Asymmetric Conservation within Pairs of Co-Occurred Motifs Mediates Weak Direct Binding of Transcription Factors in ChIP-Seq Data.

(1) Background: Transcription factors (TFs) are main regulators of eukaryotic gene expression. The cooperative binding to genomic DNA of at least two TFs is the widespread mechanism of transcription regulation. Cooperating TFs can be revealed through the analysis of co-occurrence of their motifs. (2) Methods: We applied the motifs co-occurrence tool (MCOT) that predicted pairs of spaced or overlapped motifs (composite elements, CEs) for a single ChIP-seq dataset. We improved MCOT capability for the prediction of asymmetric CEs with one of the participating motifs possessing higher conservation than another does. (3) Results: Analysis of 119 ChIP-seq datasets for 45 human TFs revealed that almost for all families of TFs the co-occurrence with an overlap between motifs of target TFs and more conserved partner motifs was significantly higher than that for less conserved partner motifs. The asymmetry toward partner TFs was the most clear for partner motifs of TFs from the ETS (E26 Transformation Specific) family. (4) Conclusion: Co-occurrence with an overlap of less conserved motif of a target TF and more conserved motifs of partner TFs explained a substantial portion of ChIP-seq data lacking conserved motifs of target TFs. Among other TF families, conservative motifs of TFs from ETS family were the most prone to mediate interaction of target TFs with its weak motifs in ChIP-seq.

A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package.

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'.

Novel approach to functional SNPs discovery from genome-wide data reveals promising variants for colon cancer risk.

In the majority of colorectal cancer (CRC) cases, the genetic basis of predisposition remains unexplained. The goal of the study was to assess the regulatory SNPs (rSNPs) in the human genome and to reveal СRC drivers based on the available chromatin immunoprecipitation sequencing (ChIP-Seq, ChIA-PET) and transcriptional profiling (RNA-Seq) data. We combined positional (locations within genome regulatory elements) and functional (associated with allele-specific binding and expression) criteria followed by an analysis using genome-wide association studies (GWAS) and minor allele frequency (MAF) datasets. DeSeq2 analysis through 70 CRC patients reinforced the regulatory potential. rSNPs (1,476) that were associated with significant (P < 0.01) allele-specific events resulting in thirty that exhibited a link with CRC according to the MAF and 27, with a risk of malignancy in general according to GWAS. Selected rSNPs may modify the expression of genes for tumor suppressors and the regulators of signaling pathways, including noncoding RNAs. However, the rSNPs from the most represented group affect the expression of genes related to splicing. Our findings strongly suggest that the identified variants might contribute to CRC susceptibility, which indicates that aberrant splicing is one of the key mechanisms for unraveling disease etiopathogenesis and provides useful inputs for interpreting how genotypic variation corresponds to phenotypic outcome.

Identification of thyroid hormone receptor homologs in the fluke Opisthorchis felineus (Platyhelminthes).

The liver fluke, Opisthorchis felineus of the Opisthorchiidae family, is a well-known causative agent of opisthorchiasis in Russia and Europe. The aim of this work was to identify genes encoding thyroid hormone receptors in O. felineus, and to analyze the expression of possible target genes in response to treatment with exogenous thyroid hormones. We identified two genes encoding thyroid hormone receptors in the O. felineus genome, THRA and THRB. The genes were differentially expressed through the life cycle. The maximal level of mRNA expression of THRA1 and THRB was observed in adult worms. Treatment of the worms with triiodothyronine and thyroxine resulted in an increase in glucose 6-phosphatase mRNA expression and a decrease in malate dehydrogenase mRNA expression, potential gene targets of thyroid hormones. These data indicate that thyroid hormone receptors may perform essential roles in physiological processes in adult O. felineus.

Application of experimentally verified transcription factor binding sites models for computational analysis of ChIP-Seq data.

