Computational Biology, Faculty of Biology, CeBiTec, Bielefeld University, Bielefeld, Germany.
Methods Mol Biol. 2024;2792:241-250. doi: 10.1007/978-1-0716-3802-6_19.
RNA-seq data in publicly available repositories enable the efficient reanalysis of transcript abundances in existing experiments. Graphical user interfaces usually only allow the visual inspection of a single gene and of predefined experiments. Here, we describe how experiments are selected from the Sequence Read Archive or the European Nucleotide Archive, how data is efficiently mapped onto a reference transcriptome, and how global transcript abundances and patterns are inspected. We exemplarily apply this analysis pipeline to study the expression of photorespiration-related genes in photosynthetic organisms, such as cyanobacteria, and to identify conditions under which photorespiratory transcript abundances are enhanced.
在公共可用的存储库中,RNA-seq 数据可实现对现有实验中转录物丰度的高效重新分析。图形用户界面通常仅允许对单个基因和预定义实验进行可视化检查。在这里,我们描述了如何从序列读取档案或欧洲核苷酸档案中选择实验,如何将数据有效地映射到参考转录组上,以及如何检查全局转录物丰度和模式。我们举例说明了如何应用此分析管道来研究光合生物(如蓝细菌)中与光呼吸相关基因的表达,并确定增强光呼吸转录物丰度的条件。