Fig. 4

Loss of Ranbp3l induces massive changes in gene expression representative of clinical RCC. A Hierarchical clustering of altered samples based on the FPKM values. Cluster analysis was performed using all significant regulated genes in R1 cells. Blue to red represents lower to higher expression. B The list of differentially expressed genes between Scr and R1 mpkCCD cells cultivated under 300 and under 600 mosmol/kg were analyzed for enrichment of KEGG pathways. The top 10 enriched pathways are presented here. (C) Gene set enrichment analysis (GSEA) of RNA-Seq results shows induction of EMT and TGF-β pathways. D Venn diagram showing the overlap of 1771 genes with equally altered gene expression at 300 and 600 mosmol/kg in R1 cell clones. E GSEA of deregulated genes showing an enrichment within the KEGG Renal Cell Carcinoma pathway. F List of regulated genes with a log₂ fold change of 3 or higher − 3 or lower and a FPKM value higher than 10 were compared with genes that have a prognostic impact on patient’s outcome with renal cell carcinomas (RCC) from the human pathology atlas. Unfavorable genes are indicated in yellow while favorable genes are blue. (G, H) Mean log₂ gene signature expression of top upregulated (not including ADGRA2) (G) and top downregulated RCC biomarkers (H) in RCC subtypes KIRC (red), KICH (blue) and KIRP (yellow) samples compared to normal tissue (N, grey). Values were analyzed using a student’s-T test and are represented in a whiskers 1–99 percentile plot, n.s. > 0.05, *, p < 0.05, **, p < 0.01, ***, p < 0.001.1-way ANOVA. Data was obtained from the TCGA database [32]. I-K Principal component (PC) analyses and the corresponding percentage of variances of the top 30 downregulated (I), top 30 upregulated (J) genes and both gene sets together (K)