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.

Graphical abstract

Keywords

RNA-Seq / mapping / reference-guided transcriptome assembly / differential expression analysis

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ABBREVIATIONS

RNA-Seq, high-throughput cDNA sequencing; NGS, next-generation sequencing; SIMD, single-instruction multiple-data; FM-index, full-text index in minute space; DEG, differentially expressed gene; DET, differentially expressed transcript; NB, negative binomial; SMRT, single molecule real-time; cDNA, complementary DNA; Iso-Seq, the isoform sequencing; RNA-FISH, fluorescent In Situ hybridization targeting ribonucleic acid molecules; FACS, fluorescence-activated cell sorting.

ACKNOWLEDGEMENTS

The authors would like to thank Ms. Jennifer Whitehead for critical reading of the manuscript. This work is supported by the National Health and Medical Research Council project grants (Nos. APP1067795 and APP1087889), National Basic Research Program of China (No. 2012CB316501) and National Natural Science Foundation of China (No. 31571310).

COMPLIANCE WITH ETHICS GUIDELINES

The authors Qiong-Yi Zhao, Jacob Gratten, Restuadi Restuadi and Xuan Li declare that they have no conflict of interest.

This article does not contain any studies with human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

2016 Higher Education Press and Springer-Verlag Berlin Heidelberg