目的 研究糖尿病、阳痿、慢性肾炎患者中筛选出的典型肾阳虚证病例的转录组学特征，揭示出肾阳虚证“同证异治”的生物学基础。 方法 分别对9例肾阳虚证患者进行Agilent人444k表达谱芯片实验，对差异表达基因进行基因本休论（GO）、Pathway分析。 结果 找出332条共同差异表达基因，其中有注释的基因为181条。通过GO分析发现肾阳虚证在免疫系统、氨基酸分解和合成、脂类代谢、生殖、能量代谢及肿瘤相关的基因有密切联系，通过Pathway分析发现与肾阳虚证相关的信号通路有39个。 结论 肾阳虚证可能导致免疫系统低下，氨基酸分解和合成、脂类代谢、生殖、能量代谢功能降低，以及与肿瘤形成相关。
ObjectiveTo reveal the potential mechanism of cisplatin resistance in non-small cell lung cancer A549 cells by comparing the expression profiles of wild-type A549 cells and cisplatin-resistant A549 cells (A549/DPP) through whole transcriptome sequencing analysis.MethodsThe cisplatin resistant A549 (A549/DDP) cell line was first established. Then, the whole-transcriptome analysis was conducted both on A549 and A549/DDP cells. Next, the differentially expressed RNAs of lncRNA-seq, circRNA-seq, and miRNA-seq data were identified, respectively, followed by functional enrichment analysis. Finally, a comprehensive analysis based on the whole transcriptome data was performed and the construction of the ceRNA network was carried out.ResultsA total of 4 517 lncRNA, 123 circRNA, and 145 miRNA were differentially expressed in A549/DDP cells compared with the A549 cell line. These different RNAs were significantly enriched in cancer-related pathways. The ceRNA network contained 12 miRNAs, 4 circRNAs, 23 lncRNAs, and 9 mRNA nodes, of which hsa-miR-125a-5p and hsa-miR-125b-5p were important miRNAs based on the topological analysis.ConclusionTumor necrosis factor signaling pathway and p53 signaling pathway are involved in A549/DPP resistance. Hsa-miR-125a-5p and hsa-miR-125b-5p may be potential targets for reversing cisplatin resistance.
With the development of life sciences and informatics, bioinformatics is developing as an interdisciplinary subject. Its main application is the relationship between genes and proteins and their expression. With the help of genomics, proteomics, transcriptomics, and metabolomics, researchers introduce bioinformatics research methods into fundus disease research. A series of gratifying research results have been achieved including the screening of genetic susceptibility genes, the screening of diagnostic markers, and the exploration of pathogenesis. Genomics has the characteristics of high efficiency and accuracy. It has been used to detect new mutation sites in retinoblastoma and retinal pigment degeneration research, which helps to further improve the pathogenesis of retinal genetic diseases. Transcriptomics, proteomics, and metabolomics have high throughput characteristics. They are used to analyze changes in the expression profiles of RNA, proteins, and metabolites in intraocular fluid or isolated cells in disease states, which help to screen biomarkers and further elucidate the pathogenesis. With the advancement of technology, bioinformatics will provide new ideas for the study of ocular fundus diseases.
ObjectiveTo study the abnormal biological pathways of intrahepatic cholangiocarcinoma (ICC) from the transcriptomics level and identify genes associated with the prognosis of ICC.MethodsThe differentially expressed genes were screened by t test and fold change method, then KEGG functional enrichment analysis was performed on related genes. The STRING database was applied to construct protein interaction network and find the hub nodes of the network by calculating the degree, betweenness, and closeness of each node. Kaplan-Meier survival analysis was performed using log-rank test to identify prognostic genes related to ICC.ResultsAll of 1 134 differentially expressed genes were overlapped in 3 datasets, which were mainly involved in 15 pathways, including DNA replication, cell cycle, drug metabolism, RNA transport, etc. signaling pathways and amino acid synthesis. According to protein interaction network analysis, TAF1, GRB2, E2F4, HNF4A, MYC, and TP53 genes were hub nodes. As GRB2 and TP53 genes were also the death related genes of ICC, it was found that patients with lower GRB2 gene expression had a better overall survival than those with higher GRB2 gene expression (P=0.040 9), while patients with lower TP53 had a worse overall survival than those with higher TP53 gene expression (P=0.027 3), which were also verified in the TCGA database.ConclusionsThe abnormal cell metabolism is notably related to the tumorigenesis of ICC. TAF1, GRB2, E2F4, HNF4A, MYC, and TP53 are the key genes in the carcinogenesis and progression of ICC. Expressions of GRB2 and TP53 genes are associated with the prognosis of ICC.
