Identification of overlay differentially expressed genes in both rats and goats with blast lung injury through comparative transcriptomics / 中华创伤杂志(英文版)

PURPOSE@#To identify the potential target genes of blast lung injury (BLI) for the diagnosis and treatment.@*METHODS@#This is an experimental study. The BLI models in rats and goats were established by conducting a fuel-air explosive power test in an unobstructed environment, which was subsequently validated through hematoxylin-eosin staining. Transcriptome sequencing was performed on lung tissues from both goats and rats. Differentially expressed genes were identified using the criteria of q ≤ 0.05 and |log2 fold change| ≥ 1. Following that, enrichment analyses were conducted for gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathways. The potential target genes were further confirmed through quantitative real-time polymerase chain reaction and enzyme linked immunosorbent assay.@*RESULTS@#Observations through microscopy unveiled the presence of reddish edema fluid, erythrocytes, and instances of focal or patchy bleeding within the alveolar cavity. Transcriptome sequencing analysis identified a total of 83 differentially expressed genes in both rats and goats. Notably, 49 genes exhibited a consistent expression pattern, with 38 genes displaying up-regulation and 11 genes demonstrating down-regulation. Enrichment analysis highlighted the potential involvement of the interleukin-17 signaling pathway and vascular smooth muscle contraction pathway in the underlying mechanism of BLI. Furthermore, the experimental findings in both goats and rats demonstrated a strong association between BLI and several key genes, including anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4, which exhibited up-regulation.@*CONCLUSIONS@#Anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4 hold potential as target genes for the prognosis, diagnosis, and treatment of BLI.

Transcriptional differential analysis of ocular surface ectoderm and surface ectoderm / 国际眼科杂志(Guoji Yanke Zazhi)

AIM:To identify transcriptional differences between the ocular surface ectoderm(OSE)and surface ectoderm(SE)using RNA-seq, and elucidate the OSE transcriptome landscape and the regulatory networks involved in its development.METHODS:OSE and SE cells were differentiated from human embryonic stem(hES)cells. Differentially expressed genes(DEGs)between OSE and SE were analyzed using RNA-seq. Based on the DEGs, we performed gene ontology(GO)analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis, and protein-protein interaction(PPI)network analysis. Transcription factors(TFs)and hub genes were screened. Subsequently, TF-gene and TF-miRNA regulatory networks were constructed using the NetworkAnalyst platform.RESULTS:A total of 4 182 DEGs were detected between OSE and SE cells, with 2 771 up-regulated and 1 411 down-regulated genes in OSE cells. GO-BP analysis revealed that up-regulated genes in OSE were enriched in the regulation of ion transmembrane transport, axon development, and modulation of chemical synaptic transmission. Down-regulated genes were primarily involved in nuclear division, chromosome segregation, and regulation of cell cycle phase transition. KEGG analysis indicated that up-regulated genes in OSE cells were enriched in signaling pathways such as cocaine addiction, axon guidance, and amphetamine addiction, while down-regulated genes were enriched in proteoglycans in cancer, ECM-receptor interaction, protein digestion and absorption, and cytokine-cytokine receptor interaction. Additionally, compared with SE, 204 TFs(including FOS, EGR1, POU5F1, SOX2, and PAX6)were up-regulated, and 80 TFs(including HAND2, HOXB6, HOXB5, HOXA5, and HOXB8)were down-regulated in OSE cells. Furthermore, we identified 6 up-regulated and 9 down-regulated hub genes in OSE cells, and constructed TF-gene and TF-miRNA regulatory networks based on these hub genes.CONCLUSIONS:The transcriptome characteristics of OSE and SE cells were elucidated through RNA-seq analysis. These findings may provide a novel insight for studies on the development and in vitro directed induction of OSE and corneal epithelial cells.

Integrated aqueous humor ceRNA and miRNA–TF–mRNA network analysis reveals potential molecular mechanisms governing primary open-angle glaucoma pathogenesis

To conduct an integrated bioinformatics analysis of extant aqueous humor (AH) gene expression datasets in order to identify key genes and the regulatory mechanism governing primary open?angle glaucoma (POAG) progression. Methods: Two datasets (GSE101727 and GSE105269) were downloaded from the Gene Expression Omnibus, and the messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs) were identified between controls and POAG patients. Differentially expressed (DE) mRNAs and DElncRNAs were then subjected to pathway enrichment analyses, after which a protein–protein interaction (PPI) network was generated. This network was then expanded to establish lncRNA–miRNA–mRNA and miRNA–transcription factor (TF)–mRNA networks. Results: The GSE101727 dataset was used to identify 2746 DElncRNAs and 2208 DEmRNAs, while the GSE105269 dataset was used to identify 45 DEmiRNAs. We ultimately constructed a competing endogenous RNA (ceRNA) network incorporating 47 lncRNAs, six miRNAs, and 17 mRNAs. The proteins encoded by these 17 hub mRNAs were found to be significantly enriched for activities that may be linked to POAG pathogenesis. In addition, we generated a miRNA–TF–mRNA regulatory network containing two miRNAs (miR?135a?5p and miR?139?5p), five TFs (TGIF2, TCF3, FOS, and so on), and five mRNAs (SHISA7, ST6GAL2, TXNIP, and so on). Conclusion: The SHISA7, ST6GAL2, TXNIP, FOS, and DCBLD2 genes may be viable therapeutic targets for the prevention or treatment of POAG and are regulated by the TFs (TGIF2, HNF1A, TCF3, and FOS)

