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01-01-2012 | Original Article

Validation of reference genes for estimating wound age in contused rat skeletal muscle by quantitative real-time PCR

Authors: Jun-hong Sun, Liang-huan Nan, Cai-rong Gao, Ying-yuan Wang

Published in: International Journal of Legal Medicine | Issue 1/2012

Abstract

Gene expression profiling by quantitative real-time PCR (RT-qPCR) is a valuable tool in forensic science for estimating the age of a wound. To accurately assess gene expression levels over time in injured tissue, the genes used as internal reference standards must be carefully validated for transcriptional stability. This study examined the transcriptional stability of nine potential reference genes (β-actin, GAPDH, RPL32, PGK1, SDHA, RPL13, HPRT, Tbp, and Ywhaz) in contused rat skeletal muscle by RT-qPCR. The raw Ct values were determined for each candidate gene at different time points following contusion, and the data were analyzed by the NormFinder, geNorm, and BestKeeper validation programs. The reference genes RPL13 and RPL32 were the most stably expressed genes in contused skeletal muscle, whereas PGK1 was the least stable. The commonly used reference genes β-actin and GAPDH appeared to be too unstable for normalization of RT-qPCR expression profiling in contused muscle. The reference genes RPL13 and RPL32 were also the best combination for multianalysis. The use of RPL13 and RPL32 as internal standards may improve the accuracy of gene expression studies aimed at determining the age of early wounds in forensic investigations.

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Title: Validation of reference genes for estimating wound age in contused rat skeletal muscle by quantitative real-time PCR
Authors: Jun-hong Sun
Liang-huan Nan
Cai-rong Gao
Ying-yuan Wang
Publication date: 01-01-2012
Publisher: Springer-Verlag
Published in: International Journal of Legal Medicine / Issue 1/2012
Print ISSN: 0937-9827
Electronic ISSN: 1437-1596
DOI: https://doi.org/10.1007/s00414-011-0604-3

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Validation of reference genes for estimating wound age in contused rat skeletal muscle by quantitative real-time PCR

Abstract

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Abstract

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