mRNA-Seq whole-transcriptome analysis of a single cell

  • Nat Methods. 2009 May;6(5):377-82. doi: 10.1038/nmeth.1315.
Fuchou Tang  1 ,  Catalin Barbacioru ,  Yangzhou Wang ,  Ellen Nordman ,  Clarence Lee ,  Nanlan Xu ,  Xiaohui Wang ,  John Bodeau ,  Brian B Tuch ,  Asim Siddiqui ,  Kaiqin Lao ,  M Azim Surani
Affiliations
  • 1. Wellcome Trust-Cancer Research UK Gurdon Institute of Cancer and Developmental Biology, University of Cambridge, Cambridge, UK.
PMID: 19349980 DOI: 10.1038/nmeth.1315
Abstract

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.