Mikhail P. Ponomarenko

Identification of sequence-dependent DNA features correlating to activity of DNA sites interacting with proteins.

MOTIVATION The commonly accepted statistical mechanical theory is now multiply confirmed by using the weight matrix methods successfully recognizing DNA sites binding regulatory proteins in prokaryotes. Nevertheless, the recent evaluation of weight matrix methods application for transcription factor binding site recognition in eukaryotes has unexpectedly revealed that the matrix scores correlate better to each other than to the activity of DNA sites interacting with proteins. This observation points out that molecular mechanisms of DNA/protein recognition are more complicated in eukaryotes than in prokaryotes. As the extra events in eukaryotes, the following processes may be considered: (i) competition between the proteins and nucleosome core particle for DNA sites binding these proteins and (ii) interaction between two synergetic/antagonist proteins recognizing a composed element compiled from two DNA sites binding these proteins. That is why identification of the sequence-dependent DNA features correlating with affinity magnitudes of DNA sites interacting with a protein can pinpoint the molecular event limiting this protein/DNA recognition machinery. RESULTS An approach for predicting site activity based on its primary nucleotide sequence has been developed. The approach is realized in the computer system ACTIVITY, containing the databases on site activity and on conformational and physicochemical DNA/RNA parameters. By using the system ACTIVITY, an analysis of some sites was provided and the methods for predicting site activity were constructed. The methods developed are in good agreement with the experimental data. AVAILABILITY The database ACTIVITY is available at http://wwwmgs.bionet.nsc.ru/systems/Activity/ and the mirror site, http://www.cbil.upenn.edu/mgs/systems/acti vity/.

Oligonucleotide frequency matrices addressed to recognizing functional DNA sites.

MOTIVATION Recognition of functional sites remains a key event in the course of genomic DNA annotation. It is well known that a number of sites have their own specific oligonucleotide content. This pinpoints the fact that the preference of the site-specific nucleotide combinations at adjacent positions within an analyzed functional site could be informative for this site recognition. Hence, Web-available resources describing the site-specific oligonucleotide content of the functional DNA sites and applying the above approach for site recognition are needed. However, they have been poorly developed up to now. RESULTS To describe the specific oligonucleotide content of the functional DNA sites, we introduce the oligonucleotide alphabets, out of which the frequency matrix for a given site could be constructed in addition to a traditional nucleotide frequency matrix. Thus, site recognition accuracy increases. This approach was implemented in the activated MATRIX database accumulating oligonucleotide frequency matrices of the functional DNA sites. We have demonstrated that the false-positive error of the functional site recognition decreases if the oligonucleotide frequency matrixes are added to the nucleotide frequency matrixes commonly used. AVAILABILITY The MATRIX database is available on the Web, http://wwwmgs.bionet.nsc.ru/Dbases/MATRIX/ and the mirror site, http://www.cbil.upenn.edu/mgs/systems/c onsfreq/.

rSNP_Guide, a database system for analysis of transcription factor binding to target sequences: application to SNPs and site-directed mutations

rSNP_Guide is a novel curated database system for analysis of transcription factor (TF) binding to target sequences in regulatory gene regions altered by mutations. It accumulates experimental data on naturally occurring site variants in regulatory gene regions and site-directed mutations. This database system also contains the web tools for SNP analysis, i.e., active applet applying weight matrices to predict the regulatory site candidates altered by a mutation. The current version of the rSNP_Guide is supplemented by six sub-databases: (i) rSNP_DB, on DNA-protein interaction caused by mutation; (ii) SYSTEM, on experimental systems; (iii) rSNP_BIB, on citations to original publications; (iv) SAMPLES, on experimentally identified sequences of known regulatory sites; (v) MATRIX, on weight matrices of known TF sites; (vi) rSNP_Report, on characteristic examples of successful rSNP_Tools implementation. These databases are useful for the analysis of natural SNPs and site-directed mutations. The databases are available through the Web, http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/.

