Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/14/2017
Publication Date: 9/21/2017
Citation: Zhou, Z., Cong, P., Tian, Y., Zhu, Y. 2017. Using RNA-Seq data to select refence genes for normalizing gene expression in apple roots. PLoS One. https://doi.org/10.1371/journal.pone.0185288. Interpretive Summary: Gene expression analysis is an important aspect for inferring the function of a gene of interest. Among the methodology of studying gene expression reverse transcription quantitative PCR (RT-qPCR) is a widely-applied technique. RT-qPCR can detect a wide-range of gene expression level with accurate quantification, but reliable data require careful normalization using validated reference genes. Most of the research interests on apple have been focusing on the fruit, leaf and flower, and apple roots and their responses to various stress conditions are a less-explored research subject. For this reason, reliable reference genes which are specifically appropriate for gene expression analysis in apple root tissues need to be validated by carefully designed experiment. In this study, a set of candidate genes with low expression variance were selected from our recent RNA-seq based transcriptome data set for apple root-Pythium ultimum interaction. The stability analysis for these candidate reference genes were analyzed by four different methods. A panel of reliable reference genes showed stable expression among apple root tissues under various biotic and abiotic stresses. The top-ranked genes are recommended for quantitative gene expression analysis in apple tissues.
Technical Abstract: Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase) and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase). Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization.