If you are seeing this message, you may be experiencing temporary network problems. Please wait a few minutes and refresh the page. If the problem persists, you may wish to report it to your local Network Manager.
It is also possible that your web browser is not configured or not able to display style sheets. In this case, although the visual presentation will be degraded, the site should continue to be functional. We recommend using the latest version of Microsoft or Mozilla web browser to help minimise these problems.
Wiley InterScience | ||
![]() The Plant JournalVolume 49 Issue 3, Pages 565 - 577 Published Online: 20 Dec 2006 Journal compilation © 2010 Blackwell Publishing Ltd and the Society for Experimental Biology Published in association with the Society for Experimental Biology
Abstract | References | Full Text: HTML, PDF (Size: 708K) | Supporting Information | Related Articles | Citation Tracking TECHNICAL ADVANCE A high-performance, small-scale microarray for expression profiling of many samples in Arabidopsis–pathogen studies Copyright 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd KEYWORDS expression profiling • systems analysis • calibration probe • stable genes-based quantile normalization • statistical model ABSTRACTStudies of the behavior of biological systems often require monitoring of the expression of many genes in a large number of samples. While whole-genome arrays provide high-quality gene-expression profiles, their high cost generally limits the number of samples that can be studied. Although inexpensive small-scale arrays representing genes of interest could be used for many applications, it is challenging to obtain accurate measurements with conventional small-scale microarrays. We have developed a small-scale microarray system that yields highly accurate and reproducible expression measurements. This was achieved by implementing a stable gene-based quantile normalization method for array-to-array normalization, and a probe-printing design that allows use of a statistical model to correct for effects of print tips and uneven hybridization. The array measures expression values in a single sample, rather than ratios between two samples. This allows accurate comparisons among many samples. The array typically yielded correlation coefficients higher than 0.99 between technically duplicated samples. Accuracy was demonstrated by a correlation coefficient of 0.88 between expression ratios determined from this array and an Affymetrix GeneChip, by quantitative RT–PCR, and by spiking known amounts of specific RNAs into the RNA samples used for profiling. The array was used to compare the responses of wild-type, rps2 and ndr1 mutant plants to infection by a Pseudomonas syringae strain expressing avrRpt2. The results suggest that ndr1 affects a defense-signaling pathway(s) in addition to the RPS2-dependent pathway, and indicate that the microarray is a powerful tool for systems analyses of the Arabidopsis disease-signaling network. Received 3 August 2006; revised 26 September 2006; accepted 5 October 2006. |