Age-Dependent Changes in the Relationships between Traits Associated with the Pathogenesis of Stress-Sensitive Hypertension in ISIAH Rats.

Hypertension is one of the most significant risk factors for many cardiovascular diseases. At different stages of hypertension development, various pathophysiological processes can play a key role in the manifestation of the hypertensive phenotype and of comorbid conditions. Accordingly, it is thought that when diagnosing and choosing a strategy for treating hypertension, it is necessary to take into account age, the stage of disorder development, comorbidities, and effects of emotional-psychosocial factors. Nonetheless, such an approach to choosing a treatment strategy is hampered by incomplete knowledge about details of age-related associations between the numerous features that may contribute to the manifestation of the hypertensive phenotype. Here, we used two groups of male F2(ISIAHxWAG) hybrids of different ages, obtained by crossing hypertensive ISIAH rats (simulating stress-sensitive arterial hypertension) and normotensive WAG rats. By principal component analysis, the relationships among 21 morphological, physiological, and behavioral traits were examined. It was shown that the development of stress-sensitive hypertension in ISIAH rats is accompanied not only by an age-dependent (FDR < 5%) persistent increase in basal blood pressure but also by a decrease in the response to stress and by an increase in anxiety. The plasma corticosterone concentration at rest and its increase during short-term restraint stress in a group of young rats did not have a straightforward relationship with the other analyzed traits. Nonetheless, in older animals, such associations were found. Thus, the study revealed age-dependent relationships between the key features that determine hypertension manifestation in ISIAH rats. Our results may be useful for designing therapeutic strategies against stress-sensitive hypertension, taking into account the patients' age.

The complex role of transcription factor GAGA in germline death during Drosophila spermatogenesis: transcriptomic and bioinformatic analyses.

The GAGA protein (also known as GAF) is a transcription factor encoded by the Trl gene in D. melanogaster. GAGA is involved in the regulation of transcription of many genes at all stages of fly development and life. Recently, we investigated the participation of GAGA in spermatogenesis and discovered that Trl mutants experience massive degradation of germline cells in the testes. Trl underexpression induces autophagic death of spermatocytes, thereby leading to reduced testis size. Here, we aimed to determine the role of the transcription factor GAGA in the regulation of ectopic germline cell death. We investigated how Trl underexpression affects gene expression in the testes. We identified 15,993 genes in three biological replicates of our RNA-seq analysis and compared transcript levels between hypomorphic Trl R85/Trl 362 and Oregon testes. A total of 2,437 differentially expressed genes were found, including 1,686 upregulated and 751 downregulated genes. At the transcriptional level, we detected the development of cellular stress in the Trl-mutant testes: downregulation of the genes normally expressed in the testes (indicating slowed or abrogated spermatocyte differentiation) and increased expression of metabolic and proteolysis-related genes, including stress response long noncoding RNAs. Nonetheless, in the Flybase Gene Ontology lists of genes related to cell death, autophagy, or stress, there was no enrichment with GAGA-binding sites. Furthermore, we did not identify any specific GAGA-dependent cell death pathway that could regulate spermatocyte death. Thus, our data suggest that GAGA deficiency in male germline cells leads to an imbalance of metabolic processes, impaired mitochondrial function, and cell death due to cellular stress.

Web-MCOT Server for Motif Co-Occurrence Search in ChIP-Seq Data.

(1) Background: The widespread application of ChIP-seq technology requires annotation of cis-regulatory modules through the search of co-occurred motifs. (2) Methods: We present the web server Motifs Co-Occurrence Tool (Web-MCOT) that for a single ChIP-seq dataset detects the composite elements (CEs) or overrepresented homo- and heterotypic pairs of motifs with spacers and overlaps, with any mutual orientations, uncovering various similarities to recognition models within pairs of motifs. The first (Anchor) motif in CEs respects the target transcription factor of the ChIP-seq experiment, while the second one (Partner) can be defined either by a user or a public library of Partner motifs being processed. (3) Results: Web-MCOT computes the significances of CEs without reference to motif conservation and those with more conserved Partner and Anchor motifs. Graphic results show histograms of CE abundance depending on orientations of motifs, overlap and spacer lengths; logos of the most common CE structural types with an overlap of motifs, and heatmaps depicting the abundance of CEs with one motif possessing higher conservation than another. (4) Conclusions: Novel capacities of Web-MCOT allow retrieving from a single ChIP-seq dataset with maximal information on the co-occurrence of motifs and potentiates planning of next ChIP-seq experiments.

Genes associated with cognitive performance in the Morris water maze: an RNA-seq study.

Learning and memory are among higher-order cognitive functions that are based on numerous molecular processes including changes in the expression of genes. To identify genes associated with learning and memory formation, here, we used the RNA-seq (high-throughput mRNA sequencing) technology to compare hippocampal transcriptomes between mice with high and low Morris water maze (MWM) cognitive performance. We identified 88 differentially expressed genes (DEGs) and 24 differentially alternatively spliced transcripts between the high- and low-MWM-performance mice. Although the sets of DEGs and differentially alternatively spliced transcripts did not overlap, both were found to be enriched with genes related to the same type of biological processes: trans-synaptic signaling, cognition, and glutamatergic transmission. These findings were supported by the results of weighted-gene co-expression network analysis (WGCNA) revealing the enrichment of MWM-cognitive-performance-correlating gene modules with very similar Gene Ontology terms. High-MWM-performance mice manifested mostly higher expression of the genes associated with glutamatergic transmission and long-term potentiation implementation, which are processes necessary for memory acquisition and consolidation. In this set, there were genes participating in the regulation of trans-synaptic signaling, primarily AMPA receptor signaling (Nrn1, Nptx1, Homer3, Prkce, Napa, Camk2b, Syt7, and Nrgn) and calcium turnover (Hpca, Caln1, Orai2, Cpne4, and Cpne9). In high-MWM-performance mice, we also demonstrated significant upregulation of the "flip" splice variant of Gria1 and Gria2 transcripts encoding subunits of AMPA receptor. Altogether, our data helped to identify specific genes in the hippocampus that are associated with learning and long-term memory. We hypothesized that the differences in MWM cognitive performance between the mouse groups are linked with increased long-term potentiation, which is mainly mediated by increased glutamatergic transmission, primarily AMPA receptor signaling.

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.

Promoters of the genes encoding the transcription factors regulating the cytokine gene expression in macrophages contain putative binding sites for aryl hydrocarbon receptor.

The computer system SITECON was used to study the regulatory regions in the transcription factor genes expressed in the activated macrophage and the genes of the proteins mediating the macrophage involvement in the immune response. Dioxin responsive elements (DREs), the specific sites responsible for expression regulation of the genes involved in the cell response to dioxin, were found in these gene regions. Thus, the role of dioxin in activity regulation of the genes involved in development of the immune response can be regulated both directly, by the transcription complex containing dioxin as a ligand, and indirectly, via intrinsic transcription factors.The double regulation, via DRE and the binding sites for the corresponding transcription factors in the promoter regions of macrophage genes, and the interregulation of the genes providing for the immune response allow the system to rapidly respond to a provocative agent (xenobiotic) and finely tune its function.

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).