Cis Regulatory Evolution

Shadow enhancers are seemingly redundant transcriptional cis-regulatory elements that regulate the same gene and drive overlapping expression patterns. Recent studies have shown that shadow enhancers are remarkably abundant and control the majority of developmental gene expression in both invertebrates and vertebrates, including mammals. Shadow enhancers might provide an important mechanism for buffering against mutations in non-coding regulatory regions of genes implicated in human disease. Technological advances in genome editing and live imaging have shed light on how shadow enhancers establish precise gene expression patterns and confer phenotypic robustness. Shadow enhancers can interact in complex ways and may also help drive the formation of transcriptional hubs within the nucleus. Despite their apparent redundancy, the prevalence and evolutionary conservation of shadow enhancers underscore their key role in emerging metazoan gene regulatory networks.

Highlights d Identification of genome-wide target genes for the RCO transcription factor d RCO delimits its own expression through autorepression by low-affinity binding d RCO represses local leaf growth via regulating multiple cytokinin (CK)-related genes d RCO negative autorepression fine-tunes CK activity and regulates leaf shape

Repeated evolutionary events imply underlying genetic constraints that can make evolutionary mechanisms predictable. Morphological traits are thought to evolve frequently through cis-regulatory changes because these mechanisms bypass constraints in pleiotropic genes that are reused during development. In contrast, the constraints acting on metabolic traits during evolution are less well studied. Here we show how a metabolic bottleneck gene has repeatedly adopted similar cis-regulatory solutions during evolution, likely due to its pleiotropic role integrating flux from multiple metabolic pathways. Specifically, the genes encoding phosphoglucomutase activity (PGM1/PGM2), which connect GALactose catabolism to glycolysis, have gained and lost direct regulation by the transcription factor Gal4 several times during yeast evolution. Through targeted mutations of predicted Gal4-binding sites in yeast genomes, we show this galactose-mediated regulation of PGM1/2 supports vigorous growth on g...

Bioinformatics is essential to walk in this direction, providing all what is available to deal with large amounts of data: databases, algorithms to generate genomic answers to standard questions, overviews and navigation capabilities, as well as statistics to perform and validate analyses. Knowledge of gene regulation in prokaryotes is quite diverse, from the constantly increasing number of full genome sequences where very little experimental work has been performed, including the many genomes that cannot yet be grown in the laboratory, the little studied archaea, to the few highly characterized bacterial genomes as Bacillus subtilis or Pseudomonas aeruginosa, with Escherichia coli K-12 being by far the best known bacteria, and still currently, free living organism. Figure 1 shows this strongly unequal distribution of knowledge with the number of publications on gene regulation, as example, in different microbial genomes. The first exhaustive historical set of regulated promoters and their associated transcription factors (TFs) and transcription factor DNA-binding sites (TFBSs) gathered around 120 σ 70 and σ 54 promoters in Escherichia coli K-12 (16, 29). This information and the experience obtained was the seed for what is now RegulonDB, the original source of expert human curated knowledge on regulation of transcription initiation and operon organization in E.coli K-12. It contains what is currently the major electronically encoded regulatory network of any free-living organism (25). This information is also contained in EcoCyc, the E.coli model-organism database with added curated knowledge on metabolism and transport (http://ecocyc.org/). We estimate to have currently around 25% of known interactions of the full cellular regulatory network of transcription initiation. RegulonDB should not be conceived as a database, but as an environment for genomic regulatory A C C E P T E D by on October 16, 2009 jb.asm.org Downloaded from investigations, linked to bioinformatics tools that facilitate analyses of upstream regions, together with datasets and tools for microarray analyses, and more recently direct access to full papers supporting its knowledge. We are not only curating up to date original papers, but also have initiated "active annotation" using Jean-Michelle Claverie´s terminology, more precisely experimentally mapping promoters by a high-throughput strategy. This minireview has been organized taking into account that most of the readers of the Journal of Bacteriology are experimentalists. We start by a few examples of lessons on gene regulation from bioinformatics focusing on promoters, their definition and regulation, and operon structure. The second section summarizes how RegulonDB has been useful to the experimentalists, as well as its role as a golden standard to implement bioinformatics predictive methods, topological analyses of the network, and models of the cell. The last section offers a compendium of links to bioinformatics resources on gene regulation in bacteria, illustrating their usage with flow charts associated to questions on the regulation of gene expression in RegulonDB (http://regulondb.ccg.unam.mx/) and associated bioinformatics resources. We illustrate the very efficient text analysis using Textpresso to access more than 2400 full papers that support the E.coli regulatory network. A cautionary note is that the examples of the three sections are biased to cases in E. coli and its RegulonDB regulatory database. This bias is natural since, on the one hand, our direct experience is with RegulonDB, and second, specially for bacterial gene regulation (see Fig. 1), we may well quote Fred Neidhardt (87) claiming that: "Not everyone is mindful of it, but all cell biologists have two organisms of interest: the one they are studying and Escherichia coli ¡".

