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

Authors: Jacqueline Ho; Jordan A. Kreidberg; Jordan A. Kreidberg; Shan Qin; Jing Zhou; Priyanka Pandey;

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

Abstract

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.

Keywords

570, Transcription, Genetic, 610, Mice, Transgenic, Models, Biological, Polymerase Chain Reaction, Mice, Structural Biology, Modelling and Simulation, Animals, Humans, Diabetic Nephropathies, Molecular Biology, Polycystic Kidney Diseases, Models, Genetic, Applied Mathematics, Gene Expression Profiling, Systems Biology, MicroRNAs, Mutation, Research Article, Genome-Wide Association Study, Signal Transduction

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    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
77
Top 10%
Top 10%
Top 10%
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gold