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Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L)

BACKGROUND: Analysis of gene expression patterns leads to functional understanding of biological processes. Quantitative real-time PCR has become the most commonly used technique for in-depth studies of gene expression. To quantify variation in specific gene expression, accurate and reliable normali...

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Autores principales: Gantasala, Nagavara Prasad, Papolu, Pradeep Kumar, Thakur, Prasoon Kumar, Kamaraju, Divya, Sreevathsa, Rohini, Rao, Uma
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750715/
https://www.ncbi.nlm.nih.gov/pubmed/23919495
http://dx.doi.org/10.1186/1756-0500-6-312
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author Gantasala, Nagavara Prasad
Papolu, Pradeep Kumar
Thakur, Prasoon Kumar
Kamaraju, Divya
Sreevathsa, Rohini
Rao, Uma
author_facet Gantasala, Nagavara Prasad
Papolu, Pradeep Kumar
Thakur, Prasoon Kumar
Kamaraju, Divya
Sreevathsa, Rohini
Rao, Uma
author_sort Gantasala, Nagavara Prasad
collection PubMed
description BACKGROUND: Analysis of gene expression patterns leads to functional understanding of biological processes. Quantitative real-time PCR has become the most commonly used technique for in-depth studies of gene expression. To quantify variation in specific gene expression, accurate and reliable normalization across different samples and tissues is necessary. This can be achieved by selecting one or more suitable reference genes to compare the target mRNA transcript levels. In the present work, we illustrate the first evaluation of potential internal control or reference genes across different developmental stages of eggplant for reliable quantification of transcripts by real-time PCR. RESULTS: We have evaluated the stability in expression of six candidate reference genes (18s rRNA, APRT, GAPDH, Cyclophilin, Actin, and RuBP) in a set of tissues representing six developmental stages of eggplant. The candidate genes were cloned from cDNA and analysed by real-time PCR. The expression data analyzed by three statistical methods (geNorm, NormFinder and BestKeeper) identified 18s rRNA, Cyclophilin and APRT as the most stable and suitable reference genes in eggplant. This was further confirmed in four different varieties, two representative lines of transgenic eggplant as well as in nematode infected eggplant. CONCLUSION: 18s rRNA, Cyclophilin and APRT have been found to be appropriate for the normalization of real-time PCR data for gene expression studies in eggplant.
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spelling pubmed-37507152013-08-24 Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L) Gantasala, Nagavara Prasad Papolu, Pradeep Kumar Thakur, Prasoon Kumar Kamaraju, Divya Sreevathsa, Rohini Rao, Uma BMC Res Notes Research Article BACKGROUND: Analysis of gene expression patterns leads to functional understanding of biological processes. Quantitative real-time PCR has become the most commonly used technique for in-depth studies of gene expression. To quantify variation in specific gene expression, accurate and reliable normalization across different samples and tissues is necessary. This can be achieved by selecting one or more suitable reference genes to compare the target mRNA transcript levels. In the present work, we illustrate the first evaluation of potential internal control or reference genes across different developmental stages of eggplant for reliable quantification of transcripts by real-time PCR. RESULTS: We have evaluated the stability in expression of six candidate reference genes (18s rRNA, APRT, GAPDH, Cyclophilin, Actin, and RuBP) in a set of tissues representing six developmental stages of eggplant. The candidate genes were cloned from cDNA and analysed by real-time PCR. The expression data analyzed by three statistical methods (geNorm, NormFinder and BestKeeper) identified 18s rRNA, Cyclophilin and APRT as the most stable and suitable reference genes in eggplant. This was further confirmed in four different varieties, two representative lines of transgenic eggplant as well as in nematode infected eggplant. CONCLUSION: 18s rRNA, Cyclophilin and APRT have been found to be appropriate for the normalization of real-time PCR data for gene expression studies in eggplant. BioMed Central 2013-08-06 /pmc/articles/PMC3750715/ /pubmed/23919495 http://dx.doi.org/10.1186/1756-0500-6-312 Text en Copyright © 2013 Gantasala et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gantasala, Nagavara Prasad
Papolu, Pradeep Kumar
Thakur, Prasoon Kumar
Kamaraju, Divya
Sreevathsa, Rohini
Rao, Uma
Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L)
title Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L)
title_full Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L)
title_fullStr Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L)
title_full_unstemmed Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L)
title_short Selection and validation of reference genes for quantitative gene expression studies by real-time PCR in eggplant (Solanum melongena L)
title_sort selection and validation of reference genes for quantitative gene expression studies by real-time pcr in eggplant (solanum melongena l)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750715/
https://www.ncbi.nlm.nih.gov/pubmed/23919495
http://dx.doi.org/10.1186/1756-0500-6-312
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