Boolean modelling reveals new regulatory connections between transcription factors orchestrating the development of the ventral spinal cord.

Anna Lovrics, Yu Gao, Bianka Juhász, István Bock, Helen M. Byrne, András Dinnyés, Krisztián A Kovács

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


We have assembled a network of cell-fate determining transcription factors that play a key role in the specification of the ventral neuronal subtypes of the spinal cord on the basis of published transcriptional interactions. Asynchronous Boolean modelling of the network was used to compare simulation results with reported experimental observations. Such comparison highlighted the need to include additional regulatory connections in order to obtain the fixed point attractors of the model associated with the five known progenitor cell types located in the ventral spinal cord. The revised gene regulatory network reproduced previously observed cell state switches between progenitor cells observed in knock-out animal models or in experiments where the transcription factors were overexpressed. Furthermore the network predicted the inhibition of Irx3 by Nkx2.2 and this prediction was tested experimentally. Our results provide evidence for the existence of an as yet undescribed inhibitory connection which could potentially have significance beyond the ventral spinal cord. The work presented in this paper demonstrates the strength of Boolean modelling for identifying gene regulatory networks.
Original languageEnglish (US)
Pages (from-to)e111430
JournalPLoS ONE
Issue number11
StatePublished - Nov 14 2014
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: This publication was based on work supported in part by IDPbyNMR, PluriSys, InduStem, RESOLVE, EpiHealth, Stem-Cam, ANISTEM (grant agreement numbers PITN-GA-2010-264257, HEALTH-F4-2009-223485, PIAP-GA-2008-230675, FP7-HEALTH-F4-2008-202047, HEALTH-2012-F2-278418, PIAP-GA-2009-251186, PIAPP-GA-2011-286264) projects funded by the EC Seventh Framework Programme, Research Centre of Excellence, 8526-5/2014/TUDPOL, Award No. KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST) and the IST FELLOWSHIP awarded to Krisztian A Kovacs (Project: P IST EU01 under REA grant agreement no 291734). Al, YG, BJ and KK were affiliated to Biotalentum Ltd. IB and AD are still affiliated to Biotalentum Ltd, and received salary from them to support this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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