Identification of core pathogenic genes and pathways in elderly osteoporosis based on bioinformatics analysis / 中华预防医学杂志

Objective: Using bioinformatics methods to analyze the core pathogenic genes and related pathways in elderly osteoporosis. Methods: From November 2020 and August 2021, eight elderly osteoporosis patients who received treatment and five healthy participants who underwent physical examinations in Beijing Jishuitan Hospital were selected as subjects. The expression level of RNA in the peripheral blood of eight elderly osteoporosis patients and five healthy participants was collected for high-throughput transcriptome sequencing and analysis. The gene ontology (GO) analysis Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for the differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING website and Cytoscape software, and the most significant modules and hub genes were screened out. Results: Among the eight elderly osteoporosis patients, there were seven females and one male, with an average age of 72.4 years (SD=4.2). Among the five healthy participants, there were four females and one male, with an average age of 68.2 years (SD=5.7). A total of 1 635 DEGs (847 up-regulated and 788 down-regulated) were identified. GO analysis revealed that the molecular functions of DEGs were mainly enriched in structural constituents of the ribosome, protein dimerization activity, and cellular components were mainly enriched in the nucleosome, DNA packaging complex, cytosolic part, protein-DNA complex and the cytosolic ribosome. KEGG pathway analysis showed that DEGs were mainly enriched in systemic lupus erythematosus and ribosome. Gene UBA52, UBB, RPS27A, RPS15, RPS12, RPL13A, RPL23A, RPL10A, RPS25 and RPS6 were selected and seven of them could encode ribosome proteins. Conclusion: The pathogenesis of elderly osteoporosis may be associated with ribosome-related genes and pathways.

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.

Analysis of Significant Genes and Pathways in Esophageal Cancer Based on Gene Expression Omnibus Database / 中国医学科学杂志(英文版)

Objective To screen antigen targets for immunotherapy by analyzing over-expressed genes, and to identify significant pathways and molecular mechanisms in esophageal cancer by using bioinformatic methods such as enrichment analysis, protein-protein interaction (PPI) network, and survival analysis based on the Gene Expression Omnibus (GEO) database.Methods By screening with highly expressed genes, we mainly analyzed proteins MUC13 and EPCAM with transmembrane domain and antigen epitope from TMHMM and IEDB websites. Significant genes and pathways associated with the pathogenesis of esophageal cancer were identified using enrichment analysis, PPI network, and survival analysis. Several software and platforms including Prism 8, R language, Cytoscape, DAVID, STRING, and GEPIA platform were used in the search and/or figure creation.Results Genes MUC13 and EPCAM were over-expressed with several antigen epitopes in esophageal squamous cell carcinoma (ESCC) tissue. Enrichment analysis revealed that the process of keratinization was focused and a series of genes were related with the development of esophageal cancer. Four genes including ALDH3A1, C2, SLC6A1,and ZBTB7C were screened with significant P value of survival curve.Conclusions Genes MUC13 and EPCAM may be promising antigen targets or biomarkers for esophageal cancer. Keratinization may greatly impact the pathogenesis of esophageal cancer. Genes ALDH3A1, C2, SLC6A1,and ZBTB7C may play important roles in the development of esophageal cancer.

Screening of housekeeping genes in Gelsemium elegans and expression patterns of genes involved in its alkaloid biosynthesis / 生物工程学报

