Gene Functional Enrichment Analysis Research Articles

Bioinformatics and Experimental Study revealed LINC00982/ miR-183-5p/ABCA8 Axis Suppresses LUAD Progression.

Lung adenocarcinoma (LUAD) is a major health challenge worldwide with an undesirable prognosis. LINC00982 has been implicated as a tumor suppressor in diverse human cancers; however, its role in LUAD has not been fully characterized. Expression level and prognostic value of LINC00982 were investigated in pan-cancer and lung cancer from The Cancer Genome Atlas (TCGA) project. Differential expression analysis based on the LINC00982 expression level was performed in LUAD followed by gene set enrichment analysis (GSEA) and functional enrichment analyses. The association between LINC00982 expression and tumor immune microenvironment characteristics was evaluated. A potential ceRNA regulatory axis was identified and experimentally validated. We found that LINC00982 expression was downregulated and correlated with poor prognosis in LUAD. Enrichment analyses revealed that LINC00982 could inhibit DNA damage repair and cell proliferation, but enhance tumor metabolic reprogramming. We identified a competing endogenous RNA network involving LINC00982, miR-183-5p, and ATP-binding cassette subfamily A member 8 (ABCA8). Luciferase assays confirmed that miR-183-5p can interact with LINC00982 and ABCA8. Forced miR-183-5p expression reduced LINC00982 transcript levels and suppressed ABCA8 expression. Our findings revealed the LINC00982/miR-183-5p/ABCA8 axis as a potential therapeutic target in LUAD.

Global transcriptome profiles provide insights into muscle cell development and differentiation on microstructured marine biopolymer scaffolds for cultured meat production

Biomaterial scaffolds play a pivotal role in the advancement of cultured meat technology, facilitating essential processes like cell attachment, growth, specialization, and alignment. Currently, there exists limited knowledge concerning the creation of consumable scaffolds tailored for cultured meat applications. This investigation aimed to produce edible scaffolds featuring both smooth and patterned surfaces, utilizing biomaterials such as salmon gelatin, alginate, agarose and glycerol, pertinent to cultured meat and adhering to food safety protocols. The primary objective of this research was to uncover variations in transcriptomes profiles between flat and microstructured edible scaffolds fabricated from marine-derived biopolymers, leveraging high-throughput sequencing techniques. Expression analysis revealed noteworthy disparities in transcriptome profiles when comparing the flat and microstructured scaffold configurations against a control condition. Employing gene functional enrichment analysis for the microstructured versus flat scaffold conditions yielded substantial enrichment ratios, highlighting pertinent gene modules linked to the development of skeletal muscle. Notable functional aspects included filament sliding, muscle contraction, and the organization of sarcomeres. By shedding light on these intricate processes, this study offers insights into the fundamental mechanisms underpinning the generation of muscle-specific cultured meat.

Novel putative causal mutations associated with fat traits in Nellore cattle uncovered by eQTLs located in open chromatin regions

Intramuscular fat (IMF) and backfat thickness (BFT) are critical economic traits impacting meat quality. However, the genetic variants controlling these traits need to be better understood. To advance knowledge in this area, we integrated RNA-seq and single nucleotide polymorphisms (SNPs) identified in genomic and transcriptomic data to generate a linkage disequilibrium filtered panel of 553,581 variants. Expression quantitative trait loci (eQTL) analysis revealed 36,916 cis-eQTLs and 14,408 trans-eQTLs. Association analysis resulted in three eQTLs associated with BFT and 24 with IMF. Functional enrichment analysis of genes regulated by these 27 eQTLs revealed noteworthy pathways that can play a fundamental role in lipid metabolism and fat deposition, such as immune response, cytoskeleton remodeling, iron transport, and phospholipid metabolism. We next used ATAC-Seq assay to identify and overlap eQTL and open chromatin regions. Six eQTLs were in regulatory regions, four in predicted insulators and possible CCCTC-binding factor DNA binding sites, one in an active enhancer region, and the last in a low signal region. Our results provided novel insights into the transcriptional regulation of IMF and BFT, unraveling putative regulatory variants.

