Identification Of Genes Research Articles

Differential Gene Analysis of Langerhans Cell Histiocytosis and the Significance of MMP1-Targeted Drug Repositioning.

Langerhans cell histiocytosis (LCH) is a rare condition predominantly affecting young children. Activation of the MAPK pathway has offered key new insights into the pathogenesis of LCH; however, the precise mechanisms underlying its occurrence and development are still far from being completely elucidated. There is still a relapse/reactivation rate in patients with multisystem LCH. Therefore, this study aimed to investigate other potential LCH pathophysiologies and prospective therapeutic targets. The gene expression omnibus (GEO) database was used to retrieve gene expression profiles of LCH (GSE16395). Three distinct types of analyses were performed after identifying the common differentially expressed genes (DEGs) in LCH: hub gene identification, functional annotation, module construction, drug repositioning, and expression analysis via immunohistochemistry (IHC). We identified 417 common DEGs and 50 central hub genes. This functional study highlighted the significance of keratinization, skin development, and inflammation. In addition, we predicted new drug candidates (RS2 drugs targeting matrix metalloprotease1, MMP1) that could be used for LCH treatment. Finally, gene-miRNA and gene-TF networks and immune cell infiltration were analyzed for MMP1-related genes. MMP1 expression levels in LCH tissues were validated by IHC. Our study identified the central communal genes and novel drug candidates. These shared pathways and hub genes offer new perspectives on future mechanisms of action and therapeutic targets.

The landscape of rare genetic variation associated with inflammatory bowel disease and Parkinson’s disease comorbidity

BackgroundInflammatory bowel disease (IBD) and Parkinson’s disease (PD) are chronic disorders that have been suggested to share common pathophysiological processes. LRRK2 has been implicated as playing a role in both diseases. Exploring the genetic basis of the IBD-PD comorbidity through studying high-impact rare genetic variants can facilitate the identification of the novel shared genetic factors underlying this comorbidity.MethodsWe analyzed whole exomes from the BioMe BioBank and UK Biobank, and whole genomes from a cohort of 67 European patients diagnosed with both IBD and PD to examine the effects of LRRK2 missense variants on IBD, PD and their co-occurrence (IBD-PD). We performed optimized sequence kernel association test (SKAT-O) and network-based heterogeneity clustering (NHC) analyses using high-impact rare variants in the IBD-PD cohort to identify novel candidate genes, which we further prioritized by biological relatedness approaches. We conducted phenome-wide association studies (PheWAS) employing BioMe BioBank and UK Biobank whole exomes to estimate the genetic relevance of the 14 prioritized genes to IBD-PD.ResultsThe analysis of LRRK2 missense variants revealed significant associations of the G2019S and N2081D variants with IBD-PD in addition to several other variants as potential contributors to increased or decreased IBD-PD risk. SKAT-O identified two significant genes, LRRK2 and IL10RA, and NHC identified 6 significant gene clusters that are biologically relevant to IBD-PD. We observed prominent overlaps between the enriched pathways in the known IBD, PD, and candidate IBD-PD gene sets. Additionally, we detected significantly enriched pathways unique to the IBD-PD, including MAPK signaling, LPS/IL-1 mediated inhibition of RXR function, and NAD signaling. Fourteen final candidate IBD-PD genes were prioritized by biological relatedness methods. The biological importance scores estimated by protein–protein interaction networks and pathway and ontology enrichment analyses indicated the involvement of genes related to immunity, inflammation, and autophagy in IBD-PD. Additionally, PheWAS provided support for the associations of candidate genes with IBD and PD.ConclusionsOur study confirms and uncovers new LRRK2 associations in IBD-PD. The identification of novel inflammation and autophagy-related genes supports and expands previous findings related to IBD-PD pathogenesis, and underscores the significance of therapeutic interventions for reducing systemic inflammation.

