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Selection and Validation of Reference Genes for Normalisation of Gene Expression in Glehnia littoralis

Li Li, Naiwei Li, Hailing Fang, Xiwu Qi, Yifeng Zhou

2020Scientific Reports38 citationsDOIOpen Access PDF

Abstract

Glehnia littoralis is an important medicinal halophyte-the dried root of which is used as Chinese herbal medicine. However, the use, selection and stability of reference genes are rarely verified in studies of G. littoralis, which hampers investigation of its salt tolerance and metabolism. In this study, we selected 13 candidate reference genes from the transcriptome data of G. littoralis-serine/threonine-protein phosphatase PP2A (PP2A), polyubiquitin 10 (UBQ10), actin (ACT), elongation factor 1-α (EF1-α), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), α-tubulin (α-TUB), β-tubulin (β-TUB), polypyrimidine tract-binding protein 1 (PTBP1), expressed protein 1 (EXP1), expressed protein 2 (EXP2), TIP41-like (TIP41), SAND family (SAND), and cyclophilin 2 (CYP2), and used qRT-PCR to analyse their expression levels in roots of G. littoralis treated with NaCl, polyethylene glycol (PEG), abscisic acid (ABA), and methyl jasmonate (MeJA), as well as in various organs of G. littoralis. The ΔCt, geNorm, NormFinder, and BestKeeper algorithms were used to assess the expression stability of the candidate reference genes and the results were then used to generate a comprehensive rank list with the RankAggreg R package. The most stable reference genes for normalisation were EXP1 and PP2A in response to NaCl, EXP2 and PP2A in response to ABA, CYP2 and α-TUB in response to MeJA, and ACT and EXP1 in the PEG and the organ subsets. GAPDH, β-TUB, and UBQ10 exhibited low stability and so were unsuitable for normalisation. This study is the first systematic analysis of candidate reference genes in G. littoralis and will facilitate further investigation of normalisation of gene expression in G. littoralis.

Topics & Concepts

Selection (genetic algorithm)GeneBiologyComputational biologyGene expressionGene selectionGeneticsReference genesBioinformaticsComputer scienceArtificial intelligenceMicroarray analysis techniquesMolecular Biology Techniques and ApplicationsPlant tissue culture and regenerationTurfgrass Adaptation and Management
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