Fifty years ago, Francois Jacob and Jacques Monod published a seminal study in the Journal of Molecular Biology on the role of "regulator genes" in controlling the expression of "structural genes" in bacteria. This turned out to accurately define the transcription factors that act to determine the subset of genes to be expressed in each cell, in interaction with the external milieu. If these findings were rapidly recognized as a milestone, the contributions of this paper to collective scientific thought are even more impressive with regard to recent functional genomics. The authors already proposed in 1961 "that the genome contains not only a series of blueprints, but a coordinated program of protein synthesis and the means of controlling its execution." This represents an extraordinary vision of the way biological systems are hardwired by genomic information, a central concept in our current view of physiology, development, and evolution. Genetic analyses in model systems later provided an unbiased portal into the molecular control of embryonic development, showing the importance of transcription factors and signaling pathways that regulate their outputs. For example, Eric Wieschaus and Christiane Nüsslein-Volhard showed that most mutations affecting the embryonic pattern in Drosophila alter regulator genes. The discovery of so-called homeotic genes by Ed Lewis and their products (which contain the homeodomain DNA-binding motif) by Walter Gehring and colleagues further demonstrate that transcription factors govern both body plan establishment and the final differentiation of tissues and organs. Three decades later, major advances have been made in our comprehension of how various protein motifs mediate specific DNA recognition, exemplified by recent successes in designing artificial proteins to target a given genomic region. Deciphering the genome of hundreds of species has revealed that transcription factors are an abundant class of molecules (representing 5-10% of the total number of proteins), displaying unexpected levels of evolutionary conservation. It bears reminding that, even in genetically amenable systems, the function of most transcription factors has yet to be discovered. While the general concepts of transcriptional regulation are now well established, a major challenge resides in understanding the logic and physical elements implementing these regulatory interactions within a given cell in a developing organism. A central problem to be addressed is how transcriptional programs are set up and then modified throughout the successive steps of embryonic development. This volume provides a broad range of insights into the molecular determinants of such transcriptional switches during development.

Background It has recently been shown [Huerta and Collado-Vides, 2003] that regulatory regions in E. coli contain high densities of potential interaction sites for sigma 70, the principal sigma transcription factor which binds to the-10 (TATAAT) and-35 (TTGACA) promoter sequences and is essential for general transcription in exponentially growing bacterial cells [

Background It has recently been shown [Huerta and Collado-Vides, 2003] that regulatory regions in E. coli contain high densities of potential interaction sites for sigma 70, the principal sigma transcription factor which binds to the-10 (TATAAT) and-35 (TTGACA) promoter sequences and is essential for general transcription in exponentially growing bacterial cells [

Motivation: Conserved non-coding elements (CNEs) represent an enigmatic class of genomic elements which, despite being extremely conserved across evolution, do not encode for proteins. Their functions are still largely unknown. Thus, there exists a need to systematically investigate their roles in genomes. Towards this direction, identifying sets of CNEs in a wide range of organisms is an important first step. Currently, there are no tools published in the literature for systematically identifying CNEs in genomes. Results: We fill this gap by presenting CNEFinder; a tool for identifying CNEs between two given DNA sequences with user-defined criteria. The results presented here show the tool's ability of identifying CNEs accurately and efficiently. CNEFinder is based on a k-mer technique for computing maximal exact matches. The tool thus does not require or compute whole-genome alignments or indexes, such as the suffix array or the Burrows Wheeler Transform (BWT), which makes it flexible to use on a wide scale. Availability and implementation: Free software under the terms of the GNU GPL (https://github. com/lorrainea/CNEFinder).

Author(s): Froula, Jeff; Francino, M. Pilar | Abstract: Background: It has been shown that selection acts to remove the promoter's 10 and 35 consensus sequences in both coding and noncoding regions, implying that it is disadvantageous to maintain misplaced sites that can strongly bind ?70 and interfere with proper gene expression. Here we analyze 56 bacterial genomes and show that the numbers of nonconsensus, potential ?70 binding sites in both regulatory and non-regulatory noncoding regions deviate significantly from the random expectations when compensating for base composition, di- and tri-nucleotide bias in a majority of eubacteria. Not only do we expect that selection is maintaining high densities of potential ?70 binding sites in regulatory DNA, but that there is selection against these sites in non-regulatory DNA. The often overlapping binding sites inregulatory DNA likely confer some subtle survival advantage, even though experimental evidence suggests only one or a few ...

Developmental programs are implemented by regulatory interactions between Transcription Factors (TFs) and their target genes, which remain poorly understood. While recent studies have focused on regulatory cascades of TFs that govern early development, little is known about how the ultimate effectors of cell differentiation are selected and controlled. We addressed this question during late Drosophila embryogenesis, when the finely tuned expression of the TF Ovo/Shavenbaby (Svb) triggers the morphological differentiation of epidermal trichomes. We defined a sizeable set of genes downstream of Svb and used in vivo assays to delineate 14 enhancers driving their specific expression in trichome cells. Coupling computational modeling to functional dissection, we investigated the regulatory logic of these enhancers. Extending the repertoire of epidermal effectors using genome-wide approaches showed that the regulatory models learned from this first sample are representative of the whole s...

ABSTRACT: We have previously demonstrated that genes within experimentally characterized operons of Es-cherichia coli are conserved together in other genomes more frequently than genes at the borders of transcription units. Here we expand the analyses and show that, as the phylogenetic distance of the genomes compared increases, the genes remaining together must belong to genes associated into operons in other prokaryotes regardless of the operon organization of the corresponding orthologous gene pair of E. coli. At the same time, we show that the ob-served tendencies of genes within operons to keep very short inter-genic distances in E. coli, is the same in any other prokaryote whose genome is currently available. We also show the relationship between our analyses of conserva-tion and the inference of functional relationships from genomic context.