Systems biology approach: identification of hub genes, signaling pathways, and molecular docking of COL1A1 gene in cervical insufficiency

Systems biology approach: identification of hub genes, signaling pathways, and molecular docking of COL1A1 gene in cervical insufficiency

Genome-wide evolutionary analysis of TKL_CTR1-DRK-2 gene family and functional characterization reveals that TaCTR1 positively regulates flowering time in wheat

BackgroundFlowering time has an important effect on regional adaptation and yields for crops. The tyrosine kinase-like (TKL) gene family is widely existed and participates in many biological processes in plants. Furthermore, only few TKLs have been characterized functions in controlling flowering time in wheat.ResultsHere, we report that TaCTR1, a tyrosine kinase-like (TKL) gene, regulates flowering time in wheat. Based on identification and evolutionary analysis of TKL_CTR1-DRK-2 subfamily in 15 plants, we proposed an evolutionary model for TaCTR1, suggesting that occurrence of some exon fusion events during evolution. The overexpression of TaCTR1 caused early flowering time in transgenic lines. Transcriptomics analysis enabled identification of mass differential expression genes including plant hormone (ET, ABA, IAA, BR) signaling, flavonoid biosynthesis, phenolamides and antioxidant, and flowering-related genes in TaCTR1 overexpression transgenic lines compared with WT plants. qRT–PCR results showed that the expression levels of ethylene (ET) signal-related genes (ETR, EIN, ERF) and flowering-related genes (FT, PPD1, CO, PRR, PHY) were altered in TaCTR1-overexpressing wheat compared with WT plants. Metabonomics analysis showed that flavonoid contents were altered.ConclusionsThus, the results show that TaCTR1 plays a positive role in controlling flowering time by activating various signaling pathways and regulating flowering-related genes, and will provide new insights on the mechanisms of wheat flowering regulation.

Evaluation of fortimicin antibiotic combinations against MDR Pseudomonas aeruginosa and resistome analysis of a whole genome sequenced pan-drug resistant isolate

BackgroundMultidrug-resistant (MDR) P. aeruginosa is a rising public health concern, challenging the treatment of such a ubiquitous pathogen with monotherapeutic anti-pseudomonal agents. Worryingly, its genome plasticity contributes to the emergence of P. aeruginosa expressing different resistant phenotypes and is now responsible for notable epidemics within hospital settings. Considering this, we aimed to evaluate the synergistic combination of fortimicin with other traditional anti-pseudomonal agents and to analyze the resistome of pan-drug resistant (PDR) isolate.MethodsStandard methods were used for analyzing the antimicrobial susceptibility tests. The checkerboard technique was used for the in vitro assessment of fortimicin antibiotic combinations against 51 MDR P. aeruginosa and whole genome sequencing was used to determine the resistome of PDR isolate.ResultsOut of 51 MDR P. aeruginosa, the highest synergistic effect was recorded for a combination of fortimicin with β-lactam group as meropenem, ceftazidime, and aztreonam at 71%, 59% and 43%, respectively. Of note, 56.8%, 39.2%, and 37.2% of the tested MDR isolates that had synergistic effects were also resistant to meropenem, ceftazidime, and aztreonam, respectively. The highest additive effects were recorded for combining fortimicin with amikacin (69%) and cefepime (44%) against MDR P. aeruginosa. Resistome analysis of the PDR isolate reflected its association with the antibiotic resistance phenotype. It ensured the presence of a wide variety of antibiotic-resistant genes (β-lactamases, aminoglycosides modifying enzymes, and efflux pump), rendering the isolate resistant to all clinically relevant anti-pseudomonal agents.ConclusionFortimicin in combination with classical anti-pseudomonal agents had shown promising synergistic activity against MDR P. aeruginosa. Resistome profiling of PDR P. aeruginosa enhanced the rapid identification of antibiotic resistance genes that are likely linked to the appearance of this resistant phenotype and may pave the way to tackle antimicrobial resistance issues shortly.

Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows

BackgroundHeat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses.ResultsA total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively.ConclusionsPhysiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.

Transcriptomic and metabolomic correlation analysis: effect of initial SO2 addition on higher alcohol synthesis in Saccharomyces cerevisiae and identification of key regulatory genes

