Details

Autor(en) / Beteiligte

• Petkova, Mariela D.
• Tkačik, Gašper
• Bialek, William
• Wieschaus, Eric F.
• Gregor, Thomas

Titel

Optimal Decoding of Cellular Identities in a Genetic Network

Ist Teil von

• Cell, 2019-02, Vol.176 (4), p.844-855.e15

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2019

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. [Display omitted] •Optimal decoding of gene expression levels can be derived from first principles•Applied to Drosophila gap genes, it specifies individual cells with 1% precision•Decoder correctly predicts downstream events in wild-type and mutant embryos•Molecular logic of gap gene readout must implement nearly optimal computations The information to specify precise cellular identities is present and decoded at the earliest stages of Drosophila development, contrasting with the view that positional information is slowly refined across successive patterning layers.