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A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets

In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here,...

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Autores principales: Nevone, Alice, Lattarulo, Francesca, Russo, Monica, Panno, Giada, Milani, Paolo, Basset, Marco, Avanzini, Maria Antonietta, Merlini, Giampaolo, Palladini, Giovanni, Nuvolone, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10135859/
https://www.ncbi.nlm.nih.gov/pubmed/37189697
http://dx.doi.org/10.3390/biomedicines11041079
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author Nevone, Alice
Lattarulo, Francesca
Russo, Monica
Panno, Giada
Milani, Paolo
Basset, Marco
Avanzini, Maria Antonietta
Merlini, Giampaolo
Palladini, Giovanni
Nuvolone, Mario
author_facet Nevone, Alice
Lattarulo, Francesca
Russo, Monica
Panno, Giada
Milani, Paolo
Basset, Marco
Avanzini, Maria Antonietta
Merlini, Giampaolo
Palladini, Giovanni
Nuvolone, Mario
author_sort Nevone, Alice
collection PubMed
description In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed “housekeeping” genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available.
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spelling pubmed-101358592023-04-28 A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets Nevone, Alice Lattarulo, Francesca Russo, Monica Panno, Giada Milani, Paolo Basset, Marco Avanzini, Maria Antonietta Merlini, Giampaolo Palladini, Giovanni Nuvolone, Mario Biomedicines Article In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed “housekeeping” genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available. MDPI 2023-04-03 /pmc/articles/PMC10135859/ /pubmed/37189697 http://dx.doi.org/10.3390/biomedicines11041079 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Nevone, Alice
Lattarulo, Francesca
Russo, Monica
Panno, Giada
Milani, Paolo
Basset, Marco
Avanzini, Maria Antonietta
Merlini, Giampaolo
Palladini, Giovanni
Nuvolone, Mario
A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets
title A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets
title_full A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets
title_fullStr A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets
title_full_unstemmed A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets
title_short A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets
title_sort strategy for the selection of rt-qpcr reference genes based on publicly available transcriptomic datasets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10135859/
https://www.ncbi.nlm.nih.gov/pubmed/37189697
http://dx.doi.org/10.3390/biomedicines11041079
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