IntroductionHigher alcohols are volatile compounds produced during alcoholic fermentation that affect the quality and safety of the final product. This study used a correlation analysis of transcriptomics and metabolomics to study the impact of the initial addition of SO2 (30, 60, and 90 mg/L) on the synthesis of higher alcohols in Saccharomyces cerevisiae EC1118a and to identify key genes and metabolic pathways involved in their metabolism.MethodsTranscriptomics and metabolomics correlation analyses were performed and differentially expressed genes (DEGs) and differential metabolites were identified. Single-gene knockouts for targeting genes of important pathways were generated to study the roles of key genes involved in the regulation of higher alcohol production.ResultsWe found that, as the SO2 concentration increased, the production of total higher alcohols showed an overall trend of first increasing and then decreasing. Multi-omics correlation analysis revealed that the addition of SO2 affected carbon metabolism (ko01200), pyruvate metabolism (ko00620), glycolysis/gluconeogenesis (ko00010), the pentose phosphate pathway (ko00030), and other metabolic pathways, thereby changing the precursor substances. The availability of SO2 indirectly affects the formation of higher alcohols. In addition, excessive SO2 affected the growth of the strain, leading to the emergence of a lag phase. We screened the ten most likely genes and constructed recombinant strains to evaluate the impact of each gene on the formation of higher alcohols. The results showed that ADH4, SER33, and GDH2 are important genes of alcohol metabolism in S. cerevisiae. The isoamyl alcohol content of the EC1118a-ADH4 strain decreased by 21.003%; The isobutanol content of the EC1118a-SER33 strain was reduced by 71.346%; and the 2-phenylethanol content of EC1118a-GDH2 strain was reduced by 25.198%.ConclusionThis study lays a theoretical foundation for investigating the mechanism of initial addition of SO2 in the synthesis of higher alcohols in S. cerevisiae, uncovering DEGs and key metabolic pathways related to the synthesis of higher alcohols, and provides guidance for regulating these mechanisms.

OsLSC6 Regulates Leaf Sheath Color and Cold Tolerance in Rice Revealed by Metabolite Genome Wide Association Study

Plant metabolites including anthocyanins play an important role in the growth of plants, as well as in regulating biotic and abiotic stress responses to the environment. Here we report comprehensive profiling of 3315 metabolites and a further metabolic-based genome-wide association study (mGWAS) based on 292,485 SNPs obtained from 311 rice accessions, including 160 wild and 151 cultivars. We identified hundreds of common variants affecting a large number of secondary metabolites with large effects at high throughput. Finally, we identified a novel gene namely OsLSC6 (Oryza sativa leaf sheath color 6), which encoded a UDP 3-O-glucosyltransferase and involved in the anthocyanin biosynthesis of Cyanidin-3-Galc (sd1825) responsible for leaf sheath color, and resulted in significant different accumulation of sd1825 between wild (purple) and cultivars (green). The results of knockout transgenic experiments showed that OsLSC6 regulated the biosynthesis and accumulation of sd1825, controlled the purple leaf sheath. Our further research revealed that OsLSC6 also confers resistance to cold stress during the seedling stage in rice. And we identified that a SNP in OsLSC6 was responsible for the leaf sheath color and chilling tolerance, supporting the importance of OsLSC6 in plant adaption. Our study could not only demonstrate that OsLSC6 is a vital regulator during anthocyanin biosynthesis and abiotic stress responses, but also provide a powerful complementary tool based on metabolites-to-genes analysis by mGWAS for functional gene identification andpromising candidate in future rice breeding and improvement.

Unravelling the complex interplay: environmental mixtures and breast cancer risk

Background. Globally, breast cancer ranks as the fourth most frequent reason for mortality when it comes to fatalities from cancer. The worrisome increases in rates of occurrence and death observed during the previous thirty years or more can be linked to several factors, such as changes in risk factor profiles, advancements in cancer registration, and the development of more effective detection technology. A strong association exists between the progression of metastasis and the mortality rate in breast cancer, with environmental pollutants seemingly contributing to this phenomenon. This association prompts a significant inquiry into the mechanisms that regulate the formation of metastases due to environmental and chemical contaminants. The impact of pollutants and chemical substances on communication pathways, which are essential for the growth and spread of tumor cells, among the numerous possible risk factors is gaining increasing focus. Material and methods. scientific research on environmental variables and additional factors linked to breast carcinoma was located and reviewed using engines such as the PubMed database, the MEDLINE database the Scopus database, and Google Scholar, among others, with search terms like “Breast Cancer”, “Risk components”, “Chemical exposures”, “Environmental toxic exposure”, “Disease progression”, “Bisphenol-A”, “Heavy metallic materials”, and “Food preparations”. Results. This literature aimed to present a thorough overview of the existing data on the impact of environmental and chemical toxins on breast cancer and as a result, a significant relationship between these toxins and breast cancer and its metastatic potential was discovered in more depth. Conclusion. In conclusion, breast cancer's complexity demands a holistic approach encompassing genetic, environmental, and early detection strategies. advancements in stem cell biology and gene identification enhance our understanding. Yet, dissemination remains a key challenge. Environmental toxins play a significant role, necessitating further epidemiological and molecular investigations to mitigate breast cancer's global impact.

