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The REDfly database provides a comprehensive curation of experimentally-validated Drosophila transcriptional cis-regulatory elements and includes information on DNA sequence, experimental evidence, patterns of regulated gene expression, and more. Now in its thirteenth year, REDfly has grown to over 23 000 records of tested reporter gene constructs and 2200 tested transcription factor binding sites. Recent developments include the start of curation of predicted cis-regulatory modules in addition to experimentally-verified ones, improved search and filtering, and increased interaction with the authors of curated papers. An expanded data model that will capture information on temporal aspects of gene regulation, regulation in response to environmental and other non-developmental cues, sexually dimorphic gene regulation, and non-endogenous (ectopic) aspects of reporter gene expression is under development and expected to be in place within the coming year. REDfly is freely accessible at http://redfly.ccr.buffalo.edu, and news about database updates and new features can be followed on Twitter at @REDfly_database.

Chromatin domain boundary elements prevent inappropriate interaction between distant or closely spaced regulatory elements and restrict enhancers and silencers to correct target promoters. In spite of having such a general role and expected frequent occurrence genome wide, there is no DNA sequence analysis based tool to identify boundary elements. Here, we report chromatin domain Boundary Element Search Tool (cdBEST), to identify boundary elements. cdBEST uses known recognition sequences of boundary interacting proteins and looks for ‘motif clusters’. Using cdBEST, we identified boundary sequences across 12 Drosophila species. Of the 4576 boundary sequences identified in Drosophila melanogaster genome, >170 sequences are repetitive in nature and have sequence homology to transposable elements. Analysis of such sequences across 12 Drosophila genomes showed that the occurrence of repetitive sequences in the context of boundaries is a common feature of drosophilids. We use a variety of genome organization criteria and also experimental test on a subset of the cdBEST boundaries in an enhancer-blocking assay and show that 80% of them indeed function as boundaries in vivo. These observations highlight the role of cdBEST in better understanding of chromatin domain boundaries in Drosophila and setting the stage for comparative analysis of boundaries across closely related species.

Drosophila melanogaster has one of the best characterized metazoan genomes in terms of functionally annotated regulatory elements. To explore how these elements contribute to gene regulation in the context of gene regulatory networks, we need convenient tools to identify the proteins that bind to them. Here, we present the development and validation of a highly automated protein-DNA interaction detection method, enabling the high-throughput yeast one-hybrid-based screening of DNA elements versus an array of full-length, sequence-verified clones containing 647 (over 85%) of predicted Drosophila transcription factors (TFs). Using six well-characterized regulatory elements (82 bp – 1kb), we identified 33 TF-DNA interactions of which 27 are novel. To simultaneously validate these interactions and locate their binding sites of involved TFs, we implemented a novel microfluidics-based approach that enables us to conduct hundreds of gel shift-like assays at once, thus allowing the retrieval of DNA occupancy data for each TF throughout the respective target DNA elements. Finally, we biologically validate several interactions and specifically identify two novel regulators of sine oculis gene expression and hence eye development.

Genome Surveyor 2.0 is a web-based tool for discovery and analysis of cis-regulatory elements in Drosophila, built on top of the GBrowse genome browser for convenient visualization. Genome Surveyor was developed as a tool for predicting transcription factor (TF) binding targets and cis-regulatory modules (CRMs/enhancers), based on motifs representing experimentally determined DNA binding specificities. Since its first publication, we have added substantial new functionality (e.g. phylogenetic averaging of motif scores from multiple species, and a novel CRM discovery technique), increased the number of supported motifs about 4-fold (from ∼100 to ∼400), added provisions for evolutionary comparison across many more Drosophila species (from 2 to 12), and improved the user-interface. The server is free and open to all users, and there is no login requirement. Address: http://veda.cs.uiuc.edu/gs.

The REDfly database of Drosophila transcriptional cis-regulatory elements provides the broadest and most comprehensive available resource for experimentally validated cis-regulatory modules and transcription factor binding sites among the metazoa. The third major release of the database extends the utility of REDfly as a powerful tool for both computational and experimental studies of transcription regulation. REDfly v3.0 includes the introduction of new data classes to expand the types of regulatory elements annotated in the database along with a roughly 40% increase in the number of records. A completely redesigned interface improves access for casual and power users alike; among other features it now automatically provides graphical views of the genome, displays images of reporter gene expression and implements improved capabilities for database searching and results filtering. REDfly is freely accessible at http://redfly.ccr.buffalo.edu.

