Dataset Information

Turnover and activity-dependent transcriptional control of NompC in the Drosophila ear.

ABSTRACT: Across their lives, biological sensors maintain near-constant functional outputs despite countless exogenous and endogenous perturbations. This sensory homeostasis is the product of multiple dynamic equilibria, the breakdown of which contributes to age-related decline. The mechanisms of homeostatic maintenance, however, are still poorly understood. The ears of vertebrates and insects are characterized by exquisite sensitivities but also by marked functional vulnerabilities. Being under the permanent load of thermal and acoustic noise, auditory transducer channels exemplify the homeostatic challenge. We show that (1) NompC-dependent mechanotransducers in the ear of the fruit fly Drosophila melanogaster undergo continual replacement with estimated turnover times of 9.1 hr; (2) a de novo synthesis of NompC can restore transducer function in the adult ears of congenitally hearing-impaired flies; (3) key components of the auditory transduction chain, including NompC, are under activity-dependent transcriptional control, likely forming a transducer-operated mechanosensory gain control system that extends beyond hearing organs.

SUBMITTER: Boyd-Gibbins N

PROVIDER: S-EPMC8134069 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Turnover and activity-dependent transcriptional control of NompC in the <i>Drosophila</i> ear.

Boyd-Gibbins Nicholas N Tardieu Camille H CH Blunskyte Modesta M Kirkwood Nerissa N Somers Jason J Albert Joerg T JT

iScience 20210429 5

Across their lives, biological sensors maintain near-constant functional outputs despite countless exogenous and endogenous perturbations. This sensory homeostasis is the product of multiple dynamic equilibria, the breakdown of which contributes to age-related decline. The mechanisms of homeostatic maintenance, however, are still poorly understood. The ears of vertebrates and insects are characterized by exquisite sensitivities but also by marked functional vulnerabilities. Being under the perma ...[more]

PMID: 34027326

Similar Datasets

Project description:The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks.

Dataset Information

Turnover and activity-dependent transcriptional control of NompC in the Drosophila ear.

Publications

Turnover and activity-dependent transcriptional control of NompC in the <i>Drosophila</i> ear.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Turnover and activity-dependent transcriptional control of NompC in the Drosophila ear.

Publications

Turnover and activity-dependent transcriptional control of NompC in the &lt;i&gt;Drosophila&lt;/i&gt; ear.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Turnover and activity-dependent transcriptional control of NompC in the <i>Drosophila</i> ear.