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Nucleic Acids Research 2004 32(15):e120; doi:10.1093/nar/gnh116
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Published online 25 August 2004

Nucleic Acids Research, Vol. 32 No. 15 © Oxford University Press 2004; all rights reserved

RNA expression microarrays (REMs), a high-throughput method to measure differences in gene expression in diverse biological samples

Charles E. Rogler*, Tatyana Tchaikovskaya, Raquel Norel, Aldo Massimi1, Christopher Plescia2, Eugeny Rubashevsky, Paul Siebert3 and Leslie E. Rogler

Department of Medicine and Marion Bessin Liver Research Center, 1 Department of Molecular Genetics, Albert Einstein College of Medicine, Bronx, NY, USA, 2 Department of Neurosciences, Mt Sinai College of Medicine, New York, NY, USA and 3 BD Biosciences-Clontech, Palo Alto, CA, USA

* To whom correspondence should be addressed. Tel: +1 718 430 2607; Fax: +1 718 430 8975; Email: crogler{at}aecom.yu.edu

Received April 12, 2004; Revised June 4, 2004; Accepted July 30, 2004

We have developed RNA expression microarrays (REMs), in which each spot on a glass support is composed of a population of cDNAs synthesized from a cell or tissue sample. We used simultaneous hybridization with test and reference (housekeeping) genes to calculate an expression ratio based on normalization with the endogenous reference gene. A test REM containing artificial mixtures of liver cDNA and dilutions of the bacterial LysA gene cDNA demonstrated the feasibility of detecting transcripts at a sensitivity of four copies of LysA mRNA per liver cell equivalent. Furthermore, LysA cDNA detection varied linearly across a standard curve that matched the sensitivity of quantitative real-time PCR. In REMs with real samples, we detected organ-specific expression of albumin, Hnf-4 and Igfbp-1, in a set of mouse organ cDNA populations and c-Myc expression in tumor samples in paired tumor/normal tissue cDNA samples. REMs extend the use of classic microarrays in that a single REM can contain cDNAs from hundreds to thousands of cell or tissue samples each representing a specific physiological or pathophysiological state. REMs will extend the analysis of valuable samples by providing a common broad based platform for their analysis and will promote research aimed at defining gene functions, by broadening our understanding of their expression patterns in health and disease.


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