Orthoscape: a cytoscape application for grouping and visualization KEGG based gene networks by taxonomy and homology principles

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus

Translation efficiency modulates gene expression in prokaryotes. The comparative analysis of translation elongation efficiency characteristics of Ralstonia genus bacteria genomes revealed that these characteristics diverge in accordance with the phylogeny of Ralstonia. The first branch of this genus is a group of bacteria commonly found in moist environments such as soil and water that includes the species R. mannitolilytica, R. insidiosa, and R. pickettii, which are also described as nosocomial infection pathogens. In contrast, the second branch is plant pathogenic bacteria consisting of R. solanacearum, R. pseudosolanacearum, and R. syzygii. We found that the soil Ralstonia have a significantly lower number and energy of potential secondary structures in mRNA and an increased role of codon usage bias in the optimization of highly expressed genes' translation elongation efficiency, not only compared to phytopathogenic Ralstonia but also to Cupriavidus necator, which is closely related to the Ralstonia genus. The observed alterations in translation elongation efficiency of orthologous genes are also reflected in the difference of potentially highly expressed gene' sets' content among Ralstonia branches with different lifestyles. Analysis of translation elongation efficiency characteristics can be considered a promising approach for studying complex mechanisms that determine the evolution and adaptation of bacteria in various environments.

Candidate SNP Markers Significantly Altering the Affinity of TATA-Binding Protein for the Promoters of Human Hub Genes for Atherogenesis, Atherosclerosis and Atheroprotection

Atherosclerosis is a systemic disease in which focal lesions in arteries promote the build-up of lipoproteins and cholesterol they are transporting. The development of atheroma (atherogenesis) narrows blood vessels, reduces the blood supply and leads to cardiovascular diseases. According to the World Health Organization (WHO), cardiovascular diseases are the leading cause of death, which has been especially boosted since the COVID-19 pandemic. There is a variety of contributors to atherosclerosis, including lifestyle factors and genetic predisposition. Antioxidant diets and recreational exercises act as atheroprotectors and can retard atherogenesis. The search for molecular markers of atherogenesis and atheroprotection for predictive, preventive and personalized medicine appears to be the most promising direction for the study of atherosclerosis. In this work, we have analyzed 1068 human genes associated with atherogenesis, atherosclerosis and atheroprotection. The hub genes regulating these processes have been found to be the most ancient. In silico analysis of all 5112 SNPs in their promoters has revealed 330 candidate SNP markers, which statistically significantly change the affinity of the TATA-binding protein (TBP) for these promoters. These molecular markers have made us confident that natural selection acts against underexpression of the hub genes for atherogenesis, atherosclerosis and atheroprotection. At the same time, upregulation of the one for atheroprotection promotes human health.

Differentially Expressed Genes and Molecular Susceptibility to Human Age-Related Diseases

Mainstream transcriptome profiling of susceptibility versus resistance to age-related diseases (ARDs) is focused on differentially expressed genes (DEGs) specific to gender, age, and pathogeneses. This approach fits in well with predictive, preventive, personalized, participatory medicine and helps understand how, why, when, and what ARDs one can develop depending on their genetic background. Within this mainstream paradigm, we wanted to find out whether the known ARD-linked DEGs available in PubMed can reveal a molecular marker that will serve the purpose in anyone's any tissue at any time. We sequenced the periaqueductal gray (PAG) transcriptome of tame versus aggressive rats, identified rat-behavior-related DEGs, and compared them with their known homologous animal ARD-linked DEGs. This analysis yielded statistically significant correlations between behavior-related and ARD-susceptibility-related fold changes (log₂ values) in the expression of these DEG homologs. We found principal components, PC1 and PC2, corresponding to the half-sum and the half-difference of these log₂ values, respectively. With the DEGs linked to ARD susceptibility and ARD resistance in humans used as controls, we verified these principal components. This yielded only one statistically significant common molecular marker for ARDs: an excess of Fcγ receptor IIb suppressing immune cell hyperactivation.

