Armond, Jonathan W., Saha, Krishanu, Rana, Anas A., Oates, Chris J., Jaenisch, Rudolf, Nicodemi, Mario and Mukherjee, Sach (2014) A stochastic model dissects cell states in biological transition processes. Scientific Reports, Volume 4 . Article number 3692. doi:10.1038/srep03692

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Abstract

Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics Q Science > QH Natural history > QH301 Biology
Divisions:	Faculty of Science > Centre for Complexity Science Faculty of Science > Statistics Faculty of Science > Centre for Systems Biology
Library of Congress Subject Headings (LCSH):	Cytology -- Research , Stochastic models, Epigenetics
Journal or Publication Title:	Scientific Reports
Publisher:	Nature Publishing Group
ISSN:	2045-2322
Official Date:	17 January 2014
Dates:	Date Event 17 January 2014 Published
Date of first compliant deposit:	26 December 2015
Volume:	Volume 4
Page Range:	Article number 3692
DOI:	10.1038/srep03692
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Netherlands Organisation for Scientific Research] (NWO)
Grant number:	EP/E501311/1 (EPSRC)

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