Streptococcus pneumoniae is a major cause of disease and death that develops resistance to multiple antibiotics. DNA topoisomerase I (TopoI) is a novel pneumococcal drug target. TopoI is the sole type-I pneumococcal topoisomerase that regulates supercoiling homeostasis in this bacterium. In this study, a direct in vitro interaction between TopoI and RNA polymerase (RNAP) was detected by surface plasmon resonance. To understand the interplay between transcription and supercoiling regulation in vivo, genome-wide association of RNAP and TopoI was studied by ChIP-Seq. RNAP and TopoI were enriched at the promoters of 435 and 356 genes, respectively. Higher levels of expression were consistently measured in those genes whose promoters recruit both RNAP and TopoI, in contrast with those enriched in only one of them. Both enzymes occupied a narrow region close to the ATG codon. In addition, RNAP displayed a regular distribution throughout the coding regions. Likewise, the summits of peaks c...

Because binding of RNAP to misplaced sites could compromise the efficiency of transcription, natural selection for the optimization of gene expression should regulate the distribution of DNA motifs capable of RNAP-binding across the genome. Here we analyze the distribution of the 210 promoter motifs that bind the s 70 subunit of RNAP in 42 bacterial genomes. We show that selection on these motifs operates across the genome, maintaining an over-representation of 210 motifs in regulatory sequences while eliminating them from the nonfunctional and, in most cases, from the protein coding regions. In some genomes, however, 210 sites are over-represented in the coding sequences; these sites could induce pauses effecting regulatory roles throughout the length of a transcriptional unit. For nonfunctional sequences, the extent of motif underrepresentation varies across genomes in a manner that broadly correlates with the number of tRNA genes, a good indicator of translational speed and growt...

Motivation: Recently, a set of highly Conserved Non-coding Elements (CNE's) was derived from a Fugu-human genome comparison. We characterise some statistical features common to these elements in order to facilitate their identification in silico. Results: We found a pronounced pattern around the borders of CNEs: GC-rich flanking regions of low entropy compared to AT-rich, high entropy sequences within the borders. We also identified the most abundant significant motifs inside and adjacent to the borders of CNE's. At the borders, motifs are significantly clustered which points to their possible role as binding sites.

A major mode of gene expression evolution is based on changes in cis-regulatory elements (CREs) whose function critically depends on the presence of transcription factor-binding sites (TFBS). Because CREs experience extensive TFBS turnover even with conserved function, alignment-based studies of CRE sequence evolution are limited to very closely related species. Here, we propose an alternative approach based on a stochastic model of TFBS turnover. We implemented a maximum likelihood model that permits variable turnover rates in different parts of the species tree. This model can be used to detect changes in turnover rate as a proxy for differences in the selective pressures acting on TFBS in different clades. We applied this method to five TFBS in the fungi methionine biosynthesis pathway and three TFBS in the HoxA clusters of vertebrates. We find that the estimated turnover rate is generally high, with half-life ranging between ;5 and 150 My and a mode around tens of millions of years. This rate is consistent with the finding that even functionally conserved enhancers can show very low sequence similarity. We also detect statistically significant differences in the equilibrium densities of estrogen-and progesterone-response elements in the HoxA clusters between mammal and nonmammal vertebrates. Even more extreme clade-specific differences were found in the fungal data. We conclude that stochastic models of TFBS turnover enable the detection of shifts in the selective pressures acting on CREs in different organisms. The analysis tool, called CRETO (Cis-Regulatory Element TurnOver) can be downloaded from

A major mode of gene expression evolution is based on changes in cis-regulatory elements (CREs) whose function critically depends on the presence of transcription factor–binding sites (TFBS). Because CREs experience extensive TFBS turnover even with conserved function, alignment-based studies of CRE sequence evolution are limited to very closely related species. Here, we propose an alternative approach based on a stochastic model of TFBS turnover. We implemented a maximum likelihood model that permits variable turnover rates in different parts of the species tree. This model can be used to detect changes in turnover rate as a proxy for differences in the selective pressures acting on TFBS in different clades. We applied this method to five TFBS in the fungi methionine biosynthesis pathway and three TFBS in the HoxA clusters of vertebrates. We find that the estimated turnover rate is generally high, with half-life ranging between ∼5 and 150 My and a mode around tens of millions of ye...

Almost 50 years following the discovery of the prokaryotic operon, the functional relevance of gene order within operons remains unclear. In this work, we take advantage of the eroded genome of Mycobacterium leprae to add evidence supporting the notion that functionally less important genes have a tendency to be located at the end of its operons. M. leprae's genome includes 1133 pseudogenes and 1614 protein-coding genes and can be compared with the close genome of M. tuberculosis. Assuming M. leprae's pseudogenes to represent dispensable genes, we have studied the position of these pseudogenes in the operons of M. leprae and of their orthologs in M. tuberculosis. We observed that both tend to be located in the 3 0 (downstream) half of the operon (P-values of 0.03 and 0.18, respectively). Analysis of pseudogenes in all available prokaryotic genomes confirms this trend (P-value of 7.1 Â 10 À7). In a complementary analysis, we found a significant tendency for essential genes to be located at the 5 0 (upstream) half of the operon (P-value of 0.006). Our work provides an indication that, in prokarya, functionally less important genes have a tendency to be located at the end of operons, while more relevant genes tend to be located toward operon starts.

