Dataset Information

Optimal Decoding of Cellular Identities in a Genetic Network.

ABSTRACT: In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy.

SUBMITTER: Petkova MD

PROVIDER: S-EPMC6526179 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Optimal Decoding of Cellular Identities in a Genetic Network.

Petkova Mariela D MD Tkačik Gašper G Bialek William W Wieschaus Eric F EF Gregor Thomas T

Cell 20190131 4

In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. ...[more]

PMID: 30712870

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Dataset Information

Optimal Decoding of Cellular Identities in a Genetic Network.

Publications

Optimal Decoding of Cellular Identities in a Genetic Network.

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