当前位置: X-MOL 学术Nat. Protoc. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal.
Nature Protocols ( IF 14.8 ) Pub Date : 2020-01-29 , DOI: 10.1038/s41596-019-0279-7
Claudio Lo Giudice 1 , Marco Antonio Tangaro 1 , Graziano Pesole 1, 2, 3 , Ernesto Picardi 1, 2, 3
Affiliation  

RNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at https://github.com/BioinfoUNIBA/REDItools.

中文翻译:

使用REDItools和REDIportal研究深度转录组数据集中的RNA编辑。

RNA编辑是一种广泛的转录后机制,能够通过插入/缺失或碱基取代来修饰转录本。它在哺乳动物中很显着,其中ADAR酶家族的成员将数百万个腺苷脱氨为肌苷。A对I RNA编辑具有多种生物学功能,但是在大规模转录组数据集中进行检测仍然是一项尚未解决的计算任务。为此,我们开发了REDItools,这是第一个专门用于RNA测序(RNAseq)数据中的RNA编辑分析的软件包。它已成功用于人类转录组中,证明了RNA编辑的组织和细胞类型特异性以及其普遍性。大规模REDItools对人RNAseq数据进行分析的结果已在我们专门的REDIportal数据库中收集,其中包含超过4个。500万个事件。在此,我们根据计算资源REDItools和REDIportal详细描述两种生物信息学程序。在第一个步骤中,我们概述了检测人类细胞系NA12878中RNA编辑的工作流程,该过程具有转录组和整个基因组数据。在第二个过程中,我们展示了如何在亨廷顿病捐赠者的验尸大脑样本中的特定编码位点识别失调的编辑。在运行Linux且具有≥32 GB随机存取内存(RAM)的64位计算机上,两个过程都应花费约76小时,使用4至24个内核。我们的协议旨在利用可用的转录组和/或基因组读数来研究不同生物体中的RNA编辑。可通过https://github.com/BioinfoUNIBA/REDItools获得完成过程和docker映像的脚本。在此,我们根据计算资源REDItools和REDIportal详细描述两种生物信息学程序。在第一个步骤中,我们概述了检测人类细胞系NA12878中RNA编辑的工作流程,该过程具有转录组和整个基因组数据。在第二个过程中,我们展示了如何在亨廷顿病捐赠者的验尸大脑样本中的特定编码位点识别失调的编辑。在运行Linux且具有≥32 GB随机存取内存(RAM)的64位计算机上,两个过程都应花费约76小时,使用4至24个内核。我们的协议旨在利用可用的转录组和/或基因组读数来研究不同生物体中的RNA编辑。可通过https://github.com/BioinfoUNIBA/REDItools获得完成过程和docker映像的脚本。在此,我们根据计算资源REDItools和REDIportal详细描述两种生物信息学程序。在第一个步骤中,我们概述了检测人类细胞系NA12878中RNA编辑的工作流程,该过程具有转录组和整个基因组数据。在第二个过程中,我们展示了如何在亨廷顿病捐赠者的验尸大脑样本中的特定编码位点识别失调的编辑。在运行Linux且具有≥32 GB随机存取内存(RAM)的64位计算机上,两个过程都应花费约76小时,使用4至24个内核。我们的协议旨在利用可用的转录组和/或基因组读数来研究不同生物体中的RNA编辑。可通过https://github.com/BioinfoUNIBA/REDItools获得完成过程和docker映像的脚本。
更新日期:2020-01-29
down
wechat
bug