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利用链特异性RNA测序数据对植物中长链非编码RNA进行基于参考的鉴定

Reference-Based Identification of Long Noncoding RNAs in Plants with Strand-Specific RNA-Sequencing Data.

作者信息

Lin Xiao, Ni Meng, Xiao Zhixia, Chan Ting-Fung, Lam Hon-Ming

机构信息

School of Life Sciences and Center for Soybean Research of the Partner State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, China.

出版信息

Methods Mol Biol. 2019;1933:245-255. doi: 10.1007/978-1-4939-9045-0_14.

Abstract

Long noncoding RNAs (lncRNAs) have been shown to play important roles in various organisms, including plant species. Several tools and pipelines have emerged for lncRNA identification, including reference-based transcriptome assembly pipelines and various coding potential calculating tools. In this protocol, we have integrated some of the most updated computational tools and described the procedures step-by-step for identifying lncRNAs from plant strand-specific RNA-sequencing datasets. We will start from clean RNA-sequencing reads, followed by reference-based transcriptome assembly, filtering of known genes, and lncRNA prediction. At the end point, users will obtain a set of predicted lncRNAs for downstream use.

摘要

长链非编码RNA(lncRNA)已被证明在包括植物物种在内的各种生物体中发挥重要作用。已经出现了几种用于lncRNA鉴定的工具和流程,包括基于参考的转录组组装流程和各种编码潜力计算工具。在本方案中,我们整合了一些最新的计算工具,并逐步描述了从植物链特异性RNA测序数据集中鉴定lncRNA的程序。我们将从干净的RNA测序读段开始,接着进行基于参考的转录组组装、已知基因过滤和lncRNA预测。最终,用户将获得一组用于下游分析的预测lncRNA。

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