In higher eukaryotes, transcriptional enhancers play critical roles in the integration of cellular signaling information, but apart from a few well-studied model enhancers, we lack a general picture of transcriptional information processing by most enhancers. Here we discuss recent studies that have provided fresh insights on information processing that occurs on enhancers, and propose that in addition to the highly cooperative and coordinate action of "enhanceosomes", a less integrative, but more flexible form of information processing is mediated by information display or "billboard" enhancers. Application of these models has important ramifications not only for the biochemical analysis of transcription, but also for the wider fields of bioinformatics and evolutionary biology.

A well-defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy-based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy-based modeling uncovered specific quantitative features of short-range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos.

Transcriptional repression is essential for establishing localized patterns of gene expression during Drosophila embryogenesis. Several mechanisms of repression have been proposed, including competition, quenching and direct repression of the transcription complex. Previous studies suggest that the knirps orphan receptor (kni) may repress transcription via competition, and exclude the binding of the bicoid (bcd) activator to an overlapping site in a target promoter. Here we present evidence that kni can quench, or locally inhibit, upstream activators within a heterologous enhancer in transgenic embryos. The range of kni repression is approximately 50–100 bp, so that neighboring enhancers in a modular promoter are free to interact with the transcription complex (enhancer autonomy). However, kni can also repress the transcription complex when bound in promoter‐proximal regions. In this position, kni functions as a dominant repressor and blocks multiple enhancers in a modular promoter. Our studies suggest that short‐range repression represents a flexible form of gene regulation, exhibiting enhancer‐ or promoter‐specific effects depending on the location of repressor binding sites.

The genes specifying chemotaxis, motility, and flagellar function in Escherichia coli are coordinately regulated and form a large and complex regulon. Despite the importance of these genes in controlling bacterial behavior, little is known of the molecular mechanisms that regulate their expression. We have identified a minor form of E. coli RNA polymerase that specifically transcribes several E. coli chemotaxis/flagellar genes in vitro and is likely to carry out transcription ofthese genes in vivo. The enzyme was purified to near homogeneity based on its ability to initiate transcription of the E. coli tar chemotaxis gene at start sites that are used in vivo. Specific tar transcription activity is associated with a polypeptide of apparent 28-kDa molecular mass that remains bound to the E. coli RNA polymerase throughout purification. This peptide behaves as a secondary v factor-designated CrF_ because it restores specific tar transcription activity when added to core RNA polymerase. The oF holoenzyme also transcribes the E. coli tsr and flaAI genes in vitro as well as several Bacillus subtilis genes that are transcribed specifically by the a28 form of B. subtilis RNA polymerase. The latter holoenzyme is implicated in transcription of flagellar and chemotaxis genes in B. subtilis. Hence E. coli oF holoenzyme appears to be analogous to the B. subtilis r28 RNA polymerase, both in its promoter specificity and in the nature of the regulon it controls. Flagellar, chemotaxis, and motility genes in Escherichia coli and Salmonella typhimurium are coordinately controlled in a large and complex unit often called the flagellar, chemotaxis, and motility regulon (1-3). Genetic analysis suggests that in E. coli these genes fall into five transcriptional subclasses, all dependent on the flbBIflaI operon (1, 2, 4). However, little is known about the mechanisms by which gene expression in the regulon is controlled.A number of flagellar and chemotaxis genes have been sequenced. While the transcriptional start sites of most of such genes have not been characterized, regions just upstream of the coding sequences contain conserved sequences (5-7) that strongly resemble promoters utilized by the or28 holoenzyme from Bacillus subtilis (8). This vegetatively active RNA polymerase is implicated in the transcription of chemotaxis and flagellar genes in B. subtilis (ref. 9; D. Mirel and M.J.C., unpublished data). In addition, the gene encoding o.28 is itself homologous to flbB and flaI (9). These findings suggested to us that the products of one or both of these genes might be an alternative o-factor responsible for the transcription of fla/che/mot genes in E. coli (7). This hypothesis led us to search in E. coli for an RNA polymerase activity that could efficiently initiate transcription of an E. coli chemotaxis gene at transcription start sites used in vivo. Assays. S1 nuclease mapping was carried out as described (17). A 348-nucleotide S1 probe was generated by digesting pDNA1 with Pst I and EcoRI, treating the digest with calf i...

The detailed analysis of transcriptional networks holds a key for understanding central biological processes, and interest in this field has exploded due to new large-scale data acquisition techniques. Mathematical modeling can provide essential insights, but the diversity of modeling approaches can be a daunting prospect to investigators new to this area. For those interested in beginning a transcriptional mathematical modeling project we provide here an overview of major types of models and their applications to transcriptional networks. In this discussion of recent literature on thermodynamic, Boolean and differential equation models we focus on considerations critical for choosing and validating a modeling approach that will be useful for quantitative understanding of biological systems.