Transcriptional profiling of tissue plasticity: role of shifts in gene expression and technical limitations

Fluck, M., Dapp, C., Schmutz, S., Wit, E. and Hoppeler, H. (2005) Transcriptional profiling of tissue plasticity: role of shifts in gene expression and technical limitations. Journal of Applied Physiology, 99, pp. 397-413. (doi: 10.1152/japplphysiol.00050.2005)

Abstract

Reprogramming of gene expression has been recognized as a main instructive modality for the adjustments of tissues to various kinds of stress. The recent application of gene expression profiling has provided a powerful tool to elucidate the molecular pathways underlying such tissue remodeling. However, the biological interpretations of expression profiling results critically depend on normalization of transcript signals to mRNA standards before statistical evaluation. A hypothesis is proposed whereby the “fluctuating nature” of gene expression represents an inherent limitation of the test system used to quantify RNA levels. Misinterpretation of gene expression data occurs when RNA quantities are normalized to a subset of mRNAs that are subject to strong regulation. The contention of contradictory biological outcomes using different RNA-normalization schemes is demonstrated in two models of skeletal muscle plasticity with data from custom-designed microarrays and biochemical and ultrastructural evidence for correspondingly altered RNA content and nucleolar activity. The prevalence of these biological constraints is underlined by a literature survey in different models of tissue plasticity with emphasis on the unique malleability of skeletal muscle. Finally, recommendations on the optimal experimental layout are given to control biological and technical variability in microarray and RT-PCR studies. It is proposed to approach normalization of transcript signals by measuring total RNA and DNA content per sample weight and by correcting for concurrently estimated endogenous standards such as major ribosomal RNAs and spiked RNA and DNA species. This allows for later conversion to diverse tissue-relevant references and should improve the physiological interpretations of phenotypic plasticity.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: UNSPECIFIED
• Authors: Fluck, M., Dapp, C., Schmutz, S., Wit, E., and Hoppeler, H.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Journal of Applied Physiology
• ISSN: 8750-7587
• ISSN (Online): 1522-1601