ABSTRACT
The prediction of the DNA capacity to form nucleosome structure based on sequence statistics is of importance in the analysis of gene expression regulation in eukaryotes. A context analysis of nucleotide sequences of experimentally defined sites of nucleosome formation made it possible to determine the sequence preference for nucleosome formation on the basis of statistical information. An improved version of the Markov model was developed to predict the preference of DNA sequences to be within a nucleosome structure. The developed VMM (Variable Memory Markov model) program computes the nucleosome formation potential for genomic DNA sequences of arbitrary lengths, including the short transcription factor binding sites. Differences in nucleosome potential for exons, introns, and promoters were revealed. A correlation of the nucleosome potential estimate with text complexity was established. The VMM is available at http://wwwmgs. bionet.nsc.ru/programs/VMM/.
Subject(s)
Gene Expression Regulation/genetics , Genome/genetics , Models, Genetic , Nucleosomes/genetics , Sequence Analysis , Software , Eukaryotic Cells , Internet , Sequence Analysis/methodsABSTRACT
A new approach, SiteGA, for the prediction of functional transcription factor binding sites has been developed. The approach is based on the detection of locally positioned dinucleotides by the genetic algorithm and discriminant analysis. The approach has been applied to recognize transcription factor binding sites involved in the regulation of immune responses and cell growth (AP-1, IRF1, ISGF3, NFkappaB, STAT1), obesity and lipid metabolism (HNF4, PPAR, SREBP), and the expression of steroidogenesis genes (SF-1). SiteGA is far superior in accuracy to the traditionally used method of position weight matrices. The approach was implemented in the web tool, SiteGA http://wwwmgs2. bionet.nsc.ru/mgs/programs/sitega.
Subject(s)
Algorithms , DNA-Binding Proteins/genetics , Response Elements/genetics , Software , Transcription Factors/genetics , Animals , DNA-Binding Proteins/immunology , Humans , Immune System/physiology , Internet , Lipid Metabolism/genetics , Lipid Metabolism/immunology , Predictive Value of Tests , Protein Binding/genetics , Response Elements/immunology , Transcription Factors/immunologyABSTRACT
The SF-1 (Steroidogenic Factor-1) is a transcription factor known as a key regulator of the steroidogenic gene expression. SF-1 is required for the development and functioning at all levels of the hypothalamic-pituitary-gonadal and adrenal axis. Also it plays an essential role in sex determination. SF-1 is a member of the nuclear receptor superfamily and it activates gene expression by binding to DNA in a monomeric form. Here, we report the results of potential SF-1 binding sites identification by using the SiteGA recognition method. The SiteGA method was implemented using a genetic algorithm (GA) involving a iterative discriminant analyses of local dinucleotide context characteristics. These characteristics were compiled not only over the core binding sites region but over its flanks as well. Developed SiteGA method is characterized by considerably better recognition accuracy when compared to that for the weight matrix method. The experimental tests demonstrated that 83% of the sites recognized by the SiteGA method in the regulatory regions of steroidogenic genes, indeed, interact with the SF-1 factor. We also estimated the density of predicted sites in regulatory region of genes, the members of different functional groups and developed the criterion to search for new SF-1 target genes in genome sequences.
Subject(s)
Algorithms , Gene Expression Regulation/physiology , Genome, Human/physiology , Homeodomain Proteins/metabolism , Receptors, Cytoplasmic and Nuclear/metabolism , Response Elements/physiology , Sequence Analysis, DNA , Transcription Factors/metabolism , Animals , Female , Humans , Male , Mice , Predictive Value of Tests , Protein Binding/physiology , Sheep , Steroidogenic Factor 1 , SwineABSTRACT
The review describes several modules of the GeneExpress integrated computer system concerning the regulation of gene expression in eukaryotes. Approaches to the presentation of experimental data in databases are considered. The employment of GeneExpress in computer analysis and modeling of the organization and function of genetic systems is illustrated with examples. GeneExpress is available at http://wwwmgs.bionet.nsc.ru/mgs/gnw/.
Subject(s)
Gene Expression Regulation , Systems Integration , Animals , Databases, Genetic , Evolution, Molecular , Promoter Regions, Genetic , RNA, Messenger/genetics , Vertebrates/geneticsABSTRACT
The structural and functional organization of locus control regions (LCR) was analyzed using data of the LCR-TRR Database. The role of several transcription factors in the LCR function was considered. A study was made of the possible nucleosomal packing of enhancer regions in LCR. The structure and the format of LCR-TRRD are described. The database has been constructed for SRS and is available at http://wwwmgs.bionet.nsc.ru/mgs/dbase/LCR/.
Subject(s)
Databases, Nucleic Acid , Locus Control Region , DNA/genetics , Deoxyribonuclease I/metabolism , Eukaryotic Cells , Transcription, GeneticABSTRACT
A new method for recognizing eukaryotic gene promoters was based on their partition and on analysis of correlations of dinucleotide frequencies for each individual fragment. The method was used to recognize the TATA-containing and TATA-less promoters of Drosophila melanogaster genes. Dinucleotide context was correlated with conformational and physicochemical DNA properties in promoter fragments. Mean values of several parameters proved to dramatically change on transition from the TATA box to its GC-rich flanks. In TATA-less promoters, specific properties were revealed in the DPE region. The method was employed in a promoter recognition program, which is available through Internet.
