Exploration of the Regulatory Network of Programmed Cell Death Genes in Rheumatoid Arthritis Based on Blood-Derived circRNA Transcriptome Information and Single-Cell Multi-omics Data.

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Yuxuan Fang, Nan Xu, Jiacheng Shen, Hongyi Chen, Guoqing Li
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引用次数: 0

Abstract

Programmed cell death (PCD) and circular RNA (circRNA) have been found to involve in the pathogenesis of rheumatoid arthritis (RA). The aim of this study was to explore PCD mechanisms and gene regulatory networks in RA. RA related to circRNA, mRNA and single-cell data sets were obtained from the GEO database. The limma package was used to screen differentially expressed circRNA and differentially expressed genes (DEGs) of RA. The PCD gene set from literature was intersected with the DEGs of RA to obtain PCD-related DEGs of RA. The ENCORI database was used to predict and construct a competing endogenous RNAs (ceRNA) regulatory network to obtain key circRNAs and PCD-related DEGs. Hub genes were identified from the key PCD-related DEGs in the ceRNA regulatory network through LASSO regression, and a diagnostic model was constructed based on these hub genes. The expression of hub genes in various cells and stages was analyzed using single-cell datasets. Finally, the expression of key circRNAs and hub genes in peripheral blood of RA patients and healthy individuals was verified by PCR. In this study, a total of 71 differential circRNAs and 221 DEGs in RA were obtained, and 23 PCD-related DEGs were identified. Through ceRNA regulatory network, three key circRNAs (hsa_circ_0001241, hsa_circ_0089761, and hsa_circ_0001654) and four hub PCD-related DEGs. Among them, TXN and RRAGD were highly expressed, and PARP1 and TXNIP were lowly expressed in RA. Single-cell analysis revealed that these genes were significantly differentially expressed in myeloid cell subpopulation. PCR results indicated that among the 7 key factors, the expression of hsa_circ_0001241, hsa_circ_0089761, TXN, and RRAGD in RA was consistent with the results of bioinformatics analysis. Hsa_circ_0001241, hsa_circ_0089761, TXN and RRAGD may be potential biomarkers for RA, and their interactions may have significant implications for the pathology of RA.

基于血源性环状rna转录组信息和单细胞多组学数据的类风湿关节炎程序性细胞死亡基因调控网络研究
程序性细胞死亡(PCD)和环状RNA (circRNA)被发现参与类风湿关节炎(RA)的发病机制。本研究的目的是探讨PCD在RA中的机制和基因调控网络。从GEO数据库中获得与circRNA、mRNA和单细胞相关的RA数据集。使用limma包筛选RA的差异表达circRNA和差异表达基因(DEGs)。将文献中的PCD基因集与RA的DEGs相交,得到PCD相关的RA DEGs。利用ENCORI数据库预测并构建竞争内源性rna (ceRNA)调控网络,获取关键环状rna和与pcd相关的deg。通过LASSO回归从ceRNA调控网络中与pcd相关的关键deg中鉴定出枢纽基因,并基于这些枢纽基因构建诊断模型。使用单细胞数据集分析hub基因在不同细胞和阶段的表达。最后,通过PCR验证RA患者和健康人外周血中关键circrna和hub基因的表达情况。在本研究中,共获得71个差异环状rna和RA中的221个deg,并鉴定出23个与pcd相关的deg。通过ceRNA调控网络,3个关键circrna (hsa_circ_0001241、hsa_circ_0089761和hsa_circ_0001654)和4个集线器pcd相关的deg。其中,TXN和RRAGD在RA中高表达,PARP1和TXNIP在RA中低表达。单细胞分析显示,这些基因在髓细胞亚群中有显著差异表达。PCR结果显示,在7个关键因子中,hsa_circ_0001241、hsa_circ_0089761、TXN和RRAGD在RA中的表达与生物信息学分析结果一致。Hsa_circ_0001241、hsa_circ_0089761、TXN和RRAGD可能是类风湿关节炎的潜在生物标志物,它们之间的相互作用可能对类风湿关节炎的病理有重要意义。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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