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Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data
Quantitative PCR (qPCR) has become the gold standard technique to measure cDNA and gDNA levels but the resulting data can be highly variable, artifactual and non-reproducible without appropriate verification and validation of both samples and primers. The root cause of poor quality data is typically...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445070/ https://www.ncbi.nlm.nih.gov/pubmed/28546538 http://dx.doi.org/10.1038/s41598-017-02217-x |
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author | Taylor, Sean C. Laperriere, Genevieve Germain, Hugo |
author_facet | Taylor, Sean C. Laperriere, Genevieve Germain, Hugo |
author_sort | Taylor, Sean C. |
collection | PubMed |
description | Quantitative PCR (qPCR) has become the gold standard technique to measure cDNA and gDNA levels but the resulting data can be highly variable, artifactual and non-reproducible without appropriate verification and validation of both samples and primers. The root cause of poor quality data is typically associated with inadequate dilution of residual protein and chemical contaminants that variably inhibit Taq polymerase and primer annealing. The most susceptible, frustrating and often most interesting samples are those containing low abundant targets with small expression differences of 2-fold or lower. Here, Droplet Digital PCR (ddPCR) and qPCR platforms were directly compared for gene expression analysis using low amounts of purified, synthetic DNA in well characterized samples under identical reaction conditions. We conclude that for sample/target combinations with low levels of nucleic acids (Cq ≥ 29) and/or variable amounts of chemical and protein contaminants, ddPCR technology will produce more precise, reproducible and statistically significant results required for publication quality data. A stepwise methodology is also described to choose between these complimentary technologies to obtain the best results for any experiment. |
format | Online Article Text |
id | pubmed-5445070 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54450702017-05-26 Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data Taylor, Sean C. Laperriere, Genevieve Germain, Hugo Sci Rep Article Quantitative PCR (qPCR) has become the gold standard technique to measure cDNA and gDNA levels but the resulting data can be highly variable, artifactual and non-reproducible without appropriate verification and validation of both samples and primers. The root cause of poor quality data is typically associated with inadequate dilution of residual protein and chemical contaminants that variably inhibit Taq polymerase and primer annealing. The most susceptible, frustrating and often most interesting samples are those containing low abundant targets with small expression differences of 2-fold or lower. Here, Droplet Digital PCR (ddPCR) and qPCR platforms were directly compared for gene expression analysis using low amounts of purified, synthetic DNA in well characterized samples under identical reaction conditions. We conclude that for sample/target combinations with low levels of nucleic acids (Cq ≥ 29) and/or variable amounts of chemical and protein contaminants, ddPCR technology will produce more precise, reproducible and statistically significant results required for publication quality data. A stepwise methodology is also described to choose between these complimentary technologies to obtain the best results for any experiment. Nature Publishing Group UK 2017-05-25 /pmc/articles/PMC5445070/ /pubmed/28546538 http://dx.doi.org/10.1038/s41598-017-02217-x Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Taylor, Sean C. Laperriere, Genevieve Germain, Hugo Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data |
title | Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data |
title_full | Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data |
title_fullStr | Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data |
title_full_unstemmed | Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data |
title_short | Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data |
title_sort | droplet digital pcr versus qpcr for gene expression analysis with low abundant targets: from variable nonsense to publication quality data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445070/ https://www.ncbi.nlm.nih.gov/pubmed/28546538 http://dx.doi.org/10.1038/s41598-017-02217-x |
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