Dynamic modelling of microRNA regulation during mesenchymal stem cell differentiation

BMC Systems Biology

Everardus J van Zoelen¹  Reinhard Guthke²  Peter Kupfer²  Ana M Sotoca¹  Michael Weber² 

[1] Department of Cell and Applied Biology, Radboud University, Heijendaalseweg 135, 6525 AJ Nijmegen, The Netherlands;Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute, Beutenbergstr. 11a, 07745 Jena, Germany

关键词: Chondrogenesis;    Mesenchymal stem cells;    MicroRNA;    NetGenerator;    Network inference;    Gene regulatory network;   

Others  :  1141815
DOI  :  10.1186/1752-0509-7-124

 received in 2013-03-04, accepted in 2013-10-30,  发布年份 2013

【 摘 要 】

Background

Network inference from gene expression data is a typical approach to reconstruct gene regulatory networks. During chondrogenic differentiation of human mesenchymal stem cells (hMSCs), a complex transcriptional network is active and regulates the temporal differentiation progress. As modulators of transcriptional regulation, microRNAs (miRNAs) play a critical role in stem cell differentiation. Integrated network inference aimes at determining interrelations between miRNAs and mRNAs on the basis of expression data as well as miRNA target predictions. We applied the NetGenerator tool in order to infer an integrated gene regulatory network.

Results

Time series experiments were performed to measure mRNA and miRNA abundances of TGF-beta1+BMP2 stimulated hMSCs. Network nodes were identified by analysing temporal expression changes, miRNA target gene predictions, time series correlation and literature knowledge. Network inference was performed using NetGenerator to reconstruct a dynamical regulatory model based on the measured data and prior knowledge. The resulting model is robust against noise and shows an optimal trade-off between fitting precision and inclusion of prior knowledge. It predicts the influence of miRNAs on the expression of chondrogenic marker genes and therefore proposes novel regulatory relations in differentiation control. By analysing the inferred network, we identified a previously unknown regulatory effect of miR-524-5p on the expression of the transcription factor SOX9 and the chondrogenic marker genes COL2A1, ACAN and COL10A1.

Conclusions

Genome-wide exploration of miRNA-mRNA regulatory relationships is a reasonable approach to identify miRNAs which have so far not been associated with the investigated differentiation process. The NetGenerator tool is able to identify valid gene regulatory networks on the basis of miRNA and mRNA time series data.

【 授权许可】

   
2013 Weber et al.; licensee BioMed Central Ltd.

【 图 表 】

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