Mapping and differential expression analysis from short‐read RNA‐Seq data in model organisms

Abstract

Recent advances in next‐generation sequencing technology allow high‐throughput RNA sequencing (RNA‐Seq) to be widely applied in transcriptomic studies. For model organisms with a reference genome, the first step in analysis of RNA‐Seq data involves mapping of short‐read sequences to the reference genome. Reference‐guided transcriptome assembly is an optional step, which is recommended if the aim is to identify novel transcripts. Following read mapping, the primary interest of biologists in many RNA‐Seq studies is the investigation of differential expression between experimental groups. In this review, we discuss recent developments in RNA‐Seq data analysis applied to model organisms, including methods and algorithms for direct mapping, reference‐guided transcriptome assembly and differential expression analysis, and provide insights for the future direction of RNA‐Seq.