Arabidopsis TCH4 gene plays an important role in the biological processes related to plant secondary growth, resistance to pathogen, and adaptation to environmental stresses. It is up-regulated by various hormonal, environmental, and mechanical stimuli. Here, we identified 9 transcriptional regulatory elements from TCH4 promoter by bioinformatics approach. In which, 4 elements have been reported previously, and 5 elements are newly identified in this study. All of the identified elements contain the sequences of known cis-elements. Especially, their distribution along some co-expressed gene promoters and the orthologous promoters is typically clustered and syntenic. Based on our predictions and the information of known cis-elements, a model representing the transcriptional regulation mechanism was proposed for TCH4 gene in response to hormonal, mechanical, and environmental stimuli.

Motivation: Predicting cis-regulatory modules (CRMs) in higher eukaryotes is a challenging computational task. Commonly used methods to predict CRMs based on the signal of transcription factor binding sites (TFBS) are limited by prior information about transcription factor specificity. More general methods that bypass the reliance on TFBS models are needed for comprehensive CRM prediction. Results: We have developed a method to predict CRMs called CisPlusFinder that identifies high density regions of perfect local ungapped sequences (PLUSs) based on multiple species conservation. By assuming that PLUSs contain core TFBS motifs that are locally overrepresented, the method attempts to capture the expected features of CRM structure and evolution. Applied to a benchmark dataset of CRMs involved in early Drosophila development, CisPlusFinder predicts more annotated CRMs than all other methods tested. Using the REDfly database, we find that some ‘false positive’ predictions in the benchmark dataset correspond to recently annotated CRMs. Our work demonstrates that CRM prediction methods that combine comparative genomic data with statistical properties of DNA may achieve reasonable performance when applied genome-wide in the absence of an a priori set of known TFBS motifs. Availability: The program CisPlusFinder can be downloaded at . All software is licensed under the Lesser GNU Public License (LGPL). Contact: nora.pierstorff@uni-koeln.de. Supplementary information: Supplementary data are available at Bioinformatics online.

Transcriptional regulation is a major tier in the periodic engine that mobilizes cell cycle progression. The availability of complete genome sequences of multiple organisms holds promise for significantly improving the specificity of computational identification of functional elements. Here, we applied a comparative genomics analysis to decipher transcriptional regulatory elements that control cell cycle phasing. We analyzed genome-wide promoter sequences from 12 organisms, including worm, fly, fish, rodents and human, and identified conserved transcriptional modules that determine the expression of genes in specific cell cycle phases. We demonstrate that a canonical E2F signal encodes for expression highly specific to the G1/S phase, and that a cis-regulatory module comprising CHR-NF-Y elements dictates expression that is restricted to the G2 and G2/M phases. B-Myb binding site signatures occur in many of the CHR-NF-Y target genes, suggesting a specific role for this triplet in the regulation of the cell cycle transcriptional program. Remarkably, E2F signals are conserved in promoters of G1/S genes in all organisms from worm to human. The CHR-NF-Y module is conserved in promoters of G2/M regulated genes in all analyzed vertebrates. Our results reveal novel modules that determine specific cell cycle phasing, and identify their respective putative target genes with remarkably high specificity.

While the number of genome-wide, in vivo transcription factor binding datasets is growing, yielding greater insight into the role of regulatory DNA in development, evolution and disease, it is difficult to tease apart signal from noise and identify truly functional binding events. Comparative studies of transcription factor binding between closely related species offer one way to combat this problem, as functionally important aspects of enhancer architecture tend to be constrained by natural selection. Here we review the current field in the area of in vivo transcription factor binding in Drosophila, illustrating how evolutionary studies within the drosophilids are helping to unravel the complexity of the genomic regulatory code. A number of techniques exist for studying transcription factor binding on a genome-wide scale, including ChIP-chip, ChIP-seq and DamID; we touch on these and address the challenges and advantages of each with regard to working on non-model species. We also describe major findings in the field so far, focusing on comparative studies of the developmental regulatory network, the logic of combinatorial binding and the evolutionary properties of noncoding DNA. Finally, we examine how insights from Drosophila compare with similar studies in the vertebrates and address some open questions that have been raised by studies conducted thus far.

Extensive genetic and biochemical analysis of Drosophila melanogaster has made this system an important model for characterization of transcriptional regulatory elements and factors. Given the striking conservation of transcriptional controls in metazoans, general principles derived from studies of Drosophila are expected to continue to illuminate transcriptional regulation in other systems, including vertebrates. With improvement in technologies for genetic manipulation of insects, research in Drosophila will also aid the design of systems for controlled expression of genes in other hosts. This review focuses on recent advances from Drosophila in analysis of the functional components of transcriptional switches, including basal promoters, enhancers, boundary elements, and maintenance elements.