FunHoP: Enhanced Visualization and Analysis of Functionally Homologous Proteins in Complex Metabolic Networks

Cytoscape is often used for visualization and analysis of metabolic pathways. For example, based on KEGG data, a reader for KEGG Markup Language (KGML) is used to load files into Cytoscape. However, although multiple genes can be responsible for the same reaction, the KGML-reader KEGGScape only presents the first listed gene in a network node for a given reaction. This can lead to incorrect interpretations of the pathways. Our new method, FunHoP, shows all possible genes in each node, making the pathways more complete. FunHoP collapses all genes in a node into one measurement using read counts from RNA-seq. Assuming that activity for an enzymatic reaction mainly depends upon the gene with the highest number of reads, and weighting the reads on gene length and ratio, a new expression value is calculated for the node as a whole. Differential expression at node level is then applied to the networks. Using prostate cancer as model, we integrate RNA-seq data from two patient cohorts with metabolism data from literature. Here we show that FunHoP gives more consistent pathways that are easier to interpret biologically. Code and documentation for running FunHoP can be found at https://github.com/kjerstirise/FunHoP.

A Streamlined Approach to Pathway Analysis from RNA-Sequencing Data

The reduction in costs associated with performing RNA-sequencing has driven an increase in the application of this analytical technique; however, restrictive factors associated with this tool have now shifted from budgetary constraints to time required for data processing. The sheer scale of the raw data produced can present a formidable challenge for researchers aiming to glean vital information about samples. Though many of the companies that perform RNA-sequencing provide a basic report for the submitted samples, this may not adequately capture particular pathways of interest for sample comparisons. To further assess these data, it can therefore be necessary to utilize various enrichment and mapping software platforms to highlight specific relations. With the wide array of these software platforms available, this can also present a daunting task. The methodology described herein aims to enable researchers new to handling RNA-sequencing data with a streamlined approach to pathway analysis. Additionally, the implemented software platforms are readily available and free to utilize, making this approach viable, even for restrictive budgets. The resulting tables and nodal networks will provide valuable insight into samples and can be used to generate high-quality graphics for publications and presentations.

Phylostratigraphic analysis of gene networks of human diseases

Phylostratigraphic analysis is an approach to the study of gene evolution that makes it possible to determine the time of the origin of genes by analyzing their orthologous groups. The age of a gene belonging to an orthologous group is def ined as the age of the most recent ancestor of all species represented in that group. Such an analysis can reveal important stages in the evolution of both the organism as a whole and groups of functionally related genes, in particular gene networks. In addition to investigating the time of origin of a gene, the level of its genetic variability and what type of selection the gene is subject to in relation to the most closely related organisms is studied. Using the Orthoscape application, gene networks from the KEGG Pathway, Human Diseases database describing various human diseases were analyzed. It was shown that the majority of genes described in gene networks are under stabilizing selection and a high reliable correlation was found between the time of gene origin and the level of genetic variability: the younger the gene, the higher the level of its variability is. It was also shown that among the gene networks analyzed, the highest proportion of evolutionarily young genes was found in the networks associated with diseases of the immune system (65 %), and the highest proportion of evolutionarily ancient genes was found in the networks responsible for the formation of human dependence on substances that cause addiction to chemical compounds (88 %); gene networks responsible for the development of infectious diseases caused by parasites are signif icantly enriched for evolutionarily young genes, and gene networks responsible for the development of specif ic types of cancer are signif icantly enriched for evolutionarily ancient genes.

Nine Genes Mediate the Therapeutic Effects of Iodine-131 Radiotherapy in Thyroid Carcinoma Patients

Background

Thyroid carcinoma (THCA) is one of the most common malignancies of the endocrine system, which is usually treated by surgery combined with iodine-131 (I¹³¹) radiotherapy.

Aims

This study is aimed at exploring the potential targets of I¹³¹ radiotherapy in THCA.

Methods

The RNA-sequencing data of THCA in The Cancer Genome Atlas database (including 568 THCA samples) was downloaded. The differentially expressed genes (DEGs) between the tumour samples whether or not subjected to I¹³¹ radiotherapy were identified using edgeR package. Using the WGCNA package, the module that was relevant with I¹³¹ radiotherapy was selected. The intersection genes of the hub module nodes and the DEGs were obtained as hub genes, followed by the function and pathway enrichment analyses using the clusterProfiler package. Moreover, the protein-protein interaction (PPI) network for the hub genes was constructed using Cytoscape software. In addition, more important hub genes were analysed with function mining using the GenCLiP2 online tool. The qPCR analysis was used to verify the mRNA expression of more important hub genes in THCA tissues.