ACTIVITY: a database on DNA/RNA sites activity adapted to apply sequence-activity relationships from one system to another

ACTIVITY is a database on DNA/RNA site sequences with known activity magnitudes, measurement systems, sequence-activity relationships under fixed experimental conditions and procedures to adapt these relationships from one measurement system to another. This database deposits information on DNA/RNA affinities to proteins and cell nuclear extracts, cutting efficiencies, gene transcription activity, mRNA translation efficiencies, mutability and other biological activities of natural sites occurring within promoters, mRNA leaders, and other regulatory regions in pro- and eukaryotic genomes, their mutant forms and synthetic analogues. Since activity magnitudes are heavily system-dependent, the current version of ACTIVITY is supplemented by three novel sub-databases: (i) SYSTEM, measurement systems; (ii) KNOWLEDGE, sequence-activity relationships under fixed experimental conditions; and (iii) CROSS_TEST, procedures adapting a relationship from one measurement system to another. These databases are useful in molecular biology, pharmacogenetics, metabolic engineering, drug design and biotechnology. The databases can be queried using SRS and are available through the Web, http://wwwmgs. bionet.nsc.ru/systems/Activity/.

An experimental verification of the predicted effects of promoter TATA-box polymorphisms associated with human diseases on interactions between the TATA boxes and TATA-binding protein.

Human genome sequencing has resulted in a great body of data, including a stunningly large number of single nucleotide polymorphisms (SNPs) with unknown phenotypic manifestations. Identification and comprehensive analysis of regulatory SNPs in human gene promoters will help quantify the effects of these SNPs on human health. Based on our experimental and computer-aided study of SNPs in TATA boxes and the use of literature data, we have derived an equation for TBP/TATA equilibrium binding in three successive steps: TATA-binding protein (TBP) sliding along DNA due to their nonspecific affinity for each other ↔ recognition of the TATA box ↔ stabilization of the TBP/TATA complex. Using this equation, we have analyzed TATA boxes containing SNPs associated with human diseases and made in silico predictions of changes in TBP/TATA affinity. An electrophoretic mobility shift assay (EMSA)-based experimental study performed under the most standardized conditions demonstrates that the experimentally measured values are highly correlated with the predicted values: the coefficient of linear correlation, r, was 0.822 at a significance level of α<10−7 for equilibrium K D values, (-ln K D), and 0.785 at a significance level of α<10−3 for changes in equilibrium K D (δ) due to SNPs in the TATA boxes (). It has been demonstrated that the SNPs associated with increased risk of human diseases such as α-, β- and δ-thalassemia, myocardial infarction and thrombophlebitis, changes in immune response, amyotrophic lateral sclerosis, lung cancer and hemophilia B Leyden cause 2–4-fold changes in TBP/TATA affinity in most cases. The results obtained strongly suggest that the TBP/TATA equilibrium binding equation derived can be used for analysis of TATA-box sequences and identification of SNPs with a potential of being functionally important.

SELEX_DB: a database on in vitro selected oligomers adapted for recognizing natural sites and for analyzing both SNPs and site-directed mutagenesis data

SELEX_DB is an online resource containing both the experimental data on in vitro selected DNA/RNA oligomers (aptamers) and the applets for recognition of these oligomers. Since in vitro experimental data are evidently system-dependent, the new release of the SELEX_DB has been supplemented by the database SYSTEM storing the experimental design. In addition, the recognition applet package, SELEX_TOOLS, applying in vitro selected data to annotation of the genome DNA, is accompanied by the cross-validation test database CROSS_TEST discriminating the sites (natural or other) related to in vitro selected sites out of random DNA. By cross-validation testing, we have unexpectedly observed that the recognition accuracy increases with the growth of homology between the training and test sets of protein binding sequences. For natural sites, the recognition accuracy was lower than that for the nearest protein homologs and higher than that for distant homologs and non-homologous proteins binding the common site. The current SELEX_DB release is available at http://wwwmgs.bionet.nsc.ru/mgs/systems/selex/.