Expression analysis of transcription factors in sugarcane during cold stress / Análise de expressão de fatores de transcrição em cana-de-açúcar sob estresse por frio

Transcription factors (TF) are a wide class of genes in plants, and these can regulate the expression of other genes in response to various environmental stresses (biotic and abiotic). In the current study, transcription factor activity in sugarcane was examined during cold stress. Initially, RNA transcript reads of two sugarcane cultivars (ROC22 and GT08-1108) under cold stress were downloaded from SRA NCBI database. The reads were aligned into a reference genome and the differential expression analyses were performed with the R/Bioconductor edgeR package. Based on our analyses in the ROC22 cultivar, 963 TF genes were significantly upregulated under cold stress among a total of 5649 upregulated genes, while 293 TF genes were downregulated among a total of 3,289 downregulated genes. In the GT08-1108 cultivar, 974 TF genes were identified among 5,649 upregulated genes and 283 TF genes were found among 3,289 downregulated genes. Most transcription factors were annotated with GO categories related to protein binding, transcription factor binding, DNA-sequence-specific binding, transcription factor complex, transcription factor activity in RNA polymerase II, the activity of nucleic acid binding transcription factor, transcription corepressor activity, sequence-specific regulatory region, the activity of transcription factor of RNA polymerase II, transcription factor cofactor activity, transcription factor activity from plastid promoter, transcription factor activity from RNA polymerase I promoter, polymerase II and RNA polymerase III. The findings of above results will help to identify differentially expressed transcription factors during cold stress. It also provides a comprehensive analysis of the regulation of the transcription activity of many genes. Therefore, this study provides the molecular basis for improving cold tolerance in sugarcane and other economically important grasses.

Fatores de transcrição (FT) são uma ampla classe de genes em plantas e podem regular a expressão de outros genes em resposta a vários estresses ambientais (estresses bióticos e abióticos). No presente estudo, a atividade do fator de transcrição na cana-de-açúcar foi examinada durante o estresse pelo frio. Inicialmente, as leituras de transcrição de RNA de duas cultivares de cana-de-açúcar (ROC22 e GT08-1108) sob estresse frio foram baixadas do banco de dados SRA NCBI. As leituras foram alinhadas em um genoma de referência e as análises de expressão diferencial foram realizadas com o pacote R / Bioconductor edgeR. Com base em nossas análises no cultivar ROC22, 963 genes TF foram significativamente regulados positivamente sob estresse pelo frio entre um total de 5.649 genes regulados positivamente, enquanto 293 genes TF foram regulados negativamente entre um total de 3.289 genes regulados negativamente. No cultivar GT08-1108, 974 genes TF foram identificados entre 5.649 genes regulados positivamente e 283 genes TF foram encontrados entre 3.289 genes regulados negativamente. Os fatores de transcrição, em sua maioria, foram anotados com categorias GO relacionadas à ligação de proteína, ligação de fator de transcrição, ligação específica de sequência de DNA, complexo de fator de transcrição, atividade de fator de transcrição em RNA polimerase II, atividade de fator de transcrição de ligação de ácido nucleico, atividade de corepressor de transcrição, sequência específica da região reguladora, atividade do fator de transcrição da RNA polimerase II, atividade do cofator do fator de transcrição, atividade do fator de transcrição do promotor do plastídio, atividade do fator de transcrição do promotor da RNA polimerase I, polimerase II e RNA polimerase III. As descobertas dos resultados acima ajudarão a identificar fatores de transcrição expressos diferencialmente durante o estresse pelo frio. Ele também fornece uma análise abrangente da regulação da atividade [...].

Expression analysis of transcription factors in sugarcane during cold stress

Abstract Transcription factors (TF) are a wide class of genes in plants, and these can regulate the expression of other genes in response to various environmental stresses (biotic and abiotic). In the current study, transcription factor activity in sugarcane was examined during cold stress. Initially, RNA transcript reads of two sugarcane cultivars (ROC22 and GT08-1108) under cold stress were downloaded from SRA NCBI database. The reads were aligned into a reference genome and the differential expression analyses were performed with the R/Bioconductor edgeR package. Based on our analyses in the ROC22 cultivar, 963 TF genes were significantly upregulated under cold stress among a total of 5649 upregulated genes, while 293 TF genes were downregulated among a total of 3,289 downregulated genes. In the GT08-1108 cultivar, 974 TF genes were identified among 5,649 upregulated genes and 283 TF genes were found among 3,289 downregulated genes. Most transcription factors were annotated with GO categories related to protein binding, transcription factor binding, DNA-sequence-specific binding, transcription factor complex, transcription factor activity in RNA polymerase II, the activity of nucleic acid binding transcription factor, transcription corepressor activity, sequence-specific regulatory region, the activity of transcription factor of RNA polymerase II, transcription factor cofactor activity, transcription factor activity from plastid promoter, transcription factor activity from RNA polymerase I promoter, polymerase II and RNA polymerase III. The findings of above results will help to identify differentially expressed transcription factors during cold stress. It also provides a comprehensive analysis of the regulation of the transcription activity of many genes. Therefore, this study provides the molecular basis for improving cold tolerance in sugarcane and other economically important grasses.

