Characterizing Protein Transcriptional Regulation
Characterizing Protein Transcriptional Regulation
A review of Transcriptional regulation of protein complexes within and across species
Note: This is a review of the published article listed below. All information, quotes, figures, methods, and findings mentioned in this review are from that article, and are the property of its authors and/or the publication in which the article originally appeared.
Transcriptional regulatory networks have been broadly characterized for many model species, using theoretical and experimental chromatin immunoprecipitation techniques. Protein-protein and transcriptional regulatory interactions have been independently characterized, yet to date there has not been an in-depth evaluation of the interplay between these interaction types. To explore transcriptional regulation of coordinately expressed protein complexes, Tan and colleagues (2007) developed a computer algorithm to predict transcriptional interactions, and tested those predictions using Agilent’s Yeast Oligo Microarray, yielding a confirmation rate (58%) comparable with that of direct immunoprecipitation experiments. When extended to compare yeast and fly networks (i.e. between species), this model identified a number of conserved coregulated complexes, as well as evidence that “protein–protein interaction networks may evolve more slowly than transcriptional interaction networks.” This research is just the beginning of defining the complex interplay between regulatory networks, particularly across organisms, but demonstrates how molecular interactions can be integrated to provide global regulatory map of the cell.
| |
Complex source |
GO enrichment,
% |
Expression coherency, % |
Conservation coherency, % |
MS-derived complexes |
Ho et al. (26) |
61 |
8 |
24 |
| |
Gavin et al. (27) |
77 |
9 |
36 |
| Protein clusters |
Current study |
99 |
26 |
22 |
| Coregulated clusters |
Current study |
100 |
45 |
59 |
Table 1. Validation of yeast clusters by functional enrichment, expression coherency, and conservation coherency of their members.
All analyses were restricted to clusters of size at least 7, although the same trends were observed over a wide range of cluster size cutoffs.
Figure 1. Transcriptional interaction prediction in yeast.
(a) Receiver operating characteristics curve of the logistic regression classifier. AUC, area under the curve; Sn, sensitivity; Sp, specificity. (b) An example of a predicted cluster regulated by Rpn4. Orange arrows, known Rpn4 TIs from Harbison et al.; purple, newly predicted Rpn4 TIs. Shades of red represent P values (<0.05) for differential gene expression. (c) Fraction of differentially expressed genes in various gene sets. Green, genes bound by Rpn4 from the Harbison data; orange, genes in cluster models but not bound by Rpn4 based on the Harbison data.
Title: Transcriptional regulation of protein complexes within and across species.
Authors: Tan K, Shlomi T, Feizi H, Ideker T, Sharan R.
Journal: Proc Natl Acad Sci U S A. 2007 Jan 23;104(4):1283-8
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