Binary Expression Enhances Reliability of Messaging in Gene Networks

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art_GAMA_Binary_Expression_Enhances_Reliability_of_Messaging_in_Gene_2020.PDF (1.29 MB)
Citações na Scopus
2
Tipo de produção
article
Data de publicação
2020
DOI
Scopus
Web of Science
Título da Revista
ISSN da Revista
Título do Volume
Editora
MDPI
Autores
BALAZSI, Gabor
Citação
ENTROPY, v.22, n.4, article ID 479, 18p, 2020
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
The promoter state of a gene and its expression levels are modulated by the amounts of transcription factors interacting with its regulatory regions. Hence, one may interpret a gene network as a communicating system in which the state of the promoter of a gene (the source) is communicated by the amounts of transcription factors that it expresses (the message) to modulate the state of the promoter and expression levels of another gene (the receptor). The reliability of the gene network dynamics can be quantified by Shannon's entropy of the message and the mutual information between the message and the promoter state. Here we consider a stochastic model for a binary gene and use its exact steady state solutions to calculate the entropy and mutual information. We show that a slow switching promoter with long and equally standing ON and OFF states maximizes the mutual information and reduces entropy. That is a binary gene expression regime generating a high variance message governed by a bimodal probability distribution with peaks of the same height. Our results indicate that Shannon's theory can be a powerful framework for understanding how bursty gene expression conciliates with the striking spatio-temporal precision exhibited in pattern formation of developing organisms.
Palavras-chave
noise in gene networks, binary gene regulation, bursty gene expression, Shannon theory, stochastic modeling
URI
https://observatorio.fm.usp.br/handle/OPI/37301
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Coleções
Artigos e Materiais de Revistas Científicas - LIM/24