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

Quantitative Biology March 2016, Volume 4, Issue 1, pp 22–35 | Cite as Mapping and differential expression analysis from short-read RNA-Seq data in model organisms AuthorsAuthors and affiliations Qiong-Yi ZhaoJacob GrattenRestuadi RestuadiXuan Li Review First Online: 04 March 2016 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. Open image in new window KeywordsRNA-Seq mapping reference-guided transcriptome assembly differential expression analysis  This article is dedicated to the Special Collection of Recent Advances in Next-Generation Bioinformatics (Ed. Xuegong Zhang). Download to read the full article text References 1. Wang, E. T., Sandberg, R., Luo S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P. and Burge, C. B. (2008) Alternative isoform regulation in human tissue transcriptomes. Nature, 456, 470–476PubMedPubMedCentralCrossRefGoogle Scholar 2. Wang, Z., Gerstein, M. and Snyder, M. (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. 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