Bayesian network analysis of targeting interactions in chromatin.
In eukaryotes, many chromatin proteins together regulate gene expression. Chromatin proteins often direct the genomic binding pattern of other chromatin proteins, for example, by recruitment or competition mechanisms. The network of such targeting interactions in chromatin is complex and still poorly understood. Based on genome-wide binding maps, we constructed a Bayesian network model of the targeting interactions among a broad set of 43 chromatin components in Drosophila cells. This model predicts many novel functional relationships. For example, we found that the homologous proteins HP1 and HP1C each target the heterochromatin protein HP3 to distinct sets of genes in a competitive manner. We also discovered a central role for the remodeling factor Brahma in the targeting of several DNA-binding factors, including GAGA factor, JRA, and SU(VAR)3-7. Our network model provides a global view of the targeting interplay among dozens of chromatin components.
van Steensel
Bas
B
Division of Gene Regulation, Netherlands Cancer Institute, 1066 CX Amsterdam, the Netherlands. b.v.steensel@nki.nl
Braunschweig
Ulrich
U
Filion
Guillaume J
GJ
Chen
Menzies
M
van Bemmel
Joke G
JG
Ideker
Trey
T
D000818:Animals; D001499:Bayes Theorem; D002843:Chromatin / Q000378:metabolism*; D004268:DNA-Binding Proteins / Q000378:metabolism*; D004331:Drosophila melanogaster / Q000235:genetics*; D053263:Gene Regulatory Networks; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D025941:Protein Interaction Mapping
D002843:Chromatin; D004268:DNA-Binding Proteins