Sequential logic model deciphers dynamic transciptional control of gene expressions

Zhen Xuan Yeo, Sum Thai Wong, Satya Nanda Vel Arjunan, Vincent Piras, Masaru Tomita, Kumar Selvarajoo, Alessandro Giuliani, Masa Tsuchiya

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Background. Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented, here. Methodology. Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of-dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. Principal Findings. SLM is verified by a set of well studied expression data on endo 16 of Strongylocentrotus purpuratus (sea urchin) during the embryonic midgut development. A dynamic regulatory mechanism for endo 16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. Conclusions/Significatwe. The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet providing rich biological insight. The demonstration of the efficacy of this approach in endo 16 is a promising step for further application of the proposed method.

Original languageEnglish
Article numbere776
JournalPLoS One
Volume2
Issue number8
DOIs
Publication statusPublished - 2007 Aug 22

Fingerprint

Gene expression
dynamic models
Dynamic models
Gene Expression
gene expression
binding sites
Binding Sites
Transcriptional Activation
Genes
Chemical activation
Switches
Strongylocentrotus purpuratus
Cell signaling
Specifications
cell communication
Strongylocentrotus
gene activation
genes
Sea Urchins
Gene Regulatory Networks

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Yeo, Z. X., Wong, S. T., Vel Arjunan, S. N., Piras, V., Tomita, M., Selvarajoo, K., ... Tsuchiya, M. (2007). Sequential logic model deciphers dynamic transciptional control of gene expressions. PLoS One, 2(8), [e776]. https://doi.org/10.1371/journal.pone.0000776

Sequential logic model deciphers dynamic transciptional control of gene expressions. / Yeo, Zhen Xuan; Wong, Sum Thai; Vel Arjunan, Satya Nanda; Piras, Vincent; Tomita, Masaru; Selvarajoo, Kumar; Giuliani, Alessandro; Tsuchiya, Masa.

In: PLoS One, Vol. 2, No. 8, e776, 22.08.2007.

Research output: Contribution to journalArticle

Yeo, ZX, Wong, ST, Vel Arjunan, SN, Piras, V, Tomita, M, Selvarajoo, K, Giuliani, A & Tsuchiya, M 2007, 'Sequential logic model deciphers dynamic transciptional control of gene expressions', PLoS One, vol. 2, no. 8, e776. https://doi.org/10.1371/journal.pone.0000776
Yeo, Zhen Xuan ; Wong, Sum Thai ; Vel Arjunan, Satya Nanda ; Piras, Vincent ; Tomita, Masaru ; Selvarajoo, Kumar ; Giuliani, Alessandro ; Tsuchiya, Masa. / Sequential logic model deciphers dynamic transciptional control of gene expressions. In: PLoS One. 2007 ; Vol. 2, No. 8.
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