Promoter sequences of Escherichia coli were compiled and their transcribed regions characterized by site-specific cluster analysis. Here we report that transcribed regions contain a non-random distribution of A/T tracts with strongly preferred positions at 6 ± ± ± ± 3, 23 ± ± ± ± 3, 40 ± ± ± ± 2 and 56 ± ± ± ± 2. The maxima of this distribution follow an unusual periodicity (~17 bp) and are in phase with important promoter elements involved in interaction with RNA polymerase, while the value of periodicity numerically fits the spacer length between the canonical-35 and-10 elements. The possible functional significance of this newly described feature is discussed in the context of promoter clearance and transcription pausing.

Developmental programs are implemented by regulatory interactions between Transcription Factors (TFs) and their target genes, which remain poorly understood. While recent studies have focused on regulatory cascades of TFs that govern early development, little is known about how the ultimate effectors of cell differentiation are selected and controlled. We addressed this question during late Drosophila embryogenesis, when the finely tuned expression of the TF Ovo/Shavenbaby (Svb) triggers the morphological differentiation of epidermal trichomes. We defined a sizeable set of genes downstream of Svb and used in vivo assays to delineate 14 enhancers driving their specific expression in trichome cells. Coupling computational modeling to functional dissection, we investigated the regulatory logic of these enhancers. Extending the repertoire of epidermal effectors using genome-wide approaches showed that the regulatory models learned from this first sample are representative of the whole s...

Understanding how regulatory networks initiate, maintain and synchronise transcriptional states remains a fundamental goal of developmental biology. Complex patterns of spatiotemporal gene expression are generated through the combined inputs of signalling and transcriptional networks converging on cis-regulatory modules (CRMs). Detailed studies in Drosophila, using transgenic reporter assays and mutagenesis analysis, have dissected the regulatory logic of a number of CRMs. These data have recently been complemented by genomewide maps of transcription factor binding, revealing an unprecedented view of CRM occupancy and network complexity. The synthesis of data for three well-characterised Drosophila developmental networks reveals emerging themes at both a CRM and a cis-regulatory network level.

SinR is a transcription factor which controls expression of stress tolerance sin genes related to alternate development processes under stress condition. Identification of genome wide SinR-box motif and their regulated genes has not been worked out yet in Bradyrhizobium japonicum. For this, a weight matrix of 9 bp was developed from the known promoter sequences of Bacillus subtilis, which was then used for genome wide identification of co-regulated genes. The methodology first involves phylogenetic footprinting of SinR regulated genes and then construction of scoring matrix through ‘Consensus’ and confirmation through MEME & D-Matrix tools. Genomic prediction was done through ‘Patser’ program and confirmation through ‘PossumSearch’ program in Linux system. Results showed that all the 371 predicted genes belongs to 9 different functional classes, in which 221 found in operons with more than 80% Sin-box motif similarity. Similar approach can be used in other bacteria to explore hidden...

Because binding of RNAP to misplaced sites could compromise the efficiency of transcription, natural selection for the optimization of gene expression should regulate the distribution of DNA motifs capable of RNAP-binding across the genome. Here we analyze the distribution of the 210 promoter motifs that bind the s 70 subunit of RNAP in 42 bacterial genomes. We show that selection on these motifs operates across the genome, maintaining an over-representation of 210 motifs in regulatory sequences while eliminating them from the nonfunctional and, in most cases, from the protein coding regions. In some genomes, however, 210 sites are over-represented in the coding sequences; these sites could induce pauses effecting regulatory roles throughout the length of a transcriptional unit. For nonfunctional sequences, the extent of motif underrepresentation varies across genomes in a manner that broadly correlates with the number of tRNA genes, a good indicator of translational speed and growth rate. This suggests that minimizing the time invested in gene transcription is an important selective pressure against spurious binding. However, selection against spurious binding is detectable in the reduced genomes of host-restricted bacteria that grow at slow rates, indicating that components of efficiency other than speed may also be important. Minimizing the number of RNAP molecules per cell required for transcription, and the corresponding energetic expense, may be most relevant in slow growers. These results indicate that genome-level properties affecting the efficiency of transcription and translation can respond in an integrated manner to optimize gene expression. The detection of selection against promoter motifs in nonfunctional regions also confirms previous results indicating that no sequence may evolve free of selective constraints, at least in the relatively small and unstructured genomes of bacteria.

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that could be recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to see the generality of this pattern, we have analyzed 43 additional genomes belonging to most established bacterial phyla. Differential densities between regulatory and nonregulatory regions are detectable in most of the analyzed genomes, with the exception of those that have evolved toward extreme genome reduction. Thus, presence of this pattern follows that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is an outcome of the process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential distribution of promoter-like signals between regulatory and nonregulatory regions detected in large bacterial genomes confers a significant, although small, fitness advantage. This study paves the way for further identification of the specific types of selective constraints that affect the organization of regulatory regions and the overall distribution of promoter-like signals through more detailed comparative analyses among closely related bacterial genomes.

