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Identifying regulatory networks by combinatorial analysis of promoter elements

Nature Genetics, 29, 153-159 (2001)

Yitzhak (Tzachi) Pilpel*
Priya Sudarsanam*
George M. Church
*These authors made equal contributions to this work

Department of Genetics, Harvard Medical School, and
Lipper Center for Computational Genetics


Abstract
Reviews on the paper
Figures
Parameter Landscape Analyses
 Tables
Data & Resources
A presentation of the approach
FORAMQ
Contacts for comments


Abstract

The recent availability of microarray data has led to the development of several computational approaches for studying genome-wide transcriptional regulation. However, few studies have addressed the combinatorial nature of transcription, a well-establishe d phenomenon in eukaryotes. We have developed a new computational method that analyzes microarray data to discover synergistic motif combinations in the promoters of S. cerevisiae. Our method suggests causal relationships between each motif in a combinati on and the overall coherence of the observed expression patterns. In addition to identifying novel motif combinations that affect expression patterns during the cell cycle, sporulation, and various stress response conditions, we have also discovered regul atory cross-talk between several of these processes. We have generated motif synergy maps that provide a global view of the transcription networks in the cell. The maps are highly connected suggesting that a small number of transcription factors are respo nsible for a complex set of expression patterns in diverse conditions. This approach should be important and applicable for modeling transcriptional regulatory networks in more complex eukaryotes.

Figures

General


Figure 1AB: General Flaw Chart Scheme
Figure 2: The effect of motif orientation on expression cohernece

Motif interaction maps

Figure 3: A Global Map of Motif Synergy

Supplementary interaction maps:

The ribosomal regulatory elements map
 

Combinograms


Figure4AB: cell cycle and sporulation
Figure5AB: heat shock and DNA damaging agents

Supplementary Combinograms:

diauxic shift
dtt treatment
cold shock
 

Parameter Landscape Analyses

Investigate here the effect of different choices of analyses parameters
 

Tables

A collection of known and putative motifs
Expression Coherence Score of individual motifs
Synergistic Motif Pairs
 

Data & Resources


All expression data were taken from ExpressDB

Motifs were derived using AlignACE and matched to promoters in the genome using ScanACE
 


Contacts


Correspondence may be addressed to George M. Church at:
Department of Genetics,
Harvard Medical School
200 Longwood Avenue,
Boston, MA 02115 USA
fax (617) 432-7266
Or Email to:
Tzachi Pilpel Priya Sudarsanam George Church