Literature DB >> 22535878

Per-unit-living tissue normalization of real-time RT-PCR data in ischemic rat hearts.

S Ellefsen1, M Bliksøen, A Rutkovskiy, I B Johansen, M-L Kaljusto, G E Nilsson, J I Vaage, K-O Stensløkken.   

Abstract

In studies of gene expression in acute ischemic heart tissue, internal reference genes need to show stable expression per-unit-living tissue to hinder dead cells from biasing real-time RT-PCR data. Until now, this important issue has not been appropriately investigated. We hypothesized that the expression of seven internal reference genes would show stable per-unit-living tissue expression in Langendorff-perfused rat hearts subjected to ischemia-reperfusion. This was found for cyclophilin A, GAPDH, RPL-32, and PolR2A mRNA, with GAPDH showing the highest degree of stability (R = 0.11), suggesting unchanged rates of mRNA transcription in live cells and complete degradation of mRNA from dead cells. The infarct size-dependent degradation of GAPDH was further supported by a close correlation between changes in GAPDH mRNA and changes in RNA quality measured as RNA integrity number (R = 0.90, P < 0.05). In contrast, β-actin and 18S rRNA showed stable expression per-unit-weight tissue and a positive correlation with infarct size (R = 0.61 and R = 0.77, P < 0.05 for both analyses). The amount of total RNA extracted per-unit-weight tissue did not differ between groups despite wide variation in infarct size (7.1-50.1%). When β-actin expression was assessed using four different normalization strategies, GAPDH and geNorm provided appropriate per-unit-living expression, while 18S and total RNA resulted in marked underestimations. In studies of ischemic tissues, we recommend using geometric averaging of carefully selected reference genes for normalization of real-time RT-PCR data. A marked shift in the mRNA/rRNA ratio renders rRNA as useless for normalization purposes.

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Year:  2012        PMID: 22535878     DOI: 10.1152/physiolgenomics.00004.2012

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  6 in total

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  6 in total

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