Resumo Fatores de transcrição (FT) são uma ampla classe de genes em plantas e podem regular a expressão de outros genes em resposta a vários estresses ambientais (estresses bióticos e abióticos). No presente estudo, a atividade do fator de transcrição na cana-de-açúcar foi examinada durante o estresse pelo frio. Inicialmente, as leituras de transcrição de RNA de duas cultivares de cana-de-açúcar (ROC22 e GT08-1108) sob estresse frio foram baixadas do banco de dados SRA NCBI. As leituras foram alinhadas em um genoma de referência e as análises de expressão diferencial foram realizadas com o pacote R / Bioconductor edgeR. Com base em nossas análises no cultivar ROC22, 963 genes TF foram significativamente regulados positivamente sob estresse pelo frio entre um total de 5.649 genes regulados positivamente, enquanto 293 genes TF foram regulados negativamente entre um total de 3.289 genes regulados negativamente. No cultivar GT08-1108, 974 genes TF foram identificados entre 5.649 genes regulados positivamente e 283 genes TF foram encontrados entre 3.289 genes regulados negativamente. Os fatores de transcrição, em sua maioria, foram anotados com categorias GO relacionadas à ligação de proteína, ligação de fator de transcrição, ligação específica de sequência de DNA, complexo de fator de transcrição, atividade de fator de transcrição em RNA polimerase II, atividade de fator de transcrição de ligação de ácido nucleico, atividade de corepressor de transcrição, sequência específica da região reguladora, atividade do fator de transcrição da RNA polimerase II, atividade do cofator do fator de transcrição, atividade do fator de transcrição do promotor do plastídio, atividade do fator de transcrição do promotor da RNA polimerase I, polimerase II e RNA polimerase III. As descobertas dos resultados acima ajudarão a identificar fatores de transcrição expressos diferencialmente durante o estresse pelo frio. Ele também fornece uma análise abrangente da regulação da atividade de transcrição de muitos genes. Portanto, este estudo fornece base molecular para melhorar a tolerância ao frio em cana-de-açúcar e outras gramíneas economicamente importantes.

Mechanism of Huangjing Qianshi Decoction in treatment of prediabetic mice based on transcriptome sequencing / 中国中药杂志

Based on transcriptome sequencing technology, the mouse model of prediabetes treated with Huangjing Qianshi Decoction was sequenced to explore the possible mechanism of treating prediabetes. First of all, transcriptome sequencing was performed on the normal BKS-DB mouse group, the prediabetic model group, and the Huangjing Qianshi Decoction treatment group(treatment group) to obtain differentially expressed genes in the skeletal muscle samples of mice. The serum biochemical indexes were detected in each group to screen out the core genes of Huangjing Qianshi Decoction in prediabetes. Gene Ontology(GO) database and Kyoto Encyclopedia of Genes and Genomes(KEGG) database were used to conduct signaling pathway enrichment analysis of differentially expressed genes, and real-time quantitative polymerase chain reaction(RT-qPCR) was used to verify them. The results showed that the levels of fasting blood glucose(FBG), fasting insulin(FINS), insulin resistance index(HOMA-IR), total cholesterol(TC), triglycerides(TG), and low-density lipoprotein cholesterol(LDL-C) in the mouse model were significantly decreased after treatment with Huangjing Qianshi Decoction. In the results of differential gene screening, there were 1 666 differentially expressed genes in the model group as compared with the normal group, and there were 971 differentially expressed genes in the treatment group as compared with the model group. Among them, interleukin-6(IL-6) and NR3C2 genes, which were closely related to the regulation of insulin resis-tance function, were significantly up-regulated between the model group and the normal group, and vascular endothelial growth factor A(VEGFA) genes were significantly down-regulated between the model group and the normal group. However, the expression results of IL-6, NR3C2, and VEGFA genes were adverse between the treatment group and the model group. GO functional enrichment analysis found that the biological process annotation mainly focused on cell synthesis, cycle, and metabolism; cell component annotation mainly focused on organelles and internal components; and molecular function annotation mainly focused on binding molecular functions. KEGG pathway enrichment analysis found that it involved the protein tyrosine kinase 6(PTK6) pathway, CD28-dependent phosphoinositide 3-kinase/protein kinase B(PI3K/AKT) pathway, p53 pathway, etc. Therefore, Huangjing Qianshi Decoction can improve the state of prediabetes, and the mechanism may be related to cell cycle and apoptosis, PI3K/AKT pathway, p53 pathway, and other biological pathways regulated by IL-6, NR3C2, and VEGFA.

Effect of Flavanomarein from Coreopsis tinctoria Ethanol Extract in Small Intestinal Organoids in Insulin-resistant Mice Based on Transcriptome Sequencing / 中国实验方剂学杂志

