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Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data.

Ruijter JM, Ramakers C, Hoogaars WM, Karlen Y, Bakker O, van den Hoff MJ, Moorman AF - Nucleic Acids Res. (2009)

Bottom Line: This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results.Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value.The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

View Article: PubMed Central - PubMed

Affiliation: Heart Failure Research Center, Academic Medical Center, University of Amsterdam, The Netherlands. j.m.ruijter@amc.uva.nl

ABSTRACT
Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

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Effect of the baseline estimation method on qPCR data analysis. (A) PCR amplification curves of NppB and NDUFB3 in samples of five different parts of the developing chicken heart. Baseline fluorescence was estimated by the system software as a linear trend through the observations of cycles 3 through 10 (BL 3–10, top panel) or with the baseline estimation method described in this article (LinRegPCR, bottom panel). See Supplementary Figure S2A for additional system baseline settings.(B) PCR efficiency values of NppB and NDUFB3 from each individual sample (open circles) in three independent PCR runs. An optimal W-o-L was applied per amplicon per plate. Mean efficiencies per plate and per amplicon were calculated. PCR efficiencies were determined after application of three baseline trends, as well as after the LinRegPCR baseline subtraction. The variation was lowest in LinRegPCR-derived PCR efficiency values (see Supplementary Figure S2B). (C) NppB/NDUFB3 gene expression ratio in different parts of the developing chicken heart for each of the baseline correction methods. Note that the pattern of observed expression ratios depends on the applied baseline correction method. Variation in expression ratios per tissue is lowest in data derived from LinRegPCR-corrected data.
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Figure 2: Effect of the baseline estimation method on qPCR data analysis. (A) PCR amplification curves of NppB and NDUFB3 in samples of five different parts of the developing chicken heart. Baseline fluorescence was estimated by the system software as a linear trend through the observations of cycles 3 through 10 (BL 3–10, top panel) or with the baseline estimation method described in this article (LinRegPCR, bottom panel). See Supplementary Figure S2A for additional system baseline settings.(B) PCR efficiency values of NppB and NDUFB3 from each individual sample (open circles) in three independent PCR runs. An optimal W-o-L was applied per amplicon per plate. Mean efficiencies per plate and per amplicon were calculated. PCR efficiencies were determined after application of three baseline trends, as well as after the LinRegPCR baseline subtraction. The variation was lowest in LinRegPCR-derived PCR efficiency values (see Supplementary Figure S2B). (C) NppB/NDUFB3 gene expression ratio in different parts of the developing chicken heart for each of the baseline correction methods. Note that the pattern of observed expression ratios depends on the applied baseline correction method. Variation in expression ratios per tissue is lowest in data derived from LinRegPCR-corrected data.

Mentions: Most PCR systems currently use a linear baseline trend derived from a user-defined set of early amplification cycles. Application of three baseline choices (‘baseline’ cycles 3–5, 3–10 and 3–15) to the three datasets results in highly variable PCR efficiencies per amplicon (Figure 2B, Supplementary Figures S2B, S3B and S4B). The log-linear plots of the baseline-corrected datasets show the characteristic convex and concave amplification curves that result from over- or underestimation of the fluorescence baseline (21) (Figure 2A; upper panel, Supplementary Figures S2A, S3A and S4A). A baseline based on a fixed number of early observations always runs the risk of being overestimated due to inclusion of amplification product.Figure 2.


Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data.

Ruijter JM, Ramakers C, Hoogaars WM, Karlen Y, Bakker O, van den Hoff MJ, Moorman AF - Nucleic Acids Res. (2009)

Effect of the baseline estimation method on qPCR data analysis. (A) PCR amplification curves of NppB and NDUFB3 in samples of five different parts of the developing chicken heart. Baseline fluorescence was estimated by the system software as a linear trend through the observations of cycles 3 through 10 (BL 3–10, top panel) or with the baseline estimation method described in this article (LinRegPCR, bottom panel). See Supplementary Figure S2A for additional system baseline settings.(B) PCR efficiency values of NppB and NDUFB3 from each individual sample (open circles) in three independent PCR runs. An optimal W-o-L was applied per amplicon per plate. Mean efficiencies per plate and per amplicon were calculated. PCR efficiencies were determined after application of three baseline trends, as well as after the LinRegPCR baseline subtraction. The variation was lowest in LinRegPCR-derived PCR efficiency values (see Supplementary Figure S2B). (C) NppB/NDUFB3 gene expression ratio in different parts of the developing chicken heart for each of the baseline correction methods. Note that the pattern of observed expression ratios depends on the applied baseline correction method. Variation in expression ratios per tissue is lowest in data derived from LinRegPCR-corrected data.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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Figure 2: Effect of the baseline estimation method on qPCR data analysis. (A) PCR amplification curves of NppB and NDUFB3 in samples of five different parts of the developing chicken heart. Baseline fluorescence was estimated by the system software as a linear trend through the observations of cycles 3 through 10 (BL 3–10, top panel) or with the baseline estimation method described in this article (LinRegPCR, bottom panel). See Supplementary Figure S2A for additional system baseline settings.(B) PCR efficiency values of NppB and NDUFB3 from each individual sample (open circles) in three independent PCR runs. An optimal W-o-L was applied per amplicon per plate. Mean efficiencies per plate and per amplicon were calculated. PCR efficiencies were determined after application of three baseline trends, as well as after the LinRegPCR baseline subtraction. The variation was lowest in LinRegPCR-derived PCR efficiency values (see Supplementary Figure S2B). (C) NppB/NDUFB3 gene expression ratio in different parts of the developing chicken heart for each of the baseline correction methods. Note that the pattern of observed expression ratios depends on the applied baseline correction method. Variation in expression ratios per tissue is lowest in data derived from LinRegPCR-corrected data.
Mentions: Most PCR systems currently use a linear baseline trend derived from a user-defined set of early amplification cycles. Application of three baseline choices (‘baseline’ cycles 3–5, 3–10 and 3–15) to the three datasets results in highly variable PCR efficiencies per amplicon (Figure 2B, Supplementary Figures S2B, S3B and S4B). The log-linear plots of the baseline-corrected datasets show the characteristic convex and concave amplification curves that result from over- or underestimation of the fluorescence baseline (21) (Figure 2A; upper panel, Supplementary Figures S2A, S3A and S4A). A baseline based on a fixed number of early observations always runs the risk of being overestimated due to inclusion of amplification product.Figure 2.

Bottom Line: This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results.Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value.The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

View Article: PubMed Central - PubMed

Affiliation: Heart Failure Research Center, Academic Medical Center, University of Amsterdam, The Netherlands. j.m.ruijter@amc.uva.nl

ABSTRACT
Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

Show MeSH
Related in: MedlinePlus