Ordered patterning of the sensory system is susceptible to stochastic features of gene expression
Abstract
Sensory neuron numbers and positions are precisely organized to accurately map environmental signals in the brain. This precision emerges from biochemical processes within and between cells that are inherently stochastic. We investigated impact of stochastic gene expression on pattern formation, focusing on senseless (sens), a key determinant of sensory fate in Drosophila. Perturbing microRNA regulation or genomic location of sens produced distinct noise signatures. Noise was greatly enhanced when both sens alleles were present in homologous loci such that each allele was regulated in trans by the other allele. This led to disordered patterning. In contrast, loss of microRNA repression of sens increased protein abundance but not sensory pattern disorder. This suggests that gene expression stochasticity is a critical feature that must be constrained during development to allow rapid yet accurate cell fate resolution.
Data availability
All data generated and analyzed during this study are included in the manuscript and supporting files. Source data is provided for all main figures and computer code for analysis and modeling are available at https://github.com/ritika-giri/stochastic-noise.
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A comprehensive map of insulator elements for the Drosophila genomeNCBI Gene Expression Omnibus, GSE16245.
Article and author information
Author details
Funding
National Institutes of Health (R35GM118144)
- Ritika Giri
- Diana M Posadas
- Hemanth K Potluri
- Richard W Carthew
Simons Foundation (597491)
- Madhav Mani
- Richard W Carthew
National Science Foundation (1764421)
- Madhav Mani
- Richard W Carthew
Pew Charitable Trusts (Pew Latin American Fellows Program)
- Diana M Posadas
Max Planck Society (MPI Funding)
- Dimitrios K Papadopoulos
- Pavel Tomancak
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Giri et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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