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Sci. STKE, 21 September 2004
Vol. 2004, Issue 251, p. tw334
[DOI: 10.1126/stke.2512004tw334]

EDITORS' CHOICE

NETWORKS Revealing Transcriptional Network Dynamics

Network analysis can reveal the overall wiring and information flow through a global system. Luscombe et al. provide a first look at the dynamics of the transcriptional network in yeast using a new statistical methodology they call SANDY (for statistical analysis of network dynamics). Using this methodology, they investigated how the transcriptional network changes in response to five different conditions: diauxic shift, DNA damage, or stress response, which they consider exogenous stimuli, or cell division or sporulation, which they consider endogenous cell processes. A minority of the interactions occurs in four or more of the conditions (66 out of 2476). Most of the transcription factors are involved in all of the conditions, whereas half of the target genes expressed are unique to a specific condition. Using multiple mathematical measurements for information flow, major differences between the endogenous and exogenous networks were revealed. For exogenous networks, the regulation of the transcription factors is simpler with fewer inputs than is observed for the endogenous networks. Furthermore, exogenous networks exhibit an increase in the number of genes targeted by each transcription factor compared with the endogenous networks. These two properties would allow faster propagation of the signal and a faster cellular response. Endogenous networks show a higher clustering coefficient than do exogenous networks, indicating that there is a high degree of interregulation among the transcription factors that participate in these endogenous cell processes. The properties of the connections between the transcription factors and their targets also vary between endogenous and exogenous networks, with exogenous networks containing many single-input motifs in which a single transcription factor has many target genes, and endogenous networks containing many feed-forward-loop motifs in which a primary transcription factor regulates a secondary factor and then both transcription factors regulate a final target gene. Transcription factor hubs, which are believed to represent the essential core of the network, were also revealed for each condition, as well as a permanent hub that was present in all conditions. The degree of interchange among the transcription factors was also measured, and with the exception of a few transcription factors in the cell cycle, most of the transcription factors in the five networks change a subset of their interactions among the conditions. Finally, SANDY allows properties within a subnetwork to be investigated, and the authors use the cell cycle network to demonstrate how the network changes during the different phases of the cell cycle.

N. M. Luscombe, M. M. Babu, H. Yu, M. Snyder, S. A. Teichmann, M. Gerstein, Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 431, 308-312 (2004). [Online Journal]

Citation: Revealing Transcriptional Network Dynamics. Sci. STKE 2004, tw334 (2004).



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