Vavilovskii Zhurnal Genetiki i Selektsii最新文献

Reconstruction and analysis of gene networks regulating biological processes are among the modern methodological approaches for studying complex biological systems that ensure the vital activity of organisms. Thermoregulation is an important evolutionary acquisition of warm-blooded animals. Multiple physiological systems (nervous, cardiovascular, endocrine, respiratory, muscular, etc.) are involved in this process, maintaining stable body temperature despite changes in ambient temperature. This study aims to perform a computer reconstruction of the human thermoregulation gene network and present the results in the Termo_Reg_Human 1.0 knowledge base. The gene network was reconstructed using the ANDSystem software and information system, designed for the automated extraction of knowledge and facts from scientific publications and biomedical databases based on machine learning and artificial intelligence methods. The Termo_Reg_Human 1.0 knowledge base (https://www.sysbio.ru/ThermoReg_Human/) contains information about the human thermoregulation gene network, including a description of 469 genes, 473 proteins, and 265 microRNAs important for its functioning, interactions between these objects, and the evolutionary characteristics of the genes. Using the ANDVisio software tool (a module of ANDSystem), each gene, protein, and microRNA involved in the thermoregulation of the human body was prioritized according to its functional significance, i. e., the number of interactions with other objects in the reconstructed gene network. It was found that the key objects with the largest number of functional interactions in the human thermoregulation gene network included the UCP1, VEGFA, PPARG and DDIT3 genes; STAT3, JUN, VEGFA, TLR4 and TNFA proteins; and the microRNAs hsa-mir-335 and hsa-mir-26b. We revealed that the set of 469 human genes from the network was enriched with genes whose ancestral forms originated at an early evolutionary stage (Unicellular organisms, the root of the phylostratigraphic tree) and at the stage of Vertebrata divergence.

Identification of the connections between the various functional components of the immune system is a crucial task in modern immunology. It is key to implementing the systems biology approach to understand the mechanisms of dynamic changes and outcomes of infectious and oncological diseases. The data characterizing an individual's immune status typically have a high-dimensional state space and a small sample size. To study the network topology of the immune system, we utilized previously published original data from Toptygina et al. (2023), which included measurements of the immune status in 19 healthy individuals (children, 9 boys and 10 girls, aged 1 to 2 years), i. e., the immune cells (42 subpopulations) obtained by flow cytometry; cytokine levels (13 types) obtained by multiplex analysis; and antibody levels (4 types) determined by using enzyme immunoassay. To correctly identify statistically significant correlations between the measured variables and construct the respective network graph, it is necessary to use an approach that takes into account the small size of the dataset. In this study, we implemented and analyzed an approach based on the regularized debiased sparse partial correlation (DSPC) algorithm to evaluate sparse partial correlations and identify the network structure of relationships in the immune system of healthy individuals (children) based on immune status data, which includes a set of indicators for subpopulations of immune cells, cytokine levels, and antibodies. For different levels of statistical significance, heatmaps of the partial correlations were constructed. The graph visualization of the DSPC networks was performed, and their topological characteristics were analyzed. It is found that with a limited measurements sample, the choice of a statistical significance threshold critically affects the structure of the partial correlations matrix. The final verification of the immunologically correct structure of the correlation-based network requires both an increase in the sample size and consideration of a priori mechanistic views and models of the functioning of the immune system components. The results of this analysis can be used to select the therapy targets and design combination therapies.