Identification and Verification of Endoplasmic Reticulum Stress-Related Genes as Novel Signatures for Osteoarthritis Diagnosis and Therapy: A Bioinformatics Analysis-Oriented Pilot Study.

Endoplasmic reticulum stress (ERS) has been reported to be closely associated with the development of osteoarthritis (OA), but the underlying mechanisms are not fully delineated. The present study was designed to investigate the involvement of ERS-related genes in regulating OA progression. The expression profiles of OA patients and normal people were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) in datasets GSE55457 and GSE55235 were screened and identified by R software with the construction of the protein-protein interaction (PPI) networks. Through the STRING and Venn diagram analysis, hub ERS-related genes were obtained. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed. Biomarkers with high diagnostic values of osteoarthritis (OA) were studied. The hematoxylin and eosin (H&E) staining and micro-CT were applied to evaluate the establishment of the OA model. The expression levels of biomarkers were validated with the use of reverse transcription‑quantitative polymerase chain reaction (RT-qPCR) and western blot. Finally, we evaluated the correlations of hub ERS-related genes with the immune infiltration cells via the CIBERSORT algorithm. A total of 60 downregulated and 52 upregulated DEGs were identified, and the following GO and KEGG pathway analyses verified that those DEGs were mainly enriched in biological process (BP), cellular component (CC), molecular function (MF), and inflammation-associated signal pathways. Interestingly, among all the DEGs, six ER stress-associated genes, including activating transcription factor 3 (ATF3), DEAD-Box Helicase 3 X-Linked (DDX3X), AP-1 transcription factor subunit (JUN), eukaryotic initiation factor 4 (EIF4A1), KDEL endoplasmic reticulum protein retention receptor 3 (KDELR3), and vascular endothelial growth factor A (VEGFA), were found to be closely associated with OA progression, and the following RT-qPCR and Western Blot analysis confirmed that DDX3X, JUN, and VEGFA were upregulated, whereas KDELR3, EIF4A1, and ATF3 were downregulated in OA rats tissues compared to the normal tissues, which were in accordance with our bioinformatics findings. Furthermore, our receiver operating characteristic (ROC) curve analysis verified that the above six ER stress-associated genes could be used as ideal biomarkers for OA diagnosis and those genes also potentially regulated immune responses by influencing the biological functions of mast cells and macrophages. Collectively, the present study firstly identified six ER stress-associated genes (ATF3, DDX3X, JUN, EIF4A1, KDELR3, and VEGFA) that may play critical role in regulating the progression of OA.

Identification of potential candidate genes for the Houyan trait in developing Wulong goose embryos by transcriptomic analysis

ABSTRACT 1. The Wulong goose is a Chinese breed and a source of high-quality meat and eggs. A characteristic of the Wulong goose is that a proportion of the birds do not have eyelids, known as the Huoyon trait. 2. Wulong geese exhibiting the Huoyan trait at embryonic stages of 9 days (E9), 12 days (E12) and 14 days (E14) were selected alongside those with normal eyelids for comprehensive transcriptome sequencing. Differentially expressed gene (DEG) and functional enrichment analyses were performed and finally, eight DEG were chosen to verify the accuracy of qPCR sequencing. 3. Overall, 466, 962 and 550 DEG were obtained from the three control groups, D9 vs. N9, D12 vs. N12 and D14 vs. N14, respectively, by differential analysis (p < 0.05). CDKN1C, CRH, CROCC and TYSND1 were significantly expressed in the three groups. Enrichment analysis revealed the enrichment of CROCC and TYSND1 in pathways of cell cycle process, endocytosis, microtubule-based process, microtubule organising centre organisation, protein processing and protein maturation. CDKN1C and CRH were enriched in the cell cycle and cAMP signalling pathway. 4. Some collagen family genes were detected among the DEGs, including COL3A1, COL4A5, COL4A2 and COL4A1. FREM1 and FREM2 genes were detected in both Huoyan and normal eyelids. There was a significant difference (p < 0.01) in FREM1 expression between ED9 and ED14 in female embryos, but this difference was not observed in male embryos.

