Facultad de Ciencias Agrarias, IBAM, Universidad Nacional de Cuyo, CONICET, Almirante Brown, Argentina.
Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo, Mendoza, Argentina.
Methods Mol Biol. 2021;2181:13-34. doi: 10.1007/978-1-0716-0787-9_2.
Computers are able to systematically exploit RNA-seq data allowing us to efficiently detect RNA editing sites in a genome-wide scale. This chapter introduces a very flexible computational framework for detecting RNA editing sites in plant organelles. This framework comprises three major steps: RNA-seq data processing, RNA read alignment, and RNA editing site detection. Each step is discussed in sufficient detail to be implemented by the reader. As a study case, the framework will be used with publicly available sequencing data to detect C-to-U RNA editing sites in the coding sequences of the mitochondrial genome of Nicotiana tabacum.
计算机能够系统地利用 RNA-seq 数据，使我们能够有效地在全基因组范围内检测 RNA 编辑位点。本章介绍了一种非常灵活的计算框架，用于检测植物细胞器中的 RNA 编辑位点。该框架包括三个主要步骤：RNA-seq 数据处理、RNA 读取比对和 RNA 编辑位点检测。每个步骤都有足够的细节讨论，以便读者实施。作为一个研究案例，该框架将与公开可用的测序数据一起使用，以检测烟草线粒体基因组编码序列中的 C 到 U RNA 编辑位点。
