Literature DB >> 30151697

A minimally parametrized branching process explaining plateau phase of qPCR amplification.

Qingyang Luo1.   

Abstract

Quantitative polymerase chain reaction (qPCR) is a commonly used molecular biology technique for measuring the concentration of a target nucleic acid sequence in a sample. The whole qPCR amplification process usually consists of an exponential, a linear and a plateau phase. In qPCR experiments, amplification curves of samples with different template concentrations often, even though not always, have the same plateau height. The biological theory for this phenomenon is that the plateau height is determined by reaction kinetics. Does it mean that the target concentration has no effect on the final plateau height? We proposed a branching process based on Michaelis-Menten kinetics. Our model can describe all phases of qPCR amplification despite its simplicity (it depends on only one parameter). We theoretically showed, through almost sure convergence, that amplification curves will eventually plateau at finite values in any experiment, under any condition. We conclude that the plateau height is largely determined by reaction kinetics but could also be affected by the template concentration. This is in accordance with the current biological theory.

Keywords:  Branching process; Michaelis–Menten kinetics; Plateau phase; Quantitative polymerase chain reaction

Year:  2018        PMID: 30151697     DOI: 10.1007/s00285-018-1291-1

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  7 in total

1.  The PCR plateau phase - towards an understanding of its limitations.

Authors:  P Kainz
Journal:  Biochim Biophys Acta       Date:  2000-11-15

2.  Validation of a quantitative method for real time PCR kinetics.

Authors:  Weihong Liu; David A Saint
Journal:  Biochem Biophys Res Commun       Date:  2002-06-07       Impact factor: 3.575

3.  Mathematics of quantitative kinetic PCR and the application of standard curves.

Authors:  R G Rutledge; C Côté
Journal:  Nucleic Acids Res       Date:  2003-08-15       Impact factor: 16.971

4.  Random variation and concentration effects in PCR.

Authors:  Peter Jagers; Fima Klebaner
Journal:  J Theor Biol       Date:  2003-10-07       Impact factor: 2.691

Review 5.  Quantitative RT-PCR: pitfalls and potential.

Authors:  W M Freeman; S J Walker; K E Vrana
Journal:  Biotechniques       Date:  1999-01       Impact factor: 1.993

6.  A mechanistic model of PCR for accurate quantification of quantitative PCR data.

Authors:  Gregory J Boggy; Peter J Woolf
Journal:  PLoS One       Date:  2010-08-30       Impact factor: 3.240

7.  What can be observed in real time PCR and when does it show?

Authors:  Pavel Chigansky; Peter Jagers; Fima C Klebaner
Journal:  J Math Biol       Date:  2017-06-30       Impact factor: 2.259

  7 in total

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