Gene Interaction Network Analysis Research Articles

Genome-Wide Identification and Expression Analysis of the BTB Gene Superfamily Provides Insight into Sex Determination and Early Gonadal Development of Alligator sinensis.

The BTB gene superfamily is widely distributed among higher eukaryotes and plays a significant role in numerous biological processes. However, there is limited knowledge about the structure and function of BTB genes in the critically endangered species Alligator sinensis, which is endemic to China. A total of 170 BTB genes were identified from the A. sinensis genome, classified into 13 families, and unevenly distributed across 16 chromosomes. Analysis of gene duplication events yielded eight pairs of tandem duplication genes and six pairs of segmental duplication genes. Phylogenetics shows that the AsBTB genes are evolutionarily conserved. The cis-regulatory elements in the AsBTB family promoter region reveal their involvement in multiple biological processes. Protein interaction network analysis indicates that the protein interactions of the AsBTB genes are centered around CLU-3, mainly participating in the regulation of biological processes through the ubiquitination pathway. The expression profile and protein interaction network analysis of AsBTB genes during sex differentiation and early gonadal development indicate that AsBTB genes are widely expressed in this process and involves numerous genes and pathways for regulation. This study provides a basis for further investigation of the role of the BTB gene in sex differentiation and gonadal development in A. sinensis.

Immune signature of gene expression pattern shared by autism spectrum disorder and Huntington's disease

Autism spectrum disorder (ASD) and Huntington's disease (HD) are complex neurological conditions with unclear causes and limited treatments, affecting individuals, families, and society. Despite ASD and HD representing two opposing stages of neuronal development and degeneration, they share similar clinical-pathological features in motor function. In this study, we leveraged transcriptomic data from the prefrontal cortex available in public databases to identify shared transcriptional characteristics of ASD and HD. Differential expression analysis revealed that the majority of differentially expressed genes (DEGs) were up-regulated in ASD carriers, whereas most DEGs were down-regulated in HD carriers. Among the DEGs shared between both diseases, three out of seven protein-coding genes were related to the immune system. Furthermore, we identified two enriched pathways shared between ASD and HD DEGs. The gene interaction network analysis unveiled four hub genes shared by both diseases, all of which are associated with immune functions. The findings suggest a shared gene expression pattern in the prefrontal cortex of people with ASD and HD, closely linked to the immune system. These findings will contribute to exploring the biological mechanisms underlying the shared phenotypes of these two diseases from an immunological perspective.

Risk prediction model of uterine corpus endometrial carcinoma based on immune-related genes

BackgroundGiven the significant role of immune-related genes in uterine corpus endometrial carcinoma (UCEC) and the long-term outcomes of patients, our objective was to develop a prognostic risk prediction model using immune-related genes to improve the accuracy of UCEC prognosis prediction.MethodsThe Limma, ESTIMATE, and CIBERSORT methods were used for cluster analysis, immune score calculation, and estimation of immune cell proportions. Univariate and multivariate analyses were utilized to develop a prognostic risk model for UCEC. Risk model scores and nomograms were used to evaluate the models. String constructs a protein-protein interaction (PPI) network of genes. The qRT-PCR, immunofluorescence, and immunohistochemistry (IHC) all confirmed the genes.ResultsCluster analysis divided the immune-related genes into four subtypes. 33 immune-related genes were used to independently predict the prognosis of UCEC and construct the prognosis model and risk score. The analysis of the survival nomogram indicated that the model has excellent predictive ability and strong reliability for predicting the survival of patients with UCEC. The protein-protein interaction network analysis of key genes indicates that four genes play a pivotal role in interactions: GZMK, IL7, GIMAP, and UBD. The quantitative real-time polymerase chain reaction (qRT-PCR), immunofluorescence, and immunohistochemistry (IHC) all confirmed the expression of the aforementioned genes and their correlation with immune cell levels. This further revealed that GZMK, IL7, GIMAP, and UBD could potentially serve as biomarkers associated with immune levels in endometrial cancer.ConclusionThe study identified genes related to immune response in UCEC, including GZMK, IL7, GIMAP, and UBD, which may serve as new biomarkers and therapeutic targets for evaluating immune levels in the future.