ObjectiveTo investigate the effects of flavanomarein on the transcriptome of small intestinal organoids in insulin-resistant mice. MethodFirstly， small intestinal organoids of C57BL/6J and db/db mice were established. Ki-67 and E-cadherin expression was determined by immunofluorescence. Small intestinal organoids were divided into the following three groups： C57BL/6J mouse small intestinal organoids as the normal control group， db/db mouse small intestinal organoids as the model group （IR group）， and db/db mouse small intestinal organoids treated with flavanomarein as the administration group （FM group）. Western blot was used to detect the expression of glucagon-like peptide-1（GLP-1） protein on the small intestinal organoids of the three groups. Finally， transcriptome sequencing was performed on samples from the three groups. ResultOn the 6th day of small intestine organoids culture， a cyclic structure was formed around the lumen， and a small intestine organoids culture model was preliminarily established. Immunofluorescence detection showed that ki-67 and E-cadherin were expressed in small intestinal organoids. Western blot results showed that the expression of GLP-1 protein was increased by flavanomarein. In the results of differential expressed gene （DEG） screening， there were 1 862 DEGs in the IR group as compared with the normal control group， and 2 282 DEGs in the FM group as compared with the IR group. Through protein-protein interaction（PPI） network analysis of the DEGs of the two groups， 10 Hub genes， including Nr1i3， Cyp2c44， Ugt2b1， Gsta1， Gstm2， Ptgs1， Gstm4， Cyp2c38， Cyp4a32， and Gpx3， were obtained. These genes were highly expressed in the normal control group， and their expression was reduced in the IR group. After the intervention of flavanomarein， the expression of the above genes was reversed. ConclusionFlavanomarein may play its role in improving insulin resistance by reversing the expression levels of 10 Hub genes， including Nr1i3， Cyp2c44， Ugt2b1， Gsta1， Gstm2， Ptgs1， Gstm4， Cyp2c38， Cyp4a32， and Gpx3.

Comparative analysis of differentially expressed genes for biosynthesis of active ingredients in fruits of different cultivars of Lycium barbarum L. based on transcriptome sequencing / 生物工程学报

To explore the differentially expressed genes (DEGs) related to biosynthesis of active ingredients in wolfberry fruits of different varieties of Lycium barbarum L. and reveal the molecular mechanism of the differences of active ingredients, we utilized Illumina NovaSeq 6000 high-throughput sequencing technology to conduct transcriptome sequencing on the fruits of 'Ningqi No.1' and 'Ningqi No.7' during the green fruit stage, color turning stage and maturity stage. Subsequently, we compared the profiles of related gene expression in the fruits of the two varieties at different development stages. The results showed that a total of 811 818 178 clean reads were obtained, resulting in 121.76 Gb of valid data. There were 2 827, 2 552 and 2 311 DEGs obtained during the green fruit stage, color turning stage and maturity stage of 'Ningqi No. 1' and 'Ningqi No. 7', respectively, among which 2 153, 2 050 and 1 825 genes were annotated in six databases, including gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) and clusters of orthologous groups of proteins (KOG). In GO database, 1 307, 865 and 624 DEGs of green fruit stage, color turning stage and maturity stage were found to be enriched in biological processes, cell components and molecular functions, respectively. In the KEGG database, the DEGs at three developmental stages were mainly concentrated in metabolic pathways, biosynthesis of secondary metabolites and plant-pathogen interaction. In KOG database, 1 775, 1 751 and 1 541 DEGs were annotated at three developmental stages, respectively. Searching the annotated genes against the PubMed database revealed 18, 26 and 24 DEGs related to the synthesis of active ingredients were mined at the green fruit stage, color turning stage and maturity stage, respectively. These genes are involved in carotenoid, flavonoid, terpenoid, alkaloid, vitamin metabolic pathways, etc. Seven DEGs were verified by RT-qPCR, which showed consistent results with transcriptome sequencing. This study provides preliminary evidences for the differences in the content of active ingredients in different Lycium barbarum L. varieties from the transcriptional level. These evidences may facilitate further exploring the key genes for active ingredients biosynthesis in Lycium barbarum L. and analyzing their expression regulation mechanism.

Identification of potential hub genes involved in alcohol use disorder via bioinformatics analysis / 四川精神卫生

BackgroundAlcohol use disorder （AUD） is a type of chronic relapsing brain disorder. Genetic factors play an important role in the pathogenesis of AUD. And screening for molecular markers of AUD is of great significance for further elucidating the pathogenesis of the disease， discovering novel therapeutic targets and preventing relapse. ObjectiveTo explore relevant hub genes and potential signal pathways associated with the development of AUD through bioinformatics analysis， and to provide a new direction for the prevention and treatment of AUD. MethodsThe GSE161986 dataset was acquired from the Gene Expression Omnibus （GEO） database. The limma package in R was utilized to identify differentially expressed genes （DEGs）. Gene set enrichment analysis （GSEA） was carried out using the Database for Annotation， Visualization and Integrated Discovery （DAVID）. A protein–protein interaction （PPI） network of DEGs was assessed using the STRING database and visualized by Cytoscape software. Finally， hub genes were validated in GSE44456 dataset. ResultsA total of 114 DEGs were identified. GSEA revealed that these genes were mainly involved in the regulation of signal transduction， protein binding， membrane trafficking and MAPK signaling pathway. PPI network and validation study indicated that GAD1， TIMP1 and CD44 were potential hub genes involved in AUD. ConclusionAberrant expression of GAD1 and TIMP1 as well as MAPK signaling pathway may play a key role in the pathogenesis of AUD， and may serve as potential molecular targets for the diagnosis and treatment of AUD. ［Funded by "Flying Project" of Shanghai Mental Health Center （number， 2022-FX-01）］

Expression analysis of transcription factors in sugarcane during cold stress / Análise de expressão de fatores de transcrição em cana-de-açúcar sob estresse por frio