Results

There were 500 DEGs (167 upregulated and 333 downregulated) between the two groups. WGCNA analysis showed that the green module (428 nodes) exhibited the most significant correlation with I¹³¹ radiotherapy. A PPI network was built after the identification of 53 hub genes. In the PPI network, CDH5, KDR, CD34, FLT4, EMCN, FLT1, ROBO4, PTPRB, and CD93 exhibited higher degrees, which were mainly implicated in the vascular function. The relative expression of nine mRNAs in the THCA tissues treated with I¹³¹ was lower.

Conclusion

I¹³¹ radiotherapy might exert therapeutic effects by targeting CDH5, KDR, CD34, FLT4, EMCN, FLT1, ROBO4, PTPRB, and CD93 in THCA patients.

Phylostratigraphic Analysis Shows the Earliest Origination of the Abiotic Stress Associated Genes in A. thaliana

Plants constantly fight with stressful factors as high or low temperature, drought, soil salinity and flooding. Plants have evolved a set of stress response mechanisms, which involve physiological and biochemical changes that result in adaptive or morphological changes. At a molecular level, stress response in plants is performed by genetic networks, which also undergo changes in the process of evolution. The study of the network structure and evolution may highlight mechanisms of plants adaptation to adverse conditions, as well as their response to stresses and help in discovery and functional characterization of the stress-related genes. We performed an analysis of Arabidopsis thaliana genes associated with several types of abiotic stresses (heat, cold, water-related, light, osmotic, salt, and oxidative) at the network level using a phylostratigraphic approach. Our results show that a substantial fraction of genes associated with various types of abiotic stress is of ancient origin and evolves under strong purifying selection. The interaction networks of genes associated with stress response have a modular structure with a regulatory component being one of the largest for five of seven stress types. We demonstrated a positive relationship between the number of interactions of gene in the stress gene network and its age. Moreover, genes of the same age tend to be connected in stress gene networks. We also demonstrated that old stress-related genes usually participate in the response for various types of stress and are involved in numerous biological processes unrelated to stress. Our results demonstrate that the stress response genes represent the ancient and one of the fundamental molecular systems in plants.

Feifukang ameliorates pulmonary fibrosis by inhibiting JAK-STAT signaling pathway

Background

Feifukang (FFK) is a traditional Chinese medicine composed of herbs that protect lung function. However, difficulty arises regarding the clinical application of FFK due to the complex mechanism of Chinese medicines. This study aimed to investigate the efficacy of FFK and explore its targeted genes and pathways.

Methods

Histopathological changes and collagen deposition were measured to evaluate the effect of FFK on bleomycin-induced pulmonary fibrosis in mice. The differentially expressed targeted genes and pathways were first screened using RNA sequencing. Then network pharmacology and other experiments were conducted to confirm RNA sequencing data.

Results

FFK treatment reduced the pathological score and collagen deposition, with a decrease in α-SMA and collagen. RNA sequencing and network pharmacology results all showed that FFK can ameliorate pulmonary fibrosis through multi-genes and multi-pathways. The targeted genes in JAK-STAT signaling pathway are some of the most notable components of these multi-genes and multi-pathways. Further experiments illustrated that FFK regulated phosphorylation of SMAD3, STAT3 and JAK1, and their co-expressed lncRNAs, which all are the important genes in JAK-STAT signaling pathway.

Conclusion

FFK can ameliorate pulmonary fibrosis by inhibiting JAK-STAT signaling pathway and has potential therapeutic value for lung fibrosis treatment. Our study provides a new idea for the study of traditional Chinese medicine.

Towards a Dynamic Interaction Network of Life to unify and expand the evolutionary theory

The classic Darwinian theory and the Synthetic evolutionary theory and their linear models, while invaluable to study the origins and evolution of species, are not primarily designed to model the evolution of organisations, typically that of ecosystems, nor that of processes. How could evolutionary theory better explain the evolution of biological complexity and diversity? Inclusive network-based analyses of dynamic systems could retrace interactions between (related or unrelated) components. This theoretical shift from a Tree of Life to a Dynamic Interaction Network of Life, which is supported by diverse molecular, cellular, microbiological, organismal, ecological and evolutionary studies, would further unify evolutionary biology.