The shared mechanism and potential diagnostic markers for premature ovarian failure and dry eye disease

Premature ovarian failure (POF), which is often comorbid with dry eye disease (DED) is a key issue affecting female health. Here, we explored the mechanism underlying comorbid POF and DED to further elucidate disease mechanisms and improve treatment. Datasets related to POF (GSE39501) and DED (GSE44101) were identified from the Gene Expression Omnibus (GEO) database and subjected to weighted gene coexpression network (WGCNA) and differentially expressed genes (DEGs) analyses, respectively, with the intersection used to obtain 158 genes comorbid in POF and DED. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses of comorbid genes revealed that identified genes were primarily related to DNA replication and Cell cycle, respectively. Protein–Protein interaction (PPI) network analysis of comorbid genes obtained the 15 hub genes: CDC20, BIRC5, PLK1, TOP2A, MCM5, MCM6, MCM7, MCM2, CENPA, FOXM1, GINS1, TIPIN, MAD2L1, and CDCA3. To validate the analysis results, additional POF- and DED-related datasets (GSE48873 and GSE171043, respectively) were selected. miRNAs-lncRNAs-genes network and machine learning methods were used to further analysis comorbid genes. The DGIdb database identified valdecoxib, amorfrutin A, and kaempferitrin as potential drugs. Herein, the comorbid genes of POF and DED were identified from a bioinformatics perspective, providing a new strategy to explore the comorbidity mechanism, opening up a new direction for the diagnosis and treatment of comorbid POF and DED.

Phytochemical analysis, in-vitro and in-silico study of antiproliferative activity of ethyl acetate fraction of Launaea cornuta (Hochst. ex Oliv. & Hiern) C. Jeffrey against human cervical cancer cell line.

Introduction: Cervical cancer is one of the leading causes of death among women globally due to the limitation of current treatment methods and their associated adverse side effects. Launaea cornuta is used as traditional medicine for the treatment of a variety of diseases including cancer. However, there is no scientific validation on the antiproliferative activity of L. cornuta against cervical cancer. Objective: This study aimed to evaluate the selective antiproliferative, cytotoxic and antimigratory effects of L. cornuta and to explore its therapeutical mechanisms in human cervical cancer cell lines (HeLa-229) through a network analysis approach. Materials and methods: The cytotoxic effect of L. cornuta ethyl acetate fraction on the proliferation of cervical cancer cells was evaluated by 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) bioassay and the antimigratory effect was assessed by wound healing assays. Compounds were analysed using the qualitative colour method and gas chromatography-mass spectroscopy (GC-MS). Subsequently, bioinformatic analyses, including the protein-protein interaction (PPI) network analysis, Gene Ontology (GO), and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis, were performed to screen for potential anticervical cancer therapeutic target genes of L. cornuta. Molecular docking (MD) was performed to predict and understand the molecular interactions of the ligands against cervical cancer. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to validate the network analysis results. Results: L. cornuta ethyl acetate fraction exhibited a remarkable cytotoxic effect on HeLa-229 proliferation (IC50 of 20.56 ± 2.83μg/mL) with a selectivity index (SI) of 2.36 with minimal cytotoxicity on non-cancerous cells (Vero-CCL 81 (IC50 of 48.83 ± 23.02). The preliminary screening revealed the presence of glycosides, phenols, saponins, terpenoids, quinones, and tannins. Thirteen compounds were also identified by GC-MS analysis. 124 potential target genes associated with the effect of L. cornuta ethyl acetate fraction on human cervical cancer were obtained, including AKT1, MDM2, CDK2, MCL1 and MTOR were identified among the top hub genes and PI3K/Akt1, Ras/MAPK, FoxO and EGFR signalling pathways were identified as the significantly enriched pathways. Molecular docking results showed that stigmasteryl methyl ether had a good binding affinity against CDK2, ATK1, BCL2, MDM2, and Casp9, with binding energy ranging from -7.0 to -12.6kcal/mol. Tremulone showed a good binding affinity against TP53 and P21 with -7.0 and -8.0kcal/mol, respectively. This suggests a stable molecular interaction of the ethyl acetate fraction of L. cornuta compounds with the selected target genes for cervical cancer. Furthermore, RT-qPCR analysis revealed that CDK2, MDM2 and BCL2 were downregulated, and Casp9 and P21 were upregulated in HeLa-229 cells treated with L. cornuta compared to the negative control (DMSO 0.2%). Conclusion: The findings indicate that L. cornuta ethyl acetate fraction phytochemicals modulates various molecular targets and pathways to exhibit selective antiproliferative and cytotoxic effects against HeLa-229 cells. This study lays a foundation for further research to develop innovative clinical anticervical cancer agents.