Various cis-regulatory module (CRM) predictors have been proposed in the last decade. Several well-established CRM predictors adopted different categories of prediction strategies, including window clustering, probabilistic modeling and phylogenetic footprinting. Appropriate integration of them has a potential to achieve high quality CRM prediction. This study analyzed four existing CRM predictors (ClusterBuster, MSCAN, CisModule and MultiModule) to seek a predictor combination that delivers a higher accuracy than individual CRM predictors. 465 CRMs across 140 Drosophila melanogaster genes from the REDfly database were used to evaluate the integrated CRM predictor proposed in this study. The results show that four predictor combinations achieved superior performance than the best individual CRM predictor.

Summary: Bioinformatics studies of transcriptional regulation in the metazoa are significantly hindered by the absence of readily available data on large numbers of transcriptional cis-regulatory modules (CRMs). Even the richly annotated Drosophila melanogaster genome lacks extensive CRM information. We therefore present here a database of Drosophila CRMs curated from the literature complete with both DNA sequence and a searchable description of the gene expression pattern regulated by each CRM. This resource should greatly facilitate the development of computational approaches to CRM discovery as well as bioinformatics analyses of regulatory sequence properties and evolution. Availability: Contact: mshalfon@buffalo.edu

Transcriptional enhancers are a primary mechanism by which tissue-specific gene expression is achieved. Despite the importance of these regulatory elements in development, responses to environmental stresses, and disease, testing enhancer activity in animals remains tedious, with a minority of enhancers having been characterized. Here, we have developed ‘enhancer-FACS-Seq’ (eFS) technology for highly parallel identification of active, tissue-specific enhancers in Drosophila embryos. Analysis of enhancers identified by eFS to be active in mesodermal tissues revealed enriched DNA binding site motifs of known and putative, novel mesodermal transcription factors (TFs). Naïve Bayes classifiers using TF binding site motifs accurately predicted mesodermal enhancer activity. Application of eFS to other cell types and organisms should accelerate the cataloging of enhancers and understanding how transcriptional regulation is encoded within them.

The faithful execution of biological processes requires a precise and carefully orchestrated set of steps that depend on the proper spatial and temporal expression of genes. Here we review the various classes of transcriptional regulatory elements (core promoters, proximal promoters, distal enhancers, silencers, insulators/boundary elements, and locus control regions) and the molecular machinery (general transcription factors, activators, and coactivators) that interacts with the regulatory elements to mediate precisely controlled patterns of gene expression. The biological importance of transcriptional regulation is highlighted by examples of how alterations in these transcriptional components can lead to disease. Finally, we discuss the methods currently used to identify transcriptional regulatory elements, and the ability of these methods to be scaled up for the purpose of annotating the entire human genome.

Bioinformatics analysis of transcriptional control is guided by knowledge of the characteristics of cis-regulatory regions or enhancers. Features such as clustering of binding sites and co-occurrence of binding sites have aided enhancer identification, but quantitative predictions of enhancer function are not yet generally feasible. To facilitate the analysis of regulatory sequences in Drosophila melanogaster, we identified quantitative parameters that affect the activity of short-range transcriptional repressors, proteins that play key roles in development. In addition to the previously noted distance dependence, repression is strongly influenced by the stoichiometry, affinity, spacing, and arrangement of activator binding sites. Repression is insensitive to the type of activation domain, suggesting that short-range repression may primarily affect activators at the level of DNA binding. The activity of several short-range, but not long-range, repressors is circumscribed by the same quantitative parameters. This cis-regulatory “grammar” may aid the identification of enhancers regulated by short-range repressors and facilitate bioinformatic prediction of the functional output of transcriptional regulatory sequences.

Summary: Despite increasing numbers of computational tools developed to predict cis-regulatory sequences, the availability of high-quality datasets of transcription factor binding sites limits advances in the bioinformatics of gene regulation. Here we present such a dataset based on a systematic literature curation and genome annotation of DNase I footprints for the fruitfly, Drosophila melanogaster. Using the experimental results of 201 primary references, we annotated 1367 binding sites from 87 transcription factors and 101 target genes in the D.melanogaster genome sequence. These data will provide a rich resource for future bioinformatics analyses of transcriptional regulation in Drosophila such as constructing motif models, training cis-regulatory module detectors, benchmarking alignment tools and continued text mining of the extensive literature on transcriptional regulation in this important model organism. Availability: http://www.flyreg.org/ Contact: cbergman@gen.cam.ac.uk

Background The core promoter region plays a critical role in the regulation of eukaryotic gene expression. We have determined the non-random distribution of DNA sequences relative to the transcriptional start site in Drosophila melanogaster promoters to identify sequences that may be biologically significant. We compare these results with those obtained for human promoters.