Dynamic cumulative activity of transcription factors as a mechanism of quantitative gene regulation
| Autor: | An-Ping Zeng, Feng-tian He, Jan Buer, Rudi Balling |
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| Přispěvatelé: | Helmholtz Centre of infection research, Inhoffenstr. 7, D38124 Braunschweig, Germany |
| Jazyk: | angličtina |
| Předmět: |
Transcription
Genetic Saccharomyces cerevisiae Amino Acid Motifs Genes Fungal Biotechnology/methods Biochemistry biophysics & molecular biology [F05] [Life sciences] Saccharomyces cerevisiae/genetics Fungal Proteins Transcription (biology) Gene Expression Regulation Fungal Correspondence Transcriptional regulation False Positive Reactions Transcription Factors/metabolism Biochimie biophysique & biologie moléculaire [F05] [Sciences du vivant] Gene Transcription factor Fungal Proteins/metabolism Regulation of gene expression Genetics Fungal protein Binding Sites biology Models Genetic Mechanism (biology) Cell Cycle Models Theoretical biology.organism_classification Algorithms Biotechnology Transcription Factors |
| Zdroj: | Genome Biology, 8(9), 181. England (2007). Genome Biology |
| ISSN: | 1465-6906 |
| DOI: | 10.1186/gb-2007-8-9-r181 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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