Gelsemium elegans is a traditional Chinese herb of medicinal importance, with indole terpene alkaloids as its main active components. To study the expression of the most suitable housekeeping reference genes in G. elegans, the root bark, stem segments, leaves and inflorescences of four different parts of G. elegans were used as materials in this study. The expression stability of 10 candidate housekeeping reference genes (18S, GAPDH, Actin, TUA, TUB, SAND, EF-1α, UBC, UBQ, and cdc25) was assessed through real-time fluorescence quantitative PCR, GeNorm, NormFinder, BestKeeper, ΔCT, and RefFinder. The results showed that EF-1α was stably expressed in all four parts of G. elegans and was the most suitable housekeeping gene. Based on the coexpression pattern of genome, full-length transcriptome and metabolome, the key candidate targets of 18 related genes (AS, AnPRT, PRAI, IGPS, TSA, TSB, TDC, GES, G8H, 8-HGO, IS, 7-DLS, 7-DLGT, 7-DLH, LAMT, SLS, STR, and SGD) involved in the Gelsemium alkaloid biosynthesis were obtained. The expression of 18 related enzyme genes were analyzed by qRT-PCR using the housekeeping gene EF-1α as a reference. The results showed that these genes' expression and gelsenicine content trends were correlated and were likely to be involved in the biosynthesis of the Gelsemium alkaloid, gelsenicine.

New strategies for the treatment of carcinoma of unknown primary / 中华肿瘤杂志

Carcinoma of unknown primary (CUP) is a kind of metastatic tumor whose primary origin cannot be identified after adequate examination and evaluation. The main treatment modality of CUP is empiric chemotherapy, and the median overall survival time is less than 1 year. Compared with immunohistochemistry, novel method based on gene expression profiling have improved the sensitivity and specificity of CUP detection, but its guiding value for treatment is still controversial. The approval of immune checkpoint inhibitors and pan-cancer antitumor agents has improved the prognosis of patients with CUP, and targeted therapy and immunotherapy based on specific molecular characteristics are the main directions of future research. Given the high heterogeneity and unique clinicopathological characteristics of CUP, "basket trial" is more suitable for clinical trial design in CUP.

Gene Expression Profiles at Different Time Points after Acute Myocardial Infarction in Mice / 法医学杂志

OBJECTIVES@#To explore the mRNA differential expressions and the sequential change pattern in acute myocardial infarction (AMI) mice.@*METHODS@#The AMI mice relevant dataset GSE4648 was downloaded from Gene Expression Omnibus (GEO). In the dataset, 6 left ventricular myocardial tissue samples were selected at 0.25, 1, 4, 12, 24 and 48 h after operation in AMI group and sham control group, and 6 left ventricular myocardial tissue samples were selected in blank control group, a total of 78 samples were analyzed. Differentially expressed genes (DEGs) were analyzed by R/Bioconductor package limma, functional pathway enrichment analysis was performed by clusterProfiler, protein-protein interaction (PPI) network was constructed by STRING database and Cytoscape software, the key genes were identified by Degree topological algorithm, cluster sequential changes on DEGs were analyzed by Mfuzz.@*RESULTS@#A total of 1 320 DEGs were associated with the development of AMI. Functional enrichment results included cellular catabolic process, regulation of inflammatory response, development of muscle system and vasculature system, cell adhesion and signaling pathways mainly enriched in mitogen-activated protein kinase (MAPK) signaling pathway. The key genes of AMI included MYL7, TSC22D2, HSPA1A, BTG2, NR4A1, RYR2 were up-regulated or down-regulated at 0.25-48 h after the occurrence of AMI.@*CONCLUSIONS@#The functional signaling pathway of DEGs and the sequential expression of key genes in AMI may provide a reference for the forensic identification of AMI.

Bioinformatics screening and analysis of key differentially expressed genes characteristics in nonalcoholic fatty liver disease / 中华肝脏病杂志

