Weighted gene co-expression network analysis and CIBERSORT screening of key genes related to m6A methylation in Hirschsprung's disease.

Hirschsprung's disease (HSCR) is a neural crest disease that results from the failure of enteric neural crest cells (ENCCs) to migrate to the corresponding intestinal segment. The RET gene, which regulates enteric neural crest cell proliferation and migration, is considered one of the main risk factors for HSCR and is commonly used to construct HSCR mouse models. The epigenetic mechanism of m6A modification is involved in HSCR. In this study, we analyzed the GEO database (GSE103070) for differentially expressed genes (DEGs) and focused on m6A-related genes. Comparing the RNA-seq data of Wide Type and RET Null, a total of 326 DEGs were identified, of which 245 genes were associated with m6A. According to the CIBERSORT analysis, the proportion of Memory B-cell in RET Null was significantly higher than that of Wide Type. Venn diagram analysis was used to identify key genes in the selected memory B-cell modules and DEGs associated with m6A. Enrichment analysis showed that seven genes were mainly involved in focal adhesion, HIV infection, actin cytoskeleton organization and regulation of binding. These findings could provide a theoretical basis for molecular mechanism studies of HSCR.

Prognostic analysis of m6A-related genes as potential biomarkers in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with limited treatment options. N6-methyladenosine (m6A) is a reversible RNA modification and has been implicated in various biological processes. However, there are few studies on m6A in IPF. This project mainly explores the prognostic value of m6A-related genes as potential biomarkers in IPF, in order to establish a set of accurate prognostic prediction model. In this study, we used GSE28042 dataset in GEO database to screen out 218 m6A-related candidate genes with high IPF correlation and high differential expression through differentially expressed gene analysis, WGCNA and m6A correlation analysis. The genes associated with the prognosis of IPF were screened out by univariate Cox regression analysis, LASSO analysis, and multivariate Cox regression analysis, and the multivariate Cox model of prognostic risk of related genes was constructed. We found that RBM11, RBM47, RIC3, TRAF5 and ZNF14 were key genes in our model. Finally, the prognostic prediction ability and independent prognostic characteristics of the risk model were evaluated by survival analysis and independent prognostic analysis, and verified by the GSE93606 dataset, which proved that the prognostic risk model we constructed has a strong and stable prediction efficiency.

Construction of a competing endogenous RNA network in head and neck squamous cell carcinoma by pan-cancer analysis.

Background: Head and neck squamous cell carcinoma (HNSC) is the sixth most common cancer worldwide, and new cases are anticipated to reach 1.08 million in 2030. Our study aimed to identify the competing endogenous RNAs (ceRNAs) involved in HNSC tumorigenesis. Methods: First, a pan-cancer correlation analysis was conducted on the expression and survival conditions of sideroflexin (SFXN3) based on data downloaded from the Xena database. Second, the upstream regulatory microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) of SFXN3 were predicted using the Encyclopedia of RNA Interactomes (ENCORI) database. Expression and survival analyses were subsequently used to construct lncRNA-miRNA-mRNA ceRNA network that correlated with HNSC. Third, the proportion of various types of immune cells in HNSC was calculated using the CIBERSORT algorithm. Finally, a correlation analysis was performed on SFXN3, including immune cell infiltration (ICI), clinical stage, and immune checkpoints. Results: The pan-cancer analysis suggested that SFXN3 was up-regulated in HNSC, and it correlated with poor prognosis. The ceRNA regulatory network MIR193BHG-miR-29c-3p-SFXN3 was identified as one of the potential biological regulatory pathways of HNSC. The upstream lncRNA MIR193BHG was associated with a poor prognosis in HNSC, and its target gene SFXN3 was correlated with tumor ICI, immune cell biomarkers, and immune checkpoints. Conclusions: By performing ceRNA analysis, our study demonstrated that MIR193HG-miR-29c-3p-SFXN3 is significantly involved in HNSC, and this action axis markedly affect the therapeutic effect and prognosis.

Genome-Wide Identification and Characterization of RNA/DNA Differences Associated with Fusarium graminearum Infection in Wheat.

RNA/DNA difference (RDD) is a post-transcriptional modification playing a crucial role in regulating diverse biological processes in eukaryotes. Although it has been extensively studied in plant chloroplast and mitochondria genomes, RDDs in plant nuclear genomes are not well studied at present. Here, we investigated the RDDs associated with fusarium head blight (FHB) through a novel method by comparing the RNA-seq data between Fusarium-infected and control samples of four wheat genotypes. A total of 187 high-confidence unique RDDs in 36 genes were identified, representing the first landscape of the FHB-responsive RDD in wheat. The majority (26) of these 36 RDD genes were correlated either positively or negatively with FHB levels. Effects of these RDDs on RNA and protein sequences have been identified, their editing frequency and the expression level of the corresponding genes provided, and the prediction of the effect on the minimum folding free energy of mRNA, miRNA binding, and colocation of RDDs with conserved domains presented. RDDs were predicted to induce modifications in the mRNA and protein structures of the corresponding genes. In two genes, TraesCS1B02G294300 and TraesCS3A02G263900, editing was predicted to enhance their affinity with tae-miR9661-5p and tae-miR9664-3p, respectively. To our knowledge, this study is the first report of the association between RDD and FHB in wheat; this will contribute to a better understanding of the molecular basis underlying FHB resistance, and potentially lead to novel strategies to improve wheat FHB resistance through epigenetic methods.

