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System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation

Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occ...

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Autores principales: Spiess, Andrej-Nikolai, Rödiger, Stefan, Burdukiewicz, Michał, Volksdorf, Thomas, Tellinghuisen, Joel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154181/
https://www.ncbi.nlm.nih.gov/pubmed/27958340
http://dx.doi.org/10.1038/srep38951
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author Spiess, Andrej-Nikolai
Rödiger, Stefan
Burdukiewicz, Michał
Volksdorf, Thomas
Tellinghuisen, Joel
author_facet Spiess, Andrej-Nikolai
Rödiger, Stefan
Burdukiewicz, Michał
Volksdorf, Thomas
Tellinghuisen, Joel
author_sort Spiess, Andrej-Nikolai
collection PubMed
description Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occurs in the baseline region and typically increases with increasing cycle number in the growth and plateau regions. Autocorrelation analysis reveals periodicities of 12 for 96-well systems and 24 for a 384-well system, indicating a correlation with block architecture. Passive dye experiments show that the effect may be from optical detector bias. Importantly, the signal periodicity manifests as periodicity in quantification cycle (C(q)) values when these are estimated by the widely applied fixed threshold approach, but not when scale-insensitive markers like first- and second-derivative maxima are used. Accordingly, any scale variability in the growth curves will lead to bias in constant-threshold-based C(q)s, making it mandatory that workers should either use scale-insensitive C(q)s or normalize their growth curves to constant amplitude before applying the constant threshold method.
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spelling pubmed-51541812016-12-28 System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation Spiess, Andrej-Nikolai Rödiger, Stefan Burdukiewicz, Michał Volksdorf, Thomas Tellinghuisen, Joel Sci Rep Article Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occurs in the baseline region and typically increases with increasing cycle number in the growth and plateau regions. Autocorrelation analysis reveals periodicities of 12 for 96-well systems and 24 for a 384-well system, indicating a correlation with block architecture. Passive dye experiments show that the effect may be from optical detector bias. Importantly, the signal periodicity manifests as periodicity in quantification cycle (C(q)) values when these are estimated by the widely applied fixed threshold approach, but not when scale-insensitive markers like first- and second-derivative maxima are used. Accordingly, any scale variability in the growth curves will lead to bias in constant-threshold-based C(q)s, making it mandatory that workers should either use scale-insensitive C(q)s or normalize their growth curves to constant amplitude before applying the constant threshold method. Nature Publishing Group 2016-12-13 /pmc/articles/PMC5154181/ /pubmed/27958340 http://dx.doi.org/10.1038/srep38951 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Spiess, Andrej-Nikolai
Rödiger, Stefan
Burdukiewicz, Michał
Volksdorf, Thomas
Tellinghuisen, Joel
System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
title System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
title_full System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
title_fullStr System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
title_full_unstemmed System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
title_short System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
title_sort system-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154181/
https://www.ncbi.nlm.nih.gov/pubmed/27958340
http://dx.doi.org/10.1038/srep38951
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