Oncological diseases remain a leading cause of pathological mortality worldwide, making the development of anticancer drugs a critical focus in medicinal chemistry. A promising strategy to enhance therapeutic efficacy and reduce chemotherapy-induced toxicity involves the combined inhibition of DNA repair enzymes and topoisomerases. Of particular interest are minor-groove DNA ligands, which exhibit potent inhibition of DNA-dependent enzymes while having low toxicity and mutagenicity. A number of research groups, including ours, are developing inhibitors of DNA repair enzymes that act simultaneously on several targets: tyrosyl-DNA phosphodiesterase 1/2 (TDP1/TDP2), poly(ADP-ribose) polymerase 1 (PARP1)/TDP1, topoisomerase 1 (TOP1)/TDP1. Such bifunctional inhibitors are designed to resolve the problem of tumor cell resistance to known chemotherapy drugs and increase the effectiveness of the latter. In this study, we evaluated the inhibitory activity of 22 minor-groove DNA ligands - bis- and trisbenzimidazoles against four key repair enzymes: TDP1, TDP2, PARP1, and PARP2. Four series of dimeric compounds and their monomeric units were studied. The difference in inhibitory activity of dimeric bisbenzimidazoles depending on the structure of the compound and the enzyme is shown. Our findings reveal distinct structure-activity relationships, with monomeric and dimeric ligands exhibiting potent TDP1 inhibition at micromolar to submicromolar IC50 values (half-maximal inhibitory concentration). Notably, dimeric compounds from the DB2Py(n) and DB3P(n) series demonstrated superior TDP1 inhibition compared to their monomers. In contrast, all tested compounds showed negligible activity against the other three repair enzymes; so, the compounds demonstrate specificity to TDP1. It should be noted that in this work, in the experiments with TDP1 and TDP2, the effect of the tested compounds as narrow-groove ligands binding to DNA was excluded, and their direct effect on the enzyme was investigated. The results of molecular docking suggest the possibility of direct interaction of active compounds with the active center of TDP1. According to the results of modeling, the inhibitors are located in the binding region of the 3'-end of DNA in the active site of TDP1 and could form stable bonds with the catalytically significant TDP1 residues His263 and His493. These interactions probably provide the high inhibitory activity of the compounds observed in biochemical experiments.

Stem rust, caused by the fungus Puccinia graminis f. sp. tritici (Pgt), is a harmful disease affecting grain crops. The traditional way to combat this and other infectious plant diseases is to use chemical pesticides. Biopesticides, as well as plant disease resistance inducers - in particular those based on chitosan, a derivative of chitin - are increasingly being considered as an effective and safe alternative. Recently, a globular form of chitosan, Novochizol, has been developed, which has a number of advantages and has shown its effectiveness in preliminary field and laboratory experiments. However, there are no works devoted to the effect of this preparation on the expression of defense genes. Therefore, the aim of this work was to search for genes involved in the response of common wheat (Triticum aestivum L.) to stem rust infection and to evaluate the effect of Novochizol treatment on their transcription during the infection process. The wheat line ISr6-Ra with the stem rust resistance gene Sr6 and two Pgt isolates - an avirulent one, Avr6, and a virulent one, vr6 - were used as a model, allowing us to compare the effects of Novochizol depending on the genetic compatibility in the plant-pathogen pathosystem. To analyze the transcription level of defense genes, leaf material was collected at different time points from 3 to 144 h after inoculation of plants with the pathogen. Quantitative PCR analysis showed an increase in the transcription levels of the CERK1, PR3, PR4, PR5, PR6 and PR9 genes in plants treated with Novochizol and infected with various Pgt isolates compared to untreated infected plants. Pgt isolate Avr6 induced the highest expression of some defense genes (primarily CERK1), which is consistent with the phytopathology data showing the maximum degree of resistance (IT1) to stem rust in Novochizol-treated plants with a combination of Sr6-Avr6 genes. The data obtained confirm that one of the optimal strategies for increasing the resistance of grain crops to fungal pathogens is a combination of selection for specific resistance genes with the use of biological control agents.

We recently proposed a novel class of nucleic acid derivatives - phosphoramidate benzoazole oligonucleotides (PABAOs). In these compounds, one of the non-bridging oxygen atoms is replaced by a phosphoramidate N-benzoazole group, such as benzimidazole, dimethylbenzimidazole, benzoxazole, or benzothiazole. Studies of the properties of these derivatives have shown that their use in PCR enhances the specificity and selectivity of the analysis. The study investigates the effect of phosphoramide N-benzimidazole modification of DNA primers on their elongation by Taq DNA polymerase using molecular dynamics simulations. We examined perfectly matched primer-template complexes with modifications at positions one through six from the 3'-end of the primer. Prior experimental work demonstrated that the degree of elongation suppression depends on the modification position: the closer to the 3'-end, the stronger the inhibition, with maximal suppression observed for the first position, especially in mismatched complexes. Furthermore, incomplete elongation products were experimentally observed for primers modified at the fourth position. Our molecular dynamics simulations and subsequent analysis revealed the molecular mechanisms underlying the interaction of modified primers with the enzyme. These include steric hindrance that impedes polymerase progression along the modified strand and local distortions in the DNA structure, which explain the experimentally observed trends. We established that both different stereoisomers of the phosphoramidate groups and conformers of the phosphoramidate N-benzimidazole moiety differentially affect the structure of the enzyme-substrate complex and the efficiency of Taq DNA polymerase interaction with the modified DNA complex. Modification of the first and second internucleoside phosphate from the 3'-end of the primer causes the most significant perturbation to the structure of the protein-nucleic acid complex. When the modification is located at the fourth phosphate group, the N-benzimidazole moiety occupies a specific pocket of the enzyme. These findings provide a foundation for the rational design of specific DNA primers bearing modified N-benzimidazole moieties with tailored properties for use in PCR diagnostics.