Objective: To screen and analyze the key differentially expressed genes characteristics in nonalcoholic fatty liver disease (NAFLD) with bioinformatics method. Methods: NAFLD-related expression matrix GSE89632 was downloaded from the GEO database. Limma package was used to screen differentially expressed genes (DEGs) in healthy, steatosis (SS), and nonalcoholic steatohepatitis (NASH) samples. WGCNA was used to analyze the output gene module. The intersection of module genes and differential genes was used to determine the differential genes characteristic, and then GO function and KEGG signaling pathway enrichment analysis were performed. The protein-protein interaction network (PPI) was constructed using the online website STRING and Cytoscape software, and the key (Hub) genes were screened. Finally, R software was used to analyze the receiver operating characteristic curve (ROC) of the Hub gene. Results: 92 differentially expressed genes characteristic were obtained through screening, which were mainly enriched in inflammatory response-related functions of "lipopolysaccharide response and molecular response of bacterial origin", as well as cancer signaling pathways of "proteoglycan in cancer" and "T-cell leukemia virus infection-related". 10 hub genes (FOS, CXCL8, SERPINE1, CYR61, THBS1, FOSL1, CCL2, MYC, SOCS3 and ATF3) had good diagnostic value. Conclusion: The differentially expressed hub genes among the 10 NAFLD disease-related characteristics obtained with bioinformatics analysis may become a diagnostic and prognostic marker and potential therapeutic target for NAFLD. However, further basic and clinical studies are needed to validate.

Bioinformatics analysis of differently expressed genes in osteoblastic sarcoma and screening of key genes / 中华肿瘤杂志

Objective: To screen the different expressed genes between osteosarcoma and normal osteoblasts, and find the key genes for the occurrence and development of osteosarcoma. Methods: The gene expression dataset GSE33382 of normal osteoblasts and osteosarcoma was obtained from Gene Expression Omnibus (GEO) database. The different expressed genes between normal osteoblasts and osteosarcoma were screened by limma package of R language, and the different expressed genes were analyzed by Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. The protein interaction network was constructed by the String database, and the network modules in the interaction network were screened by the molecular complex detection (MCODE) plug-in of Cytoscape software. The different expressed genes contained in the first three main modules screened by MCODE were analyzed by gene ontology (GO) using the BiNGO module of Cytoscape software. The MCC algorithm was used to screen the top 10 key genes in the protein interaction network. The gene expression and survival dataset GSE39055 of osteosarcoma was obtained from GEO database, and the survival analysis was performed by Kaplan-Meier method. The data of 48 patients with osteosarcoma treated in the First Affiliated Hospital of Fujian Medical University from January 2005 to December 2015 were selected for verification. The expression of STC2 protein in osteosarcoma was detected by immunohistochemical method, and the survival analysis was carried out combined with the clinical data of the patients. Results: A total of 874 different expressed genes were identified from GSE33382 dataset, including 402 down-regulated genes and 472 up-regulated genes. KEGG enrichment analysis showed that different expressed genes were mainly related to p53 signal pathway, glutathione metabolism, extracellular matrix receptor interaction, cell adhesion molecules, folate tolerance, and cell senescence. The top 10 key genes in the interaction network were GAS6, IL6, RCN1, MXRA8, STC2, EVA1A, PNPLA2, CYR61, SPARCL1 and FSTL3. STC2 was related to the survival rate of patients with osteosarcoma (P<0.05). The results showed that the expression of STC2 protein was related to tumor size and Enneking stage in 48 cases of osteosarcoma. The median survival time of 25 cases with STC2 high expression was 21.4 months, and that of 23 cases with STC2 low expression was 65.4 months. The survival rate of patients with high expression of STC2 was lower than that of patients with low expression of STC2 (P<0.05). Conclusions: Bioinformatics analysis can effectively screen the different expressed genes between osteosarcoma and normal osteoblasts. STC2 is one of the important predictors for the prognosis of osteosarcoma.

Investigation on the differentially expressed circular RNAs in myocardium of mice with diabetic cardiomyopathy / 中华心血管病杂志

