Pfizer Worldwide Research and Development, Cambridge, MA, USA.
AbSci Inc, Vancouver, WA, USA.
Methods Mol Biol. 2021;2284:135-145. doi: 10.1007/978-1-0716-1307-8_8.
RNA-sequencing (RNA-seq) is a powerful technology for transcriptome profiling. While most RNA-seq projects focus on gene-level quantification and analysis, there is growing evidence that most mammalian genes are alternatively spliced to generate different isoforms that can be subsequently translated to protein molecules with diverse or even opposing biological functions. Quantifying the expression levels of these isoforms is key to understanding the genes biological functions in healthy tissues and the progression of diseases. Among open source tools developed for isoform quantification, Salmon, Kallisto, and RSEM are recommended based upon previous systematic evaluation of these tools using both experimental and simulated RNA-seq datasets. However, isoform quantification in practical RNA-seq data analysis needs to deal with many QC issues, such as the abundance of rRNAs in mRNA-seq, the efficiency of globin RNA depletion in whole blood samples, and potential sample swapping. To overcome these practical challenges, QuickIsoSeq was developed for large-scale RNA-seq isoform quantification along with QC. In this chapter, we describe the pipeline and detailed the steps required to deploy and use it to analyze RNA-seq datasets in practice. The QuickIsoSeq package can be downloaded from https://github.com/shanrongzhao/QuickIsoSeq.
RNA 测序（RNA-seq）是一种强大的转录组分析技术。虽然大多数 RNA-seq 项目都集中在基因水平的定量和分析上，但越来越多的证据表明，大多数哺乳动物基因都通过可变剪接产生不同的异构体，这些异构体可以进一步翻译为具有不同甚至相反生物学功能的蛋白质分子。定量这些异构体的表达水平对于理解基因在健康组织中的生物学功能以及疾病的进展至关重要。在为异构体定量开发的开源工具中，Salmon、Kallisto 和 RSEM 是基于之前使用实验和模拟 RNA-seq 数据集对这些工具进行的系统评估而推荐的。然而，在实际的 RNA-seq 数据分析中，异构体定量需要处理许多 QC 问题，例如 mRNA-seq 中 rRNA 的丰度、全血样本中珠蛋白 RNA 耗尽的效率以及潜在的样本交换。为了克服这些实际挑战，开发了 QuickIsoSeq 用于大规模 RNA-seq 异构体定量和 QC。在本章中，我们描述了该流程，并详细介绍了在实践中部署和使用它来分析 RNA-seq 数据集所需的步骤。QuickIsoSeq 包可从 https://github.com/shanrongzhao/QuickIsoSeq 下载。