Objective To study the effects of connective tissue growth factor (CTGF) on retinal Müller cells based on transcriptome analysis of RNA-seq technology.MethodsRetinal Müller cells were divided into the control group and the CTGF treatment group which was continuously cultured with 10 ng/ml of CTGF for 24 h. The influence of CTGF on the migration of Müller cells were tested by scratching experiments. The RNA transcriptome analysis was applied to complete transcriptome sequencing, differentially expressed genes and functional enrichment analysis of the two groups of cells. HiSeq sequencing technology was used to sequence the whole transcriptome of the two groups of cells to obtain biological big data, and analyze the differentially expressed miRNAs on this basis. The functions and signal pathways of differential miRNAs were analyzed through gene annotation (GO) functional significance enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway significant enrichment analysis. Based on transcriptome data, genes with differential expression multiples in the top ten between the two groups were screened out, and the expression of bone morphogenetic protein 4 (BMP4) gene was verified by real time fluorescence quantification PCR (qRT-PCR), immunofluorescence and Western blot.ResultsAfter CTGF stimulation of Müller cells, cell viability and mobility which compared with the control group were significantly increased, with statistically significant differences (t=3.453, P＜0.05). The differential gene expression profile of CTGF induced Müller cells was obtained by RNA transcriptome analysis. Comparing the sequencing results of the two groups, it was found that 325 differentially expressed genes included 152 up-regulated genes and 173 down-regulated genes. The results of GO functional significance enrichment analysis showed that the functions of differential miRNA were mainly divided into three categories: biological processes, cellular components, and molecular functions. These differentially expressed genes were involved in signaling between nervous systems, adhesion between cells, and the interaction between cytokines and their receptors. These differentially expressed genes were involved in different metabolic pathways and biological processes such as tissue inflammation and fibrosis. BMP4 gene was seected for verification through immunofluorescence, qRT-PCR and western blot. The results showed that the expression of BMP4 was significantly higher than that in the control group, and the difference was statistically significant (t=39.490, 10.110, 5.470; P=0.004, 0.001, 0.006).ConclusionCTGF promotes cell proliferation and migration by up-regulating the expression of BMP4 in Müller cells, leading to tissue fibrosis and inducing inflammation.
ObjectiveTo analyze the early changes of gene expression levels and signaling pathways in 661W cell line under hypoxic conditions and to find potential functional target genes.MethodsThe cultured mouse 661W cells were divided into hypoxia treatment group and normoxia control group. Cells in the hypoxia treatment group were cultured in a three-gas incubator with volume fraction of 1% and 5% CO2 at 37 ℃. Cells in the normoxia control group were cultured in an incubator at 37 ℃ with volume fraction of 5% CO2. High-throughput sequencing technology was used to sequence the transcriptome of 661W cell treated with hypoxia and normoxia for 4 hours to screen for differentially expressed genes (DEG). Clustering heat map analysis, gene ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction network (PPI) analysis were performed. The reverse transcription-polymerase chain reaction (RT-PCR) was used to verify the accuracy of the sequencing results.ResultsA total of 506 differentially expressed genes were screened, including 459 up-regulated genes and 47 down-regulated genes. GO functional enrichment analysis showed that the main biological processes of DEG were the cell's response to hypoxia, glycolysis, negative regulation of cell proliferation and apoptosis. hypoxia inducible factor (HIF)-1α pathway, glycolysis, Forkhead box O (FoxO) pathway, Insulin signaling pathway and Adenosine 5'-monophosphate-activated protein kinase (AMPK) pathway were involved in the above process. PPI analysis results showed that hub genes related to hypoxia were Aldoa, Aldoc, Gpi1, Hk2, Hk1, Pfkl, Pfkp, Vhl, Fbxo10 and Fbxo27. The RT-PCR results showed that the relative expression levels of 15 DEG mRNA in the hypoxic treatment group were higher than that of the normoxic control group, and the difference was statistically significant (P＜0.05). The mRNA expression levels of N-myc downstream-regulated gene-1 (Ndrg1), Mt1, and vascular endothelial growth factor A (VEGFA) were time-dependent on hypoxia.ConclusionsUnder hypoxia, DEG is mainly related to glucose metabolism, cell response to hypoxia, regulation of proliferation and apoptosis. HIF-1α pathway, glycolysis, FoxO pathway and AMPK pathway are involved in the early changes of 661W cells under hypoxia. Aldoa, Aldoc, Gpi1, Hk2, Hk1, Pfkl, Pfkp, Vhl, Fbxo10, Fbxo27 may play key roles in the response of 661W cells to hypoxia. Ndrg1, Mt1 and VEGFA could be potential functional target genes for the study of ischemia and hypoxia-related fundus diseases.