Objective: To identify the differentially expressed circular RNA (circRNA) in the myocardium of diabetic cardiomyopathy (DCM) mice, and analyze their possible biological functions and related regulatory network. Methods: C57BL/6 mice, aged 8 weeks, and weighing were 21-27 g. Eight mice were selected as the control group and 15 mice were selected as the experimental group. The diabetic mice model was established by intraperitoneal injection of streptozotocin in the experimental group. One week after injection, the fasting blood glucose level of mice was measured, and 12 diabetic mice were included in the final experimental group. All mice were fed for 12 weeks under the same laboratory conditions. The cardiac structure and function were detected by echocardiography. Diabetic mice with the left ventricular ejection fraction less than 60% and the E/A less than 1.6 were selected as DCM group (n=3). Mice in DCM group and control group were then sacrificed under deep anesthesia. RNA was extracted from myocardial tissue. High-throughput RNA sequencing technology was used to sequence and identify the RNA in the myocardial tissue of DCM group and normal control group, and the difference was analyzed by DeSeq2. The analysis results were verified at the tissue level by RT-qPCR, and the differential circRNA were analyzed by GO and KEGG pathway analysis. The differentially expressed circRNA-microRNA(miRNA) interaction was predicted by the miRNA target gene prediction software. Results: A total of 63 differentially expressed circRNAs were found in the myocardium of DCM mice. The results of RT-qPCR showed that the tissue level expression of 8 differentially expressed circRNAs was consistent with the sequencing results, of which 7 were up-regulated and 1 was down-regulated. KEGG pathway analysis showed that the up-regulated circRNAs was mainly related to AMPK signal pathway and intercellular adhesion junction pathway, and the down-regulated circRNA was mainly related to cardiomyopathy. Go analysis showed that the up-regulated circRNA was mainly related to the binding process of ions, proteins, kinases and other factors in terms of molecular function, and was involved in regulating the intracellular structure, especially the composition of organelles in terms of cell components. The functional analysis of molecular function and cell components showed that the up-regulated circRNA were related to the cell component origin, recruitment and tissue, and thus participated in the regulation of cell biological process. The down regulated circRNA was related to catalytic activity in terms of molecular function, protein kinase binding process, transferase and calmodulin activity, and was closely related to the components of contractile fibers and the composition of myofibrils. These differentially expressed circRNAs were also related to biological processes such as lysine peptide modification, sarcomere composition, myofibril assembly, morphological development of myocardial tissue, myocardial hypertrophy and so on. Conclusions: In this study, we detected the novel differentially expressed circRNAs in the myocardium of DCM mice, and bioinformatics analysis confirmed that these circRNAs are related to oxidative stress, fibrosis and death of cardiomyocytes, and finally participate in the pathophysiological process of DCM.

Screening and identification of key genes ATP1B3 and ENAH in the progression of hepatocellular carcinoma: based on data mining and clinical validation / 南方医科大学学报

OBJECTIVE@#To explore the marker genes correlated with the prognosis, progression and clinical diagnosis of hepatocellular carcinoma (HCC) based on bioinformatics methods.@*METHODS@#The TCGA-LIHC, GSE84432, GSE143233 and GSE63898 datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed. The differentially expressed genes (DEGs) shared by different disease types were obtained using GEO2R and edge R packages, and Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) enrichment analyses of the DEGs were performed. The expression levels of these DEGs in normal and cancerous tissues were verified in TCGA-LIHC to identify the upregulated genes in HCC. Survival analysis, receiver-operating characteristic (ROC) curve analysis, and correlation analysis between the key genes and the clinical features of the patients were carried out using the R language. The differential expressions of 15 key genes were verified in clinical samples of HCC and adjacent tissues using RT-qPCR.@*RESULTS@#A total of 118 common DEGs were obtained in the database, and among them two genes, namely ATPase Na +/K + transport subunit beta 3 (ATP1B3) and actin regulator (ENAH), showed increased expressions with disease progression. Survival analysis combined with the TCGA-LIHC dataset suggested that high expressions of ATP1B3 and ENAH were both significantly correlated with a poor prognosis of HCC patients (P < 0.05), and their AUC values were 0.821 and 0.933, respectively. A high expression of ATP1B3 was correlated with T stage, pathological stage and pathological grade of the tumors (P < 0.05), while that of ENAH was associated only with an advanced tumor grade (P < 0.05). The results of RT-qPCR showed that ATP1B3 and ENAH were both significantly upregulated in clinical HCC tissues (P < 0.05).@*CONCLUSION@#ATPIB3 and ENAH are both upregulated in HCC, and their high expressions may serve as biomarkers of progression of liver diseases and a poor prognosis of HCC.

