Introduction

The rapid development of next-generation sequencing (NGS) technologies has revolutionized theway genomic research can be conducted. Among all successful applications of the NGS technologies, RNA-Seq has become an important tool for transcriptome profiling (Wang et al., 2009). The transcriptome is the complete set of transcripts in a cell under any given developmental stage or physiological condition. Comprehensively detecting, cataloging, and quantifying all of the components in the transcriptome are grand challenges in molecular biology and functional genomics. For the past 15 years, microarray (Schena et al., 1995; Lockhart et al., 1996) has been the technology of choice for studying transcriptome. Despite that much insight has been gained from microarray studies, factors such as the requirement of genomic sequence information when designing probes and substantial noise caused by cross-hybridization limited the application of microarray in more in-depth study of the transcriptome.

In RNA-Seq experiments, a population of RNA is converted to a library of cDNA fragments with adaptors attached to one end. Each molecule, after amplification, is then sequenced using one of the NGS technologies. After sequencing, the resulting reads are aligned to either the reference genome or known transcripts to produce a genome-scale transcriptional profile. (See Figure 5.1 for an illustration of the RNA-Seq experiment). Compared with microarray, RNA-Seq is able to provide more information about the transcriptome and possesses a list of advantages discussed next.

High resolution. The resolution of microarray expression measure is unable to go beyond the probe level. In contrast, the majority of reads generated from NGS instruments map to the reference genome with single-base resolution.