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Selection of reference genes for quantitative real‐time PCR in postharvest tomatoes ( Lycopersicon esculentum ) treated by continuous low‐voltage direct current electricity to increase secondary metabolites
Author(s) -
Leelatanawit Rungnapa,
Saetung Thunyarat,
Phuengwas Sudtida,
Karoonuthaisiri Nitsara,
Devahastin Sakamon
Publication year - 2017
Publication title -
international journal of food science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.831
H-Index - 96
eISSN - 1365-2621
pISSN - 0950-5423
DOI - 10.1111/ijfs.13477
Subject(s) - reference genes , biology , gene , real time polymerase chain reaction , gene expression , candidate gene , genetics , selection (genetic algorithm) , computational biology , artificial intelligence , computer science
Summary Quantitative real‐time PCR ( RT ‐ qPCR ) is often used for gene expression analysis to reveal molecular mechanism of how stresses can enhance the secondary metabolites production. For RT ‐ qPCR to be valid, robust reference genes are required. This study validated nine candidate genes as reference genes using BestKeeper, NormFinder and geNorm methods in RT ‐ qPCR analysis of postharvest tomatoes subjected to electricity‐induced stress. The most stable genes as indicated by each method were EF ‐1 α by BestKeeper; CAC by NormFinder; and PP 2Acs / TIP 41 by geNorm. Due to the inconsistency in the ranking of the candidate genes by the three methods, the pairwise variation from geNorm analysis was used to calculate the minimum numbers of reference genes for an accurate normalisation and revealed that a combination of PP 2Acs and TIP 41 was an optimum. This reference gene combination was further validated for their stability in RT ‐ qPCR analysis of four carotenoid‐related genes, and more reliable expression levels were obtained.