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A multi-stage stochastic model of regulatory control in pluripotentstem cells

Applicant Dr. Carsten Marr
Subject Area Bioinformatics and Theoretical Biology
Term Funded in 2011
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 197154629
 
Final Report Year 2012

Final Report Abstract

The maintenance and loss of pluripotency of mouse embryonic stem cells (mESCs) is believed to be controlled by the interaction of a handful of key pluripotency players – with the regulatory details of those players and their transcriptional dynamics barely understood. During my six month visit in the labs of Ian Chambers and Peter Swain, I approached this problem from two perspectives: (i) To get insights into the dynamics of DNA expression I quantified microscopy images of mESCs after RNA fluorescence in situ hybridization (FISH) with probes agains full-length transcripts of the genes Nanog, Esrrb, and Oct4. An analysis of active alleles reveals information about DNA localization within the nucleus, number of active alleles, and correlated activation of the two alleles. We find that for all three genes, the activation of the second allele is always at least twice as fast as the activation of the first allele. This might stem from a cooperative transcriptional effect, or indicate a regulatory interaction. In subsequent work, we will compare predictions from alternative models with experimental data, namely the heterogeneous Nanog protein expression and the activity of alleles, and propose experiments to further discriminate molecular mechanisms. (ii) Model selection requires the efficient calculation of parameter and model likelihoods. To that end, I worked on the analytical description of stochastic gene expression models together with Peter Swain and Nikola Popovic, a lecturer at the School of Mathematics. Until the end of my stay, we have obtained a systematic expansion procedure for the distribution function of proteins that can in principle be taken to any order, both in the time-dependent and the stationary model, thus improving on the results in the literature. In future work, we will develop an analogous procedure for more complicated expression models, explicitly including an mRNA step, refractory DNA state, and bursting. In total, the fellowship allowed me to embark on two projects which will be continued in the future. The developed quantification and analysis pipeline can be used to unravel the regulation of the pluripotency factors in more advanced experimental settings. The analytical expression for the propagators will enable us to calculate the likelihood of models from experimentally observed time series – resulting in a substantial increase of the accuracy and usability of the available fitting algorithms. The methods and expertise acquired during the fellowship will also be applicable to the current projects at the Helmholtz Center Munich.

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