Dataset Information

Schmitz2014 - RNA triplex formation

ABSTRACT: Schmitz2014 - RNA triplex formation The model is parameterized using the parameters for gene CCDC3 from Supplementary Table S1. The two miRNAs which form the triplex together with CCDC3 are miR-551b and miR-138. This model is described in the article: Cooperative gene regulation by microRNA pairs and their identification using a computational workflow. Schmitz U, Lai X, Winter F, Wolkenhauer O, Vera J, Gupta SK. Nucleic Acids Res. 2014 Jul; 42(12): 7539-7552 Abstract: MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns. Human RNA triplexes predicted and characterized in this study are organized in a web resource at www.sbi.uni-rostock.de/triplexrna/. This model is hosted on BioModels Database and identified by: BIOMD0000000530. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Felix Winter

PROVIDER: BIOMD0000000530 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000530?filename=BIOMD0000000530-biopax2.owl	Owl
	BIOMD0000000530?filename=BIOMD0000000530-biopax3.owl	Owl
	BIOMD0000000530?filename=BIOMD0000000530.m	Other
	BIOMD0000000530?filename=BIOMD0000000530.pdf	Pdf
	BIOMD0000000530?filename=BIOMD0000000530.png	Other

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Cooperative gene regulation by microRNA pairs and their identification using a computational workflow.

Schmitz Ulf U Lai Xin X Winter Felix F Wolkenhauer Olaf O Vera Julio J Gupta Shailendra K SK

Nucleic acids research 20140529 12

MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of co ...[more]

PMID: 24875477

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Project description:MicroRNAs (miRNAs) play roles in diverse developmental and disease processes. Distinct miRNAs have hundreds to thousands of conserved mRNA binding sites, but typically direct only modest repression via single sites. Cotargeting of individual mRNAs by different miRNAs could potentially achieve stronger and more complex patterns of repression. Comparing target sets of different miRNAs, we identified hundreds of pairs of miRNAs that share more mRNA targets than expected (often by two-fold or more) relative to stringent controls, with particularly high levels of cotargeting among brain-enriched miRNAs. We profiled miRNA expression changes over a cell culture model of neuronal differentiation, and selected the non-homologous cotargeting miRNA pair miR-138 and miR-137 to study functionally. We generated a CRISPR-mediated mir-138 double knockout (DKO) cell line in the murine CAD cell culture model of neuronal differentiation. mir-138 DKO cells lacking both mir-138 loci were unable to differentiate and project neurites following serum withdrawal. Further characterization of the DKO cells by RNA-seq showed that loss of miR-138 resulted in a de-differentiated state compared to WT cells. Specificity of the mir-138 DKO was confirmed by the rescue of neurite growth upon addition of a miR-138 mimic. Interestingly, addition of a miR-137 mimic, but not mimics of other neuronal miRNAs, could also rescue the neurite growth phenotype and allow mir-138 DKO cells to differentiate, and transcriptome profiling revealed similar gene expression changes. Clustering of all cotargeting pairs revealed a group of 9 predominantly brain-enriched miRNAs that share many targets. In reporter assays, subsets of these miRNAs together repressed gene expression by 5- to 10-fold, often exhibiting cooperative repression. Together, our results uncover an unexpected pattern in which combinations of miRNAs collaborate to robustly repress cotargets, and suggest important developmental roles for cotargeting.