Universidad Simon Bolivar, Basic and Biomedical Faculty, Barranquilla, Colombia.
CMCC- Centro de Matemática, Computação e Cognição, Laboratório do Biologia Computacional e Bioinformática-LBCB, Universidade Federal do ABC, Sao Paulo, Brazil.
PLoS One. 2019 Jun 25;14(6):e0218116. doi: 10.1371/journal.pone.0218116. eCollection 2019.
The aim of this study was to identity in silico the relationships among microRNAs (miRNAs) and genes encoding transcription factors, ubiquitylation, DNA methylation, and histone modifications in systemic lupus erythematosus (SLE). To identify miRNA dysregulation in SLE, we used miR2Disease and PhenomiR for information about miRNAs exhibiting differential regulation in disease and other biological processes, and HMDD for information about experimentally supported human miRNA-disease association data from genetics, epigenetics, circulating miRNAs, and miRNA-target interactions. This information was incorporated into the miRNA analysis. High-throughput sequencing revealed circulating miRNAs associated with kidney damage in patients with SLE. As the main finding of our in silico analysis of miRNAs differentially expressed in SLE and their interactions with disease-susceptibility genes, post-translational modifications, and transcription factors; we highlight 226 miRNAs associated with genes and processes. Moreover, we highlight that alterations of miRNAs such as hsa-miR-30a-5p, hsa-miR-16-5p, hsa-miR-142-5p, and hsa-miR-324-3p are most commonly associated with post-translational modifications. In addition, altered miRNAs that are most frequently associated with susceptibility-related genes are hsa-miR-16-5p, hsa-miR-374a-5p, hsa-miR-34a-5p, hsa-miR-31-5p, and hsa-miR-1-3p.
本研究旨在通过计算机分析系统性红斑狼疮(SLE)中 microRNAs(miRNAs)与编码转录因子、泛素化、DNA 甲基化和组蛋白修饰的基因之间的关系。为了识别 SLE 中的 miRNA 失调,我们使用 miR2Disease 和 PhenomiR 来获取疾病和其他生物学过程中表现出差异调节的 miRNA 信息,使用 HMDD 来获取遗传、表观遗传学、循环 miRNA 和 miRNA-靶相互作用方面实验支持的人类 miRNA-疾病关联数据的信息。这些信息被纳入 miRNA 分析中。高通量测序揭示了与 SLE 患者肾脏损伤相关的循环 miRNA。作为我们对 SLE 中差异表达 miRNA 及其与疾病易感性基因、翻译后修饰和转录因子相互作用的计算机分析的主要发现,我们重点介绍了 226 个与基因和过程相关的 miRNA。此外,我们还强调,miRNA 的改变,如 hsa-miR-30a-5p、hsa-miR-16-5p、hsa-miR-142-5p 和 hsa-miR-324-3p,与翻译后修饰最常相关。此外,与易感相关基因最常相关的改变 miRNA 是 hsa-miR-16-5p、hsa-miR-374a-5p、hsa-miR-34a-5p、hsa-miR-31-5p 和 hsa-miR-1-3p。