Identification of microtubule-associated biomarker using machine learning methods in osteonecrosis of the femoral head and osteosarcoma

BackgroundThis study aims to explore the microtubule-associated gene signatures and molecular processes shared by osteonecrosis of the femoral head (ONFH) and osteosarcoma (OS). MethodsDatasets from the TARGET and GEO databases were subjected to bioinformatics analysis, including the functional enrichment analysis of genes shared by ONFH and OS. Prognostic genes were identified using univariate and multivariate Cox regression analyses to develop a risk score model for predicting overall survival and immune characteristics. Furthermore, LASSO and SVM-RFE algorithms identified biomarkers for ONFH, which were validated in OS. Function prediction, ceRNA network analysis, and gene–drug interaction network construction were subsequently conducted. Biomarker expression was then validated on clinical samples by using qPCR. ResultsA total of 14 microtubule-associated disease genes were detected in ONFH and OS. Subsequently, risk score model based on four genes was then created, revealing that patients with low-risk exhibited superior survival outcomes compared with those with high-risk. Notably, ONFH with low-risk profiles may manifest an antitumor immune microenvironment. Moreover, by utilizing LASSO and SVM-RFE algorithms, four diagnostic biomarkers were pinpointed, enabling effective discrimination between patients with ONFH and healthy individuals as well as between OS and normal tissues. Additionally, 21 drugs targeting these biomarkers were predicted, and a comprehensive ceRNA network comprising four mRNAs, 71 miRNAs, and 98 lncRNAs was established. The validation of biomarker expression in clinical samples through qPCR affirmed consistency with the results of bioinformatics analysis. ConclusionMicrotubule-associated genes may play pivotal roles in OS and ONFH. Additionally, a prognostic model was constructed, and four genes were identified as potential biomarkers and therapeutic targets for both diseases.

IL1R2 is a Novel Prognostic Biomarker for Lung Adenocarcinoma.

The aim of this study is to figure out the role of IL1R2 in LUAD (lung adenocarcinoma). IL1R2, a special member of IL-1 receptor family, binds to IL-1 and plays an important role in inhibiting IL-1 pathway, which seems to be involved in tumorigenesis. Emerging studies demonstrated higher IL1R2 expression levels in several malignancies. In the present study, we assessed the expression of IL1R2 in LUAD tissues with immunohistochemistry and explored various databases to determine whether it could be a potential prognostic biomarker and therapeutic target. The expression level of IL1R2 in lung adenocarcinoma was analyzed by Immunohistochemistry and UALCAN database. The correlation between IL1R2 expression and the patient prognosis was identified by Kaplan-Meier plotter. The correlation of IL1R2 expression with immune infiltrates was clarified by TIMER database. The protein-protein interaction network and gene functional enrichment analysis were constructed and performed by STRING and Metascape database. Immunohistochemistry showed that the expression of IL1R2 was higher in tumor tissues of LUAD patients and that patients with lower IL1R2 level have a better prognosis than their counterparts. We validated our findings in several online databases and found that IL1R2 gene was also positively correlated with B cells and neutrophils and biomarkers of CD8+T cells and exhausted T cells. PPI network and gene enrichment analyses showed that expression of IL1R2 was also associated with complex functionspecific networks involving IL-1 signal, NF-KappaB transcription factors. According to these findings, we demonstrated that IL1R2 was involved in the progression and prognosis of LUAD and the underlying mechanism needs further investigation.

An In-Silico Approach to Identify Therapeutic Target and Markers Associated with Diabetic Nephropathy.

