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)+ 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.
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Acknowledgements
A.R.R.F. and S.M.G. are funded by the Australian National Health and Medical Research Council. A.R.R.F. is a C.J. Martin fellow (428261), and S.M.G. is a senior research fellow. N.C. is a University of Queensland postdoctoral fellow. G.J.F. and M.K.B. are supported by Australian Postgraduate awards. We acknowledge the Australian Research Council Centre for Functional and Applied Genomics Array Facility for expression profiling, and R. Nutter, G. Weightman and L. Stubberfield for support of this initiative.
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N.C. created and integrated the sequence mapping and visualization pipeline, performed SOLiD sequencing bioinformatics, SNP analysis and splicing studies. A.R.R.F. conceived and pioneered the SQRL library strategy, performed preliminary genomic analysis, and developed the initial visualization methods. G.K. led the array-SQRL analyses, RT-PCR, pathway analysis and contributed to SNP analysis. B.B.A.G., M.K.B., G.K. and N.C. contributed to method design. A.L.S., G.K., S.J.B. and A.C.P. contributed to sample generation. G.K., A.R.R.F. and B.B.A.G. constructed libraries. C.C.L., S.S.R., B.B.A.G., G.B. and K.J.M. contributed to library sequencing. N.C., G.K., G.J.F., A.R.R.F., S.M.G., D.F.T., H.E.P. and J.M.M. contributed to data analysis. G.K., A.J.R., S.W., N.C. and A.L.S. contributed to experimental validation. S.M.G. supervised the work and prepared the manuscript with N.C., G.K. and A.R.R.F.
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C.C.L., S.S.R., H.E.P., J.M.M. and K.J.M. are employed by Applied Biosystems, a manufacturer of DNA sequencing instrumentation and supplies.
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Supplementary Figures 1â13, Supplementary Tables 1â16, Supplementary Methods (PDF 3878 kb)
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Cloonan, N., Forrest, A., Kolle, G. et al. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat Methods 5, 613â619 (2008). https://doi.org/10.1038/nmeth.1223
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DOI: https://doi.org/10.1038/nmeth.1223
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