BACKGROUND: ChIP-Seq is widely used to detect genomic segments bound by transcription factors (TF), either directly at DNA binding sites (BSs) or indirectly via other proteins. Currently, there are many software tools implementing different approaches to identify TFBSs within ChIP-Seq peaks. However, their use for the interpretation of ChIP-Seq data is usually complicated by the absence of direct experimental verification, making it difficult both to set a threshold to avoid recognition of too many false-positive BSs, and to compare the actual performance of different models. RESULTS: Using ChIP-Seq data for FoxA2 binding loci in mouse adult liver and human HepG2 cells we compared FoxA binding-site predictions for four computational models of two fundamental classes: pattern matching based on existing training set of experimentally confirmed TFBSs (oPWM and SiteGA) and de novo motif discovery (ChIPMunk and diChIPMunk). To properly select prediction thresholds for the models, we experimentally evaluated affinity of 64 predicted FoxA BSs using EMSA that allows safely distinguishing sequences able to bind TF. As a result we identified thousands of reliable FoxA BSs within ChIP-Seq loci from mouse liver and human HepG2 cells. It was found that the performance of conventional position weight matrix (PWM) models was inferior with the highest false positive rate. On the contrary, the best recognition efficiency was achieved by the combination of SiteGA & diChIPMunk/ChIPMunk models, properly identifying FoxA BSs in up to 90% of loci for both mouse and human ChIP-Seq datasets. CONCLUSIONS: The experimental study of TF binding to oligonucleotides corresponding to predicted sites increases the reliability of computational methods for TFBS-recognition in ChIP-Seq data analysis. Regarding ChIP-Seq data interpretation, basic PWMs have inferior TFBS recognition quality compared to the more sophisticated SiteGA and de novo motif discovery methods. A combination of models from different principles allowed identification of proper TFBSs.

Detection of regulatory SNPs in human genome using ChIP-seq ENCODE data.

A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe an approach aggregating the whole set of ENCODE ChIP-seq data in order to search for rSNPs, and provide the experimental evidence of its efficiency. Its algorithm is based on the assumption that the enrichment of a genomic region with transcription factor binding loci (ChIP-seq peaks) indicates its regulatory function, and thereby SNPs located in this region are more likely to influence transcription regulation. To ensure that the approach preferably selects functionally meaningful SNPs, we performed enrichment analysis of several human SNP datasets associated with phenotypic manifestations. It was shown that all samples are significantly enriched with SNPs falling into the regions of multiple ChIP-seq peaks as compared with the randomly selected SNPs. For experimental verification, 40 SNPs falling into overlapping regions of at least 7 TF binding loci were selected from OMIM. The effect of SNPs on the binding of the DNA fragments containing them to the nuclear proteins from four human cell lines (HepG2, HeLaS3, HCT-116, and K562) has been tested by EMSA. A radical change in the binding pattern has been observed for 29 SNPs, besides, 6 more SNPs also demonstrated less pronounced changes. Taken together, the results demonstrate the effective way to search for potential rSNPs with the aid of ChIP-seq data provided by ENCODE project.

Possible link between the synthesis of GR alpha isoforms and eIF2 alpha phosphorylation state.

Glucocorticoid hormones regulate numerous physiological processes and are widely used in the treatment of inflammation, autoimmune disease and cancer. Glucocorticoid receptor (GR) - a transcription factor, derived from a single gene, is responsible for the diverse actions of glucocorticoids. It was shown that GR gene gives rise a variety of mRNA species that produces several protein isoforms, among them GRα is the most abundant. In addition, GRα N-end-truncated protein isoforms (A, B, C, D) are generated by translational mechanisms. As it was found that the ratio between the translational isoforms amounts varied in different tissues and cell lines and distinct isoforms could control transcription of different sets of genes, molecular mechanisms underlining the synthesis of translational GRα isoforms are of great interest. It was considered that GRα isoform A is translated by a conventional linear scanning, isoform B is translated by leaky scanning, isoform C is translated by leaky scanning and ribosomal shunt whereas translation of isoform D occurs through ribosomal shunt only. Since the sequence organization of GRα mRNA strongly resembles the cases of ATF4 or ATF5, the well-known examples of reinitiation-dependent synthesis of functional isoforms, we hypothesize that translation of isoform C could be controlled by reinitiation mechanism also. If this assumption is correct, the ratio between GRα N-end isoforms could depend on the eIF2α phosphorylation state that could provide an additional connection between the GR and cellular stresses. We believe that this hypothesis could be of interest to plan more robust experiments or for better interpretation of available data.

