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

Area of Science:

• Molecular Biology
• Biotechnology
• Analytical Chemistry

Background:

• Real-time quantitative PCR (qPCR) is a widely used molecular biology technique.
• qPCR data fluorescence intensity can exhibit unexpected patterns.
• Understanding these patterns is crucial for accurate quantification.

Purpose of the Study:

• To investigate periodic patterns observed in qPCR fluorescence data.
• To determine the cause and impact of these periodicities on quantification.
• To recommend methods for mitigating potential biases in qPCR analysis.

Main Methods:

• Analysis of technical replicate qPCR datasets from multiple instruments.
• Autocorrelation analysis to identify periodicities.
• Passive dye experiments to assess optical detector bias.
• Comparison of quantification cycle (Cq) estimation methods (fixed threshold vs. scale-insensitive).

Main Results:

• Periodic patterns were observed in fluorescence intensity across different qPCR instruments and regions of the amplification curve.
• Periodicity correlated with instrument block architecture (96-well and 384-well systems).
• Optical detector bias was identified as a potential cause.
• Fixed threshold-based Cq values showed periodicity, while scale-insensitive methods did not.

Conclusions:

• Periodic fluorescence patterns in qPCR can introduce bias into Cq values when using the fixed threshold method.
• Scale-insensitive Cq estimation (e.g., derivative maxima) or growth curve normalization is necessary for accurate quantification.
• Researchers must be aware of and address signal periodicity for reliable qPCR data analysis.