Comparative transcriptome analysis of slow-twitch and fast-twitch muscles in Kazakh horses

This study conducted a thorough analysis of the myofiber type composition in the extensor digitorum longus muscle (EDL) and soleus muscle (SOL) of Kazakh horses, across different genders (male and female). The results showed significant differences in myofiber type composition between EDL and SOL, with a higher proportion of Type I fibers in SOL muscles and a greater prevalence of Type II fibers in EDL muscles. Additionally, the myofiber diameter in Kazakh horses was relatively small, potentially related to the tenderness and edible quality of their muscles. Using high-throughput sequencing technology, we constructed 32 cDNA sequencing libraries and obtained high-quality read data. Gene expression analysis revealed 278 and 372 differentially expressed genes (DEGs) in EDL and SOL muscles, respectively, including genes related to muscle contraction, metabolism, and development. Intersection analysis of DEGs between genders showed that 60 DEGs were significantly different in both male and female horses. GO annotation and KEGG analysis further elucidated the roles of these DEGs in muscle structure, function, and cellular signaling. Protein-protein interaction (PPI) network analysis and identification of hub genes provided new insights into the molecular mechanisms underlying muscle growth and development. Finally, the reliability of the DEGs data was validated through quantitative real-time PCR (qRT-PCR). This study not only enhances our understanding of the biological characteristics of horse muscles but also provides potential molecular targets for improving horse muscle performance and health.

Analysis of the Mechanism of Intervention of Fangxiangxiaozhi Prescription on Dyslipidemia Based on Network Pharmacology and Molecular Docking

Objective: To explore the mechanism of intervention of Fangxiangxiaozhi prescription on dyslipidemia by using network pharmacology and molecular docking. Methods: The traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Pubchem, Uniprot, and other databases were adopted to screen the active ingredients and the corresponding targets of Fangxiangxiaozhi prescription. Dyslipidemia-related targets were identified using the databases of Disgenet and GeneCards. Then, the intersection target of drugs and diseases was demonstrated via a Venn diagram. Cytoscape3.7.2 was used to construct a “drugs-active ingredients-intersection targets” network map and the key active ingredients with the top 7-degree values were determined. The protein interaction network and topology analysis of the intersection target genes were carried out by combining STRING11.0 and Cytoscape3.7.2. Moreover, the gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the intersection target genes were carried out using the Metascape database. Lastly, the key active ingredients and targets were molecular docked by AutoDockTools, Pymol, and other software. Results: There were 51 active components and 509 target genes of which 74 intersect with dyslipidemia. The key targets included tumor necrosis factor (TNF), interleukin-6 (IL-6), AKT1, PPAR gamma (PPARG), VEGFA, and PPARα. GO enrichment analysis obtained 1040 biological processes, 33 cell components, and 84 molecular functions; KEGG enrichment analysis obtained 148 pathways. The molecular docking results showed that the key targets and compounds exhibited good binding force. Conclusion: The active ingredients of Fangxiangxiaozhi prescription regulated several pathways through multiple targets to intervene in dyslipidemia. This study can serve as a foundation for further research.

Gene-gene interaction network analysis indicates CNTN2 is a candidate gene for idiopathic generalized epilepsy.