Identification and validation of stable reference genes for RT-qPCR analyses of Kobresia littledalei seedlings

BackgroundKobreisa littledalei, belonging to the Cyperaceae family is the first Kobresia species with a reference genome and the most dominant species in Qinghai-Tibet Plateau alpine meadows. It has several resistance genes which could be used to breed improved crop varieties. Reverse Transcription Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR) is a popular and accurate gene expression analysis method. Its reliability depends on the expression levels of reference genes, which vary by species, tissues and environments. However, K.littledalei lacks a stable and normalized reference gene for RT-qPCR analysis.ResultsThe stability of 13 potential reference genes was tested and the stable reference genes were selected for RT-qPCR normalization for the expression analysis in the different tissues of K. littledalei under two abiotic stresses (salt and drought) and two hormonal treatments (abscisic acid (ABA) and gibberellin (GA)). Five algorithms were used to assess the stability of putative reference genes. The results showed a variation amongst the methods, and the same reference genes showed tissue expression differences under the same conditions. The stability of combining two reference genes was better than a single one. The expression levels of ACTIN were stable in leaves and stems under normal conditions, in leaves under drought stress and in roots under ABA treatment. The expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression was stable in the roots under the control conditions and salt stress and in stems exposed to drought stress. Expression levels of superoxide dismutase (SOD) were stable in stems of ABA-treated plants and in the roots under drought stress. Moreover, RPL6 expression was stable in the leaves and stems under salt stress and in the stems of the GA-treated plants. EF1-alpha expression was stable in leaves under ABA and GA treatments. The expression levels of 28 S were stable in the roots under GA treatment. In general, ACTIN and GAPDH could be employed as housekeeping genes for K. littledalei under different treatments.ConclusionThis study identified the best RT-qPCR reference genes for different K. littledalei tissues under five experimental conditions. ACTIN and GAPDH genes can be employed as the ideal housekeeping genes for expression analysis under different conditions. This is the first study to investigate the stable reference genes for normalized gene expression analysis of K. littledalei under different conditions. The results could aid molecular biology and gene function research on Kobresia and other related species.

Metagenome-enabled models improve genomic predictive ability and identification of herbivory-limiting genes in sweetpotato

Abstract Plant-insect interactions are often influenced by host-/insect-associated metagenomic community members. Relative abundance of insects and the microbes that modulate their interactions were obtained from sweetpotato (Ipomoea batatas) leaf-associated metagenomes using quantitative reduced representation sequencing and strain/species level profiling with the Qmatey software. Positive correlations were found between whitefly (Bemisia tabaci) and its endosymbionts (Candidatus Hamiltonella defensa, Candidatus Portiera aleyrodidarum, and Rickettsia spp.) and negative correlations with nitrogen-fixing bacteria that implicate nitric oxide in sweetpotato-whitefly interaction. Genome-wide associations using 252,975 dosage-based markers, and metagenomes as a covariate to reduce false positive rates, implicated ethylene and cell wall modification in sweetpotato-whitefly interaction. The predictive abilities (PA) for whitefly and Ocypus olens abundance were high in both populations (68-69% and 33.3-35.8%, respectively, and 69.9% for Frankliniella occidentalis). The metagBLUP (gBLUP) prediction model, which fits the background metagenome-based Cao dissimilarity matrix instead of the marker-based relationship matrix (G-matrix), revealed moderate PA (35.3-49.1%) except for O. olens (3-10.1%). Significant gain in PA after modeling the metagenome as a covariate (gGBLUP, ≤11%) confirms quantification accuracy and that the metagenome modulates phenotypic expression and might account for the missing heritability problem. Significant gains in PA were also revealed after fitting allele dosage (≤17.4%) and dominance effects (≤4.6%). Pseudo-diploidized genotype data underperformed for dominance models. Including segregation distorted loci (SDL) increased PA by 6-17.1%, suggesting traits associated with fitness cost might benefit from the inclusion of SDL. Our findings confirm the holobiont theory of host-metagenome co-evolution and underscore its potential for breeding within the context of GxGxE interactions.

