Vavilovskii Zhurnal Genetiki i Selektsii最新文献

{"title":"Ontologies in modelling and analysing of big genetic data.","authors":"N L Podkolodnyy, O A Podkolodnaya, V A Ivanisenko, M A Marchenko","doi":"10.18699/vjgb-24-101","DOIUrl":"https://doi.org/10.18699/vjgb-24-101","url":null,"abstract":"<p><p>To systematize and effectively use the huge volume of experimental data accumulated in the field of bioinformatics and biomedicine, new approaches based on ontologies are needed, including automated methods for semantic integration of heterogeneous experimental data, methods for creating large knowledge bases and self-interpreting methods for analyzing large heterogeneous data based on deep learning. The article briefly presents the features of the subject area (bioinformatics, systems biology, biomedicine), formal definitions of the concept of ontology and knowledge graphs, as well as examples of using ontologies for semantic integration of heterogeneous data and creating large knowledge bases, as well as interpreting the results of deep learning on big data. As an example of a successful project, the Gene Ontology knowledge base is described, which not only includes terminological knowledge and gene ontology annotations (GOA), but also causal influence models (GO-CAM). This makes it useful not only for genomic biology, but also for systems biology, as well as for interpreting large-scale experimental data. An approach to building large ontologies using design patterns is discussed, using the ontology of biological attributes (OBA) as an example. Here, most of the classification is automatically computed based on previously created reference ontologies using automated inference, except for a small number of high-level concepts. One of the main problems of deep learning is the lack of interpretability, since neural networks often function as \"black boxes\" unable to explain their decisions. This paper describes approaches to creating methods for interpreting deep learning models and presents two examples of self-explanatory ontology-based deep learning models: (1) Deep GONet, which integrates Gene Ontology into a hierarchical neural network architecture, where each neuron represents a biological function. Experiments on cancer diagnostic datasets show that Deep GONet is easily interpretable and has high performance in distinguishing cancerous and non-cancerous samples. (2) ONN4MST, which uses biome ontologies to trace microbial sources of samples whose niches were previously poorly studied or unknown, detecting microbial contaminants. ONN4MST can distinguish samples from ontologically similar biomes, thus offering a quantitative way to characterize the evolution of the human gut microbial community. Both examples demonstrate high performance and interpretability, making them valuable tools for analyzing and interpreting big data in biology.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"940-949"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11813802/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstruction and computer analysis of the structural and functional organization of the gene network regulating cholesterol biosynthesis in humans and the evolutionary characteristics of the genes involved in the network.","authors":"A D Mikhailova, S A Lashin, V A Ivanisenko, P S Demenkov, E V Ignatieva","doi":"10.18699/vjgb-24-94","DOIUrl":"https://doi.org/10.18699/vjgb-24-94","url":null,"abstract":"<p><p>Cholesterol is an essential structural component of cell membranes and a precursor of vitamin D, as well as steroid hormones. Humans and other animal species can absorb cholesterol from food. Cholesterol is also synthesized de novo in the cells of many tissues. We have previously reconstructed the gene network regulating intracellular cholesterol levels, which included regulatory circuits involving transcription factors from the SREBP (Sterol Regulatory Element-Binding Proteins) subfamily. The activity of SREBP transcription factors is regulated inversely depending on the intracellular cholesterol level. This mechanism is implemented with the participation of proteins SCAP, INSIG1, INSIG2, MBTPS1/S1P and MBTPS2/S2P. This group of proteins, together with the SREBP factors, is designated as \"cholesterol sensor\". An elevated cholesterol level is a risk factor for the development of cardiovascular diseases and may also be observed in obesity, diabetes and other pathological conditions. Systematization of information about the molecular mechanisms controlling the activity of SREBP factors and cholesterol biosynthesis in the form of a gene network and building new knowledge about the gene network as a single object is extremely important for understanding the molecular mechanisms underlying the predisposition to diseases. With a computer tool, ANDSystem, we have built a gene network regulating cholesterol biosynthesis. The gene network included data on: (1) the complete set of enzymes involved in cholesterol biosynthesis; (2) proteins that function as part of the \"cholesterol sensor\"; (3) proteins that regulate the activity of the \"cholesterol sensor\"; (4) genes encoding proteins of these groups; (5) genes whose transcription is regulated by SREBP factors (SREBP target genes). The gene network was analyzed and feedback loops that control the activity of SREBP factors were identified. These feedback loops involved the PPARG, NR0B2/SHP1, LPIN1, and AR genes and the proteins they encode. Analysis of the phylostratigraphic age of the genes showed that the ancestral forms of most human genes encoding the enzymes of cholesterol biosynthesis and the proteins of the \"cholesterol sensor\" may have arisen at early evolutionary stages (Cellular organisms (the root of the phylostratigraphic tree) and the stages of Eukaryota and Metazoa divergence). However, the mechanism of gene transcription regulation in response to changes in cholesterol levels may only have formed at later evolutionary stages, since the phylostratigraphic age of the genes encoding the transcription factors SREBP1 and SREBP2 corresponds to the stage of Vertebrata divergence.