E. V. Ignatieva

Databases on transcriptional regulation: TRANSFAC, TRRD and COMPEL

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): its status in 2002

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/.

GeneNet: a database on structure and functional organisation of gene networks.

The GeneNet database is designed for accumulation of information on gene networks. Original technology applied in GeneNet enables description of not only a gene network structure and functional relationships between components, but also metabolic and signal transduction pathways. Specialised software, GeneNet Viewer, automatically displays the graphical diagram of gene networks described in the database. Current release 3.0 of GeneNet database contains descriptions of 25 gene networks, 945 proteins, 567 genes, 151 other substances and 1364 relationships between components of gene networks. Information distributed between 14 interlinked tables was obtained by annotating 968 scientific publications. The SRS-version of GeneNet database is freely available (http://wwwmgs.bionet.nsc.ru/mgs/systems/genenet/).

Finding biomarkers in non-model species: literature mining of transcription factors involved in bovine embryo development

BackgroundSince processes in well-known model organisms have specific features different from those in Bos taurus, the organism under study, a good way to describe gene regulation in ruminant embryos would be a species-specific consideration of closely related species to cattle, sheep and pig. However, as highlighted by a recent report, gene dictionaries in pig are smaller than in cattle, bringing a risk to reduce the gene resources to be mined (and so for sheep dictionaries). Bioinformatics approaches that allow an integration of available information on gene function in model organisms, taking into account their specificity, are thus needed. Besides these closely related and biologically relevant species, there is indeed much more knowledge of (i) trophoblast proliferation and differentiation or (ii) embryogenesis in human and mouse species, which provides opportunities for reconstructing proliferation and/or differentiation processes in other mammalian embryos, including ruminants. The necessary knowledge can be obtained partly from (i) stem cell or cancer research to supply useful information on molecular agents or molecular interactions at work in cell proliferation and (ii) mouse embryogenesis to supply useful information on embryo differentiation. However, the total number of publications for all these topics and species is great and their manual processing would be tedious and time consuming. This is why we used text mining for automated text analysis and automated knowledge extraction. To evaluate the quality of this “mining”, we took advantage of studies that reported gene expression profiles during the elongation of bovine embryos and defined a list of transcription factors (or TF, n = 64) that we used as biological “gold standard”. When successful, the “mining” approach would identify them all, as well as novel ones.MethodsTo gain knowledge on molecular-genetic regulations in a non model organism, we offer an approach based on literature-mining and score arrangement of data from model organisms. This approach was applied to identify novel transcription factors during bovine blastocyst elongation, a process that is not observed in rodents and primates. As a result, searching through human and mouse corpuses, we identified numerous bovine homologs, among which 11 to 14% of transcription factors including the gold standard TF as well as novel TF potentially important to gene regulation in ruminant embryo development. The scripts of the workflow are written in Perl and available on demand. They require data input coming from all various databases for any kind of biological issue once the data has been prepared according to keywords for the studied topic and species; we can provide data sample to illustrate the use and functionality of the workflow.ResultsTo do so, we created a workflow that allowed the pipeline processing of literature data and biological data, extracted from Web of Science (WoS) or PubMed but also from Gene Expression Omnibus (GEO), Gene Ontology (GO), Uniprot, HomoloGene, TcoF-DB and TFe (TF encyclopedia). First, the human and mouse homologs of the bovine proteins were selected, filtered by text corpora and arranged by score functions. The score functions were based on the gene name frequencies in corpora. Then, transcription factors were identified using TcoF-DB and double-checked using TFe to characterise TF groups and families. Thus, among a search space of 18,670 bovine homologs, 489 were identified as transcription factors. Among them, 243 were absent from the high-throughput data available at the time of the study. They thus stand so far for putative TF acting during bovine embryo elongation, but might be retrieved from a recent RNA sequencing dataset (Mamo et al. , 2012). Beyond the 246 TF that appeared expressed in bovine elongating tissues, we restricted our interpretation to those occurring within a list of 50 top-ranked genes. Among the transcription factors identified therein, half belonged to the gold standard (ASCL2, c-FOS, ETS2, GATA3, HAND1) and half did not (ESR1, HES1, ID2, NANOG, PHB2, TP53, STAT3).ConclusionsA workflow providing search for transcription factors acting in bovine elongation was developed. The model assumed that proteins sharing the same protein domains in closely related species had the same protein functionalities, even if they were differently regulated among species or involved in somewhat different pathways. Under this assumption, we merged the information on different mammalian species from different databases (literature and biology) and proposed 489 TF as potential participants of embryo proliferation and differentiation, with (i) a recall of 95% with regard to a biological gold standard defined in 2011 and (ii) an extension of more than 3 times the gold standard of TF detected so far in elongating tissues. The working capacity of the workflow was supported by the manual expertise of the biologists on the results. The workflow can serve as a new kind of bioinformatics tool to work on fused data sources and can thus be useful in studies of a wide range of biological processes.

