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Nucleic Acids Research, 2003, Vol. 31, No. 23 e153
© 2003 Oxford University Press

Article

Expression profiling via novel multiplex assay allows rapid assessment of gene regulation in defined signalling pathways

Eric Eldering*, C. Arnold Spek1, Hella L. Aberson1, Annette Grummels, Ingrid A. Derks, Alex F. de Vos1, Cathal J. McElgunn2 and Jan P. Schouten2

Department of Experimental Immunology and 1 Department of Experimental Internal Medicine, Academical Medical Center, Meibergdreef 9, 1105 AZ Amsterdam and 2 MRC-Holland, Amsterdam, The Netherlands

*To whom correspondence should be addressed. Tel: +31 20 5666076; Fax: +31 20 5669756; Email: e.eldering{at}amc.uva.nl
Present address:
Cathal J. McElgunn, Randox Laboratories Ltd, Crumlin, N. Ireland, UK

The current interest in expression of groups of functionally related genes creates a demand for novel experimental tools. We describe a multiplex ligation-dependent amplification procedure (RT-MLPA), which accurately quantifies up to 45 transcripts of interest in a one-tube assay. The output, a set of fluorescent DNA fragments, is analysed via capillary sequencer and spreadsheet software. The procedure is highly sensitive and reproducible over a 100-fold range of input RNA, with excellent compatibility with RT–PCR and microarrays. We targeted two comprehensive sets of human genes: 35 apoptosis regulators and 30 genes involved in inflammation. Both probe sets accurately assessed specific changes in gene expression in two relevant model systems. Stimulation of lymphocytes with various Toll-like receptor (TLR) ligands induced distinct inflammatory profiles. Furthermore, osteosarcoma cells treated with cytostatic drugs showed as primary response strong up-regulation of the apoptogenic p53-inducible PUMA transcript. Suppression by RNAi validated that indeed Puma expression was responsible for apoptosis induction. Thus, RT-MLPA enables relevant changes in transcription patterns to be quickly pinpointed and guide further experiments. This can be an advantage compared to hypothesis-free whole genome screens where large numbers of differentially expressed genes can obscure functional interpretation.


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