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Carsten Peterson

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Haematopoietic stem cells : Entropic landscapes of differentiation

Author

  • K. Wiesner
  • J. Teles
  • M. Hartnor
  • C. Peterson

Summary, in English

The metaphor of a potential epigenetic differentiation landscape broadly suggests that during differentiation a stem cell approaches a stable equilibrium state from a higher free energy towards a stable equilibrium state which represents the final cell type. It has been conjectured that there is an analogy to the concept of entropy in statistical mechanics. In this context, in the undifferentiated state, the entropy would be large since fewer constraints exist on the gene expression programmes of the cell. As differentiation progresses, gene expression programmes become more and more constrained and thus the entropy would be expected to decrease. In order to assess these predictions, we compute the Shannon entropy for time-resolved single-cell gene expression data in two different experimental set-ups of haematopoietic differentiation. We find that the behaviour of this entropy measure is in contrast to these predictions. In particular, we find that the Shannon entropy is not a decreasing function of developmental pseudo-time but instead it increases towards the time point of commitment before decreasing again. This behaviour is consistent with an increase in gene expression disorder observed in populations sampled at the time point of commitment. Single cells in these populations exhibit different combinations of regulator activity that suggest the presence of multiple configurations of a potential differentiation network as a result of multiple entry points into the committed state.

Department/s

  • Computational Biology and Biological Physics - Has been reorganised

Publishing year

2018-12-06

Language

English

Publication/Series

Interface Focus

Volume

8

Issue

6

Document type

Journal article

Publisher

Royal Society Publishing

Topic

  • Bioinformatics (Computational Biology)
  • Other Physics Topics
  • Cell Biology

Keywords

  • Entropy
  • Shannon information theory
  • Stem cell differentiation

Status

Published

ISBN/ISSN/Other

  • ISSN: 2042-8898