Publications by authors named "Tatyana Merkulova"
(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.
View Article and Find Full Text PDFRecognition 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.
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- * It identified 1,476 rSNPs linked to allele-specific events, with 30 associated with CRC risk and 27 linked to overall malignancy.
- * The findings indicate that rSNPs may influence gene expression related to tumor suppression and splicing, suggesting that abnormal splicing is crucial in understanding CRC susceptibility.
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- The liver fluke, Opisthorchis felineus, is recognized for causing opisthorchiasis, particularly in Russia and Europe.
- This study aimed to identify thyroid hormone receptor genes in O. felineus and examine how they respond to thyroid hormone treatment.
- Two thyroid hormone receptor genes, THRA and THRB, were found to be more active in adult worms, with thyroid hormone treatment altering the expression of genes related to glucose metabolism.
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- ChIP-Seq is a technique used to identify genomic regions bound by transcription factors (TFs), but various software tools often struggle with false positives and lack experimental validation for their predictions.
- A study compared the effectiveness of four computational models for predicting FoxA binding sites in mouse liver and human HepG2 cells, finding that traditional methods had a high false positive rate.
- The best results for accurately identifying TF binding sites came from a combination of SiteGA and de novo motif discovery approaches, which successfully recognized up to 90% of the binding loci analyzed.*
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- A significant number of single nucleotide polymorphisms (SNPs) identified in genome-wide association studies are non-coding, highlighting the need to effectively identify regulatory SNPs (rSNPs), which is difficult due to poor annotation of regulatory regions in the human genome.
- The study introduces an approach that uses ENCODE ChIP-seq data to identify rSNPs by looking for SNPs in regions enriched with transcription factor binding sites, under the assumption that these regions play a regulatory role in gene expression.
- Experimental validation involved analyzing 40 selected SNPs, showing that 29 SNPs significantly affected DNA binding patterns with nuclear proteins, indicating that the method effectively identifies potential rSNPs through
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- * The GR gene produces various mRNA species, resulting in different protein isoforms, with GRα being the most prevalent, and distinct translational mechanisms generating several isoforms (A, B, C, D) that control transcription of various genes.
- * The potential mechanism for the translation of GRα isoform C may involve a reinitiation process influenced by the phosphorylation state of eIF2α, suggesting an important link between GR and responses to cellular stress, which warrants further investigation. *
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- 2'-3-dimethyl-4-aminoazobenzene (OAT) is an azo dye identified as a potential human carcinogen by IARC, but its mechanism of action is not well understood.
- Research indicates that OAT activates the Constitutive Androstane Receptor (CAR) in mice, leading to an increase in the expression of several CAR target genes in a dose-dependent manner.
- CAR plays a crucial role in mediating the effects of OAT, as mice lacking CAR did not show the same gene expression changes, and while OAT did not immediately induce liver cell proliferation, it later caused a CAR-dependent proliferative response.
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- The GR-TRRD section is the largest collection of confirmed glucocorticoid hormone receptor (GR) binding sites, featuring 160 sites from 77 vertebrate genes.
- Analysis shows that only 54% of these binding sites follow the typical structure of glucocorticoid response elements (GREs), while 40% consist of hexanucleotide "half-sites."
- The study also discusses possible roles of these half-sites in gene induction, drawing from existing literature.
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- Hepatocellular carcinoma (HCC) risk varies among humans due to environmental factors, and understanding this susceptibility is crucial for improving prevention and treatment methods.
- Research using different mouse strains shows that susceptibility to the carcinogen o-aminoazotoluene (OAT) leads to significant differences in liver cell proliferation after liver surgery, with susceptible mice experiencing a much greater reduction in cell growth.
- Findings indicate that the inhibited liver recovery in susceptible mice contributes to their higher risk of HCC, suggesting that boosting liver recovery may help reduce susceptibility and improve treatment strategies.
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.
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- Current methods for predicting transcription factor binding sites (TFBS) struggle with high false-positive rates because they mainly focus on core binding site sequence conservation.
- This study evaluated various Position Weight Matrix (PWM) algorithms to enhance the accuracy of TFBS predictions, especially for important biological processes related to growth, inflammation, obesity, and cell cycle regulation.
- The introduction of a new method called SiteGA, which considers structural interactions within the binding sites, demonstrated similar effectiveness to optimized PWMs, and the resulting recognition models can be accessed through a web tool for sequence analysis.
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.
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- The study examined the impact of various hepatocarcinogens on the induction of tyrosine aminotransferase (TAT) and the DNA-binding activity of hepatocyte nuclear factor 3 (HNF3) transcription factors in different animal models.
- Rat-specific 3'-methyl-4-dimethylaminoazobenzene (3'-MeDAB) and mouse-specific ortho-aminoazotoluene (OAT) significantly inhibited TAT induction in susceptible species, while diethylnitrosamine (DENA) affected both rats and mice, but the non-carcinogen 4'-methyl-4-dimethylaminoazobenzene (4'-MeD
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- Analyzing gene regulatory networks is a complex challenge in postgenomic research, with a focus on transcription factor (TF) binding sites that can impact disease phenotypes.
- The rSNP_Guide system helps predict these TF binding sites and has been validated by established connections between TF sites and diseases, as well as experimental data.
- The tool identifies potential TF sites in similar genes based on known alterations, classifying their TF-DNA interactions as 'present', 'weak', or 'absent', with statistical significance for each classification.
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- The human genome sequencing has spurred significant advancements in bioinformatics, particularly in analyzing single nucleotide polymorphisms (SNPs).
- rSNP_Guide is a developed tool that predicts transcription factor binding sites based on DNA sequence alterations, which may relate to diseases.
- The system has been validated using various genes linked to diseases and has shown effectiveness in analyzing important SNPs in both human and mouse genes.