Principles of transcriptome analysis and gene expression quantification: an RNA-seq tutorial

Genome-wide analyses and high-throughput screening was long reserved for biomedical applications and genetic model organisms. With the rapid development of massively parallel sequencing nanotechnology (or next-generation sequencing) and simultaneous maturation of bioinformatic tools, this situation has dramatically changed. Genome-wide thinking is forging its way into disciplines like evolutionary biology or molecular ecology that were historically confined to small-scale genetic approaches. Accessibility to genome-scale information is transforming these fields, as it allows us to answer long-standing questions like the genetic basis of local adaptation and speciation or the evolution of gene expression profiles that until recently were out of reach. Many in the eco-evolutionary sciences will be working with large-scale genomic data sets, and a basic understanding of the concepts and underlying methods is necessary to judge the work of others. Here, I briefly introduce next-generation sequencing and then focus on transcriptome shotgun sequencing (RNA-seq). This article gives a broad overview and provides practical guidance for the many steps involved in a typical RNA-seq work flow from sampling, to RNA extraction, library preparation and data analysis. I focus on principles, present useful tools where appropriate and point out where caution is needed or progress to be expected. This tutorial is mostly targeted at beginners, but also contains potentially useful reflections for the more experienced.