Twin and family studies have established the genetic contribution to idiopathic generalized epilepsy (IGE). The genetic architecture of IGE is generally complex and heterogeneous, and the majority of the genetic burden in IGE remains unsolved. We hypothesize that gene-gene interactions contribute to the complex inheritance of IGE. CNTN2 (OMIM* 615,400) variants have been identified in cases with familial adult myoclonic epilepsy and other epilepsies. To explore the gene-gene interaction network in IGE, we took the CNTN2 gene as an example and investigated its co-occurrent genetic variants in IGE cases. We performed whole-exome sequencing in 114 unrelated IGE cases and 296 healthy controls. Variants were qualified with sequencing quality, minor allele frequency, in silico prediction, genetic phenotype, and recurrent case numbers. The STRING_TOP25 gene interaction network analysis was introduced with the bait gene CNTN2 (denoted as A). The gene-gene interaction pair mode was presumed to be A + c, A + d, A + e, with a leading gene A, or A + B + f, A + B + g, A + B + h, with a double-gene A + B, or other combinations. We compared the number of gene interaction pairs between the case and control groups. We identified three pairs in the case group, CNTN2 + PTPN18, CNTN2 + CNTN1 + ANK2 + ANK3 + SNTG2, and CNTN2 + PTPRZ1, while we did not discover any pairs in the control group. The number of gene interaction pairs in the case group was much more than in the control group (p = 0.021). Taking together the genetic bioinformatics, reported epilepsy cases, and statistical evidence in the study, we supposed CNTN2 as a candidate pathogenic gene for IGE. The gene interaction network analysis might help screen candidate genes for IGE or other complex genetic disorders.

Recognizing the role of Epstein-Barr virus in gastric cancer: transcriptomic insights into malignancy modulation

BackgroundStudies show that Epstein-Barr virus (EBV) infection can play a role in malignancy and increase the risk of gastric cancer (GC). The objective of this research was to pinpoint genes whose expression may be influenced by EBV and play a role in the development of GC.MethodsCandidate genes potentially susceptible to expression modulation in the presence of EBV were identified through the analysis of GSE185627 and GSE51575 datasets. The association of candidate genes with GC and the survival rate of patients was investigated based on the cancer genome atlas (TCGA) data. Also, pathways related to candidate genes were examined through the MsigDB database. The PPI network was used to identify Hub genes. To corroborate the obtained results, we utilized the RT-qPCR method, employing GC samples from both EBV + and EBV-cases, as well as adjacent normal samples.ResultsOur results showed that genes upregulated by the EBV in the GC cell line, as well as in EBV + samples, are significantly linked to pathways involving the immune response, inflammation, and the P53 pathway. Conversely, genes downregulated by EBV are closely linked to pathways involving cell proliferation and mTORC1. Examining the candidate genes revealed that a considerable portion of genes susceptible to downregulation under the influence of EBV exhibit oncogenic roles based on TCGA data. Moreover, some of these genes are associated with an unfavorable prognosis. Protein-protein interaction network analysis of candidate genes highlighted IFI44L and OAS2 as potential hub genes in the EBV-GC axis. Our RT-qPCR results further validated these findings, demonstrating that the expression levels of IFI44L and OAS2 were higher in EBV + samples compared to both healthy and EBV-samples.ConclusionOur study underscores the capacity of EBV to exert regulatory control over genes associated with GC malignancy. In addition to its inflammatory effects, EBV elicits transcriptomic changes that appear to attenuate the progression of GC.

Construction of a co-expression network affecting intramuscular fat content and meat color redness based on transcriptome analysis.

Introduction: Intramuscular fat content (IFC) and meat color are vital indicators of pork quality. Methods: A significant positive correlation between IFC and redness of meat color (CIE a* value) indicates that these two traits are likely to be regulated by shared molecular pathways.To identify candidate genes, hub genes, and signaling pathways that regulate these two traits, we measured the IFC and CIE a* value in 147 hybrid pigs, and selected individuls with extreme phenotypes for transcriptome analysis. Results: The results revealed 485 and 394 overlapping differentially expressed genes (DEGs), using the DESeq2, limma, and edgeR packages, affecting the IFC and CIE a* value, respectively. Weighted gene co-expression network analysis (WGCNA) identified four modules significantly correlated with the IFC and CIE a* value. Moreover, we integrated functional enrichment analysis results based on DEGs, GSEA, and WGCNA conditions to identify candidate genes, and identified 47 and 53 candidate genes affecting the IFC and CIE a* value, respectively. The protein protein interaction (PPI) network analysis of candidate genes showed that 5 and 13 hub genes affect the IFC and CIE a* value, respectively. These genes mainly participate in various pathways related to lipid metabolism and redox reactions. Notably, four crucial hub genes (MYC, SOX9, CEBPB, and PPAGRC1A) were shared for these two traits. Discussion and conclusion: After functional annotation of these four hub genes, we hypothesized that the SOX9/CEBPB/PPARGC1A axis could co-regulate lipid metabolism and the myoglobin redox response. Further research on these hub genes, especially the SOX9/CEBPB/PPARGC1A axis, will help to understand the molecular mechanism of the co-regulation of the IFC and CIE a* value, which will provide a theoretical basis for improving pork quality.