Renal disease in T2DM could arise independent of hyperglycemia, aka non diabetic kidney disease. Their prevalence ranges from 33%to72.5% among T2DM patients. Specific molecular signatures that distinguish Diabetic Nephropathy from NDKD (FSGS) in T2DM might provide new targets for CKD management. Five original GEO microarray DN and FSGS datasets were evaluated (GSE111154, GSE96804, GSE125779, GSE129973 and GSE121233). Each of the three groups (DN, FSGS, and Controls) had equal renal transcriptome data (n=32) included in the analysis to eliminate bias. The DEGs were identified using TAC4.0. Pathway analysis was performed on the discovered genes that aligned to official gene symbols using Reactome, followed by functional gene enrichment analysis using Funrich,Enrichr. STRING and Network analyst investigated PPI, followed by Webgestalt's pathway enrichment. Finally, using the Targetscan7.0 and DIANA tools, filtered differential microRNAs downregulated in DN were evaluated for target identification. Between the three groups, DN, FSGS, and Control, a total of 194 DEGs. with foldchange >2&<-2 and P-value0.01 were found in the renal transcriptome. In comparison to control, 45 genes were elevated particularly in DN, whereas 43 were upregulated specifically in FSGS. DN datasets were compared to FSGS in a separate analysis. FABP4, EBF1, ADIRF, and ART4 were shown to be among the substantially up-regulated genes unique to DN in both analyses. The transcriptional regulation of white adipocytes was discovered by a pathway analysis. The molecular markers revealed might be employed as specific targets in the aetiology of DN, as well as in T2DM patients' therapeutic care.

Pectolinarigenin ameliorates osteoporosis via enhancing Wnt signaling cascade in PPARβ-dependent manner

BackgroundOsteoporosis is a prevalent metabolic bone disease in older adults. Peroxisome proliferator-activated receptor β (PPARβ), the most abundant PPAR isotype expressed in bone tissues, plays a critical role in regulating the energy metabolism of osteoblasts. However, the botanical compounds targeting PPARβ for the treatment of osteoporosis remain largely unexplored. PurposeTo discover a potent PPARβ agonist from botanical compounds, as well as to investigate the anti-osteoporosis effects and to elucidate the underlying mechanisms of the newly identified PPARβ agonist. MethodsThe PPARβ agonist effects of botanical compounds were screened by an in vitro luciferase reporter gene assay. The PPARβ agonist effects of pectolinarigenin (PEC) in bone marrow mesenchymal stromal cells (BMSCs) were validated by Western blotting. RNA-seq transcriptome analyses were conducted to reveal the underlying osteoporosis mechanisms of PEC in BMSCs. The PPARβ antagonist (GSK0660) and Wnt signaling inhibitor (XAV969) were used to explore the role of the PPARβ and Wnt signaling cascade in the anti-osteoporosis effects of PEC. PEC or the PEG-PLGA nanoparticles of PEC (PEC–NP) were intraperitoneally administrated in both wild-type mice and ovariectomy-induced osteoporosis mice to examine its anti-osteoporotic effects in vivo. ResultsPEC, a newly identified naturally occurring PPARβ agonist, significantly promotes osteogenic differentiation and up-regulates the osteogenic differentiation-related genes (Runx2, Osterix, and Bmp2) in BMSCs. RNA sequencing and functional gene enrichment analysis suggested that PEC could activate osteogenic-related signaling pathways, including Wnt and PPAR signaling pathways. Further investigations suggested that PEC could enhance Wnt/β-catenin signaling in a PPARβ-dependent manner in BMSCs. Animal tests showed that PEC–NP promoted bone mass and density, increased the bone cell matrix protein, and accelerated bone formation in wild-type mice, while PEC–NP also played a preventive role in ovariectomy-induced osteoporosis mice via maintaining the expression level of bone cell matrix protein, balancing the rate of bone formation, and slowing down bone loss. Additionally, PEC–NP did not cause any organ injury and body weight loss after long-term use (11 weeks). ConclusionPEC significantly promotes bone formation and reduces bone loss in both BMSCs and ovariectomy-induced osteoporosis mice via enhancing the Wnt signaling cascade in a PPARβ-dependent manner, providing a new alternative therapy for preventing estrogen deficiency-induced osteoporotic diseases.

