TRANSFAC, TRRD (Transcription Regulatory Region Database) and COMPEL are databases which store information about transcriptional regulation in eukaryotic cells. The three databases provide distinct views on the components involved in transcription: transcription factors and their binding sites and binding profiles (TRANSFAC), the regulatory hierarchy of whole genes (TRRD), and the structural and functional properties of composite elements (COMPEL). The quantitative and qualitative changes of all three databases and connected programs are described. The databases are accessible via WWW:http://transfac.gbf.de/TRANSFAC orhttp://www.bionet.nsc.ru/TRRD
Transcription Regulatory Regions Database (TRRD) is an informational resource containing an integrated description of the gene transcription regulation. An entry of the database corresponds to a gene and contains the data on localization and functions of the transcription regulatory regions as well as gene expression patterns. TRRD contains only experimental data that are inputted into the database through annotating scientific publication. TRRD release 6.0 comprises the information on 1167 genes, 5537 transcription factor binding sites, 1714 regulatory regions, 14 locus control regions and 5335 expression patterns obtained through annotating 3898 scientific papers. This information is arranged in seven databases: TRRDGENES (general gene description), TRRDLCR (locus control regions); TRRDUNITS (regulatory regions: promoters, enhancers, silencers, etc.), TRRDSITES (transcription factor binding sites), TRRDFACTORS (transcription factors), TRRDEXP (expression patterns) and TRRDBIB (experimental publications). Sequence Retrieval System (SRS) is used as a basic tool for navigating and searching TRRD and integrating it with external informational and software resources. The visualization tool, TRRD Viewer, provides the information representation in a form of maps of gene regulatory regions. The option allowing nucleotide sequences to be searched for according to their homology using BLAST is also included. TRRD is available at http://www.bionet.nsc.ru/trrd/.
Recognition of composite elements consisting of two transcription factor binding sites gets behind the studies of tissue-, stage- and condition-specific transcription. Genome-wide data on transcription factor binding generated with ChIP-seq method facilitate an identification of composite elements, but the existing bioinformatics tools either require ChIP-seq datasets for both partner transcription factors, or omit composite elements with motifs overlapping. Here we present an universal Motifs Co-Occurrence Tool (MCOT) that retrieves maximum information about overrepresented composite elements from a single ChIP-seq dataset. This includes homo- and heterotypic composite elements of four mutual orientations of motifs, separated with a spacer or overlapping, even if recognition of motifs within composite element requires various stringencies. Analysis of 52 ChIP-seq datasets for 18 human transcription factors confirmed that for over 60% of analyzed datasets and transcription factors predicted co-occurrence of motifs implied experimentally proven protein-protein interaction of respecting transcription factors. Analysis of 164 ChIP-seq datasets for 57 mammalian transcription factors showed that abundance of predicted composite elements with an overlap of motifs compared to those with a spacer more than doubled; and they had 1.5-fold increase of asymmetrical pairs of motifs with one more conservative ‘leading’ motif and another one ‘guided’.
The program for nucleosome sites recognition is included into the GeneExpress system; section 'DNA Nucleosomal Organization', http://wwwmgs.bionet.nsc.ru/mgs/programs/recon/.
Synthetic targeted optimization of plant promoters is becoming a part of progress in mainstream postgenomic agriculture along with hybridization of cultivated plants with wild congeners, as well as marker-assisted breeding. Therefore, here, for the first time, we compiled all the experimental data—on mutational effects in plant proximal promoters on gene expression—that we could find in PubMed. Some of these datasets cast doubt on both the existence and the uniqueness of the sought solution, which could unequivocally estimate effects of proximal promoter mutation on gene expression when plants are grown under various environmental conditions during their development. This means that the inverse problem under study is ill-posed. Furthermore, we found experimental data on in vitro interchangeability of plant and human TATA-binding proteins allowing the application of Tikhonov’s regularization, making this problem well-posed. Within these frameworks, we created our Web service Plant_SNP_TATA_Z-tester and then determined the limits of its applicability using those data that cast doubt on both the existence and the uniqueness of the sought solution. We confirmed that the effects (of proximal promoter mutations on gene expression) predicted by Plant_SNP_TATA_Z-tester correlate statistically significantly with all the experimental data under study. Lastly, we exemplified an application of Plant_SNP_TATA_Z-tester to agriculturally valuable mutations in plant promoters.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.