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RNA-Seq is not required to determine stable reference genes for qPCR normalization

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent...

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Autores principales: Sampathkumar, Nirmal Kumar, Sundaram, Venkat Krishnan, Danthi, Prakroothi S., Barakat, Rasha, Solomon, Shiden, Mondal, Mrityunjoy, Carre, Ivo, El Jalkh, Tatiana, Padilla-Ferrer, Aïda, Grenier, Julien, Massaad, Charbel, Mitchell, Jacqueline C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8912902/
https://www.ncbi.nlm.nih.gov/pubmed/35226660
http://dx.doi.org/10.1371/journal.pcbi.1009868
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author Sampathkumar, Nirmal Kumar
Sundaram, Venkat Krishnan
Danthi, Prakroothi S.
Barakat, Rasha
Solomon, Shiden
Mondal, Mrityunjoy
Carre, Ivo
El Jalkh, Tatiana
Padilla-Ferrer, Aïda
Grenier, Julien
Massaad, Charbel
Mitchell, Jacqueline C.
author_facet Sampathkumar, Nirmal Kumar
Sundaram, Venkat Krishnan
Danthi, Prakroothi S.
Barakat, Rasha
Solomon, Shiden
Mondal, Mrityunjoy
Carre, Ivo
El Jalkh, Tatiana
Padilla-Ferrer, Aïda
Grenier, Julien
Massaad, Charbel
Mitchell, Jacqueline C.
author_sort Sampathkumar, Nirmal Kumar
collection PubMed
description Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, however, we demonstrate that the statistical approach to determine the best reference genes from commonly used conventional candidates is more important than the preselection of ‘stable’ candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using conventional reference genes render the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.
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spelling pubmed-89129022022-03-11 RNA-Seq is not required to determine stable reference genes for qPCR normalization Sampathkumar, Nirmal Kumar Sundaram, Venkat Krishnan Danthi, Prakroothi S. Barakat, Rasha Solomon, Shiden Mondal, Mrityunjoy Carre, Ivo El Jalkh, Tatiana Padilla-Ferrer, Aïda Grenier, Julien Massaad, Charbel Mitchell, Jacqueline C. PLoS Comput Biol Research Article Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, however, we demonstrate that the statistical approach to determine the best reference genes from commonly used conventional candidates is more important than the preselection of ‘stable’ candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using conventional reference genes render the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays. Public Library of Science 2022-02-28 /pmc/articles/PMC8912902/ /pubmed/35226660 http://dx.doi.org/10.1371/journal.pcbi.1009868 Text en © 2022 Sampathkumar et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sampathkumar, Nirmal Kumar
Sundaram, Venkat Krishnan
Danthi, Prakroothi S.
Barakat, Rasha
Solomon, Shiden
Mondal, Mrityunjoy
Carre, Ivo
El Jalkh, Tatiana
Padilla-Ferrer, Aïda
Grenier, Julien
Massaad, Charbel
Mitchell, Jacqueline C.
RNA-Seq is not required to determine stable reference genes for qPCR normalization
title RNA-Seq is not required to determine stable reference genes for qPCR normalization
title_full RNA-Seq is not required to determine stable reference genes for qPCR normalization
title_fullStr RNA-Seq is not required to determine stable reference genes for qPCR normalization
title_full_unstemmed RNA-Seq is not required to determine stable reference genes for qPCR normalization
title_short RNA-Seq is not required to determine stable reference genes for qPCR normalization
title_sort rna-seq is not required to determine stable reference genes for qpcr normalization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8912902/
https://www.ncbi.nlm.nih.gov/pubmed/35226660
http://dx.doi.org/10.1371/journal.pcbi.1009868
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