A Genome-Wide Analysis of the BAM Gene Family and Identification of the Cold-Responsive Genes in Pomegranate (Punica granatum L.)

Beta-amylases (BAMs, EC 3.2.1.2), belonging to a multigene family, play a pivotal role in starch breakdown and are also involved in hormonal and stress responses, notably to cold stress. Pomegranate trees (Punica granatum L.) are adapted to warm climates and are sensitive to cold temperatures. In this study, we analyzed eight PgBAM genes from the pomegranate genome dataset. These members unevenly distributed across chromosomes and were categorized into four groups based on their orthologous members. The motif composition was highly consistent among most members. In contrast, exon numbers and arrangements were conserved within groups or subgroups, whereas significant diversity was observed between different groups. A syntenic analysis revealed that three PgBAM members (PgBAM1/4/5) showed a total of 11 syntenic relationships with the BAM members from Arabidopsis, kiwifruit, and Chinese white pear, respectively. Promoter binding motif prediction suggested potential roles for PgBAMs’ genes in light, stress, hormones, and development signaling. Gene expression indicated that PgBAM4 was predominantly expressed in leaves, PgBAM7 in flowers, and PgBAM8 in roots and leaves and during fruit ripening, particularly in pericarp development. A transcriptome analysis identified the starch and sucrose metabolism pathway (map00500) as a key factor in the cold stress response of cold-sensitive cultivar ‘Tunisia’ seedlings. PgBAM4 exhibited remarkable expression and was closely associated with the cold-responsive BAM genes, characterized by a closer phylogenetic relationship, conserved catalytic residues, and similar secondary and tertiary structures. Moreover, the differences in soluble sugar levels and PgBAM4 expression were closely associated with the varying cold stress resistance observed between ‘Tunisia’ and ‘Sanbai’ seedlings. Furthermore, yeast one-hybrid assays confirmed that PgCBF7, a critical transcription factor for enhancing freezing tolerance, binds to the promoter region of PgBAM4. Our findings provide a systematic overview of the PgBAM gene family and shed new light on the regulatory mechanisms underlying cold stress tolerance in pomegranate.

Exploring the interconnected between type 2 diabetes mellitus and nonalcoholic fatty liver disease: Genetic correlation and Mendelian randomization analysis.

Epidemiological and clinical studies have indicated a higher risk of nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM), implying a potentially shared genetic etiology, which is still less explored. Genetic links between T2DM and NAFLD were assessed using linkage disequilibrium score regression and pleiotropic analysis under composite null hypothesis. European GWAS data have identified shared genes, whereas SNP-level pleiotropic analysis under composite null hypothesis has explored pleiotropic loci. generalized gene-set analysis of GWAS data determines pleiotropic pathways and tissue enrichment using eQTL mapping to identify associated genes. Mendelian randomization analysis was used to investigate the causal relationship between NAFLD and T2DM. Linkage disequilibrium score regression analysis revealed a strong genetic correlation between T2DM and NAFLD, and identified 24 pleiotropic loci. These single-nucleotide polymorphisms are primarily involved in biosynthetic regulation, RNA biosynthesis, and pancreatic development. generalized gene-set analysis of GWAS data analysis revealed significant enrichment in multiple brain tissues. Gene mapping using these 3 methods led to the identification of numerous pleiotropic genes, with differences observed in liver and kidney tissues. These genes were mainly enriched in pancreas, brain, and liver tissues. The Mendelian randomization method indicated a significantly positive unidirectional causal relationship between T2DM and NAFLD. Our study identified a shared genetic structure between NAFLD and T2DM, providing new insights into the genetic pathogenesis and mechanisms of NAFLD and T2DM comorbidities.

Identification of potential hub genes and regulatory networks of smoking-related endothelial dysfunction in atherosclerosis using bioinformatics analysis.

