Division of Biostatistics and Computational Biology, College of Dentistry, University of Iowa, Iowa City, IA, USA.
McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Methods Mol Biol. 2022;2418:405-424. doi: 10.1007/978-1-0716-1920-9_22.
With the ability to obtain several millions of reads per sample, high-throughput RNA sequencing (RNA-Seq) enables investigation of any transcriptome at a fine resolution. Not just the messenger RNA (mRNA), but a wide variety of different RNA populations (e.g., total RNA, microRNA, long ncRNA, pre-mRNA) can also be investigated using RNA-Seq. While facilitating accurate quantification of gene expression, RNA-Seq offers the opportunity to estimate abundance of isoforms and find novel transcripts and allele-specific transcripts. In this chapter, we describe a protocol to construct an RNA-Seq library for sequencing on Illumina NGS platforms and a computational pipeline to perform RNA-Seq data analysis. The protocols described in this chapter can be applied to the analysis of differential gene expression in control versus 17β-estradiol treatment of in vivo or in vitro systems.
高通量 RNA 测序（RNA-Seq）能够获得每个样本数百万个读数，具有出色的能力，可实现对任何转录组的精细解析。不仅信使 RNA（mRNA），还可以使用 RNA-Seq 研究各种不同的 RNA 群体（例如，总 RNA、microRNA、长 ncRNA、前体 RNA）。RNA-Seq 不仅有助于准确量化基因表达，还提供了估计异构体丰度和发现新转录本和等位基因特异性转录本的机会。在本章中，我们描述了一种用于在 Illumina NGS 平台上进行测序的 RNA-Seq 文库构建方案和一个用于执行 RNA-Seq 数据分析的计算流程。本章中描述的方案可应用于在体或体外系统中 17β-雌二醇处理的对照与处理之间的差异基因表达分析。
