Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization

Abstract Angelica decursiva is one of the lending traditional Chinese medicinal plants producing coumarins. Notably, several studies have focused on the biosynthesis and not the RT-qPCR (quantitative real-time reverse transcription polymerase chain reaction) study of coumarins. This RT-qPCR techniqu...

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Autores principales:	Yuedong He, Yuan Zhong, Zhenzhen Bao, Weiqi Wang, Xiaoqing Xu, Yanan Gai, Jie Wu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3616474c6f3041d19f860ffc183b0353
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spelling	oai:doaj.org-article:3616474c6f3041d19f860ffc183b03532021-12-02T18:13:52ZEvaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization10.1038/s41598-021-98434-62045-2322https://doaj.org/article/3616474c6f3041d19f860ffc183b03532021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98434-6https://doaj.org/toc/2045-2322Abstract Angelica decursiva is one of the lending traditional Chinese medicinal plants producing coumarins. Notably, several studies have focused on the biosynthesis and not the RT-qPCR (quantitative real-time reverse transcription polymerase chain reaction) study of coumarins. This RT-qPCR technique has been extensively used to investigate gene expression levels in plants and the selection of reference genes which plays a crucial role in standardizing the data form the RT-qPCR analysis. In our study, 11 candidate reference genes were selected from the existing transcriptome data of Angelica decursiva. Here, four different types of statistical algorithms (geNorm, NormFinder, BestKeeper, and Delta Ct) were used to calculate and evaluate the stability of gene expression under different external treatments. Subsequently, RefFinder analysis was used to determine the geometric average of each candidate gene ranking, and to perform comprehensive index ranking. The obtained results showed that among all the 11 candidate reference genes, SAND family protein (SAND), protein phosphatase 2A gene (PP2A), and polypyrimidine tract-binding protein (PTBP) were the most stable reference genes, where Nuclear cap binding protein 2 (NCBP2), TIP41-like protein (TIP41), and Beta-6-tubulin (TUBA) were the least stable genes. To the best of our knowledge, this work is the first to evaluate the stability of reference genes in the Angelica decursiva which has provided an important foundation on the use of RT-qPCR for an accurate and far-reaching gene expression analysis in this medicinal plant.Yuedong HeYuan ZhongZhenzhen BaoWeiqi WangXiaoqing XuYanan GaiJie WuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yuedong He Yuan Zhong Zhenzhen Bao Weiqi Wang Xiaoqing Xu Yanan Gai Jie Wu Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization
description	Abstract Angelica decursiva is one of the lending traditional Chinese medicinal plants producing coumarins. Notably, several studies have focused on the biosynthesis and not the RT-qPCR (quantitative real-time reverse transcription polymerase chain reaction) study of coumarins. This RT-qPCR technique has been extensively used to investigate gene expression levels in plants and the selection of reference genes which plays a crucial role in standardizing the data form the RT-qPCR analysis. In our study, 11 candidate reference genes were selected from the existing transcriptome data of Angelica decursiva. Here, four different types of statistical algorithms (geNorm, NormFinder, BestKeeper, and Delta Ct) were used to calculate and evaluate the stability of gene expression under different external treatments. Subsequently, RefFinder analysis was used to determine the geometric average of each candidate gene ranking, and to perform comprehensive index ranking. The obtained results showed that among all the 11 candidate reference genes, SAND family protein (SAND), protein phosphatase 2A gene (PP2A), and polypyrimidine tract-binding protein (PTBP) were the most stable reference genes, where Nuclear cap binding protein 2 (NCBP2), TIP41-like protein (TIP41), and Beta-6-tubulin (TUBA) were the least stable genes. To the best of our knowledge, this work is the first to evaluate the stability of reference genes in the Angelica decursiva which has provided an important foundation on the use of RT-qPCR for an accurate and far-reaching gene expression analysis in this medicinal plant.
format	article
author	Yuedong He Yuan Zhong Zhenzhen Bao Weiqi Wang Xiaoqing Xu Yanan Gai Jie Wu
author_facet	Yuedong He Yuan Zhong Zhenzhen Bao Weiqi Wang Xiaoqing Xu Yanan Gai Jie Wu
author_sort	Yuedong He
title	Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization
title_short	Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization
title_full	Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization
title_fullStr	Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization
title_full_unstemmed	Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization
title_sort	evaluation of angelica decursiva reference genes under various stimuli for rt-qpcr data normalization
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3616474c6f3041d19f860ffc183b0353
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Evaluation of Angelica decursiva reference genes under various stimuli for RT-qPCR data normalization

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