Comprehensive analysis of combinatorial regulation using the transcriptional regulatory network of yeast

Chromatin remodelling is a major source of coexpression of linked genes in yeast

In diverse organisms, neighbouring genes in the genome tend to be positively coexpressed more than expected by chance. When the similarity of transcription regulation is controlled for, adjacent genes have much higher coexpression rates than unlinked genes, supporting a role for chromatin modelling. Consequently, many incidences of low-to-moderate level coexpression of linked genes might well be spurious rather than an indication of functional coordination. These results have implications for gene therapy and for understanding gene order evolution, suggesting that chromosomal proximity alone is adequate to achieve some level of coexpression.

Interplay between network structures, regulatory modes and sensing mechanisms of transcription factors in the transcriptional regulatory network of E. coli

Though the bacterial transcription regulation apparatus is distinct in terms of several structural and functional features from its eukaryotic counterpart, the gross structure of the transcription regulatory network (TRN) is believed to be similar in both superkingdoms. Here, we explore the fine structure of the bacterial TRN and the underlying "co-regulatory network" (CRN) to show that despite the superficial similarities to the TRN of the eukaryotic model organism yeast, the bacterial networks display entirely different organizational principles. In particular unlike in eukaryotes, hubs of the bacterial networks are both global regulators and integrators of diverse disparate transcriptional responses. These and other organizational differences might correlate with the fundamental differences in gene and promoter organization in the two superkingdoms, especially the presence of operons and regulons in bacteria. Further we explored to find the interplay, if any, between network structures, mode of regulatory interactions and signal sensing of transcription factors (TFs) in shaping up the bacterial transcriptional regulatory responses. For this purpose, we first classified TFs according to their regulatory mode (activator, repressor or dual regulator) and sensory mechanism (one-component systems responding to internal or external signals, TFs from two-component systems and chromosomal structure modifying TFs) in the bacterial model organism Escherichia coli and then we studied the overall evolutionary optimization of network structures. The incorporation of TFs in different hierarchical elements of the TRN appears to involve on a multi-dimensional selection process depending on regulatory and sensory modes of TFs in motifs, co-regulatory associations between TFs of different functional classes and transcript half-lives. As a result it appears to have generated circuits that allow intricately regulated physiological state changes. We identified the biological significance of most of these optimizations, which can be further used as the basis to explore similar controls in other bacteria. We also show that, though on the larger evolutionary scale, unrelated TFs have evolved to become hubs, within lineages like gamma-proteobacteria there is strong tendency to retain hubs, as well as certain higher-order network modules that have emerged through lineage specific paralog duplications.

Communication between levels of transcriptional control improves robustness and adaptivity

Regulation of eukaryotic gene expression depends on groups of related proteins acting at the levels of chromatin organization, transcriptional initiation, RNA processing, and nuclear transport. However, a unified understanding of how these different levels of transcriptional control interact has been lacking. Here, we combine genome-wide protein–DNA binding data from multiple sources to infer the connections between functional groups of regulators in Saccharomyces cerevisiae. Our resulting transcriptional network uncovers novel biological relationships; supporting experiments confirm new associations between actively transcribed genes and Sir2 and Esc1, two proteins normally linked to silencing chromatin. Analysis of the regulatory network also reveals an elegant architecture for transcriptional control. Using communication theory, we show that most protein regulators prefer to form modules within their functional class, whereas essential proteins maintain the sparse connections between different classes. Moreover, we provide evidence that communication between different regulatory groups improves the robustness and adaptivity of the cell.

The natural history of the WRKY-GCM1 zinc fingers and the relationship between transcription factors and transposons

WRKY and GCM1 are metal chelating DNA-binding domains (DBD) which share a four stranded fold. Using sensitive sequence searches, we show that this WRKY–GCM1 fold is also shared by the FLYWCH Zn-finger domain and the DBDs of two classes of Mutator-like element (MULE) transposases. We present evidence that they share a stabilizing core, which suggests a possible origin from a BED finger-like intermediate that was in turn ultimately derived from a C2H2 Zn-finger domain. Through a systematic study of the phyletic pattern, we show that this WRKY–GCM1 superfamily is a widespread eukaryote-specific group of transcription factors (TFs). We identified several new members across diverse eukaryotic lineages, including potential TFs in animals, fungi and Entamoeba. By integrating sequence, structure, gene expression and transcriptional network data, we present evidence that at least two major global regulators belonging to this superfamily in Saccharomyces cerevisiae (Rcs1p and Aft2p) have evolved from transposons, and attained the status of transcription regulatory hubs in recent course of ascomycete yeast evolution. In plants, we show that the lineage-specific expansion of WRKY–GCM1 domain proteins acquired functional diversity mainly through expression divergence rather than by protein sequence divergence. We also use the WRKY–GCM1 superfamily as an example to illustrate the importance of transposons in the emergence of new TFs in different lineages.

Coding limits on the number of transcription factors

Background

Transcription factor proteins bind specific DNA sequences to control the expression of genes. They contain DNA binding domains which belong to several super-families, each with a specific mechanism of DNA binding. The total number of transcription factors encoded in a genome increases with the number of genes in the genome. Here, we examined the number of transcription factors from each super-family in diverse organisms.

Results

We find that the number of transcription factors from most super-families appears to be bounded. For example, the number of winged helix factors does not generally exceed 300, even in very large genomes. The magnitude of the maximal number of transcription factors from each super-family seems to correlate with the number of DNA bases effectively recognized by the binding mechanism of that super-family. Coding theory predicts that such upper bounds on the number of transcription factors should exist, in order to minimize cross-binding errors between transcription factors. This theory further predicts that factors with similar binding sequences should tend to have similar biological effect, so that errors based on mis-recognition are minimal. We present evidence that transcription factors with similar binding sequences tend to regulate genes with similar biological functions, supporting this prediction.

Conclusion

The present study suggests limits on the transcription factor repertoire of cells, and suggests coding constraints that might apply more generally to the mapping between binding sites and biological function.