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions.

Motivation: Conserved non-coding elements (CNEs) represent an enigmatic class of genomic elements which, despite being extremely conserved across evolution, do not encode for proteins. Their functions are still largely unknown. Thus, there exists a need to systematically investigate their roles in genomes. Towards this direction, identifying sets of CNEs in a wide range of organisms is an important first step. Currently, there are no tools published in the literature for systematically identifying CNEs in genomes. Results: We fill this gap by presenting CNEFinder; a tool for identifying CNEs between two given DNA sequences with user-defined criteria. The results presented here show the tool's ability of identifying CNEs accurately and efficiently. CNEFinder is based on a k-mer technique for computing maximal exact matches. The tool thus does not require or compute whole-genome alignments or indexes, such as the suffix array or the Burrows Wheeler Transform (BWT), which makes it flexible to use on a wide scale.

The rich knowledge of operon organization in Escherichia coli, together with the completed chromosomal sequence of this bacterium, enabled us to perform an analysis of distances between genes and of functional relationships of adjacent genes in the same operon, as opposed to adjacent genes in different transcription units. We measured and demonstrated the expected tendencies of genes within operons to

The rich knowledge of operon organization in Escherichia coli, together with the completed chromosomal sequence of this bacterium, enabled us to perform an analysis of distances between genes and of functional relationships of adjacent genes in the same operon, as opposed to adjacent genes in different transcription units. We measured and demonstrated the expected tendencies of genes within operons to have much shorter intergenic distances than genes at the borders of transcription units. A clear peak at short distances between genes in the same operon contrasts with a flat frequency distribution of genes at the borders of transcription units. Also, genes in the same operon tend to have the same physiological functional class. The results of these analyses were used to implement a method to predict the genomic organization of genes into transcription units. The method has a maximum accuracy of 88% correct identification of pairs of adjacent genes to be in an operon, or at the borders of transcription units, and correctly identifies around 75% of the known transcription units when used to predict the transcription unit organization of the E. coli genome. Based on the frequency distance distributions, we estimated a total of 630 to 700 operons in E. coli. This step opens the possibility of predicting operon organization in other bacteria whose genome sequences have been finished.

Almost 50 years following the discovery of the prokaryotic operon, the functional relevance of gene order within operons remains unclear. In this work, we take advantage of the eroded genome of Mycobacterium leprae to add evidence supporting the notion that functionally less important genes have a tendency to be located at the end of its operons. M. leprae's genome includes 1133 pseudogenes and 1614 protein-coding genes and can be compared with the close genome of M. tuberculosis. Assuming M. leprae's pseudogenes to represent dispensable genes, we have studied the position of these pseudogenes in the operons of M. leprae and of their orthologs in M. tuberculosis. We observed that both tend to be located in the 3 0 (downstream) half of the operon (P-values of 0.03 and 0.18, respectively). Analysis of pseudogenes in all available prokaryotic genomes confirms this trend (P-value of 7.1 Â 10 À7 ). In a complementary analysis, we found a significant tendency for essential genes to be located at the 5 0 (upstream) half of the operon (P-value of 0.006). Our work provides an indication that, in prokarya, functionally less important genes have a tendency to be located at the end of operons, while more relevant genes tend to be located toward operon starts.

With operon predictions based on conservation of gene order and 330 Prokaryotic genomes available, I am able to show that in most of the genomes analyzed about 70% of the genes in operons are separated by distances of -20 to 30 base pairs. Most of the differences in this tendency might be related to the appearance of signals inside the operons. However, a closer look at the extreme exceptions confirms that annotation problems are partly responsible for inter-genic distance distributions that deviate from that of operons in Escherichia coli K12. I also argue that the inter-genic distances of adjacent genes in different transcription units (transcription unit boundaries or TUBs) should be expected to be more variable than those for genes in the same operon. Using phylogenetic profiles I show that predictions adjusted on a per genome basis might help increase the accuracy of operon predictions. Improvements in automated annotation might be necessary to fully evaluate the overall tendencies of genes in operons towards short inter-genic distances, and to better understand differences in regulatory complexity across Prokaryotes.

The prediction of the transcription unit organization of genomes is an important clue in the inference of functional relationships of genes, the interpretation and evaluation of transcriptome experiments, and the overall inference of the regulatory networks governing the expression of genes in response to the environment. Though several methods have been devised to predict operons, most need a high characterization of the genome analysed. Loglikelihoods derived from inter-genic distance distributions work surprisingly well to predict operons in Escherichia coli and are available for any genome as soon as the gene sets are predicted. Results: Here we provide evidence that the very same method is applicable to any prokaryotic genome. First, the method has the same efficiency when evaluated using a collection of experimentally known operons of Bacillus subtilis. Second, operons among most if not all prokaryotes seem to have the same tendencies to keep short distances between their genes, the most frequent distances being the overlaps of four and one base pairs. The universality of this structural feature allows us to predict the organization of transcription units in all prokaryotes. Third, predicted operons contain a higher proportion of genes with related phylogenetic profiles and conservation of adjacency than predicted borders of transcription units.

