Stem cell transcriptome profiling via massive-scale mRNA sequencing

N. Cloonan, A.R. Forrest, G. Kolle, B.B. Gardiner, G.J. Faulkner, M.K. Brown, D.F. Taylor, A.L. Steptoe, S. Wani, G. Bethel, A.J. Robertson, A.C. Perkins, S.J. Bruce, C.C. Lee, S.S. Ranade, H.E. Peckham, J.M. Manning, K.J. McKernan, S.M. Grimmond

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

We developed a massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, to survey the complexity, dynamics and sequence content of transcriptomes in a near-complete fashion. This method generates directional, random-primed, linear cDNA libraries that are optimized for next-generation short-tag sequencing. We surveyed the poly(A)(+) transcriptomes of undifferentiated mouse embryonic stem cells (ESCs) and embryoid bodies (EBs) at an unprecedented depth (10 Gb), using the Applied Biosystems SOLiD technology. These libraries capture the genomic landscape of expression, state-specific expression, single-nucleotide polymorphisms (SNPs), the transcriptional activity of repeat elements, and both known and new alternative splicing events. We investigated the impact of transcriptional complexity on current models of key signaling pathways controlling ESC pluripotency and differentiation, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that our understanding of transcriptional complexity is far from complete.
Original languageUndefined/Unknown
Pages (from-to)613-619
Number of pages7
JournalNature Methods
Issue number7
Publication statusPublished - 2008

Keywords / Materials (for Non-textual outputs)

  • Animals Cell Differentiation Embryonic Stem Cells/cytology/ metabolism Expressed Sequence Tags Gene Expression Profiling/ methods/statistics & numerical data Gene Library Mice Pluripotent Stem Cells/cytology/metabolism Polymorphism, Single Nucleotide RNA, Messenger/ genetics Sensitivity and Specificity Sequence Analysis, RNA/ methods Signal Transduction

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