Wang Yejun, Sun Ming-An, White Aaron P
Department of Cell Biology and Genetics, School of Basic Medicine, Shenzhen University Health Science Center, Shenzhen, P.R. China.
Epigenomics and Computational Biology Lab, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, USA.
Methods Mol Biol. 2018;1751:89-99. doi: 10.1007/978-1-4939-7710-9_6.
RNA-Seq has become a routine strategy for genome-wide gene expression comparisons in bacteria. Despite lower resolution in transcript border parsing compared with dRNA-Seq, TSS-EMOTE, Cappable-seq, Term-seq, and others, directional RNA-Seq still illustrates its advantages: low cost, quantification and transcript border analysis with a medium resolution (±10-20 nt). To facilitate mining of directional RNA-Seq datasets especially with respect to transcript structure analysis, we developed a tool, TrBorderExt, which can parse transcript start sites and termination sites accurately in bacteria. A detailed protocol is described in this chapter for how to use the software package step by step to identify bacterial transcript borders from raw RNA-Seq data. The package was developed with Perl and R programming languages, and is accessible freely through the website: http://www.szu-bioinf.org/TrBorderExt .
RNA测序已成为细菌全基因组基因表达比较的常规策略。尽管与dRNA测序、TSS-EMOTE、Cappable-seq、Term-seq等相比,在转录本边界解析方面分辨率较低,但定向RNA测序仍显示出其优势:成本低、具有中等分辨率(±10 - 20 nt)的定量和转录本边界分析。为便于挖掘定向RNA测序数据集,特别是在转录本结构分析方面,我们开发了一个工具TrBorderExt,它可以准确解析细菌中的转录起始位点和终止位点。本章详细介绍了如何逐步使用该软件包从原始RNA测序数据中识别细菌转录本边界。该软件包是用Perl和R编程语言开发的,可通过网站http://www.szu-bioinf.org/TrBorderExt免费获取。