An oracle predicts regulators of cell identity

Farrell, Jeffrey A.

doi:10.1038/d41586-023-00251-6

NEWS AND VIEWS
08 February 2023

An oracle predicts regulators of cell identity

A computational tool called CellOracle can predict how networks of genes interact to program cell identity during embryonic development. The tool should help to hone efforts to understand how development is regulated.

Jeffrey A. Farrell⁰

Jeffrey A. Farrell
1. Jeffrey A. Farrell is in the Division of Developmental Biology, NICHD Intramural Research Program, Bethesda, Maryland 20814, USA.
View author publications

You can also search for this author in PubMed Google Scholar

Access through your institution

Buy or subscribe

As an animal develops, each of its thousands or even trillions of cells must be programmed to adopt one of many possible cell identities. This programming is controlled by a group of proteins and the genes that encode them, which are collectively known as developmental regulators. Writing in Nature, Kamimoto et al.¹ present a computational approach to predict the shifts in cell identity that will occur if levels of individual developmental regulators are altered. Their systematic approach promises to help researchers determine the regulators most worthy of further study, saving valuable resources and suggesting biological phenomena that might previously have been missed.

Access options

Access through your institution

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Nature 614, 630-632 (2023)

doi: https://doi.org/10.1038/d41586-023-00251-6

References

Kamimoto, K. et al. Nature 614, 742–751 (2023).
Article Google Scholar
Davidson, E. H. et al. Science 296, 1669–1678 (2002).
Article Google Scholar
Simões-Costa, M. & Bronner, M. E. Development 142, 242–257 (2015).
Article PubMed Google Scholar
Nguyen, H., Tran, D., Tran, B., Pehlivan, B. & Nguyen, T. Brief. Bioinform. 22, bbaa190 (2021).
Article PubMed Google Scholar
Halpern, M. E. et al. Development 121, 4257–4264 (1995).
Article PubMed Google Scholar
Wontakal, S. N. et al. PLoS Genet. 7, e1001392 (2011).
Article PubMed Google Scholar
Moreau-Gachelin, F. M., Tavitian, A. & Tambourin, P. Nature 331, 277–280 (1988).
Article Google Scholar
Dal-Pra, S., Thisse, C. & Thisse, B. Dev. Biol. 350, 484–495 (2011).
Article PubMed Google Scholar
Seiliez, I., Thisse, B. & Thisse, C. Dev. Biol. 290, 152–163 (2006).
Article PubMed Google Scholar
Bravo, C. et al. Preprint at bioRxiv https://doi.org/10.1101/2022.08.19.504505 (2022).
Kamimoto, K. et al. Stem Cell Rep. 18, 97–112 (2023).
Article Google Scholar
Chopp, L. B. et al. Immunity 53, 1182–1201 (2020).
Article PubMed Google Scholar
Magaletta, M. E. et al. Nature Commun. 13, 457 (2022).
Article PubMed Google Scholar
Ravi, V. M. et al. Nature Commun. 13, 925 (2022).
Article PubMed Google Scholar
Herpelinck, T. et al. Preprint at bioRxiv https://doi.org/10.1101/2022.03.14.484345 (2022).
Argelaguet, R. et al. Preprint at biorxiv https://doi.org/10.1101/2022.06.15.496239 (2022).