Screening of differentially expressed genes for colorectal cancer and prediction of potential traditional Chinese medicine: based on bioinformatics / 中国中药杂志

This study screened and analyzed the differentially expressed genes(DEGs) between colorectal cancer(CRC) tissues and normal tissues with bioinformatics techniques to predict biomarkers and Chinese medicinals for the diagnosis and treatment of CRC. The microarray data sets GSE21815, GSE106582, and GSE41657 were downloaded from the Gene Expression Omnibus(GEO), and the DEGs were screened by GEO2 R, followed by the Gene Ontology(GO) tern enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis of the DEGs based on DAVID. The protein-protein interaction network was constructed by STRING, and MCODE and Cytohubba plug-ins were used to screen the significant modules and hub genes in the network. UCSC, cBioPortal, and Oncomine were employed for hierarchical clustering, survival analysis, Oncomine analysis, and correlation analysis of clinical data. Coremine Medical was applied to predict the Chinese medicinals acting on hub genes. A total of 284 DEGs were screened out, with 146 up-regulated and 138 down-regulated. The up-regulated genes were mainly involved in cell cycle, NLRs pathway, and TNF signaling pathway, and the down-regulated genes were related to mineral absorption, nitrogen metabolism, and bicarbonate reabsorption in proximal tubules. The 15 hub genes were CDK1, CDC20, AURKA, MELK, TOP2 A, PTTG1, BUB1, CDCA5, CDC45, TPX2, NEK2, CEP55, CENPN, TRIP13, and GINS2, among which CDK1 and CDC20 were regarded as core genes. The high expression of CDK1 and CDC20 suggested poor prognosis, and they significantly expressed in many cancers, especially breast cancer, lung cancer, and CRC. The expression of CDK1 and CDC20 was correlated with gender, tumor type, TNM stage, and KRAS gene mutation. The potential effective medicinals against CRC were Scutellariae Radix, Scutellariae Barbatae Herba, Arnebiae Radix, etc. The significant expression of CDK1 and CDC20 can help distinguish tumor tissues from normal tissues, and is related to survival prognosis. Thus, the two can be used as biomarkers for the diagnosis and treatment of CRC. This study provides a reference for related drug development.

Transcriptome-wide identification and expression pattern analysis for Dof gene family in Panax ginseng from Jilin / 中国中药杂志

Dof(DNA binding with one finger), a unique class of transcription factors in plants, play an important role in seed development, tissue differentiation, and metabolic regulation. To identify the number and function of Dof gene family members in Panax ginseng, this study identified the members of Dof gene family in P. ginseng and systematically analyzed their structures, evolution, functional differentiation, expression patterns, and interactions using bioinformatics methods at the transcriptome level. At the same time, the association analysis of Dof genes from P. ginseng with key enzyme genes for ginsenoside synthesis was carried out to screen the candidate PgDof genes involved in the regulation of ginsenoside biosynthesis. The results showed that there were 54 genes belonging to the Dof gene family in P. ginseng from Jilin. All PgDof genes had Zf-Dof conserved motifs, implying that they were evolutionarily conserved and could be divided into five groups. Expression pattern analysis confirmed that the expression of PgDof gene family members in different tissues, different year-old P. ginseng, and different farm varieties varied significantly. Simultaneously, as revealed by "gene-saponin content" and "gene-gene" linkage analysis, an important candidate PgDof14-1 gene involved in the regulation of ginsenoside biosynthesis was obtained. From the established genetic transformation system of this gene in the hairy roots of P. ginseng, a positive hairy root clone was determined. This study has laid a theoretical foundation for the study of Dof gene family in P. ginseng.