Major depressive disorder (MDD) is one of the most widespread mental illnesses, which necessitates the search for factors of increased predisposition to this disorder. Single nucleotide polymorphisms in genes of the brain's neurotransmitter systems are often considered as molecular genetic markers of MDD. Indicators of individual single nucleotide variability in neurotransmitter genes are used to assess the risk of MDD before its symptomatology at the behavioral level. However, the predictive capabilities of analyzing genomic variations to assess the risk of depression are not yet sufficiently reliable and are complemented by behavioral and neurophysiological information about patients. Neurophysiological markers of MDD provide the most reliable estimates of the severity of pathological symptoms, but they reflect a person's state at the time of examination, and not a predisposition to the occurrence of this pathological state and do not allow assessing the risk of its appearance in the future. Major depressive disorder is often accompanied by abnormalities in a person's ability to control motor responses, including the ability to voluntary suppress inappropriate behavior. The "stop-signal paradigm" (SSP) is an experimental method for assessing the functional balance between the inhibitory and activation systems of the brain during targeted movements. Combined with EEG recording, this experimental method allows for the consideration of not only participants' behavioral characteristics, such as speed or accuracy of responses, but also the brain's neurophysiological features associated with behavior control. The objective of this study was to evaluate the relationship between EEG responses in the stop-signal paradigm and individual single nucleotide variability in candidate genes for MDD detection. Dimensionality in the original genetic and neurophysiological experimental data was reduced by principal component analysis (PCA) to subsequently detect an association between EEG response components recorded during the control of random motor responses and single nucleotide variations in genes, the variability of which is asso-ciated with MDD risk. Variability in these genes has been shown to be associated with the amplitude of brain responses under the conditions of test subjects using the PCA method. The results obtained can be used to develop systems for the early diagnosis of depression, identify individual patterns of impairment in the brain, select methods for correcting the disease and control the effectiveness of therapy.

The nature of the last universal common ancestor (LUCA) of all living organisms remains a controversial issue in biology. There is evidence of both thermophilic and mesophilic LUCA origin. The increasing complexity of the cellular apparatus during the evolution from early life forms to modern organisms could have manifested itself in long-term evolutionary changes in the nucleotide composition of genetic sequences. This work is devoted to the identification of such trends in tRNA sequences. The results of an evolutionary analysis of single-nucleotide substitutions in tRNAs of 123 species from three domains - Bacteria, Archaea and Eukaryota - are presented. A universal vector of directed evolutionary change in tRNA sequences has been discovered, in which substitutions of guanine (G) to adenine (A) and cytosine (C) to uracil (U) occur more frequently than the reverse. The most striking asymmetry in the number of substitutions is observed in the following transitions: a) purine-to-purine, where G→A outnumbers A→G, b) pyrimidine-to-pyrimidine, where C→U outnumbers U→C, and c) purine-to-pyrimidine and vice versa, where G→U outnumbers U→G. As a result, tRNAs could lose "strong" three-hydrogen-bond complementary pairs formed by guanine and cytosine and fix "weak" two-hydrogen-bond complementary pairs formed by adenine and uracil. 16 out of 20 tRNA families are susceptible to the detected change in sequence composition, which corresponds to the significance level p = 0.006 according to the one-sided binomial test. The identified pattern indicates a high GC content in the common ancestor of modern tRNAs, supporting the hypothesis that the last universal common ancestor (LUCA) lived in a hotter environment than do most contemporary organisms.

