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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. [PUBLICATION ABSTRACT]

Details

Title
mRNA-Seq whole-transcriptome analysis of a single cell
Author
Tang, Fuchou; Barbacioru, Catalin; Wang, Yangzhou; Nordman, Ellen; Lee, Clarence; Xu, Nanlan; Wang, Xiaohui; Bodeau, John; Tuch, Brian B; Siddiqui, Asim; Lao, Kaiqin; Surani, M Azim
Pages
377-82
Publication year
2009
Publication date
May 2009
Publisher
Nature Publishing Group
ISSN
15487091
e-ISSN
15487105
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
223251647
Copyright
Copyright Nature Publishing Group May 2009