RNA profiling for biomarker discovery: Practical considerations for limiting sample sizes

Article type: Research Article

Authors: Kelly, Danny J. | Ghosh, Sujoy

Affiliations: Genetics Research, GlaxoSmithKline R&D, Research Triangle Park, NC 27709, USA

Note: [] Corresponding author: Dr. Sujoy Ghosh, GlaxoSmithKline, 5 Moore Drive, RTP, NC 27709, USA. E-mail: sg45653@gsk.com

Abstract: We have compared microarray data generated on Affymetrix™ chips from standard (8 micrograms) or low (100 nanograms) amounts of total RNA. We evaluated the gene signals and gene fold-change estimates obtained from the two methods and validated a subset of the results by real time, polymerase chain reaction assays. The correlation of low RNA derived gene signals to gene signals obtained from standard RNA was poor for less to moderately abundant genes. Genes with high abundance showed better correlation in signals between the two methods. The signal correlation between the low RNA and standard RNA methods was improved by including a reference sample in the microarray analysis. In contrast, the fold-change estimates for genes were better correlated between the two methods regardless of the magnitude of gene signals. A reference sample based method is suggested for studies that would end up comparing gene signal data from a combination of low and standard RNA templates; no such referencing appears to be necessary when comparing fold-changes of gene expression between standard and low template reactions.

Keywords: data comparability, submicrogram RNA, low template amplification, reference sample, gene expression

Journal: Disease Markers, vol. 21, no. 1, pp. 43-48, 2005