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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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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. |
format | Online Article Text |
id | pubmed-8912902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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