Abstract Transcription factors (TF) are a wide class of genes in plants, and these can regulate the expression of other genes in response to various environmental stresses (biotic and abiotic). In the current study, transcription factor activity in sugarcane was examined during cold stress. Initially, RNA transcript reads of two sugarcane cultivars (ROC22 and GT08-1108) under cold stress were downloaded from SRA NCBI database. The reads were aligned into a reference genome and the differential expression analyses were performed with the R/Bioconductor edgeR package. Based on our analyses in the ROC22 cultivar, 963 TF genes were significantly upregulated under cold stress among a total of 5649 upregulated genes, while 293 TF genes were downregulated among a total of 3,289 downregulated genes. In the GT08-1108 cultivar, 974 TF genes were identified among 5,649 upregulated genes and 283 TF genes were found among 3,289 downregulated genes. Most transcription factors were annotated with GO categories related to protein binding, transcription factor binding, DNA-sequence-specific binding, transcription factor complex, transcription factor activity in RNA polymerase II, the activity of nucleic acid binding transcription factor, transcription corepressor activity, sequence-specific regulatory region, the activity of transcription factor of RNA polymerase II, transcription factor cofactor activity, transcription factor activity from plastid promoter, transcription factor activity from RNA polymerase I promoter, polymerase II and RNA polymerase III. The findings of above results will help to identify differentially expressed transcription factors during cold stress. It also provides a comprehensive analysis of the regulation of the transcription activity of many genes. Therefore, this study provides the molecular basis for improving cold tolerance in sugarcane and other economically important grasses.

Resumo Fatores de transcrição (FT) são uma ampla classe de genes em plantas e podem regular a expressão de outros genes em resposta a vários estresses ambientais (estresses bióticos e abióticos). No presente estudo, a atividade do fator de transcrição na cana-de-açúcar foi examinada durante o estresse pelo frio. Inicialmente, as leituras de transcrição de RNA de duas cultivares de cana-de-açúcar (ROC22 e GT08-1108) sob estresse frio foram baixadas do banco de dados SRA NCBI. As leituras foram alinhadas em um genoma de referência e as análises de expressão diferencial foram realizadas com o pacote R / Bioconductor edgeR. Com base em nossas análises no cultivar ROC22, 963 genes TF foram significativamente regulados positivamente sob estresse pelo frio entre um total de 5.649 genes regulados positivamente, enquanto 293 genes TF foram regulados negativamente entre um total de 3.289 genes regulados negativamente. No cultivar GT08-1108, 974 genes TF foram identificados entre 5.649 genes regulados positivamente e 283 genes TF foram encontrados entre 3.289 genes regulados negativamente. Os fatores de transcrição, em sua maioria, foram anotados com categorias GO relacionadas à ligação de proteína, ligação de fator de transcrição, ligação específica de sequência de DNA, complexo de fator de transcrição, atividade de fator de transcrição em RNA polimerase II, atividade de fator de transcrição de ligação de ácido nucleico, atividade de corepressor de transcrição, sequência específica da região reguladora, atividade do fator de transcrição da RNA polimerase II, atividade do cofator do fator de transcrição, atividade do fator de transcrição do promotor do plastídio, atividade do fator de transcrição do promotor da RNA polimerase I, polimerase II e RNA polimerase III. As descobertas dos resultados acima ajudarão a identificar fatores de transcrição expressos diferencialmente durante o estresse pelo frio. Ele também fornece uma análise abrangente da regulação da atividade de transcrição de muitos genes. Portanto, este estudo fornece base molecular para melhorar a tolerância ao frio em cana-de-açúcar e outras gramíneas economicamente importantes.

Mechanism of Huashi Baidu Prescription in Treating Influenza Viral Pneumonia Based on Transcriptome / 中国实验方剂学杂志

ObjectiveTo clarify the therapeutic effect of Huashi Baidu prescription on pneumonia in mice caused by influenza A （H1N1） virus and explore its mechanism based on the transcriptome. MethodA mouse influenza viral pneumonia model was built by intranasal infection with influenza A virus， and mice were continuously administered the drug for five days， so as to investigate the general condition， lung index， viral load， pathological morphology of lung tissue， survival time， and prolongation rate of survival time of mice and clarify the therapeutic effect of Huashi Baidu prescription on influenza viral pneumonia. Transcriptome technology was used to detect the differentially expressed genes in the lung tissue of mice in the model group and the normal group， as well as the Huashi Baidu prescription group and the model group， and the potential core target of the Huashi Baidu prescription for the treatment of influenza viral pneumonia was screened. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to verify the effect of Huashi Baidu prescription on the mRNA expression level of core target genes. ResultCompared with the normal group， the lung index and viral load in the lung tissue of the model group were significantly increased （P<0.05， P<0.01）. Compared with the model group， the high-dose group of Huashi Baidu prescription significantly prolonged the survival time of mice infected with influenza A virus （P<0.05） and significantly reduced the lung index value of mice （P<0.05） and the viral load of lung tissue. The high-dose， medium-dose， and low-dose groups of Huashi Baidu prescription could significantly reduce lung tissue inflammation， blood stasis， swelling， and other pathological changes in mice （P<0.05， P<0.01）. Transcriptome analysis of lung tissue showed that core genes were mainly enriched in the nuclear transcription factor-κB （NF-κB） signaling pathway， interleukin-17 （IL-17） signaling pathway， cytokine-cytokine receptor interaction， and other pathways after the intervention of Huashi Baidu prescription. TRAF6， NFKBIA， CCL2， CCL7， and CXCL2 were the top five node genes with combined score values. Real-time PCR validation showed that Huashi Baidu prescription significantly downregulated the mRNA expression of key genes TRAF6 and NFKBIA in the NF-κB signaling pathway， as well as chemokines CCL2， CCL7， and CXCL2 （P<0.05， P<0.01）. ConclusionHuashi Baidu prescription has a therapeutic effect on influenza viral pneumonia， possibly by inhibiting the expression of key nodes TRAF6 and NFKBIA in the NF-κB signaling pathway and that of chemokines CCL2， CCL7， and CXCL2， reducing the recruitment of inflammatory cells and viral load， and exerting anti-influenza viral pneumonia effects.

