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Systems biology approach to identify transcriptome reprogramming and candidate microRNA targets during the progression of polycystic kidney disease.

Pandey P, Qin S, Ho J, Zhou J, Kreidberg JA - BMC Syst Biol (2011)

Bottom Line: We found dysregulation of developmental, metabolic, and signaling pathways (e.g. Wnt, calcium, TGF-β and MAPK) in Pkd1⁻/⁻ kidneys.We have described global transcriptional reprogramming during the progression of PKD in the Pkd1⁻/⁻ model.We propose a model for the cascade of signaling events involved in cyst formation and growth.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medicine, Children's Hospital Boston; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA.

ABSTRACT

Background: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst formation throughout the kidney parenchyma. It is caused by mutations in either of two genes, PKD1 and PKD2. Mice that lack functional Pkd1 (Pkd1⁻/⁻), develop rapidly progressive cystic disease during embryogenesis, and serve as a model to study human ADPKD. Genome wide transcriptome reprogramming and the possible roles of micro-RNAs (miRNAs) that affect the initiation and progression of cyst formation in the Pkd1⁻/⁻ have yet to be studied. miRNAs are small, regulatory non-coding RNAs, implicated in a wide spectrum of biological processes. Their expression levels are altered in several diseases including kidney cancer, diabetic nephropathy and PKD.

Results: We examined the molecular pathways that modulate renal cyst formation and growth in the Pkd1⁻/⁻ model by performing global gene-expression profiling in embryonic kidneys at days 14.5 and 17.5. Gene Ontology and gene set enrichment analysis were used to identify overrepresented signaling pathways in Pkd1⁻/⁻ kidneys. We found dysregulation of developmental, metabolic, and signaling pathways (e.g. Wnt, calcium, TGF-β and MAPK) in Pkd1⁻/⁻ kidneys. Using a comparative transcriptomics approach, we determined similarities and differences with human ADPKD: ~50% overlap at the pathway level among the mis-regulated pathways was observed. By using computational approaches (TargetScan, miRanda, microT and miRDB), we then predicted miRNAs that were suggested to target the differentially expressed mRNAs. Differential expressions of 9 candidate miRNAs, miRs-10a, -30a-5p, -96, -126-5p, -182, -200a, -204, -429 and -488, and 16 genes were confirmed by qPCR. In addition, 14 candidate miRNA:mRNA reciprocal interactions were predicted. Several of the highly regulated genes and pathways were predicted as targets of miRNAs.

Conclusions: We have described global transcriptional reprogramming during the progression of PKD in the Pkd1⁻/⁻ model. We propose a model for the cascade of signaling events involved in cyst formation and growth. Our results suggest that several miRNAs may be involved in regulating signaling pathways in ADPKD. We further describe novel putative miRNA:mRNA signatures in ADPKD, which will provide additional insights into the pathogenesis of this common genetic disease in humans.

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Pathology of Pkd1-/- mouse model at embryonic ages: E14.5 and E17.5. At E14.5 the mutant and WT kidneys are similar. Kidney development in Pkd1-/- mutants appears to proceed normally until E15.5. By E17.5, the kidneys of Pkd1-/- mutants are filled with many large numbers of renal cysts. The rate of cyst development indicates aggressive disease in Pkd1-/- mutants. Hematoxylin/Eosin stained; Scale bar 20x.
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Figure 2: Pathology of Pkd1-/- mouse model at embryonic ages: E14.5 and E17.5. At E14.5 the mutant and WT kidneys are similar. Kidney development in Pkd1-/- mutants appears to proceed normally until E15.5. By E17.5, the kidneys of Pkd1-/- mutants are filled with many large numbers of renal cysts. The rate of cyst development indicates aggressive disease in Pkd1-/- mutants. Hematoxylin/Eosin stained; Scale bar 20x.