Systematic analysis and expression of Gossypium ATG8 family reveals the roles of GhATG8f responding to salt stress in cotton.

Comprehensive analysis of Gossypium ATG8 family indicates that GhATG8f could improve salt tolerance of cotton by increasing SOD, POD and CAT activity and proline accumulation. In plants, autophagy is regulated by several genes that play important roles in initiating and controlling the process. ATG8, functioning as a protein similar to ubiquitin, is involved in crucial tasks throughout the autophagosome formation process. In this research, we conducted an extensive and all-encompassing investigation of 64 ATG8 genes across four varieties of cotton. According to the subcellular localization prediction results, 49 genes were found in the cytoplasm, 6 genes in the chloroplast, 1 gene in the peroxisome, 5 genes in the nucleus, and 3 genes in the extracellular region. Phylogenetic analysis categorized a total of 5 subfamilies containing sixty-four ATG8 genes. The expression of the majority of GhATG8 genes was induced by salt, drought, cold, and heat stresses, as revealed by RNA-seq and real-time PCR. Analysis of cis-elements in the promoters of GhATG8 genes revealed the predominant presence of responsive elements for plant hormones and abiotic stress, suggesting that GhATG8 genes might have significant functions in abiotic stress response. Furthermore, we additionally performed a gene interaction network analysis for the GhATG8 proteins. The salt stress resistance of cotton was reduced due to the downregulation of GhATG8f expression, resulting in decreased activity of CAT, SOD, and POD enzymes, as well as decreased fresh weight and proline accumulation. In summary, our research is the initial exploration of ATG8 gene components in cotton, providing a basis for future investigations into the regulatory mechanisms of ATG8 genes in autophagy and their response to abiotic stress.

Mutational Signatures Analysis of Micropapillary Components and Exploration of ZNF469 Gene in Early-stage Lung Adenocarcinoma with Ground-glass Opacities

In China, lung cancer remains the cancer with the highest incidence and mortality rate. Among early-stage lung adenocarcinomas (LUAD), the micropapillary (MPP) component is prevalent and typically exhibits high aggressiveness, significantly correlating with early metastasis, lymphatic infiltration, and reduced five-year survival rates. Therefore, the study is to explore the similarities and differences between MPP and non-micropapillary (non-MPP) components in malignant pulmonary nodules characterized by GGOs in early-stage LUAD, identify unique mutational features of the MPP component and analyze the relationship between the ZNF469 gene, a member of the zinc-finger protein family, and the prognosis of early-stage LUAD, as well as its correlation with immune infiltration. A total of 31 malignant pulmonary nodules of LUAD were collected and dissected into paired MPP and non-MPP components using microdissection. Whole-exome sequencing (WES) was performed on the components of early-stage malignant pulmonary nodules. Mutational signatures analysis was conducted using R packages such as maftools, Nonnegative Matrix Factorization (NMF), and Sigminer to unveil the genomic mutational characteristics unique to MPP components in invasive LUAD compared to other tumor tissues. Furthermore, we explored the expression of the ZNF469 gene in LUAD using The Cancer Genome Atlas (TCGA) database to investigate its potential association with the prognosis. We also investigated gene interaction networks and signaling pathways related to ZNF469 in LUAD using the GeneMANIA database and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Lastly, we analyzed the correlation between ZNF469 gene expression and levels of immune cell infiltration in LUAD using the TIMER and TISIDB databases. MPP components exhibited a higher number of genomic variations, particularly the 13th COSMIC (Catalogue of Somatic Mutations in Cancer) mutational signature characterized by the activity of the cytidine deaminase APOBEC family, which was unique to MPP components compared to non-MPP components in tumor tissues. This suggests the potential involvement of APOBEC in the progression of MPP components in early-stage LUAD. Additionally, MPP samples with high similarity to APOBEC signature displayed a higher tumor mutational burden (TMB), indicating that these patients may be more likely to benefit from immunotherapy. The expression of ZNF469 was significantly upregulated in LUAD compared to normal tissue, and was associated with poor prognosis in LUAD patients (P<0.05). Gene interaction network analysis and GO/KEGG enrichment analysis revealed that COL6A1, COL1A1, COL1A2, TGFB2, MMP2, COL8A2 and C2CD4C interacted with ZNF469 and were mainly involved in encoding collagen proteins and participating in the constitution of extracellular matrix. ZNF469 expression was positively correlated with immune cell infiltration in LUAD (P<0.05). The study has unveiled distinctive mutational signatures in the MPP components of early-stage invasive LUAD in the Asian population. Furthermore, we have identified that the elevated expression of mutated ZNF469 impacts the prognosis and immune infiltration in LUAD, suggesting its potential as a diagnostic and prognostic biomarker in LUAD.