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"864-873"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143411024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of brain activity metrics in Chinese and Russian students while perceiving information referencing self or others.","authors":"Q Si, J Tian, V A Savostyanov, D A Lebedkin, A V Bocharov, A N Savostyanov","doi":"10.18699/vjgb-24-105","DOIUrl":"https://doi.org/10.18699/vjgb-24-105","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Neurocomputing technology is a field of interdisciplinary research and development widely applied in modern digital medicine. One of the problems of neuroimaging technology is the creation of methods for studying human brain activity in socially oriented conditions by using modern information approaches. The aim of this study is to develop a methodology for collecting and processing psychophysiological data, which makes it possible to estimate the functional states of the human brain associated with the attribution of external information to oneself or other people. Self-reference is a person's subjective assessment of information coming from the external environment as related to himself/herself. Assigning information to other people or inanimate objects is evaluating information as a message about someone else or about things. In modern neurophysiology, two approaches to the study of self-referential processing have been developed: (1) recording brain activity at rest, then questioning the participant for self-reported thoughts; (2) recording brain activity induced by self-assigned stimuli. In the presented paper, a technology was tested that combines registration and analysis of EEG with viewing facial video recordings. The novelty of our approach is the use of video recordings obtained in the first stage of the survey to induce resting states associated with recognition of information about different subjects in later stages of the survey. We have developed a software and hardware module, i. e. a set of related programs and procedures for their application consisting of blocks that allow for a full cycle of registration and processing of psychological and neurophysiological data. Using this module, brain electrical activity (EEG) indicators reflecting individual characteristics of recognition of information related to oneself and other people were compared between groups of 30 Chinese (14 men and 16 women, average age 23.2 ± 0.4 years) and 32 Russian (15 men, 17 women, average age 22.1 ± 0.4 years) participants. We tested the hypothesis that differences in brain activity in functional rest intervals between Chinese and Russian participants depend on their psychological differences in collectivism scores. It was revealed that brain functional activity depends on the subject relevance of the facial video that the participants viewed between resting-state intervals. Interethnic differences were observed in the activity of the anterior and parietal hubs of the default-mode network and depended on the subject attribution of information. In Chinese, but not Russian, participants significant positive correlations were revealed between the level of collectivism and spectral density in the anterior hub of the default-mode network in all experimental conditions for a wide range of frequencies. The developed software and hardware module is included in an integrated digital platform for conducting research in the field of systems biology and digita","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"982-992"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811493/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143411209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MetArea: a software package for analysis of the mutually exclusive occurrence in pairs of motifs of transcription factor binding sites based on ChIP-seq data.","authors":"V G Levitsky, A V Tsukanov, T I Merkulova","doi":"10.18699/vjgb-24-90","DOIUrl":"https://doi.org/10.18699/vjgb-24-90","url":null,"abstract":"<p><p>ChIP-seq technology, which is based on chromatin immunoprecipitation (ChIP), allows mapping a set of genomic loci (peaks) containing binding sites (BS) for the investigated (target) transcription factor (TF). A TF may recognize several structurally different BS motifs. The multiprotein complex mapped in a ChIP-seq experiment includes target and other \"partner\" TFs linked by protein-protein interactions. Not all these TFs bind to DNA directly. Therefore, both target and partner TFs recognize enriched BS motifs in peaks. A de novo search approach is used to search for enriched TF BS motifs in ChIP-seq data. For a pair of enriched BS motifs of TFs, the co-occurrence or mutually exclusive occurrence can be detected from a set of peaks: the co-occurrence reflects a more