Analysis of cuproptosis-related genes in prognosis and immune infiltration in grade 4 diffuse gliomas

BackgroundGrade 4 diffuse gliomas are highly malignant tumours with poor prognosis. Cuproptosis is a novel form of cell death. Cuproptosis genes are associated with various tumours and affect the prognosis of patients with these tumours. However, the relationship between cuproptosis and grade 4 diffuse gliomas remains unclear. MethodsDifferentially expressed genes associated with cuproptosis in grade 4 diffuse gliomas were identified. Second, the prognostic model was established by univariate and multivariate COX regression analyses, and the genes (p < 0.05) were selected for subsequent analysis. The endpoint of the study was death. Single-gene analysis was performed in accordance with the expression levels of SLC31A1. Third, based on the expression levels of SLC31A1, gene function enrichment, drug sensitivity, and immune cell infiltration analyses were performed. Finally, the expression and biological functions of SLC31A1 in grade 4 diffuse gliomas were identified using immunohistochemical staining, qRT-PCR, and related biological experiments. ResultsWe identified six coproptosis genes in the grade 4 diffuse gliomas dataset (SLC31A1, PDHA1, GLS, FDX1, LIPT1, and ATP7B). The six key cuproptosis genes of grade 4 diffuse gliomas were analysed using univariate COX analysis. Basic patient data, including age, race, year of diagnosis, sex, and treatment, were included in the univariate COX analysis. Then, multivariate COX analysis was performed for the factors with p < 0.2 in the univariate COX analysis. Age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 levels were found to be independent prognostic factors. A nomogram was constructed using these 5 factors. Through experiments, we found that SLC31A1 had a higher expression level in cancer tissue than that near cancer among the three genes, SLC31A1, PDHA1, and FDX1; therefore, we focused on SLC31A1. According on the expression level of SLC31A1, we performed gene function enrichment, drug sensitivity, and immune cell infiltration analyses. Navitoclax was the most sensitive drug. Differential gene function enrichment was observed for metalloendopeptidase activity. SLC31A1 is expressed in dendritic cells, macrophages, neutrophils, and CD8+T cells. SLC31A1 is highly expressed in grade 4 diffuse gliomas, whereas SLC31A1 knockdown significantly reduces cell proliferation and mobility. ConclusionsAge, year of diagnosis, and SLC31A1, PDHA1, and FDX1 expression were independent prognostic factors. A nomogram was constructed based on age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 levels. Through analysis and experimental verification, SLC31A1 was found to affect the prognosis and progression of patients with grade 4 diffuse gliomas and was associated with immune cell infiltration.

Network pharmacology and molecular docking analysis on Shenfu Qiangxin indicate mTOR is a potential target to treat heart failure

BackgroundHeart failure (HF) is one of the major causes of mortality worldwide with high recurrence rate and poor prognosis. Our study aimed to investigate potential mechanisms and drug targets of Shenfu Qiangxin (SFQX), a cardiotonic-diuretic traditional Chinese medicine, in treating HF.MethodsAn HF-related and SFQX-targeted gene set was established using disease-gene databases and the Traditional Chinese Medicine Systems Pharmacology database. We performed gene function and pathway enrichment analysis and constructed protein–protein interaction (PPI) network to investigate the potential mechanisms. We also performed molecular docking to analyze the interaction patterns between the active compounds and targeted protein.ResultsA gene set with 217 genes was identified. The gene function enrichment indicated that SFQX can regulate apoptotic process, inflammatory response, response to oxidative stress and cellular response to hypoxia. The pathway enrichment indicated that most genes were involved in PI3K–Akt pathway. Eighteen hub target genes were identified in PPI network and subnetworks. mTOR was the key gene among hub genes, which are involved in PI3K–Akt pathway. The molecular docking analysis indicated that 6 active compounds of SFQX can bind to the kinase domain of mTOR, which exerted potential therapeutic mechanisms of SFQX in treating HF.ConclusionsThe results of network pharmacology analysis highlight the intervention on PI3K–Akt pathway of SFQX in the treatment of HF. mTOR is a key drug target to help protect myocardium.

