Identification of Reference Genes for Quantitative Expression Analysis Using Large-scale RNA-seq Data of Arabidopsis thaliana and Model Crop Plants

In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Recently emerging RNA sequencing (RNA-seq) provides an ideal source for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. Through the use of this method, we report the results of comprehensive exploration of reference genes using public RNA-seq data of plants such as Arabidopsis thaliana (arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato), and Oryza sativa(rice). By selecting genes showing stable expression in broader experimental conditions as possible, 13, 10, 12, and 21 top candidates for reference genes were proposed in arabidopsis, soybean, tomato, and rice, respectively. These novel reference genes will be useful to analyze the gene expression profile across experiments designed with various experimental conditions.

   This study was supported in part by MEXT Grants-in-Aid for Scientific Research on Innovative Areas (No. 26113716 to K.Y., No. 23113006 to G.S., K.S., M.W., No. 23113005 to M.M., No. 23113001 to G.S., M.W., M.M.); Scientific Research (A) (No. 25252001 to M.W.) from the Japan Society for Promotion of Science (JSPS); MEXT-Supported Program for the Strategic Research Foundation at Private Universities (2014-2018); and Research Funding for Computational Software Supporting Program from Meiji University to K.Y.. Computations were partially performed on the NIG supercomputer at ROIS National Institute of Genetics.