Hoang Van L T, Tom Lisa N, Quek Xiu-Cheng, Tan Jean-Marie, Payne Elizabeth J, Lin Lynlee L, Sinnya Sudipta, Raphael Anthony P, Lambie Duncan, Frazer Ian H, Dinger Marcel E, Soyer H Peter, Prow Tarl W
Dermatology Research Centre, Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital, The University of Queensland, Brisbane, Queensland, Australia.
Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
PeerJ. 2017 Aug 21;5:e3631. doi: 10.7717/peerj.3631. eCollection 2017.
Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.
确定合适的内参基因（RGs）对于定量实时PCR（qPCR）实验中准确的数据解读至关重要。在本研究中，我们利用下一代RNA测序（RNA-seq）分析了一组非黑色素瘤皮肤癌病变的转录组，鉴定出在所有样本中均持续表达的基因。编码核糖体蛋白的基因是该数据集中最稳定的基因之一。使用qPCR对该RNA-seq数据进行验证，以确认一组高度稳定的基因用作qPCR内参基因的适用性。这些基因将为非黑色素瘤皮肤癌分析的qPCR数据标准化提供宝贵资源。
