Published November 30, 2022
| Version v1
Publication
Fusion of Domain Knowledge for Dynamic Learning in Transcriptional Networks
Description
A critical challenge of the postgenomic era is to understand how
genes are differentially regulated even when they belong to a given network.
Because the fundamental mechanism controlling gene expression operates at
the level of transcription initiation, computational techniques have been devel oped that identify cis-regulatory features and map such features into differential
expression patterns. The fact that such co-regulated genes may be differentially
regulated suggests that subtle differences in the shared cis-acting regulatory
elements are likely significant. Thus, we carry out an exhaustive description of
cis-acting regulatory features including the orientation, location and number of
binding sites for a regulatory protein, the presence of binding site submotifs, the
class and number of RNA polymerase sites, as well as gene expression data,
which is treated as one feature among many. These features, derived from dif ferent domain sources, are analyzed concurrently, and dynamic relations are re cognized to generate profiles, which are groups of promoters sharing common
features. We apply this method to probe the regulatory networks governed by
the PhoP/PhoQ two-component system in the enteric bacteria Escherichia coli
and Salmonella enterica. Our analysis uncovered novel members of the PhoP
regulon as and the resulting profiles group genes that share underlying biologi cal that characterize the system kinetics. The predictions were experimentally
validated to establish that the PhoP protein uses multiple mechanisms to control
gene transcription and is a central element in a highly connected network.
Abstract
Ministerio de Ciencia y Tecnología BIO2004-0270-EAdditional details
Identifiers
- URL
- https://idus.us.es/handle//11441/139928
- URN
- urn:oai:idus.us.es:11441/139928