The link between gluten intake and the risk of cancers.

Gluten is a complex mixture of hundreds of related proteins, with the two major groups being gliadin and glutenin. Gliadin primarily affects the viscosity of dough, while glutenin contributes to its strength. Nowadays, there is evidence suggesting an increase in gluten exposure due to advancements in cereal technology. Consumption of gluten can lead to development of gluten-related disorders (GRDs) in susceptible individuals. Some GRDs have been strongly associated with an increased risk of developing certain types of cancer. Colorectal cancer and lymphoma are among the most commonly reported malignancies associated with GRDs. Dietary factors, including gluten intake, have been recognized as significant modifiable risk factors for the development of digestive system cancers. The present study aimed to collect current information on the effect of gluten on the incidence of cancer in the general population and among GRDs patients. Protein-Protein Interaction (PPI) Network analysis of common genes between celiac disease (CD) and cancer was also conducted.

Dermatophagoides farinae microRNAs released to external environments via exosomes regulate inflammation-related gene expression in human bronchial epithelial cells.

Dermatophagoides farinae (DFA) is an important species of house dust mites (HDMs) that causes allergic diseases. Previous studies have focused on allergens with protein components to explain the allergic effect of HDMs; however, there is little knowledge on the role of microRNAs (miRNAs) in the allergic effect of HDMs. This study aimed to unravel the new mechanism of dust mite sensitization from the perspective of cross-species transport of extracellular vesicles-encapsulated miRNAs from HDMs. Small RNA (sRNA) sequencing was performed to detect miRNAs expression profiles from DFA, DFA-derived exosomes and DFA culture supernatants. A quantitative fluorescent real-time PCR (qPCR) assay was used to detect miRNAs expression in dust specimens. BEAS-2B cells endocytosed exosomes were modeled in vitro to detect miRNAs from DFA and the expression of related inflammatory factors. Representative dfa-miR-276-3p and dfa-novel-miR2 were transfected into BEAS-2B cells, and then differentially expressed genes (DEGs) were analyzed by RNA sequencing. Protein-protein interaction (PPI) network analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) terms enrichment analyses were performed on the first 300 nodes of DEGs. sRNA sequencing identified 42 conserved miRNAs and 66 novel miRNAs in DFA, DFA-derived exosomes, and DFA culture supernatants. A homology analysis was performed on the top 18 conserved miRNAs with high expression levels. The presence of dust mites and miRNAs from HDMs in living environment were also validated. Following uptake of DFA-derived exosomes by BEAS-2B cells, exosomes transported miRNAs from DFA to target cells and produced pro-inflammatory effects in corresponding cells. RNA sequencing identified DEGs in dfa-miR-276-3p and dfa-novel-miR2 transfected BEAS-2B cells. GO and KEGG enrichment analyses revealed the role of exosomes with cross-species transporting of DFA miRNAs in inflammatory signaling pathways, such as JAK-STAT signaling pathway, PI3K/AKT signaling pathway and IL-6-mediated signaling pathway. Our findings demonstrate the miRNAs expression profiles in DFA for the first time. The DFA miRNAs are delivered into living environments via exosomes, and engulfed by human bronchial epithelial cells, and cross-species regulation may contribute to inflammation-related processes.

Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. To investigate global interactions in MM, we combined a known protein interaction network with a large clinically annotated MM dataset. We hypothesized that an unbiased network analysis method based on large-scale similarities in gene expression, copy number aberration, and protein interactions may provide novel biological insights. Applying a novel measure of network robustness, Ollivier-Ricci Curvature, we examined patterns in the RNA-Seq gene expression and CNA data and how they relate to clinical outcomes. Hierarchical clustering using ORC differentiated high-risk subtypes with low progression free survival. Differential gene expression analysis defined 118 genes with significantly aberrant expression. These genes, while not previously associated with MM, were associated with DNA repair, apoptosis, and the immune system. Univariate analysis identified 8/118 to be prognostic genes; all associated with the immune system. A network topology analysis identified both hub and bridge genes which connect known genes of biological significance of MM. Taken together, gene interaction network analysis in MM uses a novel method of global assessment to demonstrate complex immune dysregulation associated with shorter survival.

Identifying Genetic Signatures from Single-Cell RNA Sequencing Data by Matrix Imputation and Reduced Set Gene Clustering

In this current era, the identification of both known and novel cell types, the representation of cells, predicting cell fates, classifying various tumor types, and studying heterogeneity in various cells are the key areas of interest in the analysis of single-cell RNA sequencing (scRNA-seq) data. Due to the nature of the data, cluster identification in single-cell sequencing data with high dimensions presents several difficulties. In this paper, we introduce a new framework that combines various strategies such as imputed matrix, minimum redundancy maximum relevance (MRMR) feature selection, and shrinkage clustering to discover gene signatures from scRNA-seq data. Firstly, we conducted the pre-filtering of the “drop-out” value in the data focusing solely on imputing the identified “drop-out” values. Next, we applied the MRMR feature selection method to the imputed data and obtained the top 100 features based on the MRMR feature selection optimization scores for further downstream analysis. Thereafter, we employed shrinkage clustering on the selected feature matrix to identify the cell clusters using a global optimization approach. Finally, we applied the Limma-Voom R tool employing voom normalization and an empirical Bayes test to detect differentially expressed features with a false discovery rate (FDR) &lt; 0.001. In addition, we performed the KEGG pathway and gene ontology enrichment analysis of the identified biomarkers using David 6.8 software. Furthermore, we conducted miRNA target detection for the top gene markers and performed miRNA target gene interaction network analysis using the Cytoscape online tool. Subsequently, we compared our detected 100 markers with our previously detected top 100 cluster-specified markers ranked by FDR of the latest published article and discovered three common markers; namely, Cyp2b10, Mt1, Alpi, along with 97 novel markers. In addition, the Gene Set Enrichment Analysis (GSEA) of both marker sets also yields similar outcomes. Apart from this, we performed another comparative study with another published method, demonstrating that our model detects more significant markers than that model. To assess the efficiency of our framework, we apply it to another dataset and identify 20 strongly significant up-regulated markers. Additionally, we perform a comparative study of different imputation methods and include an ablation study to prove that every key phase of our framework is essential and strongly recommended. In summary, our proposed integrated framework efficiently discovers differentially expressed stronger gene signatures as well as up-regulated markers in single-cell RNA sequencing data.

Widely Targeted Metabolomic Profiling Combined with Transcriptome Analysis Provides New Insights into Lipid Biosynthesis in Seed Kernels of Pinus koraiensis.

Lipid-rich Pinus koraiensis seed kernels are highly regarded for their nutritional and health benefits. To ascertain the molecular mechanism of lipid synthesis, we conducted widely targeted metabolomic profiling together with a transcriptome analysis of the kernels in P. koraiensis cones at various developmental stages. The findings reveal that 148 different types of lipid metabolites, or 29.6% of total metabolites, are present in kernels. Among those metabolites, the concentrations of linoleic acid, palmitic acid, and α-linolenic acid were higher, and they steadily rose as the kernels developed. An additional 10 hub genes implicated in kernel lipid synthesis were discovered using weighted gene co-expression network analysis (WGCNA), gene interaction network analysis, oil body biosynthesis, and transcriptome analysis. This study used lipid metabolome and transcriptome analyses to investigate the mechanisms of key regulatory genes and lipid synthesis molecules during kernel development, which served as a solid foundation for future research on lipid metabolism and the creation of P. koraiensis kernel food.

