Literature DB >> 26986358

Stochastic model for gene transcription on Drosophila melanogaster embryos.

Guilherme N Prata1, José Eduardo M Hornos2, Alexandre F Ramos1,3,4.   

Abstract

We examine immunostaining experimental data for the formation of stripe 2 of even-skipped (eve) transcripts on D. melanogaster embryos. An estimate of the factor converting immunofluorescence intensity units into molecular numbers is given. The analysis of the eve dynamics at the region of stripe 2 suggests that the promoter site of the gene has two distinct regimes: an earlier phase when it is predominantly activated until a critical time when it becomes mainly repressed. That suggests proposing a stochastic binary model for gene transcription on D. melanogaster embryos. Our model has two random variables: the transcripts number and the state of the source of mRNAs given as active or repressed. We are able to reproduce available experimental data for the average number of transcripts. An analysis of the random fluctuations on the number of eves and their consequences on the spatial precision of stripe 2 is presented. We show that the position of the anterior or posterior borders fluctuate around their average position by ∼1% of the embryo length, which is similar to what is found experimentally. The fitting of data by such a simple model suggests that it can be useful to understand the functions of randomness during developmental processes.

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Year:  2016        PMID: 26986358     DOI: 10.1103/PhysRevE.93.022403

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  3 in total

1.  Synthetic enhancer design by in silico compensatory evolution reveals flexibility and constraint in cis-regulation.

Authors:  Kenneth A Barr; Carlos Martinez; Jennifer R Moran; Ah-Ram Kim; Alexandre F Ramos; John Reinitz
Journal:  BMC Syst Biol       Date:  2017-11-29

2.  Transcriptional bursting in Drosophila development: Stochastic dynamics of eve stripe 2 expression.

Authors:  David M Holloway; Alexander V Spirov
Journal:  PLoS One       Date:  2017-04-24       Impact factor: 3.240

Review 3.  Lessons and perspectives for applications of stochastic models in biological and cancer research.

Authors:  Alan U Sabino; Miguel Fs Vasconcelos; Misaki Yamada Sittoni; Willian W Lautenschlager; Alexandre S Queiroga; Mauro Cc Morais; Alexandre F Ramos
Journal:  Clinics (Sao Paulo)       Date:  2018-09-21       Impact factor: 2.365

  3 in total

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