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Updated: Jul 16, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
Published on: July 29, 2022
Dynamic measure of gene co-regulation
L Farina1, A De Santis, G Morelli
1Dipartimento di Informatica e Sistemistica Antonio Ruberti, Università di Roma La Sapienza, Via Eudossiana 18, Rome 00184, Italy. lorenzo.farina@uniroma1.it
Abstract:
Gene expression is to a large extent controlled at the level of mRNA accumulation. Genes whose products function together are likely under a common regulatory system (e.g., signal transduction pathways, sets of regulatory proteins) such that they are expressed in a coordinated manner. This property has been frequently used in the analysis of genome-wide expression data, as the experimental observation that a group of genes is co-expressed frequently implies that the genes share a common regulatory mechanism. The authors have investigated the situation in which dissimilarity in gene-expression time profiles may still result from the presence of the same regulatory signal, as in the case of common transcription factors. To this aim, a dynamic model that takes into account the effect of specific mRNA degradation on the shape of gene-expression time series has been developed, and the concept of 'dynamically co-regulated' genes has accordingly been introduced as the goodness-of-fit to such a model (called dynamic R2). The statistical analysis of dynamic R2 over a number of different experimental data sets and organisms shows that the presence of dynamically co-regulated genes is by far more significant than that expected from the randomised data. Furthermore, as an example of the usefulness of the proposed method, genome-wide yeast measurements such as cell-cycle time series and transcription factors targets data, were used to prove that dynamic co-regulation is statistically related to the presence of common transcription factor(s). This latter property is very useful when trying to infer computational indications of co-regulation for not-yet annotated genes that do not display a co-expression pattern.
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