Progress in adverse effects of sleep deprivation on body fertility / 中国药理学与毒理学杂志

Sleep is essential for the maintenance of human normal functions.Nowadays,the occurrence of active sleep deprivation(ASD)or passive sleep depriva-tion(PSD)is becoming more and more common due to the inability of the body adapting to the rapid changes in the internal and external environment.SD is not only an action,a brief process or a result,but also a directly or indirectly sustained state,which is associated to sleep time,circadian rhythm or sleep quality.SD can lead to numerous adverse effects on the body,such as sleep-related acute and chronic diseases.Long-term SD increases the risk of neurological and cardiovascular dis-eases as well as immune system dysfunction.In addi-tion,SD may affect the reproductive health of the body,giving rise to a series of potential fertility problems.In recent years,the correlation research and mechanism between SD and the related diseases have become a focus of scholars' attention.Numerous lines of evidence suggest that pathological sleep,such as insomnia and sleep apnea syndrome,is associated with impaired repro-ductive function.Disruptions in the circadian rhythm can also lead to impaired hypothalamic-pituitary-gonadal(HPG)axis function and thereby interfere with the repro-ductive process.Our research team has demonstrated that SD significantly affects the fertility of male and female rats and has adverse effects on reproduction.By new generation sequencing(NGS)and RT-PCR verifica-tion,we have identified differently expressed genes that are involved in mediating the effect of SD on fertility.However,the mechanisms and biological macromolecules regulated by SD are worthy of being further explored.This paper provides a brief review of SD research and then focuses on the adverse impact of SD on fertility,conducting a literature review to sort out the ideas and pro-vide references for research in this field.

Search for potential target genes in dexamethasone-induced open-angle glaucoma by bioinformatics / 中华实验眼科杂志

Objective:To predict potential target genes in dexamethasone-induced open-angle glaucoma via bioinformatics technology.Methods:The GEO datasets GSE16643, GSE37474, and GSE124114 were used to analyze the differentially expressed genes by GEO2R.Gene Set Enrichment Analysis (GSEA) was performed on the differentially expressed genes between GSE37474 and GSE124114.Intersection of the three datasets were displayed by Venn diagram.The annotation and enrichment analysis of the intersection genes were performed through Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and then were compared with normal tissue in GTEx Portal database.The corresponding protein interaction network was obtained by STRING.Finally, the candidate genes were searched for their transcription factors in UCSC and JASPAR.Primary human trabecular cells were divided into dexamethasone group and control group, treated with 2 ml 500 nmol/L dexamethasone and the same amount of ethanol, respectively.The expression of BDKRB1 and TAGLN in trabecular cells was detected by Western blot.Results:Differential genes between GSE37474 and GSE124114 datasets enriched in complement and coagulation cascade by GSEA.There were 89 intersecting genes of the three datasets.These genes mainly regulated the formation of extracellular matrix by GO analysis.The gene with the highest enrichment score and collagen-containing extracellular matrix was found to be associated with fibroblasts in GTEx Portal database.ACTA2, MYL9, TAGLN, and LMOD1 were closely related in STRING protein-protein interaction network.Transcription factor SP1 in UCSC and JASPAR according to related genes, BDKRB1, NID1, MFGE8 and TAGLN.The relative expression levels of BDKRB1 and TAGLN proteins were 1.32±0.14 and 0.44±0.09 in dexamethasone group, respectively, which were significantly higher than 1.00±0.00 and 0.20±0.10 in the control group, respectively ( t=-3.61, 2.89; both at P<0.05). Conclusions:Bioinformatics analysis showed that transcription factor SP1 may play a role in human trabecular meshwork cells to myofibroblasts transition after dexamethasone treatment.

Integrated bioinformatics approach reveals methylation-regulated differentially expressed genes in obesity

ABSTRACT Objective: To identify DNA methylation and gene expression profiles involved in obesity by implementing an integrated bioinformatics approach. Materials and methods: Gene expression (GSE94752, GSE55200, and GSE48964) and DNA methylation (GSE67024 and GSE111632) datasets were obtained from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in subcutaneous adipose tissue of patients with obesity were identified using GEO2R. Methylation-regulated DEGs (MeDEGs) were identified by overlapping DEGs and DMGs. The protein-protein interaction (PPI) network was constructed with the STRING database and analyzed using Cytoscape. Functional modules and hub-bottleneck genes were identified by using MCODE and CytoHubba plugins. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG pathways. To prioritize and identify candidate genes for obesity, MeDEGs were compared with obesity-related genes available at the DisGeNET database. Results: A total of 54 MeDEGs were identified after overlapping the lists of significant 274 DEGs and 11,556 DMGs. Of these, 25 were hypermethylated-low expression genes and 29 were hypomethylated-high expression genes. The PPI network showed three hub-bottleneck genes (PTGS2, TNFAIP3, and FBXL20) and one functional module. The 54 MeDEGs were mainly involved in the regulation of fibroblast growth factor production, the molecular function of arachidonic acid, and ubiquitin-protein transferase activity. Data collected from DisGeNET showed that 11 of the 54 MeDEGs were involved in obesity. Conclusion: This study identifies new MeDEGs involved in obesity and assessed their related pathways and functions. These results data may provide a deeper understanding of methylation-mediated regulatory mechanisms of obesity.

