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 Massimi, Christopher Plescia, Eugeny Rubashevsky, Paul Siebert, Leslie E. Rogler

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)e120
JournalNucleic acids research
Volume32
Issue number15
DOIs
StatePublished - 2004

ASJC Scopus subject areas

  • Genetics

Fingerprint

Dive into the research topics of 'RNA expression microarrays (REMs), a high-throughput method to measure differences in gene expression in diverse biological samples.'. Together they form a unique fingerprint.

Cite this