Assessment of normalization strategies for quantitative RT-PCR using microdissected tissue samples

Abstract

Gene expression measurement techniques such as quantitative reverse transcriptase (qRT)-PCR require a normalization strategy to allow meaningful comparisons across biological samples. Typically, this is accomplished through the use of an endogenous housekeeping gene that is presumed to show stable expression levels in the samples under study. There is concern regarding how precisely specific genes can be measured in limited amounts of mRNA such as those from microdissected (MD) tissues. To address this issue, we evaluated three different approaches for qRT-PCR normalization of dissected samples; cell count during microdissection, total RNA measurement, and endogenous control genes. The data indicate that both cell count and total RNA are useful in calibrating input amounts at the outset of a study, but do not provide enough precision to serve as normalization standards. However, endogenous control genes can accurately determine the relative abundance of a target gene relative to the entire cellular transcriptome. Taken together, these results suggest that precise gene expression measurements can be made from MD samples if the appropriate normalization strategy is employed.

ADAM12 and ADAM17 Gene Expression in Laser-capture Microdissected and Non-microdissected Breast Tumors

“…Smaller ΔC T , less difference between the reference and interest gene expression, resulting in an increased expression of the target gene (smaller ΔC T , higher target gene expression); **cancers (n=34), benign tumors (n=15), non-tumor (n=20); *** cancers (n=50), benign tumors (n=10), non-tumor (n=30) between samples, irrespective the type of processed samples. Our results regarding the amount and the purity of the RNA (measured spectrophotometrically) and RNA integrity number (RIN) (quantified on RNA electrophoregrams) obtained from LCM samples were comparable with other studies [32,35,36].…”

Twenty-Five Years of Quantitative PCR for Gene Expression Analysis

“…Additionally, transcription of these genes is generally resistant to experimental conditions, making them suitable endogenous controls for single-gene normalization (52,55). The use of a single gene for data normalization can decrease cost and increase throughput, and is a standard approach for normalizing qPCR (52,53,56,57). It is only accurate, however, if the above requirements are satisfied.…”

Selection of reference genes for real-time PCR in human hepatocellular carcinoma tissues

“…Expression of the housekeeping gene (HKG) is run in parallel with qRT-PCR detection of genes that change expression levels due to experimental conditions. HKG expression is superior to other qRT-PCR normalization standards, such as cell count and total RNA levels (Erickson et al 2007).…”