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.
Flavonoids/metabolism* ; Fruit/genetics* ; Gene Expression Profiling/methods* ; Gene Expression Regulation, Plant ; Lycium/metabolism* ; Metabolic Networks and Pathways ; Transcriptome

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.
Humans ; Esophageal Neoplasms/metabolism* ; Esophageal Squamous Cell Carcinoma/metabolism* ; Epithelial Cell Adhesion Molecule/metabolism* ; Gene Expression Profiling/methods* ; Gene Regulatory Networks ; Gene Expression ; Gene Expression Regulation, Neoplastic ; Intracellular Signaling Peptides and Proteins

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.
Female ; Humans ; Male ; Aged ; Gene Expression Profiling/methods* ; Transcriptome ; Protein Interaction Maps/genetics* ; Computational Biology/methods* ; Osteoporosis/genetics*

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.
Humans ; Neoplasms, Unknown Primary/genetics* ; Carcinoma/drug therapy* ; Gene Expression Profiling/methods* ; Microarray Analysis ; Prognosis

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.
Genes, Essential ; Gelsemium/genetics* ; Peptide Elongation Factor 1/genetics* ; Transcriptome ; Gene Expression Profiling/methods* ; Alkaloids ; Real-Time Polymerase Chain Reaction/methods* ; Reference Standards

Paeonia veitchii and P. lactiflora are both original plants of the famous Chinese medicinal drug Paeoniae Radix Rubra in the Chinese Pharmacopoeia. They have important medicinal value and great potential in the flower market. The selection of stable and reliable reference genes is a necessary prerequisite for molecular research on P. veitchii. In this study, two reference genes, Actin and GAPDH, were selected as candidate genes from the transcriptome data of P. veitchii. The expression levels of the two candidate genes in different tissues(phloem, xylem, stem, leaf, petiole, and ovary) and different growth stages(bud stage, flowering stage, and dormant stage) of P. veitchii were detected using real-time fluorescence quantitative technology(qRT-PCR). Then, the stability of the expression of the two reference genes was comprehensively analyzed using geNorm, NormFinder, BestKeeper, ΔCT, and RefFinder. The results showed that the expression patterns of Actin and GAPDH were stable in different tissues and growth stages of P. veitchii. Furthermore, the expression levels of eight genes(Pv-TPS01, Pv-TPS02, Pv-CYP01, Pv-CYP02, Pv-CYP03, Pv-BAHD01, Pv-UGT01, and Pv-UGT02) in different tissues were further detected based on the transcriptome data of P. veitchii. The results showed that when Actin and GAPDH were used as reference genes, the expression trends of the eight genes in different tissues of P. veitchii were consistent, validating the reliability of Actin and GAPDH as reference genes for P. veitchii. In conclusion, this study finds that Actin and GAPDH can be used as reference genes for studying gene expression levels in different tissues and growth stages of P. veitchii.
Real-Time Polymerase Chain Reaction/methods* ; Paeonia/genetics* ; Actins/genetics* ; Reproducibility of Results ; Transcriptome ; Glyceraldehyde-3-Phosphate Dehydrogenases/genetics* ; Reference Standards ; Gene Expression Profiling/methods*

This study aims to identify the novel biomarkers of cold-dampness syndrome(RA-Cold) of rheumatoid arthritis(RA) by gene set enrichment analysis(GSEA), weighted gene correlation network analysis(WGCNA), and clinical validation. Firstly, transcriptome sequencing was carried out for the whole blood samples from RA-Cold patients, RA patients with other traditional Chinese medicine(TCM) syndromes, and healthy volunteers. The differentially expressed gene(DEG) sets of RA-Cold were screened by comparison with the RA patients with other TCM syndromes and healthy volunteers. Then, GSEA and WGCNA were carried out to screen the key DEGs as candidate biomarkers for RA-Cold. Experimentally, the expression levels of the candidate biomarkers were determined by RT-qPCR for an independent clinical cohort(not less than 10 cases/group), and the clinical efficacy of the candidates was assessed using the receiver operating characteristic(ROC) curve. The results showed that 3 601 DEGs associated with RA-Cold were obtained, including 106 up-regulated genes and 3 495 down-regulated genes. The DEGs of RA-Cold were mainly enriched in the pathways associated with inflammation-immunity regulation, hormone regulation, substance and energy metabolism, cell function regulation, and synovial pannus formation. GSEA and WGCNA showed that recombinant proteasome 26S subunit, ATPase 2(PSMC2), which ranked in the top 50% in terms of coefficient of variation, representativeness of pathway, and biological modules, was a candidate biomarker of RA-Cold. Furthermore, the validation results based on the clinical independent sample set showed that the F1 value, specificity, accuracy, and precision of PSMC2 for RA-Cold were 70.3%, 61.9%, 64.5%, and 81.3%, respectively, and the area under the curve(AUC) value was 0.96. In summary, this study employed the "GSEA-WGCNA-validation" integrated strategy to identify novel biomarkers of RA-Cold, which helped to improve the TCM clinical diagnosis and treatment of core syndromes in RA and provided an experimental basis for TCM syndrome differentiation.
Humans ; Arthritis, Rheumatoid/drug therapy* ; Biomarkers/metabolism* ; Medicine, Chinese Traditional ; Gene Expression Profiling/methods* ; Computational Biology ; Gene Regulatory Networks ; ATPases Associated with Diverse Cellular Activities/therapeutic use* ; Proteasome Endopeptidase Complex/therapeutic use*