We have previously demonstrated that genes within experimentally characterized operons of Escherichia coli are conserved together in other genomes more frequently than genes at the borders of transcription units. Here we expand the analyses and show that, as the phylogenetic distance of the genomes compared increases, the genes remaining together must belong to genes associated into operons in other prokaryotes regardless of the operon organization of the corresponding orthologous gene pair of E. coli. At the same time, we show that the observed tendencies of genes within operons to keep very short inter-genic distances in E. coli, is the same in any other prokaryote whose genome is currently available. We also show the relationship between our analyses of conservation and the inference of functional relationships from genomic context.

The phenomenon of functional site turnover has important implications for the study of regulatory region evolution, such as for promoter sequence alignments and transcription factor binding site (TFBS) identification. At present, it remains difficult to estimate TFBS turnover rates on real genomic sequences, as reliable mappings of functional sites across related species are often not available. As an alternative, we introduce a flexible new simulation system, Phylogenetic Simulation of Promoter Evolution (PSPE), designed to study functional site turnovers in regulatory sequences. Using PSPE, we study replacement turnover rates of different individual TFBSs and simple modules of two sites under neutral evolutionary functional constraints. We find that TFBS replacement turnover can happen rapidly in promoters, and turnover rates vary significantly among different TFBSs and modules. We assess the influence of different constraints such as insertion/deletion rate and translocation dist...

Gene expression evolution occurs through changes in cis-or trans-regulatory elements or both. Interactions between transcription factors (TFs) and their binding sites (TFBSs) constitute one of the most important points where these two regulatory components intersect. In this study, we investigated the evolution of TFBSs in the promoter regions of different Saccharomyces strains and species. We divided the promoter of a gene into the proximal region and the distal region, which are defined, respectively, as the 200-bp region upstream of the transcription starting site and as the 200-bp region upstream of the proximal region. We found that the predicted TFBSs in the proximal promoter regions tend to be evolutionarily more conserved than those in the distal promoter regions. Additionally, Saccharomyces cerevisiae strains used in the fermentation of alcoholic drinks have experienced more TFBS losses than gains compared with strains from other environments (wild strains, laboratory strains, and clinical strains). We also showed that differences in TFBSs correlate with the cis component of gene expression evolution between species (comparing S. cerevisiae and its sister species Saccharomyces paradoxus) and within species (comparing two closely related S. cerevisiae strains).

Background: Bacterial promoters, which increase the efficiency of gene expression, differ from other promoters by several characteristics. This difference, not yet widely exploited in bioinformatics, looks promising for the development of relevant computational tools to search for strong promoters in bacterial genomes.

The database PRODORIC aims to systematically organize information on prokaryotic gene expression, and to integrate this information into regulatory networks. The present version focuses on pathogenic bacteria such as Pseudomonas aeruginosa. PRODORIC links data on environmental stimuli with trans-acting transcription factors, cis-acting promoter elements and regulon definition. Interactive graphical representations of operon, gene and promoter structures including regulator-binding sites, transcriptional and translational start sites, supplemented with information on regulatory proteins are available at varying levels of detail. The data collection provided is based on exhaustive analyses of scientific literature and computational sequence prediction. Included within PRODORIC are tools to define and predict regulator binding sites. It is accessible at http://prodoric.tu-bs.de.

Genomics, which has been identified as the science of the century, is dramatically changing the historically weak relationship between experimental and theoretical biology. The addition to the Journal of Bacteriology of a section for computational biology marks a turning point in the history of this dialogue. This minireview is focused on the computational biology of gene regulation in bacteria, defined as the extensive use of bioinformatics tools to increase our understanding of the regulation of gene expression. The study of gene regulation has been radically affected by the elucidation of full-genome DNA sequences and the subsequent development of high-throughput methodologies for deciphering their expression. Before the genomics era, most research was focused on individual biological systems. A large number of our colleagues, contributors to this journal, have devoted much of their academic careers to the understanding of individual regulatory units describing operons, regulators, and promoters and their roles in the physiology of the cell. These contributions have provided fundamental information to support the most recent efforts for the integrative knowledge of the cell that all the genomics sciences are achieving. Genomics offers for the microbiologist studying gene regulation the opportunity to understand individual systems in the context of the whole cell. These integrative sciences have also changed the landscape of data available for new discoveries in the evolution of gene regulation. The major challenge of the genomics era is dealing with large amounts of data at all molecular levels and being able to generate integrated biological knowledge from the data. Bioinformatics is essential to progress in this direction, as it provides what is necessary to deal with large amounts of data: databases, algorithms to generate genomic answers to standard questions, overviews, and navigation capabilities, as well as statistical methods to perform and validate analyses. Current knowledge of gene regulation in prokaryotes is quite diverse, from the constantly increasing number of full genome sequences for which very little experimental work has been performed, including the many genomes that cannot yet be grown in the laboratory or the little-studied archaea, to the few highly characterized bacterial genomes, such as those of Bacillus subtilis and Pseudomonas aeruginosa, with Escherichia coli K-12 being by far the best-known bacterium and free-living organism. Figure 1 shows this strongly unequal distribution of knowledge, with the number of publications on gene regulation , as an example, for the different microbial genomes. The first exhaustive historical set of regulated promoters and their associated transcription factors (TFs) and TF DNA-binding sites (TFBSs) gathered around 120 70 and 54 promoters of E. coli K-12 (16, 29). This information and the experience obtained were the seeds for what is now RegulonDB (http: //regulondb.ccg.unam.mx/), the original source of expert cu-rated knowledge on the regulation of transcription initiation and operon organization in E. coli K-12. It contains what is currently the major electronically encoded regulatory network for any free-living organism (25). This information is also contained in EcoCyc, the E. coli model organism database, with added curated knowledge on metabolism and transport (http: //ecocyc.org/). We estimate that currently around 25% of the interactions of the full cellular regulatory network of transcription initiation have been assembled. RegulonDB should not be conceived of as a database, but as an environment for genomic regulatory investigations, linked to bioinformatics tools that facilitate analyses of upstream regions, together with data sets and tools for microarray analyses and, more recently, direct access to full papers supporting its knowledge. We are not only curating up-to-date original papers, but have also initiated " active annotation, " to use Jean-Michelle Claverie's terminology , to more precisely experimentally map promoters by using a high-throughput strategy. This minireview has been organized taking into account the fact that most of the readers of the Journal of Bacteriology are experimentalists. We start with a few examples of lessons on gene regulation from bioinformatics, focusing on promoters, their definition and regulation, and operon structure. The second section summarizes how RegulonDB has been useful to experimentalists, as well as its role as the " gold standard " for implementing bioinformatics predictive methods, topological analyses of the network, and models of the cell. The last section offers a compendium of links to bioinformatics resources on gene regulation in bacteria, illustrating their usage with flowcharts associated with questions on the regulation of gene