SITEVIDEO: a computer system for functional site analysis and recognition. Investigation of the human splice sites

We developed the computer system SITEVIDEO for analysis and recognition of the functional sites in DNA and RNA molecules. It reveals contextual features essential for site function and thus enable the user to design efficient methods for recognition of the functional sites. We mainly considered only quantitative characteristics reflecting the uneven distribution of oligonucleotides in the sequences of functional sites of interest. The approach suggested makes use of available information about the hierarchical organization of the functional sites, and ensures highly precise prediction of the sites. The present analysis is concerned with the human donor and acceptor splice sites. A method for recognizing these sites in the sequences with an accuracy of approximately 90% was developed.

SELEX_DB: an activated database on selected randomized DNA/RNA sequences addressed to genomic sequence annotation

SELEX_DB is a novel curated database on selected randomized DNA/RNA sequences designed for accumulation of experimental data on functional site sequences obtained by using SELEX and SELEX-like technologies from the pools of random sequences. This database also contains the programs for DNA/RNA functional site recognition within arbitrary nucleotide sequences. The first release of SELEX_DB has been installed under SRS and is available through the WWW at http://wwwmgs.bionet.nsc.ru/mgs/systems/selex/

Mining DNA sequences to predict sites which mutations cause genetic diseases

Currently single nucleotide polymorphism (SNP) analysis becomes the crossroad of bioinformatics and medicine. We have developed a data mining system, http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/, called rSNP_Guide, to discover regulatory sites in DNA sequences, which mutations could be the cause of genetic diseases. During the first step, we estimate the abilities of the proteins considered to bind to genomic DNA, which alterations by mutations are associated with a genetic disease under study. During the second step, we formalize the disease-associated experimental data on the SNP-referred alterations in DNA binding to unknown protein. During the third step, we cluster fuzzily all known proteins examined so that to determine one of them, which specific site is altered by mutations in consistence with that of the unknown protein experimentally associated with genetic disease. During the fourth step, we predict the known protein, which binding site is (i) resent on DNA and (ii) altered by mutations associated with genetic disease. Finally, during the last step, we estimate the robustness of this prediction. The rSNP_Guide has been tested on the SNPs with the known relationships between regulatory site alterations and genetic disease penetration. Besides, the novel SNPs-referred regulatory sites associated with the genetic disease penetrations were discovered and, then, successfully confirmed experimentally.

How to Use SNP_TATA_Comparator to Find a Significant Change in Gene Expression Caused by the Regulatory SNP of This Gene's Promoter via a Change in Affinity of the TATA-Binding Protein for This Promoter

The use of biomedical SNP markers of diseases can improve effectiveness of treatment. Genotyping of patients with subsequent searching for SNPs more frequent than in norm is the only commonly accepted method for identification of SNP markers within the framework of translational research. The bioinformatics applications aimed at millions of unannotated SNPs of the “1000 Genomes” can make this search for SNP markers more focused and less expensive. We used our Web service involving Fishers Z-score for candidate SNP markers to find a significant change in a genes expression. Here we analyzed the change caused by SNPs in the genes promoter via a change in affinity of the TATA-binding protein for this promoter. We provide examples and discuss how to use this bioinformatics application in the course of practical analysis of unannotated SNPs from the “1000 Genomes” project. Using known biomedical SNP markers, we identified 17 novel candidate SNP markers nearby: rs549858786 (rheumatoid arthritis); rs72661131 (cardiovascular events in rheumatoid arthritis); rs562962093 (stroke); rs563558831 (cyclophosphamide bioactivation); rs55878706 (malaria resistance, leukopenia), rs572527200 (asthma, systemic sclerosis, and psoriasis), rs371045754 (hemophilia B), rs587745372 (cardiovascular events); rs372329931, rs200209906, rs367732974, and rs549591993 (all four: cancer); rs17231520 and rs569033466 (both: atherosclerosis); rs63750953, rs281864525, and rs34166473 (all three: malaria resistance, thalassemia).