor
- genome wide
- network analysis
- small molecule
- polycystic ovary syndrome
- single cell
- wastewater treatment
- long noncoding rna
- dna methylation
- gene expression
- oxidative stress
- cell cycle arrest
- high throughput
- induced apoptosis
- signaling pathway
- metabolic syndrome