1. Li Chen 4/3/2009 CSc 8910 Analysis of Biological Network, Spring 2009 Dr. Yi Pan

2.  Introduction  Results  Conclusions

3.  Transcriptional Regulatory Network A complex network of interactions among transcription factors and promoter regions of genes and operons.  Goal of Identifying Motifs in Transcriptional Regulatory Network To simplify networks’ architecture and better understand the system-level function of such networks.  Previous achievement The motifs could be identified in the network. But they are small, overrepresented, topologically distinct regulatory interaction patterns.

4.  First organizational level: motifs Each network being characterized by its own set of distinct motifs. In the E.coli transcriptional regulatory network, majority of motifs are feed-forward motifs and bi- fan motifs.

5. Feed-forward and bi-fan motifs can be classified by the functionality of their links, namely, activating or inhibitory. (1) coherent type feed-forward motif (FF) (2) incoherent type feed-forward motif (FF) (3) coherent bi-fan motif (BF) (4) incoherent bi-fan motif (BF) Graphical representation of the network.

6. Blue diamonds: transcription factors (TF) Red circles: regulated operons Links: blue -- activator green -- repressor brown -- activator or repressor effect

7. Detailed statistics of the nodes (upper table) and the two statistically significant motifs (bottom table) found in the network.

8.  Second organizational level: homologous motif clusters Feed-forward motifs that share at least one link and/or node with another feed-forward motif. Forty-one of the 42 individual feed-forward motif clusters Six motif clusters, three have one highly shared link, while a a shared node plays a critical role in establishing the other three motif clusters.

9. Bi-fan motifs that share at least one link and/or node with another bi-fan motif. 208 of the 209 bi-fan motifs join together into just two bi- fan motif clusters. Most of links are shared by at least two adjacent motifs, and also among multiple motifs.

10.  Third organizational level: motif super-cluster Merge all feed-forward and bi-fan homologous motif clusters Form a single large connected component (motif super-cluster) Vast majority of feed-forward motif clusters share the same links with the bi-fan motif clusters

11.  The relationship of organizational levels to the global network topology The connected giant component of the complete E.coli transcriptional regulatory

12. Cumulative connectivity distribution P(k) The solid black line has an exponent γ=-1.5, provides the best fit for the original network (black circles)

13. The clustering distribution C(k) The solid black line has slope ζ = -1, and the is the best fit for all networks. The clustering coefficient of a node is a measure of its near-neighbors connectivity, and thus for the BF motifs this value is zero.

14. Demonstrate the heterologous motif super-cluster represents the backbone of the connected giant component Removing all 250 links of super-cluster from the network.

15. Removal of 250 randomly chosen links. Network break into 16 small sub-graphs, a connected giant component was retained.

16. The connectivity distribution P(k) of the remaining networks The solid line has slope γ = -2, and is the best fit for the random link removal. After random link removal, P(k) is relatively unaltered, being reminiscent to that observed for the original network.

17. The clustering distribution C(k) The solid line has slope ζ = -2. After super-cluster links removal, C(k) and k was completely absent.

18.  For the E. coli transcriptional regulatory network, Individual motifs, homologous motif clusters and super-cluster are key determinants of the network’s global topological organization.  Individual motifs, homologous motif clusters and super-cluster may represent distinct organizational hierarchies of transcriptional regulation.  It is likely that the aggregation of motifs into motif clusters and super-clusters is a general property of all cellular networks.