Parallel analysis of mRNA and microRNA microarray profiles to explore functional regulatory patterns in polycystic kidney disease: using PKD/Mhm rat model

Abstract

Autosomal polycystic kidney disease (ADPKD) is a frequent monogenic renal disease, characterised by fluid-filled cysts that are thought to result from multiple deregulated pathways such as cell proliferation and apoptosis. MicroRNAs (miRNAs) are small non-coding RNAs that regulate the expression of many genes associated with such biological processes and human pathologies. To explore the possible regulatory role of miRNAs in PKD, the PKD/Mhm (cy/+) rat, served as a model to study human ADPKD. A parallel microarray-based approach was conducted to profile the expression changes of mRNAs and miRNAs in PKD/Mhm rats. 1,573 up- and 1,760 down-regulated genes were differentially expressed in PKD/Mhm. These genes are associated with 17 pathways (such as focal adhesion, cell cycle, ECM-receptor interaction, DNA replication and metabolic pathways) and 47 (e.g., cell proliferation, Wnt and Tgfβ signaling) Gene Ontologies. Furthermore, we found the similar expression patterns of deregulated genes between PKD/Mhm (cy/+) rat and human ADPKD, PKD1(L3/L3), PKD1(-/-), Hnf1α-deficient, and Glis2(lacZ/lacZ) models. Additionally, several differentially regulated genes were noted to be target hubs for miRNAs. We also obtained 8 significantly up-regulated miRNAs (rno-miR-199a-5p, -214, -146b, -21, -34a, -132, -31 and -503) in diseased kidneys of PKD/Mhm rats. Additionally, the binding site overrepresentation and pathway enrichment analyses were accomplished on the putative targets of these 8 miRNAs. 7 out of these 8 miRNAs and their possible interactions have not been previously described in ADPKD. We have shown a strong overlap of functional patterns (pathways) between deregulated miRNAs and mRNAs in the PKD/Mhm (cy/+) rat model. Our findings suggest that several miRNAs may be associated in regulating pathways in ADPKD. We further describe novel miRNAs and their possible targets in ADPKD, which will open new avenues to understand the pathogenesis of human ADPKD. Furthermore they could serve as a useful resource for anti-fibrotic therapeutics.

Figure 1. Systematic workflow to explore functional regulatory patterns in PKD.

Figure 2. Differential expression of top 30 genes in PKD and control animals.

The heatmap was produced by clustering the data matrix of top 30 genes using Pearson correlation. The gene clustering tree is shown on the left and the sample clustering tree is shown on the top. The other information such as fold change expression, p-value, gene symbol and involvement are given on the right. The samples are broadly divided into two groups, healthy (control) and PKD. The color scale shown at the top illustrates the relative expression level of the indicated genes across all samples.

Figure 3. Overview of fold changes of miRNAs versus a measure of statistical significance.

The volcano plot shows the -log₁₀ (p-value) on the y-axis and the fold change (log₂) on the x-axis. A cut-off [-log₁₀ (p-value) = 1.86] was considered to determine differentially expressed miRNAs between diseased and health (control) animals. Seven miRNAs i.e. rno-miR-146b, -132, -21, -503, -199a-5p, -214 and -34a were found to be significantly up-regulated in diseased animals with a fold change ≥0.5 with significant p-value ≤0.01.

Figure 4. TaqMan assays for miRNAs.

The figure shows high abundance of transcripts of rno-miR-146b, -199a-5p, -214 and -31 in PKD/Mhm (cy/+) rat model as observed on microarrays. ‘***’ indicates for p-value <0.0001. The black and white box plots represent cystic and healthy kidneys.