Endothelial dysfunction, the earliest stage of atherosclerosis, can be caused by smoking, but its molecular mechanism requires further investigation. This study aimed to use bioinformatics analysis to identify potential mechanisms involved in smoking-related atherosclerotic endothelial dysfunction. The transcriptome data used for this bioinformatics analysis were obtained from the Gene Expression Omnibus (GEO) database. The GSE137578 and GSE141136 datasets were used to identify common differentially expressed genes (co-DEGs) in endothelial cells treated with oxidized low-density lipoprotein (ox-LDL) and tobacco. The co-DEGs were annotated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG) databases. Additionally, a protein-protein interaction (PPI) network was constructed to visualize their interactions and screen for hub genes. GSE120521 dataset was used to verify the expression of hub genes in unstable plaques. The miRNA expression profile GSE137580 and online databases (starBase 2.0, TargetScan 8.0 and DGIdb v4.2.0) were used to predict the related non-coding RNAs and drugs. A total of 232 co-DEGs were identified, including 113 up-regulated genes and 119 down-regulated genes. These DEGs were primarily enriched in detrimental autophagy, cell death, transcription factors, and cytokines, and were implicated in ferroptosis, abnormal lipid metabolism, inflammation, and oxidative stress pathways. Ten hub genes were screened from the constructed PPI network, including up-regulated genes such as FOS, HMOX1, SQSTM1, PTGS2, ATF3, DDIT3, and down-regulated genes MCM4, KIF15, UHRF1, and CCL2. Importantly, HMOX1 was further up-regulated in unstable plaques (p= 0.034). Finally, a regulatory network involving lncRNA/circRNA-miRNA-hub genes and drug-hub genes was established. Atherosclerotic endothelial dysfunction is associated with smoking-induced injury. Through bioinformatics analysis, we identified potential mechanisms and provided potential therapeutic targets.

Where do obesity and male infertility collide?

The parallel rise in obesity and male infertility in modern societies necessitates the identification of susceptibility genes underlying these interconnected health issues. In our study, we conducted a comprehensive search in the OMIM database to identify genes commonly associated with male infertility and obesity. Subsequently, we performed an insilico analysis using the REVEL algorithm to detect pathogenic single nucleotide polymorphisms (SNPs) in the coding region of these candidate genes. To validate our findings in vivo, we conducted a comprehensive analysis of SNPs and gene expression of candidate genes in 200 obese infertile subjects and 240 obese fertile individuals using ARMS-PCR. Additionally, we analyzed 20 fertile and 22 infertile obese individuals using Realtime-qPCR. By removing duplicated queries, we obtained 197 obesity-related genes and 102 male infertility-related genes from the OMIM database. Interestingly, the APOB gene was found in common between the two datasets. REVEL identified the rs13306194 variant as potentially pathogenic with a calculated score of 0.524. The study identified a significant association between the AA (P value = 0.001) genotype and A allele (P value = 0.003) of the APOB rs13306194 variant and infertility in obese men. APOB expression levels were significantly lower in obese infertile men compared to obese fertile controls (p < 0.01). Moreover, the AA genotype of rs13306194 APOB was associated with a significant decrease in APOB gene expression in obese infertile men (p = 0.05). There is a significant association between the Waist-to-Hip Ratio (WHR) and LH with infertility in the obese infertile group. These results are likely to contribute to a better understanding of the causes of male infertility and its association with obesity.

Meningioma recurrence: Time for an online prediction tool?

Background: Meningioma, the most common brain tumor, traditionally considered benign, has a relatively high risk of recurrence over a patient’s lifespan. In addition, with the emergence of several clinical, radiological, and molecular variables, it is becoming evident that existing grading criteria, including Simpson’s and World Health Organization classification, may not be sufficient or accurate. As web-based tools for widespread accessibility and usage become commonplace, such as those for gene identification or other cancers, it is timely for meningioma care to take advantage of evolving new markers to help advance patient care. Methods: A scoping review of the meningioma literature was undertaken using the MEDLINE and Embase databases. We reviewed original studies and review articles from September 2022 to December 2023 that provided the most updated information on the demographic, clinical, radiographic, histopathological, molecular genetics, and management of meningiomas in the adult population. Results: Our scoping review reveals a large body of meningioma literature that has evaluated the determinants for recurrence and aggressive tumor biology, including older age, female sex, genetic abnormalities such as telomerase reverse transcriptase promoter mutation, CDKN2A deletion, subtotal resection, and higher grade. Despite a large body of evidence on meningiomas, however, we noted a lack of tools to aid the clinician in decision-making. We identified the need for an online, self-updating, and machine-learning-based dynamic model that can incorporate demographic, clinical, radiographic, histopathological, and genetic variables to predict the recurrence risk of meningiomas. Conclusion: Although a challenging endeavor, a recurrence prediction tool for meningioma would provide critical information for the meningioma patient and the clinician making decisions on long-term surveillance and management of meningiomas.

