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miRNA regulatory circuits in ES cells differentiation: a chemical kinetics modeling approach.

Luo Z, Xu X, Gu P, Lonard D, Gunaratne PH, Cooney AJ, Azencott R - PLoS ONE (2011)

Bottom Line: For each pair (M,G) of potentially interacting miRMA gene M and mRNA gene G, we parameterize our associated kinetic equations by optimizing their fit with microarray data.When this fit is high enough, we validate the pair (M,G) as a highly probable repressive interaction.This approach leads to the computation of a highly selective and drastically reduced list of repressive pairs (M,G) involved in ES cells differentiation.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of Houston, Houston, Texas, United States of America. boluomiduo1@gmail.com

ABSTRACT
MicroRNAs (miRNAs) play an important role in gene regulation for Embryonic Stem cells (ES cells), where they either down-regulate target mRNA genes by degradation or repress protein expression of these mRNA genes by inhibiting translation. Well known tables TargetScan and miRanda may predict quite long lists of potential miRNAs inhibitors for each mRNA gene, and one of our goals was to strongly narrow down the list of mRNA targets potentially repressed by a known large list of 400 miRNAs. Our paper focuses on algorithmic analysis of ES cells microarray data to reliably detect repressive interactions between miRNAs and mRNAs. We model, by chemical kinetics equations, the interaction architectures implementing the two basic silencing processes of miRNAs, namely "direct degradation" or "translation inhibition" of targeted mRNAs. For each pair (M,G) of potentially interacting miRMA gene M and mRNA gene G, we parameterize our associated kinetic equations by optimizing their fit with microarray data. When this fit is high enough, we validate the pair (M,G) as a highly probable repressive interaction. This approach leads to the computation of a highly selective and drastically reduced list of repressive pairs (M,G) involved in ES cells differentiation.

Show MeSH
Transcription-Degradation (Transcr.Degr.) architectures and Translation-Inhibition (Transl.Inhib.) architectures.
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pone-0023263-g003: Transcription-Degradation (Transcr.Degr.) architectures and Translation-Inhibition (Transl.Inhib.) architectures.

Mentions: Hence for each key ES regulatory gene G, we have selected a family Transcr.Degr(G) of small Transcription-Degradation (Transcr.Degr.) architectures (see Figure 3) potentially involving transcription-degradation of G by one or several miRNAs as well as the interactions of G with the main proteins acting as transcriptional factors of G. Combinatorial considerations show that the size of Transcr.Degr.(G) can be quite large (see below).


miRNA regulatory circuits in ES cells differentiation: a chemical kinetics modeling approach.

Luo Z, Xu X, Gu P, Lonard D, Gunaratne PH, Cooney AJ, Azencott R - PLoS ONE (2011)

Transcription-Degradation (Transcr.Degr.) architectures and Translation-Inhibition (Transl.Inhib.) architectures.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3198445&req=5

pone-0023263-g003: Transcription-Degradation (Transcr.Degr.) architectures and Translation-Inhibition (Transl.Inhib.) architectures.
Mentions: Hence for each key ES regulatory gene G, we have selected a family Transcr.Degr(G) of small Transcription-Degradation (Transcr.Degr.) architectures (see Figure 3) potentially involving transcription-degradation of G by one or several miRNAs as well as the interactions of G with the main proteins acting as transcriptional factors of G. Combinatorial considerations show that the size of Transcr.Degr.(G) can be quite large (see below).

Bottom Line: For each pair (M,G) of potentially interacting miRMA gene M and mRNA gene G, we parameterize our associated kinetic equations by optimizing their fit with microarray data.When this fit is high enough, we validate the pair (M,G) as a highly probable repressive interaction.This approach leads to the computation of a highly selective and drastically reduced list of repressive pairs (M,G) involved in ES cells differentiation.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of Houston, Houston, Texas, United States of America. boluomiduo1@gmail.com

ABSTRACT
MicroRNAs (miRNAs) play an important role in gene regulation for Embryonic Stem cells (ES cells), where they either down-regulate target mRNA genes by degradation or repress protein expression of these mRNA genes by inhibiting translation. Well known tables TargetScan and miRanda may predict quite long lists of potential miRNAs inhibitors for each mRNA gene, and one of our goals was to strongly narrow down the list of mRNA targets potentially repressed by a known large list of 400 miRNAs. Our paper focuses on algorithmic analysis of ES cells microarray data to reliably detect repressive interactions between miRNAs and mRNAs. We model, by chemical kinetics equations, the interaction architectures implementing the two basic silencing processes of miRNAs, namely "direct degradation" or "translation inhibition" of targeted mRNAs. For each pair (M,G) of potentially interacting miRMA gene M and mRNA gene G, we parameterize our associated kinetic equations by optimizing their fit with microarray data. When this fit is high enough, we validate the pair (M,G) as a highly probable repressive interaction. This approach leads to the computation of a highly selective and drastically reduced list of repressive pairs (M,G) involved in ES cells differentiation.

Show MeSH