Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of arabidopsis thaliana and model crop plants

Toru Kudo, Yohei Sasaki, Shin Terashima, Noriko Matsuda-Imai, Tomoyuki Takano, Misa Saito, Maasa Kanno, Soichi Ozaki, Keita Suwabe, Go Suzuki, Masao Watanabe, Makoto Matsuoka, Seiji Takayama, Kentaro Yano

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)

    Abstract

    In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Efforts have been devoted to exploring superior novel reference genes using microarray transcriptomic data and to evaluating commonly used reference genes by targeting analysis. However, because the number of specifically detectable genes is totally dependent on probe design in the microarray analysis, exploration using microarray data may miss some of the best choices for the reference genes. Recently emerging RNA sequencing (RNA-seq) provides an ideal resource for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. We report the results of a comprehensive exploration of reference genes using public RNA-seq data from plants such as Arabidopsis thaliana (Arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato) and Oryza sativa (rice). To select reference genes suitable for the broadest experimental conditions possible, candidates were surveyed by the following four steps: (1) evaluation of the basal expression level of each gene in each experiment; (2) evaluation of the expression stability of each gene in each experiment; (3) evaluation of the expression stability of each gene across the experiments; and (4) selection of top-ranked genes, after ranking according to the number of experiments in which the gene was expressed stably. Employing this procedure, 13, 10, 12 and 21 top candidates for reference genes were proposed in Arabidopsis, soybean, tomato and rice, respectively. Microarray expression data confirmed that the expression of the proposed reference genes under broad experimental conditions was more stable than that of commonly used reference genes. These novel reference genes will be useful for analyzing gene expression profiles across experiments carried out under various experimental conditions.

    Original languageEnglish
    Pages (from-to)111-125
    Number of pages15
    JournalGenes and Genetic Systems
    Volume91
    Issue number2
    DOIs
    Publication statusPublished - 2016

    Keywords

    • Gene expression analysis
    • RNA-seq
    • Reference gene

    ASJC Scopus subject areas

    • Molecular Biology
    • Genetics

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