The complete sequencing of the human genome shows that only 1% of the entire genome encodes for proteins. The major part of the genome is made up of non-coding DNA, regulatory elements and junk DNA. Transcriptional regulation plays a central role in a multitude of critical cellular processes and responses, and it is a central force in the development and differentiation of multicellular organisms. Identifying regulatory elements is one of the major tasks in this challenge. To accomplish this task, we developed a solid and simple suite that allows direct access to genomic database and immediate result check. We introduce COMPASSS (COMplex PAttern of Sequence Search Software), a simple and effective tool for motif search in entire genomes. Motifs can be partially degenerated and interrupted by spacers of variable length. Results: We demonstrate through real biological data mining the simplicity and robustness of this tool. The test was performed on two well-known protein domains and a highly variable cis-acting element. COMPASSS successfully identifies both protein domains and cis-acting semi-conserved elements.

Developmental programs are implemented by regulatory interactions between Transcription Factors (TFs) and their target genes, which remain poorly understood. While recent studies have focused on regulatory cascades of TFs that govern early development, little is known about how the ultimate effectors of cell differentiation are selected and controlled. We addressed this question during late Drosophila embryogenesis, when the finely tuned expression of the TF Ovo/Shavenbaby (Svb) triggers the morphological differentiation of epidermal trichomes. We defined a sizeable set of genes downstream of Svb and used in vivo assays to delineate 14 enhancers driving their specific expression in trichome cells. Coupling computational modeling to functional dissection, we investigated the regulatory logic of these enhancers. Extending the repertoire of epidermal effectors using genome-wide approaches showed that the regulatory models learned from this first sample are representative of the whole s...

Enhancers lie at the heart of transcriptional and developmental gene regulation. Therefore, changes in enhancer sequences usually
disrupt the target gene expression and result in disease phenotypes. Despite the well-established role of enhancers in development
and disease, evolutionary sequence studies are lacking. The current study attempts to unravel the puzzle of bony vertebrates’
conserved noncoding elements (CNE) enhancer evolution. Bayesian phylogenetics of enhancer sequences spotlights promising
interordinal relationships among placental mammals, proposing a closer relationship between humans and laurasiatherians while
placing rodents at the basal position. Clock-based estimates of enhancer evolution provided a dynamic picture of interspecific rate
changes across the bony vertebrate lineage. Moreover, coelacanth in the study augmented our appreciation of the vertebrate cis regulatory
evolution during water–land transition. Intriguingly, we observed a pronounced upsurge in enhancer evolution in land dwelling
vertebrates. These novel findings triggered us to further investigate the evolutionary trend of coding as well as CNE
non enhancer repertoires, to highlight the relative evolutionary dynamics of diverse genomic landscapes. Surprisingly, the evolutionary
rates of enhancer sequences were clearly at odds with those of the coding and the CNE non enhancer sequences during vertebrate
adaptation to land, with land vertebrates exhibiting significantly reduced rates of coding sequence evolution in comparison to their
fast evolving regulatory landscape. The observed variation in tetrapod cis-regulatory elements caused the fine-tuning of associated
gene regulatory networks. Therefore, the increased evolutionary rate of tetrapods’ enhancer sequences might be responsible for the
variation in developmental regulatory circuits during the process of vertebrate adaptation to land.

