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Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla

Real time quantitative PCR (RT-qPCR or qPCR) has been extensively applied for analyzing gene expression because of its accuracy, sensitivity, and high throughput. However, the unsuitable choice of reference gene(s) can lead to a misinterpretation of results. We evaluated the stability of 10 candidat...

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Autores principales: He, Yihan, Yan, Hailing, Hua, Wenping, Huang, Yaya, Wang, Zhezhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4925707/
https://www.ncbi.nlm.nih.gov/pubmed/27446172
http://dx.doi.org/10.3389/fpls.2016.00945
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author He, Yihan
Yan, Hailing
Hua, Wenping
Huang, Yaya
Wang, Zhezhi
author_facet He, Yihan
Yan, Hailing
Hua, Wenping
Huang, Yaya
Wang, Zhezhi
author_sort He, Yihan
collection PubMed
description Real time quantitative PCR (RT-qPCR or qPCR) has been extensively applied for analyzing gene expression because of its accuracy, sensitivity, and high throughput. However, the unsuitable choice of reference gene(s) can lead to a misinterpretation of results. We evaluated the stability of 10 candidates – five traditional housekeeping genes (UBC21, GAPC2, EF-1α4, UBQ10, and UBC10) and five novel genes (SAND1, FBOX, PTB1, ARP, and Expressed1) – using the transcriptome data of Gentiana macrophylla. Common statistical algorithms ΔC(t), GeNorm, NormFinder, and BestKeeper were run with samples collected from plants under various experimental conditions. For normalizing expression levels from tissues at different developmental stages, GAPC2 and UBC21 had the highest rankings. Both SAND1 and GAPC2 proved to be the optimal reference genes for roots from plants exposed to abiotic stresses while EF-1α4 and SAND1 were optimal when examining expression data from the leaves of stressed plants. Based on a comprehensive ranking of stability under different experimental conditions, we recommend that SAND1 and EF-1α4 are the most suitable overall. In this study, to find a suitable reference gene and its real-time PCR assay for G. macrophylla DNA content quantification, we evaluated three target genes including WRKY30, G10H, and SLS, through qualitative and absolute quantitative PCR with leaves under elicitors stressed experimental conditions. Arbitrary use of reference genes without previous evaluation can lead to a misinterpretation of the data. Our results will benefit future research on the expression of genes related to secoiridoid biosynthesis in this species under different experimental conditions.
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spelling pubmed-49257072016-07-21 Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla He, Yihan Yan, Hailing Hua, Wenping Huang, Yaya Wang, Zhezhi Front Plant Sci Plant Science Real time quantitative PCR (RT-qPCR or qPCR) has been extensively applied for analyzing gene expression because of its accuracy, sensitivity, and high throughput. However, the unsuitable choice of reference gene(s) can lead to a misinterpretation of results. We evaluated the stability of 10 candidates – five traditional housekeeping genes (UBC21, GAPC2, EF-1α4, UBQ10, and UBC10) and five novel genes (SAND1, FBOX, PTB1, ARP, and Expressed1) – using the transcriptome data of Gentiana macrophylla. Common statistical algorithms ΔC(t), GeNorm, NormFinder, and BestKeeper were run with samples collected from plants under various experimental conditions. For normalizing expression levels from tissues at different developmental stages, GAPC2 and UBC21 had the highest rankings. Both SAND1 and GAPC2 proved to be the optimal reference genes for roots from plants exposed to abiotic stresses while EF-1α4 and SAND1 were optimal when examining expression data from the leaves of stressed plants. Based on a comprehensive ranking of stability under different experimental conditions, we recommend that SAND1 and EF-1α4 are the most suitable overall. In this study, to find a suitable reference gene and its real-time PCR assay for G. macrophylla DNA content quantification, we evaluated three target genes including WRKY30, G10H, and SLS, through qualitative and absolute quantitative PCR with leaves under elicitors stressed experimental conditions. Arbitrary use of reference genes without previous evaluation can lead to a misinterpretation of the data. Our results will benefit future research on the expression of genes related to secoiridoid biosynthesis in this species under different experimental conditions. Frontiers Media S.A. 2016-06-29 /pmc/articles/PMC4925707/ /pubmed/27446172 http://dx.doi.org/10.3389/fpls.2016.00945 Text en Copyright © 2016 He, Yan, Hua, Huang and Wang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
He, Yihan
Yan, Hailing
Hua, Wenping
Huang, Yaya
Wang, Zhezhi
Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla
title Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla
title_full Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla
title_fullStr Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla
title_full_unstemmed Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla
title_short Selection and Validation of Reference Genes for Quantitative Real-time PCR in Gentiana macrophylla
title_sort selection and validation of reference genes for quantitative real-time pcr in gentiana macrophylla
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4925707/
https://www.ncbi.nlm.nih.gov/pubmed/27446172
http://dx.doi.org/10.3389/fpls.2016.00945
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