Skip to Main content Skip to Navigation
Journal articles

Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to Listeria monocytogenes

Abstract : Automatic de novo identification of the main regulons of a bacterium from genome and transcriptome data remains a challenge. To address this task, we propose a statistical model that can use information on exact positions of the transcription start sites and condition-dependent expression profiles. The central idea of this model is to improve the probabilistic representation of the promoter DNA sequences by incorporating covariates summarizing expression profiles (e.g. coordinates in projection spaces or hierarchical clustering trees). A dedicated trans-dimensional Markov chain Monte Carlo algorithm adjusts the width and palindromic properties of the corresponding position-weight matrices, the number of parameters to describe exact position relative to the transcription start site, and chooses the expression covariates relevant for each motif. All parameters are estimated simultaneously, for many motifs and many expression covariates. The method is applied to a dataset of transcription start sites and expression profiles available for Listeria monocytogenes . The results validate the approach and provide a new global view of the transcription regulatory network of this important pathogen. Remarkably, a previously unreported motif is found in promoter regions of ribosomal protein genes, suggesting a role in the regulation of growth.
Document type :
Journal articles
Complete list of metadata

https://hal.inrae.fr/hal-03270230
Contributor : Roselyne Tâche <>
Submitted on : Thursday, June 24, 2021 - 4:03:42 PM
Last modification on : Saturday, July 17, 2021 - 3:50:33 AM

File

2021_Sultan_The Royal Society....
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Ibrahim Sultan, Vincent Fromion, Sophie Schbath, Pierre Nicolas. Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to Listeria monocytogenes. Journal of the Royal Society Interface, the Royal Society, 2020, 17 (171), pp.20200600. ⟨10.1098/rsif.2020.0600⟩. ⟨hal-03270230⟩

Share

Metrics

Record views

8

Files downloads

6