Ortho-aminoazotoluene activates mouse constitutive androstane receptor (mCAR) and increases expression of mCAR target genes.

2'-3-dimethyl-4-aminoazobenzene (ortho-aminoazotoluene, OAT) is an azo dye and a rodent carcinogen that has been evaluated by the International Agency for Research on Cancer (IARC) as a possible (class 2B) human carcinogen. Its mechanism of action remains unclear. We examined the role of the xenobiotic receptor Constitutive Androstane Receptor (CAR, NR1I3) as a mediator of the effects of OAT. We found that OAT increases mouse CAR (mCAR) transactivation in a dose-dependent manner. This effect is specific because another closely related azo dye, 3'-methyl-4-dimethyl-aminoazobenzene (3'MeDAB), did not activate mCAR. Real-time Q-PCR analysis in wild-type C57BL/6 mice revealed that OAT induces the hepatic mRNA expression of the following CAR target genes: Cyp2b10, Cyp2c29, Cyp3a11, Ugt1a1, Mrp4, Mrp2 and c-Myc. CAR-null (Car(-/-)) mice showed no increased expression of these genes following OAT treatment, demonstrating that CAR is required for their OAT dependent induction. The OAT-induced CAR-dependent increase of Cyp2b10 and c-Myc expression was confirmed by Western blotting. Immunohistochemistry analysis of wild-type and Car(-/-) livers showed that OAT did not acutely induce hepatocyte proliferation, but at much later time points showed an unexpected CAR-dependent proliferative response. These studies demonstrate that mCAR is an OAT xenosensor, and indicate that at least some of the biological effects of this compound are mediated by this nuclear receptor.

Structural variants of glucocorticoid receptor binding sites and different versions of positive glucocorticoid responsive elements: Analysis of GR-TRRD database.

The GR-TRRD section of the TRRD database contains the presently largest sample of published nucleotide sequences with experimentally confirmed binding to the glucocorticoid hormone receptor (GR). This sample comprises 160 glucocorticoid receptor binding sites (GRbs) from 77 vertebrate glucocorticoid-regulated genes. Analysis of this sample has demonstrated that the structure of only half GRbs (54%) corresponds to the generally accepted organization of glucocorticoid response element (GRE) as an inverted repeat of the TGTTCT hexanucleotide. As many as 40% of GRbs contain only the hexanucleotide, and the majority of such "half-sites" belong to the glucocorticoid-inducible genes. An expansion of the sample allowed the consensus of GRbs organized as an inverted repeat to be determined more precisely. Several possible mechanisms underlying the role of the noncanonical receptor binding sites (hexanucleotide half-sites) in the glucocorticoid induction are proposed based on analysis of the literature data.

Effects of o-aminoazotoluene on liver regeneration and p53 activation in mice susceptible and resistant to hepatocarcinogenesis.

