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mirTarRnaSeq:用于 miRNA-mRNA 靶标识别和相互作用分析的 R/Bioconductor 统计软件包。

mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis.

机构信息

Dana Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, United States.

Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.

出版信息

BMC Genomics. 2022 Jun 13;23(1):439. doi: 10.1186/s12864-022-08558-w.

Abstract

We introduce mirTarRnaSeq, an R/Bioconductor package for quantitative assessment of miRNA-mRNA relationships within sample cohorts. mirTarRnaSeq is a statistical package to explore predicted or pre-hypothesized miRNA-mRNA relationships following target prediction.We present two use cases applying mirTarRnaSeq. First, to identify miRNA targets, we examined EBV miRNAs for interaction with human and virus transcriptomes of stomach adenocarcinoma. This revealed enrichment of mRNA targets highly expressed in CD105+ endothelial cells, monocytes, CD4+ T cells, NK cells, CD19+ B cells, and CD34 cells. Next, to investigate miRNA-mRNA relationships in SARS-CoV-2 (COVID-19) infection across time, we used paired miRNA and RNA sequenced datasets of SARS-CoV-2 infected lung epithelial cells across three time points (4, 12, and 24 hours post-infection). mirTarRnaSeq identified evidence for human miRNAs targeting cytokine signaling and neutrophil regulation immune pathways from 4 to 24 hours after SARS-CoV-2 infection. Confirming the clinical relevance of these predictions, three of the immune specific mRNA-miRNA relationships identified in human lung epithelial cells after SARS-CoV-2 infection were also observed to be differentially expressed in blood from patients with COVID-19. Overall, mirTarRnaSeq is a robust tool that can address a wide-range of biological questions providing improved prediction of miRNA-mRNA interactions.

摘要

我们介绍了 mirTarRnaSeq,这是一个用于在样本队列中定量评估 miRNA-mRNA 关系的 R/Bioconductor 包。mirTarRnaSeq 是一个统计软件包,用于探索基于靶标预测的预测或预先假设的 miRNA-mRNA 关系。我们提出了两个应用 mirTarRnaSeq 的用例。首先,为了识别 miRNA 靶标,我们研究了 EBV miRNAs 与胃腺癌的人类和病毒转录组的相互作用。这揭示了在 CD105+内皮细胞、单核细胞、CD4+T 细胞、NK 细胞、CD19+B 细胞和 CD34 细胞中高度表达的 mRNA 靶标富集。接下来,为了研究 SARS-CoV-2(COVID-19)感染过程中 miRNA-mRNA 关系,我们使用了 SARS-CoV-2 感染肺上皮细胞的配对 miRNA 和 RNA 测序数据集,跨越三个时间点(感染后 4、12 和 24 小时)。mirTarRnaSeq 鉴定了人类 miRNA 靶向细胞因子信号和中性粒细胞调节免疫途径的证据,从 SARS-CoV-2 感染后 4 小时到 24 小时。证实了这些预测的临床相关性,在 SARS-CoV-2 感染后人类肺上皮细胞中鉴定的三个免疫特异性 mRNA-miRNA 关系也在 COVID-19 患者的血液中观察到差异表达。总体而言,mirTarRnaSeq 是一个强大的工具,可以解决广泛的生物学问题,提供 miRNA-mRNA 相互作用的改进预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7d3/9195306/a2c8ca3d978d/12864_2022_8558_Fig1_HTML.jpg

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