Reference : Dynamic cumulative activity of transcription factors as a mechanism of quantitative g...
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
Dynamic cumulative activity of transcription factors as a mechanism of quantitative gene regulation.
He, Feng mailto [> >]
Buer, Jan [> >]
Zeng, An-Ping [> >]
Balling, Rudi mailto [Helmholtz Centre for Infection Research, Inhoffenstra├če, Braunschweig, Germany]
Genome Biology
Yes (verified by ORBilu)
[en] Algorithms ; Amino Acid Motifs ; Binding Sites ; Biotechnology/methods ; Cell Cycle ; False Positive Reactions ; Fungal Proteins/metabolism ; Gene Expression Regulation, Fungal ; Genes, Fungal ; Models, Genetic ; Models, Theoretical ; Saccharomyces cerevisiae/genetics ; Transcription Factors/metabolism ; Transcription, Genetic
[en] BACKGROUND: The regulation of genes in multicellular organisms is generally achieved through the combinatorial activity of different transcription factors. However, the quantitative mechanisms of how a combination of transcription factors controls the expression of their target genes remain unknown. RESULTS: By using the information on the yeast transcription network and high-resolution time-series data, the combinatorial expression profiles of regulators that best correlate with the expression of their target genes are identified. We demonstrate that a number of factors, particularly time-shifts among the different regulators as well as conversion efficiencies of transcription factor mRNAs into functional binding regulators, play a key role in the quantification of target gene expression. By quantifying and integrating these factors, we have found a highly significant correlation between the combinatorial time-series expression profile of regulators and their target gene expression in 67.1% of the 161 known yeast three-regulator motifs and in 32.9% of 544 two-regulator motifs. For network motifs involved in the cell cycle, these percentages are much higher. Furthermore, the results have been verified with a high consistency in a second independent set of time-series data. Additional support comes from the finding that a high percentage of motifs again show a significant correlation in time-series data from stress-response studies. CONCLUSION: Our data strongly support the concept that dynamic cumulative regulation is a major principle of quantitative transcriptional control. The proposed concept might also apply to other organisms and could be relevant for a wide range of biotechnological applications in which quantitative gene regulation plays a role.
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