title: RNA sequencing: current and prospective uses in metabolic research.
abstract: Previous global RNA analysis was restricted to known transcripts in species with a defined transcriptome. Next generation sequencing has transformed transcriptomics by making it possible to analyse expressed genes with an exon level resolution from any tissue in any species without any a priori knowledge of which genes that are being expressed, splice patterns or their nucleotide sequence. In addition, RNA sequencing is a more sensitive technique compared with microarrays with a larger dynamic range, and it also allows for investigation of imprinting and allele-specific expression. This can be done for a cost that is able to compete with that of a microarray, making RNA sequencing a technique available to most researchers. Therefore RNA sequencing has recently become the state of the art with regards to large-scale RNA investigations and has to a large extent replaced microarrays. The only drawback is the large data amounts produced, which together with the complexity of the data can make a researcher spend far more time on analysis than performing the actual experiment.
authors.affiliation: Diabetes and EndocrinologyDepartment of Clinical Sciences, Malmö University Hospital, CRC, Lund University, Building 60, Level 13, Entrance 72, S-205 02 Malmö, Skåne, Sweden petter.vikman@med.lu.se.
authors.forename: Petter
authors.initials: P
authors.lastname: Vikman
authors.affiliation: Diabetes and EndocrinologyDepartment of Clinical Sciences, Malmö University Hospital, CRC, Lund University, Building 60, Level 13, Entrance 72, S-205 02 Malmö, Skåne, Sweden.
authors.forename: Joao
authors.initials: J
authors.lastname: Fadista
authors.affiliation: Diabetes and EndocrinologyDepartment of Clinical Sciences, Malmö University Hospital, CRC, Lund University, Building 60, Level 13, Entrance 72, S-205 02 Malmö, Skåne, Sweden.
authors.forename: Nikolay
authors.initials: N
authors.lastname: Oskolkov
mesh_terms: D000483:Alleles; D000818:Animals; D019295:Computational Biology / Q000379:methods; D015870:Gene Expression; D018392:Genomic Imprinting; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D017423:Sequence Analysis, RNA / Q000379:methods / Q000639:trends; D014158:Transcription, Genetic; D059467:Transcriptome
keywords: RNA; gene expression; gene transcription; methodology; microarray; sequencing