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Journal of Biomedicine and Biotechnology
Volume 2010, Article ID 853916, 19 pages
http://dx.doi.org/10.1155/2010/853916
Review Article

Uncovering the Complexity of Transcriptomes with RNA-Seq

1Institute of Genetics and Biophysics “A. Buzzati-Traverso”, IGB-CNR, 80131 Naples, Italy
2Istituto per le Applicazioni del Calcolo “Mauro Picone”, IAC-CNR, 80131 Naples, Italy

Received 22 February 2010; Accepted 7 April 2010

Academic Editor: Momiao Xiong

Copyright © 2010 Valerio Costa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In recent years, the introduction of massively parallel sequencing platforms for Next Generation Sequencing (NGS) protocols, able to simultaneously sequence hundred thousand DNA fragments, dramatically changed the landscape of the genetics studies. RNA-Seq for transcriptome studies, Chip-Seq for DNA-proteins interaction, CNV-Seq for large genome nucleotide variations are only some of the intriguing new applications supported by these innovative platforms. Among them RNA-Seq is perhaps the most complex NGS application. Expression levels of specific genes, differential splicing, allele-specific expression of transcripts can be accurately determined by RNA-Seq experiments to address many biological-related issues. All these attributes are not readily achievable from previously widespread hybridization-based or tag sequence-based approaches. However, the unprecedented level of sensitivity and the large amount of available data produced by NGS platforms provide clear advantages as well as new challenges and issues. This technology brings the great power to make several new biological observations and discoveries, it also requires a considerable effort in the development of new bioinformatics tools to deal with these massive data files. The paper aims to give a survey of the RNA-Seq methodology, particularly focusing on the challenges that this application presents both from a biological and a bioinformatics point of view.