Use of RNA amplification in the optimal characterization of global gene expression using cDNA microarrays

✍ Scribed by Radka Stoyanova; John J. Upson; Christos Patriotis; Eric A. Ross; Elizabeth P. Henske; Ketaki Datta; Bruce Boman; Margie L. Clapper; Alfred G. Knudson; Alfonso Bellacosa

• Publisher: John Wiley and Sons
• Year: 2004
• Tongue: English
• Weight: 143 KB
• Volume: 201
• Category: Article
• ISSN: 0021-9541
• DOI: 10.1002/jcp.20074

✦ Synopsis

Abstract

Microarray analysis of human tissue is frequently hindered by the limited amount of RNA available. Although amplification protocols can be utilized, the relative representation of transcripts present in the starting material must remain unaltered. In this study, 200 ng of total RNA derived from cultured renal epithelial cells from tuberous sclerosis complex (TSC) carriers and control individuals was amplified by in vitro transcription with T7 RNA polymerase. The resulting Cy‐labeled cDNAs (from total or amplified RNA (aRNA)) were analyzed as direct replicates and dye‐flips on slides containing 10,000 human cDNAs. The Pearson correlation coefficients for the direct replicate experiments were 0.80 (20 μg total RNA), 0.85 (40 μg total RNA), and 0.93 (2 μg of aRNA). Comparisons between the array data revealed that the majority of genes expressed in total RNA (97% for 20 μg and 85% for 40 μg) were also detected in aRNA. The correlation coefficient of the expression ratios for genes detected in both total RNA (40 μg) and aRNA was 0.63. Further, Student's t‐test indicated no significant difference (P = 0.83) between these ratios. These results indicate that the number of expressed genes detected with total RNA is proportional to the amount of RNA used and underscore the requirement of large amounts of total RNA for a comprehensive characterization of gene expression profiles. RNA amplification allows the detection of a large number of genes expressed in the starting RNA population without altering their relative intensities significantly. Thus, an RNA amplification step improves the quality of gene expression results obtained by microarray analysis. This study indicates that high quality microarray data can be generated from small amounts of RNA, including those extracted from limiting clinical samples and microdissected histological specimens. © 2004 Wiley‐Liss, Inc.