The susceptibility to hepatocellular carcinoma (HCC) varies greatly within human populations in response to environmental risk agents. The mechanisms underlying differential susceptibility are still largely unknown and need to be clarified to improve HCC chemoprevention and therapeutic treatment. Inbred rodent strains with established predispositions for hepatocarcinogenesis offer the opportunity to identify intrinsic susceptibility and resistance factors. Previously, we have characterized mouse strains showing differential susceptibility to o-aminoazotoluene (OAT) and established that susceptibility does not result from OAT metabolism or genotoxicity in the livers of resistant and susceptible mice. In this study we have found that OAT differently affects hepatocyte proliferation in mice after partial hepatectomy (PH). OAT inhibited hepatocyte proliferation by 60-80% in the livers of susceptible mice, whereas resistant mice showed less than 15% inhibition. The inhibition resulted in significant delay of hepatic mass recovery in susceptible mice. OAT induced p53 stabilization and transcriptional activation in response to carcinogen treatment to the same degree in both, susceptible and resistant mice. Taken together, our data support inhibition of hepatocyte proliferation as a major cause for increased mouse susceptibility to hepatocarcinogenesis, and acceleration of functional liver recovery may offer a way to increase resistance to hepatic neoplasms. These results may have relevance to clinical observations of HCCs and implications for HCC chemoprevention and treatment.

Netrin-4 inhibits angiogenesis via binding to neogenin and recruitment of Unc5B.

Netrins are secreted molecules with roles in axon guidance and angiogenesis. We identified Netrin-4 as a gene specifically overexpressed in VEGF-stimulated endothelial cells (EC) in vitro as well as in vivo. Knockdown of Netrin-4 expression in EC increased their ability to form tubular structures on Matrigel. To identify which receptor is involved, we showed by quantitative RT-PCR that EC express three of the six Netrin-1 cognate receptors: neogenin, Unc5B, and Unc5C. In contrast to Netrin-1, Netrin-4 bound only to neogenin but not to Unc5B or Unc5C receptors. Neutralization of Netrin-4 binding to neogenin by blocking antibodies abolished the chemotactic effect of Netrin-4. Furthermore, the silencing of either neogenin or Unc5B abolished Netrin-4 inhibitory effect on EC migration, suggesting that both receptors are essential for its function in vitro. Coimmunoprecipitation experiments demonstrated that Netrin-4 increased the association between Unc5B and neogenin on VEGF- or FGF-2-stimulated EC. Finally, we showed that Netrin-4 significantly reduced pathological angiogenesis in Matrigel and laser-induced choroidal neovascularization models. Interestingly, Netrin-4, neogenin, and Unc5B receptor expression was up-regulated in choroidal neovessel EC after laser injury. Moreover, Netrin-4 overexpression delayed tumor angiogenesis in a model of s.c. xenograft. We propose that Netrin-4 acts as an antiangiogenic factor through binding to neogenin and recruitment of Unc5B.

Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions.

BACKGROUND: Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered. RESULTS: To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM) algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-kappaB, ISGF3, IRF1, STAT1), obesity and lipid metabolism (PPAR, SREBP, HNF4), regulation of the steroidogenic (SF-1) and cell cycle (E2F) genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA) with a discriminant function of locally positioned dinucleotide (LPD) frequencies. To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together) to sequences in the Eukaryotic Promoter Database (EPD). The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA. Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint) region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied together, this substantially reduced false positives at least at higher stringencies. CONCLUSION: Based on this analysis, SiteGA adds substantial specificity even to optimized PWMs and may be considered for large-scale genome analysis. It adds to the range of techniques available for TFBS prediction, and EPD analysis has led to a list of genes which appear to be regulated by the above TFs.

Combined experimental and computational approaches to study the regulatory elements in eukaryotic genes.

The recognition of transcription factor binding sites (TFBSs) is the first step on the way to deciphering the DNA regulatory code. There is a large variety of experimental approaches providing information on TFBS location in genomic sequences. Many computational approaches to TFBS recognition based on the experimental data obtained are available, each having its own advantages and shortcomings. This article provides short review of approaches to computational recognition of TFBS in genomic sequences and methods of experimental verification of predicted sites. We also present a case study of the interplay between experimental and theoretical approaches to the successful prediction of Steroidogenic Factor 1 (SF1).

Species-specific effects of the hepatocarcinogens 3'-methyl-4-dimethyl-aminoazobenzene and ortho-aminoazotoluene in mouse and rat liver.