The emergence of single-cell sequencing technology enables people to observe cells with unprecedented precision. However, it is difficult to capture the information on all cells and genes in one single-cell RNA sequencing (scRNA-seq) experiment. Single-cell data of a single modality cannot explain cell state and system changes in detail. The integrative analysis of single-cell data aims to address these two types of problems. Integrating multiple scRNA-seq data can collect complete cell types and provide a powerful boost for the construction of cell atlases. Integrating single-cell multimodal data can be used to study the causal relationship and gene regulation mechanism across modalities. The development and application of data integration methods helps fully explore the richness and relevance of single-cell data and discover meaningful biological changes. Based on this, this article reviews the basic principles, methods and applications of multiple scRNA-seq data integration and single-cell multimodal data integration. Moreover, the advantages and disadvantages of existing methods are discussed. Finally, the future development is prospected.
ObjectiveTo screening differentially expressed genes (DEGs) in proliferative diabetic retinopathy (DR) patients to provide new biological therapeutic targets for proliferative DR (PDR) therapy. MethodsA basic research. A total of 3 PDR patients (group PDR) and 3 non-diabetic patients (control group) were enrolled in the study in Tianjin Medical University Eye Hospital in October 2020. In addition, 40 cases of PDR and non-diabetic patients were selected and divided into PDR validation group and control validation group. Peripheral blood validation test was performed in PDR validation group and control validation group; RNA sequencing was performed in PDR group and control group. Transcriptomics (RNAseq) sequencing technology was used to screen DEG in PDR group and control group. The selected DEGs were analyzed by gene ontology (GO) function enrichment analysis, signal pathway enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction network (PPI). The gene expression database was used to find the high-throughput data related to PDR, and multi queue comparison analysis was carried out. The target genes of differentially expressed miRNAs were predicted through targetscan platform, so as to clearly screen the correlation between DEG and PDR. Reverse transcription polymerase chain reaction and Western blot were used to verify the expression of DEG mRNA and protein related to PDR. The relative expression of PDR related DEG mRNA and protein between PDR validation group and control validation group were compared by paired t-test. ResultsA total of 1 337 DEGs were screened by RNAseq sequencing in the peripheral blood of patients with PDR, of which 419 genes were up-regulated and 918 down-regulated. Among them, direct inhibitor of apoptosis protein-binding protein with low isoelectric point (DIABLO), zinc finger and BTB domain containing 10 (ZBTB10), polo-like kinases 3 (PLK3), regulatory subunit 1 (PIK3R1) and B cell translocation gene 3 (BTG3) were differentially expressed in PDR patients. The function of GO was enriched from the analysis of molecular function, biological process and cellular composition. The results showed that DIABLO, ZBTB10, PLK3, PIK3R1, BTG3 were involved in the pathological process related to PDR. KEGG enrichment analysis showed that glucose metabolic pathways such as extracellular matrix receptors, cytokine regulatory pathway, p53 signal pathway and galactose metabolism may be involved in the process of differential genes. The analysis of PPI protein interaction network showed that the larger the DEG-associated protein node, the greater the number of associated nodes. Among them, DIABLO, ZBTB10, PLK3, PIK3R1 and BTG3 played significant roles in the formation of the action network. By comparing and analyzing the existing high-throughput data related to diabetic retinopathy in Gene Expression Omnibus database and predicting by Targetscan platform, it was found that some significant differences in miRNA reported in aqueous humor, vitreous fluid and plasma of DR patients can be regulated by the differential genes found in this study. Compared with the control verification group, the relative expressions of DIABLO, ZBTB10, PLK3, PIK3R1 mRNA and protein in peripheral blood of the PDR verification group were up-regulated, and the relative expression of BTG3 mRNA and protein was down-regulated. ConclusionDIABLO, ZBTB10, PLK3, PIK3R1 and BTG3 are DEGs in patients with PDR, and they can participate in the disease process by regulating the biological processes of cell proliferation, fibrosis and oxidative stress.
Uveal melanoma (UM) is an aggressive and lethal tumor in the eye. The complexity and heterogeneity of UM and its microenvironment leads to a lack of strategies for early prevention and treatment of metastases. Single-cell sequencing technologies provide critical insights into deciphering the complexity of intratumor heterogeneity and the microenvironment by enabling genomic, transcriptomic, and epigenetic analysis at the single-cell level. With the help of bioinformatics analysis combined with artificial intelligence algorithms, molecular indicator systems related to prognosis as well as therapeutic targets can be found, which can provide a basis for guiding the selection of clinical treatment plans. However, the single-cell sequencing technology also has certain limitations, such as high sample requirements, expensive and time-consuming sequencing. It is believed that with the improvement of science and technology and the update of analytical methods, these shortcomings can be gradually solved, and this rare tumor will eventually be overcome in the future, and the goal of long-term survival of UM patients will be achieved.