Mentions: To study the detailed changes in molecular profiles during the progression of ADPKD, we generated and compared gene expression profiles of Pkd1-/- embryonic kidneys and age-matched WT kidneys at two stages, E14.5 and E17.5 (Figure 1; Additional file 4). Pkd1-/- embryos develop rapidly progressive kidney cysts during embryogenesis, with mutant kidneys showing no cysts at E14.5 and marked cystic changes by E17.5 (Figure 2). Unsupervised hierarchical clustering was able to discriminate WT and mutant kidney samples at both time points (Figure 3). At the same time, the cluster analysis was also able to distinguish changes between E14.5 and E17.5 kidneys (Figure 3). Table 1 shows a summary of number of differentially expressed genes and pathways for all of the comparisons. Genes showing a greater than 2-fold difference in expression between WT and mutant kidneys at E14.5 as well as at E17.5 (empirical Bayes moderated t-statistic, unequal variance, uncorrected p-value ≤0.05), were considered to be differentially expressed whereas in the comparisons of WT kidneys at E14.5 vs E17.5 and Pkd1-/- kidneys at E14.5 vs E17.5, genes with ≥ 2-fold difference in expression at p-value ≤0.05 (corrected for multiple testing by Benjamini-Hochberg method) were considered as differentially expressed. The expression of 454 genes was significantly changed between WT and mutant kidneys at E14.5 (Table 1, Additional file 5) whereas 884 genes were significantly changed at E17.5 between WT and mutant kidneys (Table 1, Additional file 6). The comparison of E14.5 and E17.5 WT kidneys yielded 1189 differentially expressed genes (Additional file 7) whereas 2287 genes were differentially expressed in comparison of Pkd1-/- kidneys at E14.5 vs E17.5 (Table 1, Additional file 8). Comparing differentially expressed genes observed in Pkd1-/- at E14.5 vs E17.5 (2287 genes) and in WT at E14.5 vs E17.5 (1189 genes) identified genes that were specifically changing during development in diseased (Additional file 9) or healthy conditions (Additional file 10) as shown in Figure 4. This comparison also indicated genes that were regulated during aging from E14.5 to E17.5 regardless of the genotype (Figure 4; Additional file 11). These results indicate that maturation accounted for the greatest number of changes in gene expression, more so than the cyst formation. Nevertheless, 1397 genes (Additional file 9) could be identified for which changes in gene expression levels were specific for Pkd1-/- kidneys. Thus, this analysis served to identify a set of genes specifically changing in PKD that can yield insights about the regulation of gene expression during cystogenesis.


Systems biology approach to identify transcriptome reprogramming and candidate microRNA targets during the progression of polycystic kidney disease.

Pandey P, Qin S, Ho J, Zhou J, Kreidberg JA - BMC Syst Biol (2011)

Pathology of Pkd1-/- mouse model at embryonic ages: E14.5 and E17.5. At E14.5 the mutant and WT kidneys are similar. Kidney development in Pkd1-/- mutants appears to proceed normally until E15.5. By E17.5, the kidneys of Pkd1-/- mutants are filled with many large numbers of renal cysts. The rate of cyst development indicates aggressive disease in Pkd1-/- mutants. Hematoxylin/Eosin stained; Scale bar 20x.
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC3111376&req=5

