Systematic determination of genetic network architecture
Nature Genetics 22: 281-285
Saeed Tavazoie(1), Jason D. Hughes(1,2), Michael J. Campbell(3), Raymond J. Cho(4) and George M. Church(1)
1-Department of Genetics, Harvard Medical School, 200 Longwood Ave., Boston, MA, 02115, USA
2-Graduate Program in Biophysics, 200 Longwood Ave., Harvard University, Boston, MA 02115, USA
3-Molecular Applications Group, 607 Hansen Way, Building One, Palo Alto, CA 94303-1110
4-Department of Genetics, B400 Beckman Center, 279 Campus Drive, Stanford Medical Center, Palo Alto, CA 94304

We present a systematic approach for determining the higher order organization of the transcriptional regulatory network from whole-genome mRNA expression data.  Time-series of mRNA abundance, measured over two synchronized Saccharomyces cerevisiae cell cycles, were used to group 3000 genes into various expression classes which were highly enriched for genes of similar function.  A systematic, upstream DNA motif search identified many known and putative cis-regulatory elements, highly specific to each expression class.  The identification of many expected cis-regulatory elements, together with the expression-class specificity of many novel motifs, makes this combination approach promising for the rapid elucidation of regulatory network architecture in the myriad of organisms which are now completely described at the DNA sequence level.

Questions and Comments should be addressed to: Saeed Tavazoie (

 Schematic overview of our approach

Cluster members (together with distances and annotations)

Enrichment of clusters for MIPS functional categories

Temporal profile of clusters:         Clusters 1-10          Clusters 11-20          Clusters 21-30

 DNA sequence motifs and their statistical characterization

DNA sequence motifs and their occurences within upstream sequences