Mapping and quantifying mammalian transcriptomes by RNA-Seq

Nat Methods. 2008 Jul;5(7):621-8. doi: 10.1038/nmeth.1226. Epub 2008 May 30.

Abstract

We have mapped and quantified mouse transcriptomes by deeply sequencing them and recording how frequently each gene is represented in the sequence sample (RNA-Seq). This provides a digital measure of the presence and prevalence of transcripts from known and previously unknown genes. We report reference measurements composed of 41-52 million mapped 25-base-pair reads for poly(A)-selected RNA from adult mouse brain, liver and skeletal muscle tissues. We used RNA standards to quantify transcript prevalence and to test the linear range of transcript detection, which spanned five orders of magnitude. Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3' untranscribed regions, as well as new candidate microRNA precursors. RNA splice events, which are not readily measured by standard gene expression microarray or serial analysis of gene expression methods, were detected directly by mapping splice-crossing sequence reads. We observed 1.45 x 10(5) distinct splices, and alternative splices were prominent, with 3,500 different genes expressing one or more alternate internal splices.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • 3' Untranslated Regions
  • Algorithms
  • Alternative Splicing
  • Animals
  • Brain / metabolism
  • Chromosome Mapping / methods
  • Databases, Nucleic Acid
  • Exons
  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / statistics & numerical data
  • Liver / metabolism
  • Mice
  • Mice, Inbred C57BL
  • Muscle, Skeletal / metabolism
  • Oligonucleotide Array Sequence Analysis
  • Promoter Regions, Genetic
  • RNA / genetics*
  • RNA Splicing
  • RNA, Messenger / genetics
  • RNA, Messenger / metabolism
  • Sensitivity and Specificity
  • Sequence Analysis, RNA / methods*
  • Sequence Analysis, RNA / statistics & numerical data
  • Software

Substances

  • 3' Untranslated Regions
  • RNA, Messenger
  • RNA