How a cell decides its own fate: a single-cell view of molecular mechanisms and dynamics of cell-type specification.
computational models
developmental biology
epigenomics
eukaryotic gene expression
transcriptomics
Journal
Biochemical Society transactions
ISSN: 1470-8752
Titre abrégé: Biochem Soc Trans
Pays: England
ID NLM: 7506897
Informations de publication
Date de publication:
17 12 2021
17 12 2021
Historique:
received:
13
08
2021
revised:
06
11
2021
accepted:
08
11
2021
pubmed:
3
12
2021
medline:
2
4
2022
entrez:
2
12
2021
Statut:
ppublish
Résumé
On its path from a fertilized egg to one of the many cell types in a multicellular organism, a cell turns the blank canvas of its early embryonic state into a molecular profile fine-tuned to achieve a vital organismal function. This remarkable transformation emerges from the interplay between dynamically changing external signals, the cell's internal, variable state, and tremendously complex molecular machinery; we are only beginning to understand. Recently developed single-cell omics techniques have started to provide an unprecedented, comprehensive view of the molecular changes during cell-type specification and promise to reveal the underlying gene regulatory mechanism. The exponentially increasing amount of quantitative molecular data being created at the moment is slated to inform predictive, mathematical models. Such models can suggest novel ways to manipulate cell types experimentally, which has important biomedical applications. This review is meant to give the reader a starting point to participate in this exciting phase of molecular developmental biology. We first introduce some of the principal molecular players involved in cell-type specification and discuss the important organizing ability of biomolecular condensates, which has been discovered recently. We then review some of the most important single-cell omics methods and relevant findings they produced. We devote special attention to the dynamics of the molecular changes and discuss methods to measure them, most importantly lineage tracing. Finally, we introduce a conceptual framework that connects all molecular agents in a mathematical model and helps us make sense of the experimental data.
Identifiants
pubmed: 34854897
pii: 230359
doi: 10.1042/BST20210135
pmc: PMC8786291
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
2509-2525Informations de copyright
© 2021 The Author(s).
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