RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more

Abstract

This article summarizes our progress with RegulonDB (http://regulondb.ccg.unam.mx/) during the past 2 years. We have kept up-to-date the knowledge from the published literature regarding transcriptional regulation in Escherichia coli K-12. We have maintained and expanded our curation efforts to improve the breadth and quality of the encoded experimental knowledge, and we have implemented criteria for the quality of our computational predictions. Regulatory phrases now provide high-level descriptions of regulatory regions. We expanded the assignment of quality to various sources of evidence, particularly for knowledge generated through high-throughput (HT) technology. Based on our analysis of most relevant methods, we defined rules for determining the quality of evidence when multiple independent sources support an entry. With this latest release of RegulonDB, we present a new highly reliable larger collection of transcription start sites, a result of our experimental HT genome-wide efforts. These improvements, together with several novel enhancements (the tracks display, uploading format and curational guidelines), address the challenges of incorporating HT-generated knowledge into RegulonDB. Information on the evolutionary conservation of regulatory elements is also available now. Altogether, RegulonDB version 8.0 is a much better home for integrating knowledge on gene regulation from the sources of information currently available.

Figure 1.

Analysis of TFBSs to improve the quality of PWMs in the RegulonDB database. OxyR binds in tandem, covering regions of ∼40 bp (a). We identified within these regions, two inverted-repeat motifs of 17 bp, separated by 5 bp (b). Therefore, we now propose a new consensus sequence, GATAGGTTnAACCTATC, for the binding sites of OxyR. This new annotation has improved the quality of the matrices (b) and, therefore, also the predictions of binding sites for OxyR.

Figure 2.

Overview of the GU of the Fur TF. In the presence of Fe⁺, Fur represses genes involved in transport and release of Fe⁺ from siderophores and genes for biosynthesis and assembly of FeS clusters; in addition, it activates genes involved in Fe⁺ storage and activates/represses genes that encode proteins that contain Fe⁺ or a group heme as a cofactor. In the presence of the signal, Fur also regulates transcription of nine TFs, the σ¹⁹ and σ³⁸ factors and a regulatory sRNA, RhyB, submaps of which are depicted as dark gray squares that can be expanded to see their corresponding GU. In addition, Fur regulates genes that encode metal-binding proteins (other than Fe⁺) and other proteins that apparently have no direct relationship with Fe⁺ or other metals.

Figure 3.

The [CRP,+] regulatory phrase. The graph shows sites of the [CRP,+] phrase for five promoters, and the table includes all additional sites that regulate these promoters. Each promoter name is a link to the page in RegulonDB presenting all phrases for that promoter. Proximal sites are those within the interval from −93 to +20, from which the TF can directly interact with RNA polymerase. All other sites are considered remote, either upstream or downstream.

Figure 4.

Schematic drawing of the classification of evidence in RegulonDB. Evidence codes for classical experiments: BCE, binding of cellular extracts; IMP, inferred by mutant phenotype; IGI, inferred by genetic interaction; GEA, gene expression analysis; FP, footprinting; SM, site mutation; BPP, binding of purified protein; APPH, assay with protein purified to homogeneity; RPF, RNA-polymerase footprinting; TA, in vitro transcription assays; TIM, transcription initiation mapping; PM, effect of polar mutation on neighboring genes; LTED, length of transcript experimentally determined; BTEI, identification of the boundaries of a transcript, ITCR, inferred through co-regulation; Evidence codes for HT experiments; gSELEX, genomic SELEX; ROMA, run-off transcription microarray analysis; ChIP, chromatin immunoprecipitation; GEA, microarray or RNA-seq gene expression analysis; IMP, inferred from mutant phenotype; RS, RNA-seq; RS-EPT-CBR, RNA-seq with at least two different enrichment strategies for primary transcripts and consistent biological replicates; RS-EPT-ENCG-CBR, RNA-seq with at least two different enrichment strategies for primary transcripts and evidence for a ncRNA, consistent biological replicates; MSI, mapping of signal intensities by microarray analysis or RNA-seq; PET, paired-end di-tagging; MSI-ESG, mapping of signal intensities and evidence for a single gene; Computational approaches: AIBSCS, automated inference based on similarity to consensus sequences; AIPP, automated inference of promoter position; ICWHO, inferred computationally without human oversight; IHBCE, inferred by a human based on computational evidence; PAGTSBP, products of adjacent genes in the same biological process; AISGDTU, automated inference that a single-gene direction is a TU; EC, evolutionary conservation; Human inference: HIBSCS, human inference based on similarity to consensus sequences; AS, author statements; HIPP, human inference on promoter position; IC, inferred by curator. CHIP-SV describes statistical validation of ChIP data sets. CV(A/B) describes independent cross-validation of evidence A and B.

Figure 5.

Evolutionary conservation of regulatory interactions and promoters. The figure shows the conservation of both promoters and regulatory interactions in a subset of orthologous regulatory regions corresponding to nhaA. The complete set can be directly searched in RegulonDB. Orthologs were selected by using a bidirectional best hit method (35), and sequences are masked to eliminate sequence redundancy to assess an unbiased conservation score. Nonetheless, the maps like the one shown here show all the sites found in all orthologous regions including masked sequences. Blue boxes correspond to the detected binding sites for the NhaR TF; the width of the boxes correspond to the scores of the sites, with the highest obtained score indicated in the symbol key (11.4). Red vertical lines indicate the predicted position for the TSSs based on identification of the promoter −10 and −35 boxes. The zero coordinate is that of the beginning of the gene.