Identification and analysis of chemokine-related and NETosis-related genes in acute pancreatitis to develop a predictive model

Background: Chemokines and NETosis are significant contributors to the inflammatory response, yet there still needs to be a more comprehensive understanding regarding the specific molecular characteristics and interactions of NETosis and chemokines in the context of acute pancreatitis (AP) and severe AP (SAP).Methods: To address this gap, the mRNA expression profile dataset GSE194331 was utilized for analysis, comprising 87 AP samples (77 non-SAP and 10 SAP) and 32 healthy control samples. Enrichment analyses were conducted for differentially expressed chemokine-related genes (DECRGs) and NETosis-related genes (DENRGs). Three machine-learning algorithms were used for the identification of signature genes, which were subsequently utilized in the development and validation of nomogram diagnostic models for the prediction of AP and SAP. Furthermore, single-gene Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed. Lastly, an interaction network for the identified signature genes was constructed.Results: We identified 12 DECRGs and 7 DENRGs, and enrichment analyses indicated they were primarily enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and T cell receptor signaling pathway. Moreover, these machine learning algorithms finally recognized three signature genes (S100A8, AIF1, and IL18). Utilizing the identified signature genes, we developed nomogram models with high predictive accuracy for AP and differentiation of SAP from non-SAP, as demonstrated by area under the curve (AUC) values of 0.968 (95% CI 0.937–0.990) and 0.862 (95% CI 0.742–0.955), respectively, in receiver operating characteristic (ROC) curve analysis. Subsequent single-gene GESA and GSVA indicated a significant positive correlation between these signature genes and the proteasome complex. At the same time, a negative association was observed with the Th1 and Th2 cell differentiation signaling pathways.Conclusion: We have identified three genes (S100A8, AIF1, and IL18) related to chemokines and NETosis, and have developed accurate diagnostic models that might provide a novel method for diagnosing AP and differentiating between severe and non-severe cases.

Identification of key genes affecting ventilator-induced diaphragmatic dysfunction in diabetic mice

BackgroundMechanical ventilation (MV) is often required in critically ill patients. However, prolonged mechanical ventilation can lead to Ventilator-induced diaphragmatic dysfunction (VIDD), resulting in difficulty in extubation after tracheal intubation, prolonged ICU stay, and increased mortality. At present, the incidence of diabetes is high in the world, and the prognosis of diabetic patients with mechanical ventilation is generally poor. Therefore, the role of diabetes in the development of VIDD needs to be discovered.MethodsMV modeling was performed on C57 mice and DB mice, and the control group was set up in each group. After 12 h of mechanical ventilation, the muscle strength of the diaphragm was measured, and the muscle fiber immunofluorescence staining was used to verify the successful establishment of the MV model. RNA sequencing (RNA-seq) method was used to detect mRNA expression levels of the diaphragms of each group, and then differential expressed gene analysis, Heatmap analysis, WGCNA analysis, Venn analysis, GO and KEGG enrichment analysis were performed. qRT-PCR was used to verify the expression of the selected mRNAs.ResultsOur results showed that, compared with C57 control mice, the muscle strength and muscle fiber cross-sectional area of mice after mechanical ventilation decreased, and DB mice showed more obvious in this respect. RNA-seq showed that these differential expressed (DE) mRNAs were mainly related to genes such as extracellular matrix, collagen, elastic fiber and Fbxo32. GO and KEGG enrichment analysis showed that the signaling pathways associated with diabetes were mainly as follows: extracellular matrix (ECM), protein digestion and absorption, PI3K-Akt signaling pathway, calcium signaling pathway, MAPK signaling pathway and AGE-RAGE signaling pathway in diabetic complications, etc. ECM has the closest relationship with VIDD in diabetic mice. The key genes determined by WGCNA and Venn analysis were validated by quantitative real-time polymerase chain reaction (qRT-PCR), which exhibited trends similar to those observed by RNA-seq.ConclusionVIDD can be aggravated in diabetic environment. This study provides new evidence for mRNA changes after mechanical ventilation in diabetic mice, suggesting that ECM and collagen may play an important role in the pathophysiological mechanism and progression of VIDD in diabetic mice, and provides some clues for the research, diagnosis, and treatment of VIDD in diabetic context.