Bioinformatics Analysis on Key Genes and Immune Infiltration of Osteosarcoma / 中国医学科学院学报

Objective To screen the potential key genes of osteosarcoma by bioinformatics methods and analyze their immune infiltration patterns. Methods The gene expression profiles GSE16088 and GSE12865 associated with osteosarcoma were obtained from the Gene Expression Omnibus(GEO),and the differentially expressed genes(DEGs)related to osteosarcoma were screened by bioinformatics tools.Gene Ontology(GO)annotation,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment,and analysis of immune cell infiltration were then carried out for the DEGs.The potential Hub genes of osteosarcoma were identified by protein-protein interaction network,and the expression of Hub genes in osteosarcoma and normal tissue samples was verified via the Cancer Genome Atlas(TCGA). Results A total of 108 DEGs were screened out.GO annotation and KEGG pathway enrichment revealed that the DEGs were mainly involved in integrin binding,extracellular matrix (ECM) structural components,ECM receptor interactions,and phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt)signaling pathway.Macrophages were the predominant infiltrating immune cells in osteosarcoma.Secreted phosphoprotein 1(SPP1),matrix metallopeptidase 2(MMP2),lysyl oxidase(LOX),collagen type V alpha(II)chain(COL5A2),and melanoma cell adhesion molecule(MCAM)presented differential expression between osteosarcoma and normal tissue samples(all P<0.05). Conclusions SPP1,MMP2,LOX,COL5A2,and MCAM are all up-regulated in osteosarcoma,which may serve as potential biomarkers of osteosarcoma.Macrophages are the key infiltrating immune cells in osteosarcoma,which may provide new perspectives for the treatment of osteosarcoma.

Transcriptome profiling and digital gene expression analysis of genes associated with salinity resistance in peanut

Background: Soil salinity can significantly reduce crop production, but the molecular mechanism of salinity tolerance in peanut is poorly understood. A mutant (S1) with higher salinity resistance than its mutagenic parent HY22 (S3) was obtained. Transcriptome sequencing and digital gene expression (DGE) analysis were performed with leaves of S1 and S3 before and after plants were irrigated with 250 mM NaCl. Results: A total of 107,725 comprehensive transcripts were assembled into 67,738 unigenes using TIGR Gene Indices clustering tools (TGICL). All unigenes were searched against the euKaryotic Ortholog Groups (KOG), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, and these unigenes were assigned to 26 functional KOG categories, 56 GO terms, 32 KEGG groups, respectively. In total 112 differentially expressed genes (DEGs) between S1 and S3 after salinity stress were screened, among them, 86 were responsive to salinity stress in S1 and/or S3. These 86 DEGs included genes that encoded the following kinds of proteins that are known to be involved in resistance to salinity stress: late embryogenesis abundant proteins (LEAs), major intrinsic proteins (MIPs) or aquaporins, metallothioneins (MTs), lipid transfer protein (LTP), calcineurin B-like protein-interacting protein kinases (CIPKs), 9-cis-epoxycarotenoid dioxygenase (NCED) and oleosins, etc. Of these 86 DEGs, 18 could not be matched with known proteins. Conclusion: The results from this study will be useful for further research on the mechanism of salinity resistance and will provide a useful gene resource for the variety breeding of salinity resistance in peanut.

Exploration of gene functions for esophageal squamous cell carcinoma using network-based guilt by association principle

Gene networks have been broadly used to predict gene functions based on guilt by association (GBA) principle. Thus, in order to better understand the molecular mechanisms of esophageal squamous cell carcinoma (ESCC), our study was designed to use a network-based GBA method to identify the optimal gene functions for ESCC. To identify genomic bio-signatures for ESCC, microarray data of GSE20347 were first downloaded from a public functional genomics data repository of Gene Expression Omnibus database. Then, differentially expressed genes (DEGs) between ESCC patients and controls were identified using the LIMMA method. Afterwards, construction of differential co-expression network (DCN) was performed relying on DEGs, followed by gene ontology (GO) enrichment analysis based on a known confirmed database and DEGs. Eventually, the optimal gene functions were predicted using GBA algorithm based on the area under the curve (AUC) for each GO term. Overall, 43 DEGs and 67 GO terms were gained for subsequent analysis. GBA predictions demonstrated that 13 GO functions with AUC>0.7 had a good classification ability. Significantly, 6 out of 13 GO terms yielded AUC>0.8, which were determined as the optimal gene functions. Interestingly, there were two GO categories with AUC>0.9, which included cell cycle checkpoint (AUC=0.91648), and mitotic sister chromatid segregation (AUC=0.91597). Our findings highlight the clinical implications of cell cycle checkpoint and mitotic sister chromatid segregation in ESCC progression and provide the molecular foundation for developing therapeutic targets.

Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways

Given that the pathogenesis of ankylosing spondylitis (AS) remains unclear, the aim of this study was to detect the potentially functional pathway cross-talk in AS to further reveal the pathogenesis of this disease. Using microarray profile of AS and biological pathways as study objects, Monte Carlo cross-validation method was used to identify the significant pathway cross-talks. In the process of Monte Carlo cross-validation, all steps were iterated 50 times. For each run, detection of differentially expressed genes (DEGs) between two groups was conducted. The extraction of the potential disrupted pathways enriched by DEGs was then implemented. Subsequently, we established a discriminating score (DS) for each pathway pair according to the distribution of gene expression levels. After that, we utilized random forest (RF) classification model to screen out the top 10 paired pathways with the highest area under the curve (AUCs), which was computed using 10-fold cross-validation approach. After 50 bootstrap, the best pairs of pathways were identified. According to their AUC values, the pair of pathways, antigen presentation pathway and fMLP signaling in neutrophils, achieved the best AUC value of 1.000, which indicated that this pathway cross-talk could distinguish AS patients from normal subjects. Moreover, the paired pathways of SAPK/JNK signaling and mitochondrial dysfunction were involved in 5 bootstraps. Two paired pathways (antigen presentation pathway and fMLP signaling in neutrophil, as well as SAPK/JNK signaling and mitochondrial dysfunction) can accurately distinguish AS and control samples. These paired pathways may be helpful to identify patients with AS for early intervention.

Independent prognostic genes and mechanism investigation for colon cancer

PROPOSE: We aimed to explore the potential molecular mechanism and independent prognostic genes for colon cancer (CC). METHODS: Microarray datasets GSE17536 and GSE39582 were downloaded from Gene Expression Omnibus. Meanwhile, the whole CC-related dataset were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNA (DEMs) were identified between cancer tissue samples and para-carcinoma tissue samples in TCGA dataset, followed by the KEGG pathway and GO function analyses. Furthermore, the clinical prognostic analysis including overall survival (OS) and disease-free survival (DFS) were performed in all three datasets. RESULTS: A total of 633 up- and 321 down-regulated mRNAs were revealed in TCGA dataset. The up-regulated mRNAs were mainly assembled in functions including extracellular matrix and pathways including Wnt signaling. The down-regulated mRNAs were mainly assembled in functions like Digestion and pathways like Drug metabolism. Furthermore, up-regulation of UL16-binding protein 2 (ULBP2) was associated with OS in CC patients. A total of 12 DEMs including Surfactant Associated 2 (SFTA2) were potential DFS prognostic genes in CC patients. Meanwhile, the GRP and Transmembrane Protein 37 (TMEM37) were two outstanding independent DFS prognostic genes in CC. CONCLUSIONS: ULBP2 might be a potential novel OS prognostic biomarker in CC, while GRP and TMEM37 could be served as the independent DFS prognostic genes in CC. Furthermore, functions including extracellular matrix and digestion, as well as pathways including Wnt signaling and drug metabolism might play important roles in the process of CC.

