A comparison of analog and Next-Generation transcriptomic tools for mammalian studies

Abstract

This review focuses on tools for studying a cell's transcriptome, the collection of all RNA transcripts produced at a specific time, and the tools available for determining how these changes in gene expression relate to the functional changes in an organism. While the microarray-based (analog) gene-expression profiling technology has dominated the 'omics' era, Next-Generation Sequencing based gene-expression profiling (RNA-Seq) is likely to replace this analog technology in the future. RNA-Seq shows much promise for transcriptomic studies as the genes of interest do not have to be known a priori, new classes of RNA, SNPs and alternative splice variants can be detected, and it is also theoretically possible to detect transcripts from all biologically relevant abundance classes. However, the technology also brings with it new issues to resolve: the specific technical properties of RNA-Seq data differ to those of analog data, leading to novel systematic biases which must be accounted for when analysing this type of data. Additionally, multireads and splice junctions can cause problems when mapping the sequences back to a genome, and concepts such as cloud computing may be required because of the massive amounts of data generated.