Lineages of embryonic stem cells show non-Markovian state transitions.

Cell biology Developmental biology Embryology Stem cells research Systems and computational biology

Journal

iScience
ISSN: 2589-0042
Titre abrégé: iScience
Pays: United States
ID NLM: 101724038

Informations de publication

Date de publication:
20 Aug 2021
Historique:
received: 30 11 2020
revised: 13 06 2021
accepted: 15 07 2021
entrez: 17 8 2021
pubmed: 18 8 2021
medline: 18 8 2021
Statut: epublish

Résumé

Pluripotent embryonic stem cells (ESCs) constitute the cell types of the adult vertebrate through a series of developmental state transitions. These states can be defined by expression levels of marker genes, such as Nanog and Sox2. In culture, ESCs reversibly transition between states. However, whether ESCs retain memory of their previous states or transition in a memoryless (Markovian) process remains relatively unknown. Here, we show some highly dynamic lineages of ESCs do not exhibit the Markovian property: their previous states and kin relations influence future choices. Unexpectedly, the distribution of lineages across their composition between states is constant over time, contrasting with the predictions of a Markov model. Additionally, highly dynamic ESC lineages show skewed cell fate distributions after retinoic acid differentiation. Together, these data suggest ESC lineage is an important variable governing future cell states, with implications for stem cell function and development.

Identifiants

pubmed: 34401663
doi: 10.1016/j.isci.2021.102879
pii: S2589-0042(21)00847-6
pmc: PMC8353490
doi:

Types de publication

Journal Article

Langues

eng

Pagination

102879

Subventions

Organisme : NCI NIH HHS
ID : F30 CA260739
Pays : United States
Organisme : NCI NIH HHS
ID : K08 CA237856
Pays : United States

Informations de copyright

© 2021 The Author(s).

Déclaration de conflit d'intérêts

The authors declare no competing interests.

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Auteurs

Tee Udomlumleart (T)

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.

Sofia Hu (S)

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
Harvard-MIT MD PhD Program, Harvard Medical School, Boston, MA 02115, USA.

Salil Garg (S)

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA.

Classifications MeSH