Gut transcriptome analysis on females of Ornithodoros mimon (Acari: Argasidae) and phylogenetic inference of ticks / Transcriptoma do intestino de fêmeas de Ornithodoros mimon (Acari: Argasidae) e inferência filogenética de carrapatos

Abstract Ornithodoros mimon is an argasid tick that parasitizes bats, birds and opossums and is also harmful to humans. Knowledge of the transcripts present in the tick gut helps in understanding the role of vital molecules in the digestion process and parasite-host relationship, while also providing information about the evolution of arthropod hematophagy. Thus, the present study aimed to know and ascertain the main molecules expressed in the gut of argasid after their blood meal, through analysis on the gut transcriptome of engorged females of O. mimon using 454-based RNA sequencing. The gut transcriptome analysis reveals several transcripts associated with hemoglobin digestion, such as serine, cysteine, aspartic proteases and metalloenzymes. The phylogenetic analysis on the peptidases confirmed that most of them are clustered with other tick genes. We recorded the presence a cathepsin O peptidase-coding transcript in ticks. The topology of the phylogenetic inferences, based on transcripts of inferred families of homologues, was similar to that of previous reports based on mitochondrial genome and nuclear rRNA sequences. We deposited 2,213 sequence of O. mimon to the public databases. Our findings may help towards better understanding of important argasid metabolic processes, such as digestion, nutrition and immunity.

Resumo Ornithodoros mimon é um carrapato argasídeo parasita de morcegos, aves e marsupiais, além de ser bastante agressivo aos humanos. O conhecimento dos transcritos presentes no intestino dos carrapatos auxilia no entendimento do papel de moléculas vitais no processo de digestão e na relação parasito-hospedeiro, além de fornecer também informações sobre a evolução dos artrópodes hematófagos. Desta maneira, o presente estudo teve como objetivo conhecer e identificar as principais moléculas expressas no intestino de uma espécie de carrapato argasídeo após o repasto sanguíneo, através de uma análise transcritômica descritiva do intestino de fêmeas ingurgitadas de O. mimon, utilizando um sequenciamento de RNA de nova geração da plataforma 454. Além de inferir a relação filogenética de carrapatos através de um conjunto de dados transcritômicos. O transcriptoma do intestino revelou diversos transcritos associados com a digestão da hemoglobina, como proteinases das classes serino, cisteína, aspártica e metalo. Registramos a presença de um transcrito de uma cisteína peptidase do tipo catepsina O em carrapatos. A inferência filogenética baseada em conjunto de dados transcritos homólogos tem uma resolução topológica similar a de outros conjuntos de dados moleculares. Foram depositados no banco de dados gênico público 2213 transcritos de O. mimon. Os achados obtidos no presente estudo podem contribuir para compreensão dos importantes processos, como digestão, nutrição e imunidade dos carrapatos da família Argasidae, além de fornecer informações sobre a filogenia da ordem Ixodida.

Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways

Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC) based on the functional dependency among pathways. Protein-protein interaction (PPI) information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA) method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN), where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

MicroRNA profiling identifies miR-7-5p and miR-26b-5p as differentially expressed in hypertensive patients with left ventricular hypertrophy

Recent evidence suggests that cell-derived circulating miRNAs may serve as biomarkers of cardiovascular diseases. However, a few studies have investigated the potential of circulating miRNAs as biomarkers for left ventricular hypertrophy (LVH). In this study, we aimed to characterize the miRNA profiles that could distinguish hypertensive patients with LHV, hypertensive patients without LVH and control subjects, and identify potential miRNAs as biomarkers of LVH. LVH was defined by left ventricular mass indexed to body surface area >125 g/m2 in men and >110 g/m2 in women and patients were classified as hypertensive when presenting a systolic blood pressure of 140 mmHg or more, or a diastolic blood pressure of 90 mmHg or more. We employed miRNA PCR array to screen serum miRNAs profiles of patients with LVH, essential hypertension and healthy subjects. We identified 75 differentially expressed miRNAs, including 49 upregulated miRNAs and 26 downregulated miRNAs between LVH and control patients. We chose 2 miRNAs with significant differences for further testing in 59 patients. RT-PCR analysis of serum samples confirmed that miR-7-5p and miR-26b-5p were upregulated in the serum of LVH hypertensive patients compared with healthy subjects. Our findings suggest that these miRNAs may play a role in the pathogenesis of hypertensive LVH and may represent novel biomarkers for this disease.