Precision in a rush: Trade-offs between reproducibility and steepness of the hunchback expression pattern - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue PLoS Computational Biology Année : 2018

Precision in a rush: Trade-offs between reproducibility and steepness of the hunchback expression pattern

Résumé

Fly development amazes us by the precision and reproducibility of gene expression, especially since the initial expression patterns are established during very short nuclear cycles. Recent live imaging of hunchback promoter dynamics shows a stable steep binary expression pattern established within the three minute interphase of nuclear cycle 11. Considering expression models of different complexity, we explore the trade-off between the ability of a regulatory system to produce a steep boundary and minimize expression variability between different nuclei. We show how a limited readout time imposed by short developmental cycles affects the gene’s ability to read positional information along the embryo’s anterior posterior axis and express reliably. Comparing our theoretical results to real-time monitoring of the hunchback transcription dynamics in live flies, we discuss possible regulatory strategies, suggesting an important role for additional binding sites, gradients or non-equilibrium binding and modified transcription factor search strategies.
Fichier principal
Vignette du fichier
journal.pcbi.1006513.pdf (1.76 Mo) Télécharger le fichier
Origine : Publication financée par une institution
Loading...

Dates et versions

hal-01949561 , version 1 (10-12-2018)

Identifiants

  • HAL Id : hal-01949561 , version 1

Citer

Huy Tran, Jonathan Desponds, Carmina Angelica Perez Romero, Mathieu Coppey, Cecile Fradin, et al.. Precision in a rush: Trade-offs between reproducibility and steepness of the hunchback expression pattern. PLoS Computational Biology, 2018, 14 (10), pp.e1006513. ⟨hal-01949561⟩
61 Consultations
46 Téléchargements

Partager

Gmail Facebook X LinkedIn More