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Nucleic Acids Research 2005 33(13):e111; doi:10.1093/nar/gni104
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Published online 19 July 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oupjournals.org

Methods Online

Cell-type-specific transcriptomics in chimeric models using transcriptome-based masks

Felix Naef1,2 and Joerg Huelsken1,*

1Swiss Institute for Experimental Cancer Research (ISREC), NCCR Molecular Oncology Chemin des Boveresses 155, 1066 Epalinges, Switzerland 2Swiss Institute of Bioinformatics Chemin des Boveresses 155, 1066 Epalinges, Switzerland

*To whom correspondence should be addressed. Tel: +41 (0)21 692 58 58; Fax: +41 (0)21 652 69 33; Email: joerg.huelsken{at}isrec.ch

Received March 29, 2005. Revised June 13, 2005. Accepted June 13, 2005.

Regulatory networks involving different cell types control inflammation, morphogenesis and tissue homeostasis. Cell-type-specific transcriptional profiling offers a powerful tool for analyzing such cross-talk but is often hampered by mingling of cells within a tissue. Here, we present a novel method that performs cell-type-specific expression measurements without prior cell separation. This involves inter-species transplantation or chimeric co-culture models among which the human mouse system is frequently used. Here, we exploit the sufficiently divergent transcriptomes of human and mouse in conjunction with high-density oligonucleotide arrays. This required a masking procedure based on transcriptome databases and exhaustive fuzzy mapping of oligonucleotide probes onto these data. The approach was tested in a human–mouse experiment, demonstrating that we can efficiently measure species-specific transcriptional profiles in chimeric RNA samples without physically separating cells. Our results stress the importance of transcriptome databases with accurate 3' mRNA termination for computational prediction of accurate probe masks. We find that most human and mouse 3'-untranslated region contain unique stretches to allow for an effective control of cross-hybridization between the two species. This approach can be applied to xenograft models studying tumor–host interactions, morphogenesis or immune responses.


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