Stem cell transcriptome profiling via massive-scale mRNA sequencing

Cloonan, N. et al. (2008) Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nature Methods, 5(7), pp. 613-619. (doi: 10.1038/nmeth.1223)

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Publisher's URL: http://dx.doi.org/10.1038/nmeth.1223

Abstract

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)<sup>+</sup> 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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Grimmond, Professor Sean
Authors: Cloonan, N., Forrest, A.R.R., Kolle, G., Gardiner, B.B.A., Faulkner, G.J., Brown, M.K., Taylor, D.F., Steptoe, A.L., Wani, S., Bethel, G., Robertson, A.J., Perkins, A.C., Bruce, S.J., Lee, C.C., Ranade, S.S., Peckham, H.E., Manning, J.M., McKernan, K.J., and Grimmond, S.M.
College/School:College of Medical Veterinary and Life Sciences > School of Cancer Sciences
Journal Name:Nature Methods
ISSN:1548-7091
ISSN (Online):1548-7105

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