Yeast transcriptional regulatory network & metabolic network

1. Yeast transcriptional regulatory network & metabolic network Tony 28/09/2004

2. Transcriptional regulatory code of a eukaryotic genome Richard A. Young, et al. (2004) Nature 431, 99-104.

3. Summary of the work • This work presents mainly some novel experimental results. Probably for the first time to date, the transcriptional regulatory code is deciphered genome-widely. • The genome-scale TR code • Simple analysis of the code

4. TR code of yeast genome • Genome-wide location analysis • Integration of genome-wide location data, phylogenetically conserved sequences, and prior knowledge. • The code

5. Simple statistics of the code • The distribution of the binding sites for transcriptional regulators • Promoter architectures: • Single regulator • Repetitive motifs • Multiple regulators • Co-occurring regulators • Environment-dependent binding behaviors • Condition-invariant • Condition-enabled • Condition-expanded • Condition-altered

6. Global organization of metabolic fluxes in the bacterium Escherichia coli A.-L. Barabasi, et al. (2004) Nature 427, 839-842.

7. Summary of the work • This paper utilizes FBA techniques to study the metabolic fluxes in the yeast metabolic network. The paper has two major conclusions: • The flux distribution is scale free. • The existence of High-flux backbone (HFB).

8. Flux distribution • Flux Balance Analysis (FBA) • Flux distribution is scale free, independent of the environmental conditions and regardless of whether it’s optimized for maximal growth rate or not. • “These findings imply that the observed flux distribution is a generic feature of flux conservation on a scale-free network.”

9. High-flux backbone • The local flux is inhomogenous. • High-flux backbone (HFB) • Only the reactions in the HFB undergo noticeable flux change when conditions change.