frequent occurrence of two motifs in the same peaks, while the mutually exclusive means their more frequent detection in different peaks. We propose the MetArea software package to identify pairs of TF BS motifs with the mutually exclusive occurrence in ChIP-seq data. MetArea was designed to predict the structural diversity of BS motifs of the same TFs, and the functional relation of BS motifs of different TFs. The functional relation of the motifs of the two distinct TFs presumes that they are interchangeable as part of a multiprotein complex that uses the BS of these TFs to bind directly to DNA in different peaks. MetArea calculates the estimates of recognition performance pAUPRC (partial area under the Precision-Recall curve) for each of the two input single motifs, identifies the \"joint\" motif, and computes the performance for it too. The goal of the analysis is to find pairs of single motifs A and B for which the accuracy of the joint A&B motif is higher than those of both single motifs.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"822-833"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11813801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis.","authors":"N V Basov, A V Adamovskaya, A D Rogachev, E V Gaisler, P S Demenkov, T V Ivanisenko, A S Venzel, S V Mishinov, V V Stupak, S V Cheresiz, O S Oleshko, E A Butikova, A E Osechkova, Yu S Sotnikova, Y V Patrushev, A S Pozdnyakov, I N Lavrik, V A Ivanisenko, A G Pokrovsky","doi":"10.18699/vjgb-24-96","DOIUrl":"https://doi.org/10.18699/vjgb-24-96","url":null,"abstract":"<p><p>The metabolomic profiles of glioblastoma and surrounding brain tissue, comprising 17 glioblastoma samples and 15 peritumoral tissue samples, were thoroughly analyzed in this investigation. The LC-MS/MS method was used to analyze over 400 metabolites, revealing significant variations in metabolite content between tumor and peritumoral tissues. Statistical analyses, including the Mann-Whitney and Cucconi tests, identified several metabolites, particularly ceramides, that showed significant differences between glioblastoma and peritumoral tissues. Pathway analysis using the KEGG database, conducted with MetaboAnalyst 6.0, revealed a statistically significant overrepresentation of sphingolipid metabolism, suggesting a critical role of these lipid molecules in glioblastoma pathogenesis. Using computational systems biology and artificial intelligence methods implemented in a cognitive platform, ANDSystem, molecular genetic regulatory pathways were reconstructed to describe potential mechanisms underlying the dysfunction of sphingolipid metabolism enzymes. These reconstructed pathways were integrated into a regulatory gene network comprising 15 genes, 329 proteins, and 389 interactions. Notably, 119 out of the 294 proteins regulating the key enzymes of sphingolipid metabolism were associated with glioblastoma. Analysis of the overrepresentation of Gene Ontology biological processes revealed the statistical significance of 184 processes, including apoptosis, the NF-kB signaling pathway, proliferation, migration, angiogenesis, and pyroptosis, many of which play an important role in oncogenesis. The findings of this study emphasize the pivotal role of sphingolipid metabolism in glioblastoma development and open new prospects for therapeutic approaches modulating this metabolism.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"882-896"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Search for and functional annotation of multi-domain PLA2 family proteins in flatworms.","authors":"M E Bocharnikova, I I Turnaev, D A Afonnikov","doi":"10.18699/vjgb-24-93","DOIUrl":"https://doi.org/10.18699/vjgb-24-93","url":null,"abstract":"<p><p>The phospholipase A2 (PLA2) is a superfamily of hydrolases that catalyze the hydrolysis of phospholipids and play a key role in many molecular processes in the cells and the organism as a whole. This family consists of 16 groups divided into six main types. PLA2 were first isolated from venom toxins and porcine pancreatic juice. The study of these enzymes is currently of great interest, since it has been shown that a number of PLA2 are involved in the processes of carcinogenesis. PLA2 enzymes were characterized in detail in model organisms and humans. However, their presence and functional role in non-model organisms is poorly understood. Such poorly studied taxa include flatworms, a number of species of which are human parasites. Several PLA2 genes have previously been characterized in parasitic flatworms and their possible role in parasite-host interaction has been shown. However, no systematic identification of the PLA2 genes in this taxon has been carried out. The paper provides a search for and a comparative analysis of PLA2 sequences encoded in the genomes of flatworms. 