Whole-transcriptome sequencing reveals key biomarkers and pathways in renal fibrosis

Abstract To systematically delineate the transcriptomic landscape of progressive renal fibrosis and identify its critical biomarkers using a systems biology approach, we performed whole-transcriptome sequencing employing a mouse model with fibrotic kidneys caused by Unilateral Ureteral Obstruction (UUO) at three distinct time points (After 3, 7, and 14 days of UUO). Subsequently, gene set enrichment analysis (GSEA) and differential expression analysis was independently carried out on the UUO and sham groups, this was followed by an analysis predicting functional interactions to form a network of competing endogenous RNA (ceRNA) complexes for the purpose of identifying significant biomarkers. Moreover, multiple Gene Expression Omnibus (GEO) datasets along with sequential quantitative real-time PCR (qPCR) experiments were carried out to validate the results. Overall, 876 messenger RNAs with differential expression (dif-mRNAs), 53 microRNAs with differential expression (dif-miRNAs) and 296 long non-coding RNAs with differential expression (dif-lncRNAs) sustained differential expression throughout the emergence and advancement of renal fibrosis. Enrichment analysis on all detected genes, dif-mRNAs, PPI network module genes, and hub genes, along with those genes individually related to dif-miRNA and dif-lncRNA, all identified functions pertained to the cell cycle. A large number of dif-mRNAs and dif-miRNAs have been successfully validated by GEO data. Notably, Kif20a , Cep55 , Mki67 , Morrbid , and Dnm3os are upregulated and significantly enriched nodes in the ceRNA network. Particularly, miR-30e-5p is downregulated, prominently featured in the ceRNA network, and selectively expressed in the kidney. This downregulation is also reflected in plasma and urine, aligning with the renal tissue findings. In summary, Kif20a , Cep55 , Mki67 , Morrbid, and Dnm3os , along with miR-30e-5p, may be pivotal in driving progressive renal fibrosis and have strong potential as clinical biomarkers.