The effects of rat-specific hepatocarcinogen 3'-methyl-4-dimethylaminoazobenzene (3'-MeDAB), mouse-specific hepatocarcinogen ortho-aminoazotoluene (OAT), non-species-specific hepatocarcinogen diethylnitrosamine (DENA), and non-carcinogenic 4'-methyl-4-dimethylaminoazobenzene (4'-MeDAB) on glucocorticoid induction of tyrosine aminotransferase (TAT) and DNA-binding activity of hepatocyte nuclear factor 3 (HNF3) family of transcription factors were investigated with carcinogen-susceptible and -resistant animals. Species-specific hepatocarcinogens 3'-MeDAB and OAT strongly inhibited glucocorticoid induction of TAT in the liver of susceptible but not resistant animals. DENA, which is highly carcinogenic for the liver of both rats and mice inhibited glucocorticoid induction of TAT in both species, while non-carcinogenic 4'-MeDAB was absolutely ineffective both in rats and mice. The inhibition of TAT activity by the carcinogens was due to reduced levels of TAT mRNA, which is most likely to be a result of the reduced rate of transcription initiation of the TAT gene. In all cases, the TAT inhibition was accompanied by significant reduction of DNA-binding activity of the HNF3 transcription factor, which is known to be critical to glucocorticoid regulation of TAT gene. We also demonstrated that the described species-specific effects of OAT and of 3'-MeDAB on HNF3 DNA-binding activity may be initiated not only by administration in vivo, but also by their direct administration to homogenate, intact nuclei or nuclear lysate, but not to nuclear extract fraction, obtained by precipitation with 0.32 g/mL of ammonium sulfate (Fraction I). We showed, that a factor responsible for this effect might be precipitated in 0.32-0.47 g/mL interval of ammonium sulfate concentration. In contrast, non-specific hepatocarcinogen DENA was effective upon being added directly to Fraction I, implying a different mechanism of its action.

rSNP_Guide, a database system for analysis of transcription factor binding to DNA with variations: application to genome annotation.

The analysis of gene regulatory networks has become one of the most challenging problems of the postgenomic era. Earlier we developed rSNP_Guide (http://util.bionet.nsc.ru/databases/rsnp.html), a computer system and database devoted to prediction of transcription factor (TF) binding sites (TF sites), which can be responsible for disease phenotypes. The prediction results were confirmed by 70 known relationships between TF sites and diseases, as well as by site-directed mutagenesis data. The rSNP_Guide is being investigated as a tool for TF site annotation. Previously analyzed and characterized cases of altered TF sites were used to annotate potential sites of the same type and at the same location in homologous genes. Based on 20 TF sites with known alterations in TF binding to DNA, we localized 245 potential TF sites in homologous genes. For these potential TF sites, rSNP_Guide estimates TF-DNA interaction according to three categories: 'present', 'weak', and 'absent'. The significance of each assignment is statistically measured.

rSNP_Guide: an integrated database-tools system for studying SNPs and site-directed mutations in transcription factor binding sites.

Since the human genome was sequenced in draft, single nucleotide polymorphism (SNP) analysis has become one of the keynote fields of bioinformatics. We have developed an integrated database-tools system, rSNP_Guide (http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/), devoted to prediction of transcription factor (TF) binding sites, alterations of which could be associated with disease phenotype. By inputting data on alterations in DNA sequence and in DNA binding pattern of an unknown TF, rSNP_Guide searches for a known TF with alterations in the recognition score calculated on the basis of TF site's sequence and consistent with the input alterations in DNA binding to the unknown TF. Our system has been tested on many relationships between known TF sites and diseases, as well as on site-directed mutagenesis data. Experimental verification of rSNP_Guide system was made on functionally important SNPs in human TDO2and mouse K-ras genes. Additional examples of analysis are reported involving variants in the human gammaA-globin (HBG1), hsp70(HSPA1A), and Factor IX (F9) gene promoters.