44 species represented by two free-living and 42 parasitic organisms were studied. The analysis was based on identification of orthologous groups of protein-coding genes, taking into account the domain structure of proteins. In flatworms, 12 of the 13 known types of animal A2 phospholipases were found, represented by 11 orthologous groups. Some phospholipases of several types fell into one orthologous group, some types split into several orthogroups in accordance with their domain structure. It has been shown that phospholipases A2 of the calcium-independent type, platelet-activating phospholipases from group G8 and lysosomal phospholipases from group G15 are represented in all large taxa of flatworms and the vast majority of the species studied by us. In free-living flatworms PLA2 genes have multiple copies. In parasitic flatworms, on the contrary, loss of genes occur specifically in individual taxa specifically for groups or subfamilies of PLAs. An orthologous group of secreted phospholipases has been identified, which is represented only in Digenea and this family has undergone duplications in the genomes of opisthorchids. Interestingly, a number of experimental studies have previously shown the effect of Clonorchis sinensis proteins of this orthogroup on the cancer transformation of host cells. Our results made it possible for the first time to systematically identify PLA2 sequences in flatworms, and demonstrated that their evolution is subject to gene loss processes characteristic of parasite genomes in general. In addition, our analysis allowed us to identify taxon-specific processes of duplication and loss of PLA2 genes in parasitic organisms, which may be associated with the processes of their interaction with the host organism.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"854-863"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811501/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143411093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer analysis shows differences between mitochondrial miRNAs and other miRNAs.","authors":"P S Vorozheykin, I I Titov","doi":"10.18699/vjgb-24-91","DOIUrl":"https://doi.org/10.18699/vjgb-24-91","url":null,"abstract":"<p><p>A subclass of miRNAs with as yet unknown specific functions is mitomiRs - mitochondrial miRNAs that are mainly derived from nuclear DNA and are imported into mitochondria; moreover, changes in the expression levels of mitomiRs are associated with some diseases. To identify the most pronounced characteristics of mitochondrial miRNAs that distinguish them from other miRNAs, we classified mitomiR sequences using the Random Forest algorithm. The analysis revealed, for the first time, a significant difference between mitomiRs and other microRNAs by the following criteria (in descending order of importance in the classification): mitomiRs are evolutionarily older (have a lower phylostratigraphic age index, PAI); have more targets and disease associations, including mitochondrial ones (two-sided Fisher's exact test, average p-values 1.82 × 10-89/1.13 × 10-96 for all mRNA/diseases and 6.01 × 10-22/1.09 × 10-9 for mitochondria, respectively); and are in the class of \"circulating\" miRNAs (average p- value 1.20 × 10-56). The identified differences between mitomiRs and other miRNAs may help uncover the mode of miRNA delivery into mitochondria, indicate the evolutionary conservation and importance of mitomiRs in the regulation of mitochondrial function and metabolism, and generally show that mitomiRs are not randomly encountered miRNAs. Information on 1,312 experimentally validated mitomiR sequences for three organisms (Homo sapiens, Mus musculus and Rattus norvegicus) is collected in the mitomiRdb database (https://mitomiRdb.org).Key words: mitomiR; mitochondria; miRNA; evolution; database.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"834-842"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811498/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gene networks and metabolomic screening analysis revealed specific pathways of amino acid and acylcarnitine profile alterations in blood plasma of patients with Parkinson's disease and vascular parkinsonism.","authors":"A A Makarova, P M Melnikova, A D Rogachev, P S Demenkov, T V Ivanisenko, E V Predtechenskaya, S Y Karmanov, V V Koval, A G Pokrovsky, I N Lavrik, N A Kolchanov, V A Ivanisenko","doi":"10.18699/vjgb-24-100","DOIUrl":"https://doi.org/10.18699/vjgb-24-100","url":null,"abstract":"<p><p>Parkinson's disease (PD) and vascular parkinsonism (VP) are characterized by similar neurological syndromes but differ in pathogenesis, morphology, and therapeutic approaches. The molecular genetic mechanisms of these pathologies are multifactorial and involve multiple biological processes. To comprehensively analyze the pathophysiology of PD and VP, the methods of systems biology and gene network reconstruction are essential. In the current study, we performed metabolomic screening of amino acids and acylcarnitines in blood plasma of three groups of subjects: PD patients, VP patients and the control group. Comparative statistical analysis of the metabolic profiles identified significantly altered metabolites in the PD and the VP group. To identify potential mechanisms of amino acid and acylcarnitine metabolism disorders in PD and VP, regulatory gene networks were reconstructed using ANDSystem, a cognitive system. Regulatory pathways to the enzymes converting significant metabolites were found from PD-specific genetic markers, VP-specific genetic markers, and the group of genetic markers common to the two diseases. Comparative analysis of molecular genetic pathways in gene networks allowed us to identify both specific and non-specific molecular mechanisms associated with changes in the metabolomic profile in PD and VP. Regulatory pathways with potentially impaired function in these pathologies were discovered. The regulatory pathways to the enzymes ALDH2, BCAT1, AL1B1, and UD11 were found to be specific for PD, while the pathways regulating OCTC, FURIN, and S22A6 were specific for VP. The pathways regulating BCAT2, ODPB and P4HA1 were associated with genetic markers common to both diseases. The results obtained deepen the understanding of pathological processes in PD and VP and can be used for application of diagnostic systems based on the evaluation of the amino acids and acylcarnitines profile in blood plasma of patients with PD and VP.