Identification of genes related to growth from transcriptome profiles of the muscle and liver of Chinese longsnout catfish (Leiocassis longirostris)

The Chinese longsnout catfish (Leiocassis longirostris) is a commercially important freshwater fish species in China. To understand the molecular mechanisms underlying its growth, we performed a comparative transcriptomic analysis of muscle and liver tissues of fast- and slow-growing L. longirostris. A total of 580 and 511 differentially expressed genes (DEGs) were obtained in the muscle and liver tissues, respectively. We selected 10 DEGs each from muscle and liver tissues by qRT-PCR to verify the reliability of RNA-seq, and it was found that the expression patterns of these genes were consistent with RNA-seq analysis results. According to the differential expression and functional enrichment analysis of genes, we found differences in the expression of several growth-related genes between fast- and slow-growing individuals. These genes may contribute to the differences in the growth of L. longirostris by influencing muscle growth and the metabolism of substances and energy. In particular, the pk and fabp genes were highly expressed in fast-growing individuals, while the cart, leptin, pepck, murf1, trim32, and pparα genes exhibited higher levels in slow-growing individuals. It was speculated that genes related to feeding behavior might be the key genes in regulating the growth of L. longirostris, while glycolytic/gluconeogenic metabolic pathway, lipid metabolism, and ubiquitin-proteasome pathway might be the main pathways involved in regulating body weight of L. longirostris. This study could enrich the available gene resources and provide a valuable basis for further studies on the regulatory mechanisms of growth in L. longirostris.

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.).

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

Transcriptomics and metabolomics analysis reveal the dietary copper deficiency and supplementation effects of liver gene expression and metabolite change in grazing sheep.

The appropriate mineral nutrients are essential for sheep growth and reproduction. However, traditional grazing sheep often experience mineral nutrient deficiencies, especially copper (Cu), due to inadequate mineral nutrients from natural pastures. The results indicated that dietary Cu deficiency and supplementation significantly reduced and elevated liver concentration of Cu, respectively (p < 0.05). FOXO3, PLIN1, ACTN2, and GHRHR were identified as critical genes using the weighted gene co-expression network analysis (WGCNA), quantitative real-time polymerase chain reaction (qRT-PCR), and receiver operating characteristic curve (ROC) validation as potential biomarkers for evaluating Cu status in grazing sheep. Combining these critical genes with gene functional enrichment analysis, it was observed that dietary Cu deficiency may impair liver regeneration and compromise ribosomal function. Conversely, dietary Cu supplementation may enhance ribosomal function, promote lipid accumulation, and stimulate growth and metabolism in grazing sheep. Metabolomics analysis indicated that dietary Cu deficiency significantly decreased the abundance of metabolites such as cholic acid (p < 0.05). On the other hand, dietary Cu supplementation significantly increased the abundance of metabolites such as palmitic acid (p < 0.05). Integrative analysis of the transcriptome and metabolome revealed that dietary Cu deficiency may reduce liver lipid metabolism while Cu supplementation may elevate it in grazing sheep. The Cu content in diets may have an impact on hepatic lipid metabolism in grazing sheep. These findings provide new insights into the consequences of dietary Cu deficiency and supplementation on sheep liver and can provide valuable guidance for herders to rationalize the use of mineral supplements.

Global gene expression profile of proliferative verrucous leukoplakia and its underlying biological disease mechanisms

BackgroundProliferative verrucous leukoplakia (PVL) is a rare and enigmatic oral potentially malignant disorder which almost invariably results in oral squamous cell carcinoma (OSCC). The aims of this project were to use transcriptome profiling to characterise PVL gene expression patterns for biomarker identification and gain insight into the molecular aetiopathogenesis of PVL. MethodsForty-three oral cavity mucosal biopsies from 32 patients with oral lesions clinically compatible with either PVL or non-PVL conventional oral leukoplakia (OLK) underwent transcriptome profiling by RNA sequencing. Data was analysed by hierarchical clustering, differential gene expression, functional enrichment and network analysis, sparse partial least squares discriminant analysis sPLS-DA, and immune cell phenotypic estimation. ResultsWe found 464 genes significantly differentially expressed at least 2-fold between PVL and non-PVL OLK (193 up and 271 down). HOX genes, including HOXA1 and HOXB7, keratin-associated proteins (KRTAPs) and olfactory receptor G proteins (OR) were significantly upregulated in PVL. Other upregulated genes in PVL included FOS, WNT16 and IFNA1. Pathway analysis showed that there was a significant downregulation of connective tissue signalling in PVL. Classifying multivariate models based upon 22 genes discriminated PVL from non-PVL OLK. Bioinformatic profiling showed that immune cell profiles in PVL and OLK were similar except that fibroblast markers were reduced in PVL. ConclusionThese results demonstrate that PVL and conventional OLK are molecularly distinct with upregulation of many cancer-associated genes. They provide insight into the pathogenesis of PVL and show that biomarker based molecular diagnostics is feasible to discriminate and inform diagnosis and management.