Figure 2: Pathology of Pkd1-/- mouse model at embryonic ages: E14.5 and E17.5. At E14.5 the mutant and WT kidneys are similar. Kidney development in Pkd1-/- mutants appears to proceed normally until E15.5. By E17.5, the kidneys of Pkd1-/- mutants are filled with many large numbers of renal cysts. The rate of cyst development indicates aggressive disease in Pkd1-/- mutants. Hematoxylin/Eosin stained; Scale bar 20x.
Mentions: To study the detailed changes in molecular profiles during the progression of ADPKD, we generated and compared gene expression profiles of Pkd1-/- embryonic kidneys and age-matched WT kidneys at two stages, E14.5 and E17.5 (Figure 1; Additional file 4). Pkd1-/- embryos develop rapidly progressive kidney cysts during embryogenesis, with mutant kidneys showing no cysts at E14.5 and marked cystic changes by E17.5 (Figure 2). Unsupervised hierarchical clustering was able to discriminate WT and mutant kidney samples at both time points (Figure 3). At the same time, the cluster analysis was also able to distinguish changes between E14.5 and E17.5 kidneys (Figure 3). Table 1 shows a summary of number of differentially expressed genes and pathways for all of the comparisons. Genes showing a greater than 2-fold difference in expression between WT and mutant kidneys at E14.5 as well as at E17.5 (empirical Bayes moderated t-statistic, unequal variance, uncorrected p-value ≤0.05), were considered to be differentially expressed whereas in the comparisons of WT kidneys at E14.5 vs E17.5 and Pkd1-/- kidneys at E14.5 vs E17.5, genes with ≥ 2-fold difference in expression at p-value ≤0.05 (corrected for multiple testing by Benjamini-Hochberg method) were considered as differentially expressed. The expression of 454 genes was significantly changed between WT and mutant kidneys at E14.5 (Table 1, Additional file 5) whereas 884 genes were significantly changed at E17.5 between WT and mutant kidneys (Table 1, Additional file 6). The comparison of E14.5 and E17.5 WT kidneys yielded 1189 differentially expressed genes (Additional file 7) whereas 2287 genes were differentially expressed in comparison of Pkd1-/- kidneys at E14.5 vs E17.5 (Table 1, Additional file 8). Comparing differentially expressed genes observed in Pkd1-/- at E14.5 vs E17.5 (2287 genes) and in WT at E14.5 vs E17.5 (1189 genes) identified genes that were specifically changing during development in diseased (Additional file 9) or healthy conditions (Additional file 10) as shown in Figure 4. This comparison also indicated genes that were regulated during aging from E14.5 to E17.5 regardless of the genotype (Figure 4; Additional file 11). These results indicate that maturation accounted for the greatest number of changes in gene expression, more so than the cyst formation. Nevertheless, 1397 genes (Additional file 9) could be identified for which changes in gene expression levels were specific for Pkd1-/- kidneys. Thus, this analysis served to identify a set of genes specifically changing in PKD that can yield insights about the regulation of gene expression during cystogenesis.

Bottom Line: We found dysregulation of developmental, metabolic, and signaling pathways (e.g. Wnt, calcium, TGF-β and MAPK) in Pkd1⁻/⁻ kidneys.We have described global transcriptional reprogramming during the progression of PKD in the Pkd1⁻/⁻ model.We propose a model for the cascade of signaling events involved in cyst formation and growth.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medicine, Children's Hospital Boston; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA.

ABSTRACT

Background: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst formation throughout the kidney parenchyma. It is caused by mutations in either of two genes, PKD1 and PKD2. Mice that lack functional Pkd1 (Pkd1⁻/⁻), develop rapidly progressive cystic disease during embryogenesis, and serve as a model to study human ADPKD. Genome wide transcriptome reprogramming and the possible roles of micro-RNAs (miRNAs) that affect the initiation and progression of cyst formation in the Pkd1⁻/⁻ have yet to be studied. miRNAs are small, regulatory non-coding RNAs, implicated in a wide spectrum of biological processes. Their expression levels are altered in several diseases including kidney cancer, diabetic nephropathy and PKD.

Results: We examined the molecular pathways that modulate renal cyst formation and growth in the Pkd1⁻/⁻ model by performing global gene-expression profiling in embryonic kidneys at days 14.5 and 17.5. Gene Ontology and gene set enrichment analysis were used to identify overrepresented signaling pathways in Pkd1⁻/⁻ kidneys. We found dysregulation of developmental, metabolic, and signaling pathways (e.g. Wnt, calcium, TGF-β and MAPK) in Pkd1⁻/⁻ kidneys. Using a comparative transcriptomics approach, we determined similarities and differences with human ADPKD: ~50% overlap at the pathway level among the mis-regulated pathways was observed. By using computational approaches (TargetScan, miRanda, microT and miRDB), we then predicted miRNAs that were suggested to target the differentially expressed mRNAs. Differential expressions of 9 candidate miRNAs, miRs-10a, -30a-5p, -96, -126-5p, -182, -200a, -204, -429 and -488, and 16 genes were confirmed by qPCR. In addition, 14 candidate miRNA:mRNA reciprocal interactions were predicted. Several of the highly regulated genes and pathways were predicted as targets of miRNAs.

Conclusions: We have described global transcriptional reprogramming during the progression of PKD in the Pkd1⁻/⁻ model. We propose a model for the cascade of signaling events involved in cyst formation and growth. Our results suggest that several miRNAs may be involved in regulating signaling pathways in ADPKD. We further describe novel putative miRNA:mRNA signatures in ADPKD, which will provide additional insights into the pathogenesis of this common genetic disease in humans.

Show MeSH
Related in: MedlinePlus