Spatiotemporal control of gene expression boundaries using a feedforward loop

• Published in: Developmental dynamics Vol. 249; no. 3; pp. 369 - 382
• Main Authors: Bandodkar, Prasad U., Al Asafen, Hadel, Reeves, Gregory T.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01-03-2020; Wiley Subscription Services, Inc
• Subjects: Animals; Body Patterning - genetics; Body Patterning - physiology; Boundaries; Computer networks; Control theory; dorsal morphogen; Drosophila embryo; Drosophila melanogaster; Drosophila Proteins - genetics; Drosophila Proteins - metabolism; Embryo, Nonmammalian - metabolism; Embryos; Feedforward control; feedforward loop; Fruit flies; Gene expression; gene expression model; Gene Expression Regulation, Developmental - genetics; Gene Expression Regulation, Developmental - physiology; Homology; NF-kappa B - metabolism; Parameterization; Pattern formation; Signal Transduction - genetics; Signal Transduction - physiology; spatiotemporal dynamics; transcription factor; Twist; Variation; Zelda; Twist; gene expression model; transcription factor; feedforward loop; Drosophila embryo; Zelda; dorsal morphogen; spatiotemporal dynamics
• ISSN: 1058-8388; 1097-0177
• DOI: 10.1002/dvdy.150

Background
A feedforward loop (FFL) is commonly observed in several biological networks. The FFL network motif has been mostly studied with respect to variation of the input signal in time, with only a few studies of FFL activity in a spatially distributed system such as morphogen‐mediated tissue patterning. However, most morphogen gradients also evolve in time.
Results
We studied the spatiotemporal behavior of a coherent FFL in two contexts: (a) a generic, oscillating morphogen gradient and (b) the dorsal‐ventral patterning of the early Drosophila embryo by a gradient of the NF‐κB homolog dorsal with its early target Twist. In both models, we found features in the dynamics of the intermediate node—phase difference and noise filtering—that were largely independent of the parameterization of the models, and thus were functions of the structure of the FFL itself. In the dorsal gradient model, we also found that proper target gene expression was not possible without including the effect of maternal pioneer factor Zelda.
Conclusions
An FFL buffers fluctuation to changes in the morphogen signal ensuring stable gene expression boundaries.
Key Findings
A phase difference between the morphogen signal and intermediate node results in a stable signal.
Intermediate node acts as a noise filter.
Proper target gene expression of the Dorsal system needs the inclusion of the effect of pioneer factor Zelda.