Abstract
Tea is one of three major non-alcoholic beverages that are popular all around the world. The economic value of tea product largely depends on the post-harvest physiology of tea leaves. The utilization of quantitative reverse transcription polymerase chain reaction is a widely accepted and precise approach to determine the target gene expression of tea plants, and the reliability of results hinges on the selection of suitable reference genes. A few reliable reference genes have been documented using various treatments and different tissues of tea plants, but none has been done on post-harvest leaves during the tea manufacturing process. The present study selected and analyzed 15 candidate reference genes: Cs18SrRNA, CsGADPH, CsACT, CsEF-1α, CsUbi, CsTUA, Cs26SrRNA, CsRuBP, CsCYP, CselF-4α, CsMON1, CsPCS1, CsSAND, CsPPA2, CsTBP. This study made an assessment on the expression stability under two kinds of post-harvest treatment, turn over and withering, using three algorithms—GeNorm, Normfinder, and Bestkeeper. The results indicated that the three commonly used reference genes, CsTUA, Cs18SrRNA, CsRuBP, together with Cs26SrRNA, were the most unstable genes in both the turn over and withering treatments. CsACT, CsEF-1α, CsPPA2, and CsTBP were the top four reference genes in the turn over treatment, while CsTBP, CsPCS1, CsPPA2, CselF-4α, and CsACT were the five best reference genes in the withering group. The expression level of lipoxygenase genes, which were involved in a number of diverse aspects of plant physiology, including wounding, was evaluated to validate the findings. To conclude, we found a basis for the selection of reference genes for accurate transcription normalization in post-harvest leaves of tea plants.
Highlights
The quantitative real-time polymerase chain reaction (RT-qPCR) is being used widely as a preferred and powerful approach applied to detect gene expression levels in molecular biology based on the polymerase chain reaction (PCR) (Peters et al, 2004; Zhang et al, 2009)
Many reference genes are expressed at relatively constant levels under most situations of biotic and abiotic stress, such as LDHA, NONO, and PPIH, they could change based on different experimental conditions (Keshishian et al, 2015)
That meant the level of gene transcription still existed, which layed the foundation of RT-qPCR assay as follow
Summary
The quantitative real-time polymerase chain reaction (RT-qPCR) is being used widely as a preferred and powerful approach applied to detect gene expression levels in molecular biology based on the polymerase chain reaction (PCR) (Peters et al, 2004; Zhang et al, 2009). According to the different methods of calculation, RT-qPCR can be divided into two. In contrast to absolute quantification, relative quantification utilizes a relatively stable control gene as a reference. Many reference genes are expressed at relatively constant levels under most situations of biotic and abiotic stress, such as LDHA, NONO, and PPIH, they could change based on different experimental conditions (Keshishian et al, 2015). An important impact part of the RT-qPCR assay is the selection of a reliable reference gene to normalize the result as this determines the accuracy of the assay results
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