Integrated analysis and validation of ferroptosis-related genes and immune infiltration in acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) is indeed a significant cause of mortality and morbidity in individuals with coronary heart disease. Ferroptosis, an iron-dependent cell death, is characterized by the accumulation of intracellular lipid peroxides, which is implicated in cardiomyocyte injury. This study aims to identify biomarkers that are indicative of ferroptosis in the context of AMI, and to examine their potential roles in immune infiltration.MethodsFirstly, the GSE59867 dataset was used to identify differentially expressed ferroptosis-related genes (DE-FRGs) in AMI. We then performed gene ontology (GO) and functional enrichment analysis on these DE-FRGs. Secondly, we analyzed the GSE76591 dataset and used bioinformatic methods to build ceRNA networks. Thirdly, we identified hub genes in protein–protein interaction (PPI) network. After obtaining the key DE-FRGs through the junction of hub genes with ceRNA and least absolute shrinkage and selection operator (LASSO). ImmucellAI was applied to estimate the immune cell infiltration in each sample and examine the relationship between key DE-FRGs and 24 immunocyte subsets. The diagnostic performance of these genes was further evaluated using the receiver operating characteristic (ROC) curve analysis. Ultimately, we identified an immune-related ceRNA regulatory axis linked to ferroptosis in AMI.ResultsAmong 56 DE-FRGs identified in AMI, 41 of them were integrated into the construction of competitive endogenous RNA (ceRNA) networks. TLR4 and PIK3CA were identified as key DE-FRGs and PIK3CA was confirmed as a diagnostic biomarker for AMI. Moreover, CD4_native cells, nTreg cells, Th2 cells, Th17 cells, central-memory cells, effector-memory cells, and CD8_T cells had higher infiltrates in AMI samples compared to control samples. In contrast, exhausted cells, iTreg cells, and Tfh cells had lower infiltrates in AMI samples. Spearman analysis confirmed the correlation between 24 immune cells and PIK3CA/TLR4. Ultimately, we constructed an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA.ConclusionOur comprehensive analysis has identified PIK3CA as a robust and promising biomarker for this condition. Moreover, we have also identified an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA, which may play a key role in regulating ferroptosis during AMI progression.

Long noncoding RNA and messenger RNA profiling in epicardial adipose tissue of patients with new-onset postoperative atrial fibrillation after coronary artery bypass grafting

BackgroundPostoperative atrial fibrillation (POAF) constitutes a significant complication following coronary artery bypass graft surgery (CABG), potentially linked to epicardial adipose tissue (EAT). This investigation seeks to elucidate the association between POAF and EAT at the genetic level.MethodsEAT and clinical data from patients undergoing CABG were systematically acquired, adhering to established inclusion and exclusion criteria. Patients were categorized into POAF and Non-POAF groups based on the presence or absence of POAF. High-throughput sequencing data of EAT were subjected to differential expression analysis and gene function assessment. A random selection of long noncoding RNAs (lncRNAs) underwent quantitative real-time polymerase chain reaction (qRT-PCR) for validation of the high-throughput sequencing findings. Coexpression analysis was employed to elucidate the interactions between lncRNAs and messenger RNAs (mRNAs).ResultsRNA sequencing yielded a total of 69,685 transcripts (37,740 coding and 31,945 noncoding sequences), representing 16,920 genes. Within this dataset, 38 mRNAs and 12 lncRNAs exhibited differential expression between the POAF and Non-POAF groups (P < 0.05, fold change > 1.5). The qRT-PCR results for lncRNAs corroborated the sequencing findings (P < 0.01). Functional enrichment analysis of genes and the coexpression network indicated that these differentially expressed RNAs were primarily implicated in processes such as cell growth, differentiation, signal transduction, as well as influencing tissue fibrosis and ion transmembrane transport.ConclusionsThis study unveils a potential association between myocardial fibrosis and ion channels co-regulated by mRNAs and lncRNAs, closely linked to the emergence of new-onset POAF, after accounting for clinical risk factors. This discovery holds promise for further advances in clinical and fundamental research.