Objective To identify immune-related dysregulation mechanisms and potential diagnostic predictive biomarkers in osteoporosis. Methods Gene expression data for both osteoporosis and control populations were retrieved from the GSE35958 and GSE56815 datasets. Immune-related differentially expressed genes (DEGs) were obtained by screening DEGs and were compared with the immunology database and analysis portal (ImmPort) database. Enrichment analysis of these immune-related DEGs was conducted using the Clusterprofiler software package. A protein-protein interaction network was built with the STRING database, which is a search tool for finding interacting genes/proteins, and the top 10 genes with the highest network connectivity were identified as candidate genes. Subsequently, the diagnostic predictive effect of candidate genes was evaluated using receiver operating characteristic (ROC) curves, logistic regression, and column plots. Finally, PCR and Western blot analysis were applied to detect the differential expression of these genes in bone marrow tissue of patients with osteoporosis. Results A total of 138 immune-related DEGs were obtained through intersection analysis. The results of the enrichment analysis indicated that these genes were involved in biological functions such as immune inflammation and signaling pathways including T cell receptors, mitogen activated protein kinase (MAPK), rat sarcoma virus oncogene homologs (Ras), osteoclast differentiation, and B cell receptors. In addition, among the candidate genes, upregulated vascular endothelial growth factor A (VEGFA) and epidermal growth factor receptor (EGFR) and downregulated AKT1, SRC, and JUN in osteoporosis showed the highest connectivity. Among them, VEGFA, EGFR, JUN, and AKT1 demonstrated the best diagnostic predictive value. Conclusion The screening of immune-related DEGs will enhance the understanding of osteoporosis and facilitate the development of immunotherapy targets.
Humans ; Vascular Endothelial Growth Factor A/genetics* ; Biomarkers ; Osteoporosis/genetics* ; Computational Biology/methods* ; ErbB Receptors/genetics* ; Gene Expression Profiling/methods*

Glioma, the most common intrinsic tumor of the central nervous system, is characterized by its high incidence and poor prognosis. The aim of this study was to identify differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade glioma (LGG) to explore prognostic factors of different grades of gliomas. Single-cell transcriptome sequencing data of gliomas were collected from the NCBI Gene Expression Omnibus (GEO), which included a total of 29 097 cell samples from three datasets. For the analysis of human gliomas of different grades, 21 071 cells were obtained by filtering, and 70 genes were screened from differentially expressed genes by gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, from which the gene DLL3 was focused by reviewing the literature. The TCGA-based gene expression profiling interactive analysis (GEPIA) database was used to explore the survival curves of genes in LGG and GBM, and the gene expression profiling interactive analysis and tumor immune estimation resource (TIMER) database was used to study the expression of key genes in gliomas of different grades, predicting biomarkers that were closely related to immunotherapy. The cBioPortal database was used to explore the relationship between DLL3 expression and 25 immune checkpoints. Gene set enrichment analysis (GSEA) further identified pathways associated with central genes. Finally, the efficacy of biomarkers in prognosis and prediction was validated in the Chinese glioma genome atlas (CGGA). These results demonstrated that prognostic genes are associated with tumor proliferation and progression. Analysis of biological information and survival suggested that these genes might serve as a promising prognostic biomarker and as new targets for selecting therapeutic strategies.
Humans ; Biomarkers ; Brain Neoplasms/pathology* ; Gene Expression Profiling/methods* ; Glioblastoma/pathology* ; Glioma/pathology* ; Intracellular Signaling Peptides and Proteins ; Membrane Proteins/genetics* ; Prognosis ; Transcriptome ; Tumor Microenvironment/genetics* ; Biomarkers, Tumor

To provide a theoretical basis for controlling the spread of rust disease, cultivating disease-resistant varieties and reducing yield losses, we investigated the transcriptome differences between Gymnosporangium yamadae and Gymnosporangium asiaticum at the haustorial stage and revealed a specialized selection mechanism for Gymnosporangium species to infect host plants. We sequenced the transcriptomes of the haustoria in rust-infected leaves when basidiospores of G. yamadae and G. asiaticum infected their hosts, and obtained 21 213 and 13 015 unigenes, respectively. Real-time fluorescence quantitative PCR validation of five genes selected from G. yamadae and G. asiaticum, respectively, showed that their expression profiles were generally consistent with the results of transcriptome analysis, demonstrating the reliability of the transcriptome data. We used seven databases such as Nr, GO, KEGG, and KOG to perform gene function annotation and enrichment analysis, and found that the genes from both rusts were mainly enriched in cellular processes, translation, and metabolism-related pathways. Moreover, we used SignalP, TMHMM online website and other software such as dbCAN, BLSAT, HMMER to show that there were 343 (2.51%) and 175 (2.79%) candidate effector proteins containing 14 and 5 proteases and 10 and 3 lipases in the haustoria of G. yamadae and G. asiaticum, respectively. Furthermore, we used OrthoFinder, BLAST and KaKs Calculator software to analyze the evolutionary relationship of the two fungi. Among one-to-one homologous genes, gene pairs with > 82% alignment were considered to be under conservative selection, and 12.37% under positive selection. Five effectors of G. asiaticum were under positive selection, and one of which was a lipase. No significant differences were found in the enrichment of expressed genes between G. yamadae and G. asiaticum, indicating the biological processes involved in haustoria were relatively conserved, despite the typical host selectivity between species. The low protein similarity between the two species suggested that they were under greater host selective pressure and there was significant evolutionary divergence, which might be related to the host-specific selection mechanism. In the haustorial, the main purpose of the effectors might be to regulate physiological processes in the plants rather than attacking the host directly, and G. yamadae and G. asiaticum might use plant lipids as energy sources.
Transcriptome ; Reproducibility of Results ; Plant Diseases/microbiology* ; Gene Expression Profiling/methods*