Identification of hub genes in airway epithelial cells of asthma patients by WGCNA and PPI network

Bronchial asthma is a common chronic disease of airway inflammation, high mucus secretion and airway hyper responsiveness. The pathogenetic mechanisms of asthma remain unclear. In this study, we aimed at identifying genes playing an import role in disease-related pathways in airway epithelial cells of asthma patients. Microarray data GSE41861 of asthma airway epithelial cells was used to screen differentially expressed genes (DEGs) through GEO2R analysis. The weighted gene co-expression network analysis (WGCNA) was performed to identify gene co-expression network modules in bronchial asthma. The DAVID database was then used to perform functional and pathway enrichment analysis of these DEGs. In addition, we have conducted protein-protein interaction (PPI) network of DEGs by STRING, and eventually found key genes and significant modules. A total of 315 DEGs (111 up-regulated and 204 down-regulated) were identified between severe asthma and healthy individual, which were mainly involved in pathways of cilium assembly, cilium morphogenesis, axon guidance, positive regulation of fat cell differentiation, and positive regulation of cell substrate adhesion. A total of 60 genes in the black module and green module were considered to be correlated with the severity of asthma. Combining PPI network, several key genes were identified, such as BP2RY14, PTGS1, SLC18A2, SIGLEC6, RGS13, CPA3, and HPGDS. Our findings revealed several genes that may be involved in the process of development of bronchial asthma and potentially be candidate targets for diagnosis or therapy of bronchial asthma.

Prediction of protein-protein interaction networks and druggable genes associated with parkinson’s disease-Supplementary data

Parkinson’s disease (PD) affects about 2-3% of the global population over 65 years of age and hence, it is the second most common neurodegenerative disorder in the world. This study explored the key genes and miRNA involved in PD. Microarray dataset (accession number GSE19587) comprising of two regions of medulla: dorsal motor nucleus of vagus (DMNV) and inferior olivary nucleus (ION) was downloaded from Gene Expression Omnibus (GEO) database. A total of 697 DEGs from ION (605 up-regulated genes and 92 down-regulated genes) and 663 DEGs from DMNV (638 up-regulated genes and 25 down-regulated genes) were screened. These DEGs were found to be enriched in 46 (DMNV) and 24 (ION) pathways common in DAVID and Comparative Toxicogenomics Database. In PPI network analysis, IGF1 and CD44 were identified as hub genes in DMNV whereas for ION, the hub genes identified were CSF2 and CD44. In TF-miRNA-target gene networks, an aggregate of 11 transcription factors and 46 miRNA were observed to influence the target genes. In drug-gene interaction studies, CYP3A5 and ESR1 had higher connective degrees and hence, they might be novel druggable targets for Parkinson’s disease.

Prediction of protein-protein interaction networks and druggable genes associated with parkinson’s disease

Parkinson’s disease (PD) affects about 2-3% of the global population over 65 years of age and hence, it is the second most common neurodegenerative disorder in the world. This study explored the key genes and miRNA involved in PD. Microarray dataset (accession number GSE19587) comprising of two regions of medulla: dorsal motor nucleus of vagus (DMNV) and inferior olivary nucleus (ION) was downloaded from Gene Expression Omnibus (GEO) database. A total of 697 DEGs from ION (605 up-regulated genes and 92 down-regulated genes) and 663 DEGs from DMNV (638 up-regulated genes and 25 down-regulated genes) were screened. These DEGs were found to be enriched in 46 (DMNV) and 24 (ION) pathways common in DAVID and Comparative Toxicogenomics Database. In PPI network analysis, IGF1 and CD44 were identified as hub genes in DMNV whereas for ION, the hub genes identified were CSF2 and CD44. In TF-miRNA-target gene networks, an aggregate of 11 transcription factors and 46 miRNA were observed to influence the target genes. In drug-gene interaction studies, CYP3A5 and ESR1 had higher connective degrees and hence, they might be novel druggable targets for Parkinson’s disease.

Construction of a diagnostic model for oral squamous cell carcinoma based on principal component analysis and differentially expressed genes / 口腔疾病防治

