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Nucleic Acids Research Advance Access originally published online on October 27, 2006
Nucleic Acids Research 2006 34(21):e143; doi:10.1093/nar/gkl740
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Nucleic Acids Research, 2006, Vol. 34, No. 21 e143
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Methods Online

Gene expression profiling of single cells on large-scale oligonucleotide arrays

Claudia H. Hartmann and Christoph A. Klein*

Institut für Immunologie, Ludwig-Maximilians Universität Goethestr. 31, 80336 München, Germany

*To whom correspondence should be addressed. Tel/Fax: +49 89 218075696; Email: christoph.klein{at}med.uni-muenchen.de

Received July 10, 2006. Revised September 6, 2006. Accepted September 25, 2006.

Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells.


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