Transcriptome profile analysis in spinal cord injury rats with transplantation of menstrual blood-derived stem cells.

Menstrual blood-derived stem cells (MenSCs) are vital in treating many degenerative and traumatic disorders. However, the underlying molecular mechanisms remain obscure in MenSCs-treating spinal cord injury (SCI) rats. MenSCs were adopted into the injured sites of rat spinal cords at day 7 post surgery and the tissues were harvested for total RNA sequencing analysis at day 21 after surgery to investigate the expression patterns of RNAs. The differentially expressed genes (DEGs) were analyzed with volcano and heatmap plot. DEGs were sequentially analyzed by weighted gene co-expression network, functional enrichment, and competitive endogenous RNAs (ceRNA) network analysis. Next, expression of selected miRNAs, lncRNAs, circRNAs and mRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). Bioinformatics packages and extra databases were enrolled to scoop the genes functions and their interaction relationships. A total of 89 lncRNAs, 65 circRNAs, 120 miRNAs and 422 mRNAs were significantly upregulated and 65 lncRNAs, 72 circRNAs, 74 miRNAs, and 190 mRNAs were significantly downregulated in the MenSCs treated rats compared to SCI ones. Current investigation revealed that MenSCs treatment improve the recovery of the injured rats and the most significantly involved pathways in SCI regeneration were cell adhesion molecules, nature killer cell mediated cytotoxicity, primary immunodeficiency, chemokine signaling pathway, T cell receptor signaling pathway and B cell receptor signaling pathway. Moreover, the lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA ceRNA network of SCI was constructed. Finally, the protein-protein interaction (PPI) network was constructed using the top 100 DE mRNAs. The constructed PPI network included 47 nodes and 70 edges. In summary, the above results revealed the expression profile and potential functions of differentially expressed (DE) RNAs in the injured spinal cords of rats in the MenSCs-treated and SCI groups, and this study may provide new clues to understand the mechanisms of MenSCs in treating SCI.

Exploration of Positive and Negative Schizophrenia Symptom Heterogeneity and Establishment of Symptom-Related miRNA-mRNA Regulatory Network: Based on Transcriptome Sequencing Data.

Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.

Identification, characterization and expression analysis of circRNA encoded by SARS-CoV-1 and SARS-CoV-2.

Virus-encoded circular RNA (circRNA) participates in the immune response to viral infection, affects the human immune system, and can be used as a target for precision therapy and tumor biomarker. The coronaviruses SARS-CoV-1 and SARS-CoV-2 (SARS-CoV-1/2) that have emerged in recent years are highly contagious and have high mortality rates. In coronaviruses, little is known about the circRNA encoded by the SARS-CoV-1/2. Therefore, this study explores whether SARS-CoV-1/2 encodes circRNA and characteristics and functions of circRNA. Based on RNA-seq data of SARS-CoV-1 and SARS-CoV-2 infections, we used circRNA identification tools (circRNA_finder, find_circ and CIRI2) to identify circRNAs. The number of circRNAs encoded by SARS-CoV-1 and SARS-CoV-2 was identified as 151 and 470, respectively. It can be found that SARS-CoV-2 shows more prominent circRNA encoding ability than SARS-CoV-1. Expression analysis showed that only a few circRNAs encoded by SARS-CoV-1/2 showed high expression levels, and the positive strand produced more abundant circRNAs. Then, based on the identified SARS-CoV-1/2-encoded circRNAs, we performed circRNA identification and characterization using the previously developed CirRNAPL. Finally, target gene prediction and functional enrichment analysis were performed. It was found that viral circRNA is closely related to cancer and has a potential role in regulating host cell functions. This study studied the characteristics and functions of viral circRNA encoded by coronavirus SARS-CoV-1/2, providing a valuable resource for further research on the function and molecular mechanism of coronavirus circRNA.