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"927-939"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811507/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GlucoGenes®, a database of genes and proteins associated with glucose metabolism disorders, its description and applications in bioinformatics research.","authors":"V V Klimontov, K S Shishin, R A Ivanov, M P Ponomarenko, K A Zolotareva, S A Lashin","doi":"10.18699/vjgb-24-107","DOIUrl":"https://doi.org/10.18699/vjgb-24-107","url":null,"abstract":"<p><p>Data on the genetics and molecular biology of diabetes are accumulating rapidly. This poses the challenge of creating research tools for a rapid search for, structuring and analysis of information in this field. We have developed a web resource, GlucoGenes®, which includes a database and an Internet portal of genes and proteins associated with high glucose (hyperglycemia), low glucose (hypoglycemia), and both metabolic disorders. The data were collected using text mining of the publications indexed in PubMed and PubMed Central and analysis of gene networks associated with hyperglycemia, hypoglycemia and glucose variability performed with ANDSystems, a bioinformatics tool. GlucoGenes® is freely available at: https://glucogenes.sysbio.ru/genes/main. GlucoGenes® enables users to access and download information about genes and proteins associated with the risk of hyperglycemia and hypoglycemia, molecular regulators with hyperglycemic and antihyperglycemic activity, genes up-regulated by high glucose and/or low glucose, genes down-regulated by high glucose and/or low glucose, and molecules otherwise associated with the glucose metabolism disorders. With GlucoGenes®, an evolutionary analysis of genes associated with glucose metabolism disorders was performed. The results of the analysis revealed a significant increase (up to 40 %) in the proportion of genes with phylostratigraphic age index (PAI) values corresponding to the time of origin of multicellular organisms. Analysis of sequence conservation using the divergence index (DI) showed that most of the corresponding genes are highly conserved (DI < 0.6) or conservative (DI < 1). When analyzing single nucleotide polymorphism (SNP) in the proximal regions of promoters affecting the affinity of the TATA-binding protein, 181 SNP markers were found in the GlucoGenes® database, which can reduce (45 SNP markers) or increase (136 SNP markers) the expression of 52 genes. We believe that this resource will be a useful tool for further research in the field of molecular biology of diabetes.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"1008-1017"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstruction and computational analysis of the microRNA regulation gene network in wheat drought response mechanisms.","authors":"M A Kleshchev, A V Maltseva, E A Antropova, P S Demenkov, T V Ivanisenko, Y L Orlov, H Chao, M Chen, N A Kolchanov, V A Ivanisenko","doi":"10.18699/vjgb-24-98","DOIUrl":"https://doi.org/10.18699/vjgb-24-98","url":null,"abstract":"<p><p>Drought is a critical factor limiting the productivity of bread wheat (Triticum aestivum L.), one of the key agricultural crops. Wheat adaptation to water deficit is ensured by complex molecular genetic mechanisms, including the coordinated work of multiple genes regulated by transcription factors and signaling non-coding RNAs, particularly microRNAs (miRNAs). miRNA-mediated regulation of gene expression is considered one of the main mechanisms of plant resistance to abiotic stresses. Studying these mechanisms necessitates computational systems biology methods. This work aims to reconstruct and analyze the gene network associated with miRNA regulation of wheat adaptation to drought. Using the ANDSystem software and the specialized Smart crop knowledge base adapted for wheat genetics and breeding, we reconstructed a wheat gene network responding to water deficit, comprising 144 genes, 1,017 proteins, and 21 wheat miRNAs. Analysis revealed that miRNAs primarily regulate genes controlling the morphogenesis of shoots and roots, crucial for morphological adaptation to drought. The key network components regulated by miRNAs are the MYBa and WRKY41 family transcription factors, heat-shock protein HSP90, and the RPM1 protein. These proteins are associated with phytohormone signaling pathways and calcium-dependent protein kinases significant in plant water deficit adaptation. Several miRNAs (MIR7757, MIR9653a, MIR9671 and MIR9672b) were identified that had not been previously discussed in wheat drought adaptation. These miRNAs regulate many network nodes and are promising candidates for experimental studies to enhance wheat resistance to water deficiency. The results obtained can find application in breeding for the development of new wheat varieties with increased resistance to water deficit, which is of substantial importance for agriculture in the context of climate change.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":"28 8","pages":"904-917"},"PeriodicalIF":0.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143411019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}