Phenolic compounds constitute a significant group of secondary metabolites in barley grain and influence its technological qualities when used in brewing, feed production, and food manufacturing. Proanthocyanidins - polymeric flavonoids localized in the seed coat - play a particularly important role among them. These compounds are responsible for several production issues, such as colloidal haze in beer and browning of groats after heat treatment. Although proanthocyanidins possess health-beneficial properties based on their antioxidant activity, they can act as antinutritional factors due to their ability to bind proteins. In this regard, the breeding of barley varieties completely lacking proanthocyanidins in the grain was initiated, primarily for use in the brewing industry. Initially, it was assumed that their absence would not be critical for the plant, since wheat, corn, and rice varieties lacking proanthocyanidins in the grain had been identified. However, accumulated evidence indicates that proanthocyanidins perform important physiological functions: they contribute to the maintenance of seed dormancy, provide protection against fungal and bacterial pathogens and pests, and their absence negatively affects agronomic traits. For instance, proanthocyanidin-free barley mutants obtained through induced mutagenesis exhibit reduced productivity and pathogen resistance, an increased risk of pre-harvest sprouting, and deterioration of several technologically important properties. Nevertheless, these mutant lines are actively used in breeding programs to develop varieties for various purposes. This review aims to systematize and analyze global experience in breeding proanthocyanidin-free barley varieties, describing achieved results to identify the most successful approaches and define future research directions. The work examines challenges faced by breeders when using mutant lines, as well as strategies that have helped minimize negative side effects. It is demonstrated that through targeted crossing and optimal selection of mutant alleles, competitive varieties have been developed that combine the required technological qualities with satisfactory agronomic performance, meeting the demands of both the brewing and food industries.

The development of high-throughput sequencing has expanded the possibilities for studying the regulation of gene expression, including the reconstruction of gene regulatory networks and transcription factor regulatory networks (TFRNs). Identifying the molecular aspects for regulation of biological processes via these networks remains a challenge. Solving this problem for plants will significantly advance the understanding of the mechanisms shaping agronomically important traits. Previously, we developed the PlantReg program to reconstruct the transcriptional regulation of biological processes in the model species Arabidopsis thaliana L. The links established by this program between TFRNs and the genes regulating biological processes specify the type of regulation (activation/suppression). However, the program does not determine whether activation/suppression of the target gene is due to the cooperative or competitive interaction of transcription factors (TFs). We assumed that using information on the mutual arrangement of TF binding sites (BSs) in the target gene promoter as well as data on the activity type of TF effector domains would help to identify the cooperative/competitive action of TFs. We improved the program and created PlantReg 1.1, which enables precise localization of TF BSs in extended TF binding regions identified from genome-wide DAP-seq profiles (https://plamorph.sysbio.ru/fannotf/). To demonstrate the capabilities of the program, we used it to investigate the regulation of target genes in previously reconstructed TFRNs for auxin response and early reaction to salt stress in A. thaliana. The study focused on genes encoding proteins involved in chlorophyll and lignin biosynthesis, ribosome biogenesis, and abscisic acid (ABA) signaling. We revealed that the frequency of competitive regulation under the influence of auxin or salt stress could be quite high (approximately 30 %). We demonstrated that competition between bZIP family TFs for common BS is a significant mechanism of transcriptional repression in response to auxin, and that auxin and salt stress can engage common competitive regulatory mechanisms to modulate the expression of some genes in the ABA signaling pathway.

The rapid advancement of omics technologies (genomics, transcriptomics, proteomics, metabolomics) and other high-throughput methods for experimental studies of molecular genetic systems and processes has led to the generation of an unprecedentedly vast amount of heterogeneous and complex biological data. Effective use of this information resource requires systematic approaches to its analysis. One such approach involves the creation of domain-specific knowledge/data repositories that integrate information from multiple sources. This not only enables the storage and structuring of heterogeneous data distributed across various resources but also facilitates the acquisition of new insights into biological systems and processes. A systematic approach is also critical to solving the fundamental problem of biology - clarifying the regularities of morphogenesis. Morphogenesis is regulated through evolutionarily conserved signaling pathways (Hedgehog, Wnt, Notch, etc.). The Hedgehog (HH) pathway plays a key role in this process, as it begins functioning earlier than others in ontogenesis and determines the progression of every stage of an organism's life cycle: from structuring embryonic primordia, histo- and organogenesis, to maintaining tissue homeostasis and regeneration in adults. Our work presents HH_Signal_pathway_db, a knowledge base that integrates curated data on the molecular components and functional roles of the human Hedgehog (HH) signaling pathway. The first release of the database (available upon request at bukharina@bionet.nsc.ru) contains information on 56 genes, their protein products, the regulatory interaction network, and established associations with pathological conditions in humans. HH_Signal_pathway_db provides researchers with a tool for gaining new knowledge about the role of the Hedgehog pathway in health and disease, and its potential applications in developmental biology and translational medicine.