Identification of potential biomarkers for nonsurvivor sepsis patients via microarray technology: A study based on GEO datasets

Background: The mechanism of sepsis especially non-survivors has not yet been identified. Objective: To identify the key genes concerned with non-survivor sepsis (NSS) and analyze its molecular mechanism. Methods: The original data were obtained from the GEO database to screen deferentially expressed genes (DEGs). GO and KEGG analysis were performed to analyze the functional annotation of DEGs. The protein-protein interaction (PPI) network and related analysis of hub genes were carried out. Further, hub genes were confirmed in the lipopolysaccharide (LPS)-induced septic mice by western blotting and immunohistochemistry. Results: We obtained 188 DEGs and 32 hub genes between NSS patients and healthy volunteers. Among of them, the top 10 hub genes including STAT1, ISG15, HERC1, EIF2AK2, RPL27, LY6E, IFI44L, XAF1, RSAD2 and HERC6 were studied, which predict sepsis based on receiver operator characteristic curve analysis. These hub genes were enriched in positive regulation of biomedical process including translation, response to virus and suppression of mitochondrial depolarization, etc.; cell component including mitochondrial inner membrane; molecular function containing ligase activity, etc. These hub genes are also enriched in influenza A infection and leukocyte trans-endothelial migration. The expression of these hub genes is better involved in a diagnosis of NSS, such as HERC6 (AUC = 0.9753, p = .0007), RPL27 (AUC = 0.9691, p = .0008), ISG15 (AUC = 0.9630, p = .0009), STAT1 (AUC = 0.9383, p = .0017), HERC1 (AUC = 0.9259, p = .0023), and XAF1 (AUC = 0.9259, p = .0023). Furthermore, 20 mg/kg of LPS injection up-regulated the expression of ISG15, RPL27, LY6E and HERC6 in the lung tissues compared with control mice. Conclusion: These identified 188 DEGs and 10 hub genes were associated with NSS, especially ISG15, RPL27, LY6E and HERC6 genes expressed in the lung as the most vulnerable organ.

Genome-wide identification of xylan glucuronosyltransferase family in cotton and function characterization of GhGUX5 in regulating Verticillium wilt resistance

Xylan glucuronosyltransferase (GUX) is widely involved in a variety of physiological processes in plants, including plant development, growth and the defense response to pathogens. However, the function of GUX regulators in Verticillium dahliae (V. dahliae) infection has not been considered previously in cotton. Overall, 119 GUX genes were identified from multiple species and were phylogenetically categorized into seven classes. Duplication event analysis indicated that GUXs in Gossypium hirsutum primarily originated from segmental duplication. GhGUXs promoter analysis indicated cis-regulatory elements capable of reacting to several different stresses. RNA-Seq data and qRT-PCR analysis both indicated that most GhGUXs were associated with V. dahliae infection. Gene interaction network analysis showed that GhGUX5 interacted with 11 proteins, and the relative expression of these 11 proteins changed significantly following V. dahliae infection. In addition, silencing and overexpression of GhGUX5 results to enhance and reduce plant's susceptibility to V. dahliae. Further study showed that TRV:GhGUX5 silenced cotton plants exhibited a decrease in the degree of lignification, total lignin content, gene expression levels involved in lignin biosynthesis, and enzyme activity compared with TRV:00. The above results indicate that GhGUX5 enhances Verticillium wilt resistance through the lignin biosynthesis pathway.

Unveiling the role of hub proteins in controlling quorum sensing regulated virulence through analogues in Pseudomonas aeruginosa PAO1: A functional protein-protein network biology approach

The protein-protein interaction (PPI) network analysis of specific genes identified for biofilm production and virulence/secretion system mediated by quorum sensing. The PPI depicted 13 hub proteins (namely rhlR, lasR, pscU, vfr, exsA, lasI, gacA, toxA, pilJ, pscC, fleQ, algR, and chpA) out of 160 nodes involving 627 edges. The PPI network analysis based on topographical features depicted pcrD with the highest degree value and vfr gene with the greatest betweenness centrality and closeness centrality (BC and CC) values. Based on in silico results, curcumin used as an Acyl homo-serine lactone (AHL) mimicker in P. aeruginosa, was also found effective in suppressing the quorum sensing regulated virulence factors such as elastase and pyocyanin. Based on in vitro experiment, curcumin suppressed biofilm formation at 62 μg/ml concentration. Host-pathogen interaction experiment showed that curcumin was also proved to be efficient in saving C. elegans from paralysis and killing effects of P. aeruginosa PAO1.