Development and Validation of a Machine Learning Prognostic Model of m5C Related immune Genes in Lung Adenocarcinoma.

The aim of this retrospective research was to develop an immune-related genes significantly associated with m5C methylation methylation (m5C-IRGs)-related signature associated with lung adenocarainoma (LUAD). We introduced transcriptome data to screen out m5C-IRGs in The Cancer Genome Atlas (TCGA)-LUAD dataset. Subsequently, the m5C-IRGs associated with survival were certificated by Kaplan Meier (K-M) analysis. The univariate Cox, least absolute shrinkage and selection operator (LASSO) regression, and xgboost.surv tool were adopted to build a LUAD prognostic signature. We further conducted gene functional enrichment, immune microenvironment and immunotherapy analysis between 2 risk subgroups. Finally, we verified m5C-IRGs-related prognostic gene expression in transcription level. A total of 76 m5C-IRGs were identified in TCGA-LUAD dataset. Furthermore, 27 m5C-IRGs associated with survival were retained. Then, a m5C-IRGs prognostic signature was build based on the 3 prognostic genes (HLA-DMB, PPIA, and GPI). Independent prognostic analysis suggested that stage and RiskScore could be used as independent prognostic factors. We found that 4104 differentially expressed genes (DEGs) between the 2 risk subgroups were mainly concerned in immune receptor pathways. We found certain distinction in LUAD immune microenvironment between the 2 risk subgroups. Then, immunotherapy analysis and chemotherapeutic drug sensitivity results indicated that the m5C-IRGs-related gene signature might be applied as a therapy predictor. Finally, we found significant higher expression of PPIA and GPI in LUAD group compared to the normal group. The prognostic signature comprised of HLA-DMB, PPIA, and GPI based on m5C-IRGs was established, which might provide theoretical basis and reference value for the research of LUAD. TCGA-LUAD dataset was collected from the TCGA (https://portal.gdc.cancer.gov/) database, GSE31210 (validation set) was retrieved from GEO (https://www.ncbi.nlm.nih.gov/geo/) database.

Identification of Biomarker IL2Rβ in Ankylosing Spondylitis via Multi-Chip Integration Analysis of Gene Differential Expression.

Ankylosing spondylitis (AS) is a chronic inflammatory autoimmune disease that affects axial joints such as the spine. Early diagnosis is essential to improve treatment outcomes. The purpose of this study is to uncover underlying genetic diagnostic features of AS. We downloaded gene expression data from the Gene Expression Omnibus (GEO) database for three studies of groups of healthy and AS samples. After preprocessing and normalizing the data, we employed linear models to identify significant differentially expressed genes (DEGs) and further integrated the differential genes to acquire reliable differential transcriptional markers. Gene functional enrichment analysis was conducted to obtain enriched pathways and regulatory gene interactions were extracted from pathways to further elucidate pathway networks. Seventy-three reliably differentially expressed genes (DEGs) were integrated by differential analysis. Utilizing the regulatory relationships of the 21 Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway genes that were enriched in the analysis, a regulatory network of 622 genes was constructed and its topological properties were further analyzed. Functional enrichment analysis found 73 DEGs that were strongly associated with immune pathways like Th17, Th1 and Th2 cell differentiation. Using KEGG combined with DEGs, six hub genes (KLRD1, HLA-DRB3, HLA-DRB5, IL2Rβ, CD247, and CXCL10) were suggested from the network. Of these, the IL2Rβ gene was significantly differentially expressed compared with the normal control. IL2Rβ (Interleukin-2 receptor beta) is strongly associated with the onset and progression of autoimmune joint diseases, and may be used as a potential biomarker of AS. This study offers new characteristics that can help in the diagnosis and individualized therapy of AS.