mRNA-Seq Whole-Transcriptome Analysis of a Single Cell

Article abstract

Nature Methods 6, 377 – 382 (2009)

Published online: 6 April 2009 | Corrected online: 19 April 2009 | doi:10.1038/nmeth.1315

Fuchou Tang1,3, Catalin Barbacioru2,3, Yangzhou Wang2, Ellen Nordman2, Clarence Lee2, Nanlan Xu2, Xiaohui Wang2, John Bodeau2, Brian B Tuch2, Asim Siddiqui2, Kaiqin Lao2 & M Azim Surani1


Next-generation sequencing technology is a powerful tool for transcriptome analysis. However, under certain conditions, only a small amount of material is available, which requires more sensitive techniques that can preferably be used at the single-cell level. Here we describe a single-cell digital gene expression profiling assay. Using our mRNA-Seq assay with only a single mouse blastomere, we detected the expression of 75% (5,270) more genes than microarray techniques and identified 1,753 previously unknown splice junctions called by at least 5 reads. Moreover, 8–19% of the genes with multiple known transcript isoforms expressed at least two isoforms in the same blastomere or oocyte, which unambiguously demonstrated the complexity of the transcript variants at whole-genome scale in individual cells. Finally, for Dicer1-/- and Ago2-/- (Eif2c2-/-) oocytes, we found that 1,696 and 1,553 genes, respectively, were abnormally upregulated compared to wild-type controls, with 619 genes in common.

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  1. Wellcome Trust–Cancer Research UK Gurdon Institute of Cancer and Developmental Biology, University of Cambridge, Cambridge, UK.
  2. Molecular Cell Biology Division, Applied Biosystems, Foster City, California, USA.
  3. These authors contributed equally to this work.

Correspondence to: M Azim Surani1 e-mail: as10021@mole.bio.cam.ac.uk

Correspondence to: Kaiqin Lao2 e-mail: laokq@appliedbiosystems.com

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