Editorial: RNA-Seq Analysis: Methods, Applications and Challenges

RNA-seq has revolutionized the research community approach to studying gene expression. Infact, this technology has opened up the possibility of quantifying the expression level of all genes atonce, allowing an ex post (rather than ex ante) selection of candidates that could be interesting for acertain study. The continuous drop in costs and the independence of library preparation protocolsfrom the model species, have convinced the stakeholders to invest in this technology, by creatingconsortia able to produce large disease-specific datasets that, in turn, fostered transcriptomicresearch at a population level. Among many others, a virtuous example in this sense is The CancerGenome Atlas. In a short time RNA-seq has moved from a technology to merely quantify the expression of genes to a powerful tool to: discover new transcripts (via de novo transcriptome assembly), characterize alternative splicing variants or new cell types (through single cell RNAsequencing). Leveraging on RNA-seq for daily diagnostic activities is no longer a dream but a consolidated reality.