RNA-seq reveals more consistent reference genes for gene expression studies in human non-melanoma skin cancers

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ID: 99334
2017
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Abstract
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.
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hoang2017rnaseqpeerj Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Van L.T. Hoang, Lisa N. Tom, Xiu-Cheng Quek, Jean-Marie Tan, Elizabeth J. Payne, Lynlee L. Lin, Sudipta Sinnya, Anthony P. Raphael, Duncan Lambie, Ian H. Frazer, Marcel E. Dinger, H. Peter Soyer, Tarl W. Prow
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Journal PeerJ
Year 2017
DOI
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URL
https://peerj.com/articles/3631.pdf
Keywords
Medicine personnel management. employment management

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