Operons are a major feature of all prokaryotic genomes, but how and why operon structures vary is not well understood. To elucidate the life-cycle of operons, we compared gene order between Escherichia coli K12 and its relatives and identified the recently formed and destroyed operons in E. coli. This allowed us to determine how operons form, how they become closely spaced, and how they die. Our findings suggest that operon evolution may be driven by selection on gene expression patterns. First, both operon creation and operon destruction lead to large changes in gene expression patterns. For example, the removal of lysA and ruvA from ancestral operons that contained essential genes allowed their expression to respond to lysine levels and DNA damage, respectively. Second, some operons have undergone accelerated evolution, with multiple new genes being added during a brief period. Third, although genes within operons are usually closely spaced because of a neutral bias toward deletio...

Background Transcription is the first step in cellular information processing. It is regulated by cis-acting elements such as promoters and operators in the DNA, and trans-acting elements such as transcription factors and sigma factors. Identification of cis-acting regulatory elements on a genomic scale requires computational analysis. Results We have used oligonucleotide profiling to predict regulatory regions in a bacterial genome. The method has been applied to the Escherichia coli K12 genome and the results analyzed. The information content of the putative regulatory oligonucleotides so predicted is validated through intra-genomic analyses, correlations with experimental data and inter-genome comparisons. Based on the results we have proposed a model for the bacterial promoter. The results show that the method is capable of identifying, in the E.coli genome, cis-acting elements such as TATAAT (sigma70 binding site), CCCTAT (1 base relative of sigma32 binding site), CTATNN (LexA binding site), AGGA-containing hexanucleotides (Shine Dalgarno consensus) and CTAG-containing hexanucleotides (core binding sites for Trp and Met repressors). Conclusion The method adopted is simple yet effective in predicting upstream regulatory elements in bacteria. It does not need any prior experimental data except the sequence itself. This method should be applicable to most known genomes. Profiling, as applied to the E.coli genome, picks up known cis-acting and regulatory elements. Based on the profile results, we propose a model for the bacterial promoter that is extensible even to eukaryotes. The model is that the core promoter lies within a plateau of bent AT-rich DNA. This bent DNA acts as a homing segment for the sigma factor to recognize the promoter. The model thus suggests an important role for local landscapes in prokaryotic and eukaryotic gene regulation.

Background: Developmental programs are implemented by regulatory interactions between Transcription Factors (TFs) and their target genes, which remain poorly understood. While recent studies have focused on regulatory cascades of TFs that govern early development, little is known about how the ultimate effectors of cell differentiation are selected and controlled. We addressed this question during late Drosophila embryogenesis, when the finely tuned expression of the TF Ovo/Shavenbaby (Svb) triggers the morphological differentiation of epidermal trichomes. Results: We defined a sizeable set of genes downstream of Svb and used in vivo assays to delineate 14 enhancers driving their specific expression in trichome cells. Coupling computational modeling to functional dissection, we investigated the regulatory logic of these enhancers. Extending the repertoire of epidermal effectors using genome-wide approaches showed that the regulatory models learned from this first sample are representative of the whole set of trichome enhancers. These enhancers harbor remarkable features with respect to their functional architectures, including a weak or non-existent clustering of Svb binding sites. The in vivo function of each site relies on its intimate context, notably the flanking nucleotides. Two additional cis-regulatory motifs, present in a broad diversity of composition and positioning among trichome enhancers, critically contribute to enhancer activity.

Background Transcription is the first step in cellular information processing. It is regulated by cis-acting elements such as promoters and operators in the DNA, and trans-acting elements such as transcription factors and sigma factors. Identification of cis-acting regulatory elements on a genomic scale requires computational analysis. Results We have used oligonucleotide profiling to predict regulatory regions in a bacterial genome. The method has been applied to the Escherichia coli K12 genome and the results analyzed. The information content of the putative regulatory oligonucleotides so predicted is validated through intra-genomic analyses, correlations with experimental data and inter-genome comparisons. Based on the results we have proposed a model for the bacterial promoter. The results show that the method is capable of identifying, in the E.coli genome, cis-acting elements such as TATAAT (sigma70 binding site), CCCTAT (1 base relative of sigma32 binding site), CTATNN (LexA binding site), AGGA-containing hexanucleotides (Shine Dalgarno consensus) and CTAG-containing hexanucleotides (core binding sites for Trp and Met repressors). Conclusion The method adopted is simple yet effective in predicting upstream regulatory elements in bacteria. It does not need any prior experimental data except the sequence itself. This method should be applicable to most known genomes. Profiling, as applied to the E.coli genome, picks up known cis-acting and regulatory elements. Based on the profile results, we propose a model for the bacterial promoter that is extensible even to eukaryotes. The model is that the core promoter lies within a plateau of bent AT-rich DNA. This bent DNA acts as a homing segment for the sigma factor to recognize the promoter. The model thus suggests an important role for local landscapes in prokaryotic and eukaryotic gene regulation.

Abstract The evolution of morphological characters is mediated by the evolution of developmental genes. Evolutionary changes can either affect cis–regulatory elements, leading to differences in their temporal and spatial regulation, or affect the coding region. Although there is ample evidence for the importance of cis–regulatory evolution, it has only recently been shown that transcription factors do not remain functionally equivalent during evolution.

Abstract The evolution of morphological characters is mediated by the evolution of developmental genes. Evolutionary changes can either affect cis–regulatory elements, leading to differences in their temporal and spatial regulation, or affect the coding region. Although there is ample evidence for the importance of cis–regulatory evolution, it has only recently been shown that transcription factors do not remain functionally equivalent during evolution.