Genome-Wide Identification and Characterization of RNA/DNA Differences Associated with Drought Response in Wheat.

RNA/DNA difference (RDD) is a post-transcriptional RNA modification to enrich genetic information, widely involved in regulating diverse biological processes in eukaryotes. RDDs in the wheat nuclear genome, especially those associated with drought response or tolerance, were not well studied up to now. In this study, we investigated the RDDs related to drought response based on the RNA-seq data of drought-stressed and control samples in wheat. In total, 21,782 unique RDDs were identified, of which 265 were found to be drought-induced, representing the first drought-responsive RDD landscape in the wheat nuclear genome. The drought-responsive RDDs were located in 69 genes, of which 35 were differentially expressed under drought stress. Furthermore, the effects of RNA/DNA differences were investigated, showing that they could result in changes of RNA secondary structure, miRNA-target binding as well as protein conserved domains in the RDD-containing genes. In particular, the A to C mutation in TraesCS2A02G053100 (orthology to OsRLCK) led to the loss of tae-miR9657b-5p targeting, indicating that RNA/DNA difference might mediate miRNA to regulate the drought-response process. This study reported the first drought-responsive RDDs in the wheat nuclear genome. It sheds light on the roles of RDD in drought tolerance, and may also contribute to wheat genetic improvement based on epi-transcriptome methods.

Identification of key genes associated with sepsis patients infected by staphylococcus aureus through weighted gene co-expression network analysis.

The prevention and treatment of staphylococcus aureus septicemia is one of the thorniest problems in modern medicine. However, as the underlying pathogenesis of sepsis is still unclear, there is currently no golden standard for clinical diagnosis. In this study, we used GSE33341 dataset for differentially expressed gene (DEG) analysis and screened out 857 differentially expressed genes associated with staphylococcus aureus infection. The module having the highest correlation with clinical features of sepsis was screened by weighted gene co-expression network analysis (WGCNA). The genes in the selected module and the differentially expressed genes were represented in Venn diagram, and 59 pathogenic genes at the intersection were obtained. GO and KEGG analysis showed that these genes were mainly related to aerobic respiration, cellular stress response, mitochondrial electron transport, mitochondrial transport, oxidative phosphorylation. Kaplan-Meier was used to analyze the influence of the top 10 key genes on the prognosis of sepsis patients. The results showed that the high expression of NDUFA4, NDUFB3, COX7A2, ATP5J and COX7C was significantly correlated with the poor overall survival (OS) in patients with bacterial sepsis. These findings may potentially provide a reference for the diagnosis and treatment of bacterial septicemia.

A Mendelian Randomization Analysis to Expose the Causal Effect of IL-18 on Osteoporosis Based on Genome-Wide Association Study Data.

Accumulating evidence showed that Interleukin (IL) level is associated with Osteoporosis. Whereas, most of these associations are based on observational studies. Thus, their causality was still unclear. Mendelian randomization (MR) is a widely used statistical framework that uses genetic instrumental variables (IVs) to explore the causality of intermediate phenotype with disease. To classify their causality, we conducted a MR analysis to investigate the effect of IL-18 level on the risk of Osteoporosis. First, based on summarized genome-wide association study (GWAS) data, 8 independent IL-18 SNPs reaching genome-wide significance were deemed as IVs. Next, Simple median method was used to calculate the pooled odds ratio (OR) of these 8 SNPs for the assessment of IL-8 on the risk of Osteoporosis. Then, MR-Egger regression was utilized to detect potential bias due to the horizontal pleiotropy of these IVs. As a result of simple median method, we get the SE (-0.001; 95% CI-0.002 to 0; P = 0.042), which means low IL-18 level could increases the risk of the development of Osteoporosis. The low intercept (0; 95% CI -0.001 to 0; P = 0.59) shows there is no bias due to the horizontal pleiotropy of the IVs.

Tongue Coating Microbiota Community and Risk Effect on Gastric Cancer.

Background: Although oral hygiene and health have long been reported to be associated with increased risk of gastric cancer (GC), the direct relationship of oral microbes with the risk of GC have not been evaluated fully. We aimed to test whether tongue coating microbiome was associated with GC risk. Methods: Pyrosequencing of 16S rRNA gene of tongue coating microbiome was used in 57 newly diagnosed gastric adenocarcinomas and 80 healthy controls. Benjamini-Hochberg (BH) was applied for multiple comparison correction. Co-abundance group (CAGs) analysis was adopted. Results: We found that higher relative abundance of Firmicutes, and lower of Bacteroidetes were associated with increased risk of GC. In genus level, Streptococcus trended with a higher risk of GC, the four other genera (Neisseria, Prevotella, Prevotella7, and Porphyromonas) were found to have a decreased risk of GC. Different from overall GC and non-cardia cancer, Alloprevotella and Veillonella trended with the higher risk of cardia cancer. Finally, we analyzed the microbiota by determining CAGs and six clusters were identified. Except the Cluster 2 (mainly Streptococcus and Abiotrophia), the other clusters had an inverse association with GC. Of them, the Cluster 6 (mainly Prevotella and Prevotella7 etc) had a relatively good classification power with 0.76 of AUC. Conclusion: Microbiome in tongue coating may have potential guiding value for early detection and prevention of GC.