Bioinformatical and experimental approaches to investigation of transcription factor binding sites in vertebrate genes

The development of computer-assisted methods for transcription factor binding sites (TFBS) recognition is necessary for study the DNA regulatory transcription code. There are a great number of experimental methods that enable TFBS identification in genome sequences. The experimental data can be used to elaborate multiple computer approaches to recognition of TFBS, each of which has its own advantages and limitations. A short review of the characteristics of computer methods of TFBS prediction based on various principles is presented. Methods used for experimental monitoring of predicted sites are analyzed. Data concerning DNA regulatory potential and its realization at the chromatin level, obtained using these methods, are discussed along with approaches to recognition of target genes of certain transcription factors in the genome sequences.

Transcription regulatory codes of eukaryotic genomes

The key aspects of transcription regulation in multicellular organisms were discussed in the paper, including characteristics of promoters, transcription factor binding sites and composite elements. The functional roles of transcriptional regulators (GTFs and transcription factors) were described together with mechanisms, which regulate its activity. The importance of DNA-encoded nucleosome organization and chromatin modifications for the process of transcription regulation have been declared. Also the significance of mechanisms which regulate activity of transcription factors within Gene Networks have been stressed. In light of recent data transcriptional regulatory codes of a eukaryotic genome were discussed.

Artsite Database: Comparison of In Vitro Selected and Natural Binding Sites of Eukaryotic Transcription Factors

The ArtSite database was developed; the database compiles the information on the structures of eukaryotic transcription factor binding sites and/or their DNA-binding domains obtained from in vitro selected sequences. Current release of the database comprises 420 matrices describing specific features of binding sites or their DNA-binding domains for over 200 transcription factors. The matrices were constructed basing on alignments of representative samples of transcription factor binding sites, totally containing over 10 thousand sequences.

Potential binding sites for SF-1: Recognition by the SiteGA method, experimental verification, and search for new target genes

The transcription factor SF-1 (steroidogenic factor 1) regulates the expression of the steroidogenesis genes, coordinates the development and function of the hypothalamic-pituitary-gonadal and adrenal systems, and plays an important role in the development and function of the reproductive system. SF-1 belongs to the superfamily of nuclear receptors and activates gene expression via binding as a monomer to DNA. The SiteGA method was developed for recognizing the binding sites for SF-1. The method utilizes a genetic algorithm and discriminant analysis to identify the context features of extended (93-bp) regions harboring the SF-1 sites in a training sample. Recognition of the SF-1 sites showed that the SiteGA method allows more reliable predictions as compared to the common weight matrix method. Experimental verification of 18 putative SF-1 sites predicted for the regulatory regions of the steroidogenesis genes showed that 15 (83%) of them did indeed interact with SF-1. The density of putative SF-1 sites was analyzed in the regulatory regions of genes from various functional groups, and new target genes of SF-1 were sought in the human genome. The potential targets of SF-1 include the genes coding for cytokine receptors, growth factor receptors, and proteins involved in the corresponding signal transduction pathways, as well as genes expressed in the epididymis. Expression of SF-1 in the epididymis was predicted and verified experimentally.

Binding Sites for Transcription Factor SF-1 in Promoter Regions of Genes Encoding Mouse Steroidogenesis Enzymes 3βHSDI and P450c17

Using gel retardation of DNA samples and specific antibodies, binding sites for the transcription factor SF-1 were found in positions −53/−44-and −285/−270 in the promoter region of the mouse Cyp17 gene and in position −117/−108 of the promoter region of the mouse 3βHSDI gene.

Generalized Chemokinetic Method for Gene Network Simulation

Development of methods for mathematical simulation of biological systems and building specific simulations is an important trend of bioinformatics. Here we describe the method of generalized chemokinetic simulation generating flexible and adequate simulations of various biological systems. Adequate simulations of complex nonlinear gene networks—control system of cholesterol by synthesis in the cell and erythrocyte differentiation and maturation—are given as examples. The simulations were expressed in terms of unit processes—biochemical reactions. Optimal sets of parameters were determined and the systems were numerically simulated under various conditions. The simulations allow us to study the possible functional conditions of these gene networks, calculate the consequences of mutations, and define optimal strategies for their correction including therapeutic ones. A graphical user interface for these simulations is available at http://wwwmgs.bionet.nsc.ru/systems/MGL/GeneNet/