Objective@#To explore the value of an oral squamous cell carcinoma (OSCC) diagnostic model constructed by using principal component analysis (PCA) to analyze a database of differentially expressed genes in OSCC and to provide a reference for clinical diagnosis and treatment.@*Methods@# RNA-seq expression data of OSCC and normal control samples were obtained from The Cancer Genome Atlas (TCGA) database, and then, normalized and differentially expressed genes (DEGs) were identified by R software. DEGs were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to identify their main biological characteristics. 70% of DEGs expression data in RNA-seq were randomly selected as the training set and 30% were selected as the test set. Then, the PCA method was applied to analyze the training set data and extract the principal components (PCs) related to the diagnosis of OSCC in order to construct a PCA model. Then, the receiver operating characteristic (ROC) curves of PCA models in the training set and the test set were respectively drawn, and the area under curve (AUC) was calculated to evaluate the accuracy of the PCA model in the diagnosis of OSCC.@*Results@#RNA-seq expression data of OSCC and normal control samples obtained from TCGA database included 330 samples and 32 samples, respectively. Using false discovery rate (FDR) <0.001 and |log2 fold change| (|log2FC|) >4 as the thresholds, a total of 159 downregulated and 248 upregulated DEGs were identified, which were mainly enriched in cellular components such as intermediate fiber and melanosomal membrane, pigment and salivation-related biological processes and mainly involved in salivary secretion and tyrosine metabolism pathways (P.adjust<0.05 and Q<0.05). The DEGs were proposed as tumor markers for OSCC, and PCA analysis of the training set showed that the cumulative ratio of variance of PC1, PC2 and PC3: [including submaxillary gland androgen regulated protein 3B (SMR3B), proline rich 27 (PRR27), histatin 3 (HTN3), statherin (STATH), cystatin D (CST5), BPI fold containing family A member 2 (BPIFA2), proline rich protein Hae Ⅲ subfamily 2 (PRH2), keratin 35(KRT35), histatin 1 (HTN1), amylase alpha 1B (AMY1B)] were 0.873, 0.100 and 0.023, respectively, and the total weight of the three was 0.996. The PCA diagnostic model of OSCC was further constructed by combining the eigenvectors of the above three components. The ROC curves of the training set and test set showed that the AUC values of the PCA model were 0.852 and 0.844, respectively, which were higher than those of other single genes.@*Conclusion @#The OSCC diagnostic model based on the expression levels of SMR3B, PRR27, HTN3, STATH, CST5, BPIFA2, PRH2, KRT35, HTN1 and AMY1B constructed with the PCA method and DEGs has a high diagnostic advantage. This study provides a theoretical basis for the early genetic diagnosis of OSCC and the application of the PCA model in clinical diagnosis.

Advances in research on biological information of ophthalmology disease / 国际眼科杂志(Guoji Yanke Zazhi)

Bioinformatics, an emerging discipline focusing on genomics and proteomics, is both comprehensive and interdisciplinary of biology, computer science, information engineering and statistics. In the ophthalmic biological genetic research, cornea, lens, aqueous humor, vitreous and retina are ideal bioinformatic research objects in the field of ophthalmic biological genes because of their abundance in biological information. Genomics testing techniques have the characteristics of high efficiency and accuracy, which helps us to screen the differentially expressed genes related to ophthalmic tumors and genetic diseases; Proteomics can help us analyze the protein expression profile and functional changes caused by the high and low gene expression in intraocular fluid or isolated cells in diseases states, revealing the mechanism of disease. This paper mainly summarizes the application of bioinformatics in ophthalmic diseases, and preliminarily envisage its impact on the current treatment, the existing problems and the development trend in the future.

Differentially expressed genes in chronic periodontitis and the correlation with disease severity / 国际生物医学工程杂志

Objective:To study the differentially expressed genes in chronic periodontitis (CP) and to explore the correlation with disease severity.Methods:Gene expression profile data associated with CP were screened in the Gene Expression Omnibus (GEO) database and analyzed with GEO2R online software to create volcano maps. Kyoto Encyclopedia of Genes and Genomes (KEEG) and Gene Ontology (GO) analyses were performed on the screened CP-associated differentially expressed genes to predict their possible functions and signaling pathways. The protein-protein interaction database (STRING) was used to analyze the interaction relationships between the encoded proteins of the screened CP-related differentially expressed genes. Cytohubba software was used to identify key genes in the signaling pathway. One120 CP patients and 40 healthy controls were selected. The screened CP-related genes were validated by the real-time polymerase chain reaction (q-PCR) method.Results:A total of 1 151 CP differentially expressed genes that met the requirements were screened. These genes were mainly enriched in the GO pathway for positive regulation of granulocyte differentiation, helper T-cell differentiation, leukocyte aggregation, regulation of acute inflammatory response, chemokine-mediated and endoplasmic reticulum unfolded protein response, as well as in the KEGG pathway for NFB pathway, chemokine pathway, cytokine receptor interaction, leukocyte transendothelial migration pathway, B-cell receptor pathway, Toll-like receptor pathway, etc. The protein-protein interaction network was constructed using the screened CP-related differentially expressed genes, which included 78 nodes and 496 links, with a mean aggregation coefficient and mean connectivity of 0.69 and 12.7, respectively. Cytohubba analysis showed that Sell was a key gene in the signaling pathway, and its relative expression levels in the gingival fluids of the three CP groups with different degrees(1.14±0.46, 0.86±0.41, 0.52±0.46) was significantly lower than that of the control group (1.50±0.65) (all P<0.05). The area under the ROC curve (AUC) of subjects diagnosed with CP using Sell expression levels in gingival fluid was 0.79 (95% CI: 0.71 to 0.86). The AUC values were greater than 0.65 at 95% CI when Sell was used as a biological marker to evaluate the severity of CP. Conclusions:CP-related differentially expressed genes are mainly enriched in the number of pathways associated with the inflammatory response of periodontitis. The expression levels of Sell genes were significantly reduced in the gingival sulcus fluid of CP patients and correlated with the severity of the disease. The Sell genes are expected to be a biomarker for CP grading.