We propose a stochastic modelling of the PCR amplification process
by a size-dependent branching process starting as a supercritical
Bienaymé-Galton-Watson transient phase and then having a
saturation near-critical size-dependent phase. This model allows
us to estimate the probability of replication of a DNA molecule at
each cycle of a single PCR trajectory with a very good accuracy.
References
Dacunha-Castelle, D. and Duflo, M. (1982). Probabilités et Statistiques, Tome 1. Masson, Paris.
Mathematical Reviews (MathSciNet):
MR680578
Ferré, F. (ed.) (1998). Gene Quantification. Birkhäuser, Boston.
Gilliland, G., Perrin, S., Blanchard, K. and Bunn, H. F. (1990). Analysis of cytokine mRNA and DNA: detection and quantitation by competitive polymerase chain reaction. Proc. Nat. Acad. Sci. USA 87, 2725--2729.
Higuchi, R., Dollinger, G., Walsh, P. S. and Griffith, R. (1992). Simultaneous amplification and detection of specific DNA sequences. Biotechnology 10, 413--417.
Jacob, C. and Peccoud, J. (1998). Estimation of the parameters of a branching process from migrating binomial observations. Adv. Appl. Prob. 30, 948--967.
Jagers, P. (1975). Branching Processes with Biological Applications. John Wiley, London.
Mathematical Reviews (MathSciNet):
MR488341
Jagers, P. and Klebaner, F. C. (2003). Random variation and concentration effects in PCR. J. Theoret. Biol. 224, 299--304.
Kersting, G. (1990). Some properties of stochastic difference equations. In Stochastic Modelling in Biology, ed. P. Tautu, World Scientific, Singapore, pp. 328--339.
Kimura, B., Kawasaki, S., Nakano, H. and Fujii, T. (2001). Rapid, quantitative PCR monitoring of growth of clostridium botulinum type E in modified-atmosphere-packaged fish. Appl. Environ. Microbiol. 67, 206--216.
Krawczak, M., Reiss, J., Schmidtke, J. and Rosler, U. (1989). Polymerase chain reaction: replication errors and reliability of gene diagnosis. Nucleic Acids Res. 17, 2197--2201.
Lalam, N. and Jacob, C. (2003). Estimation of the offspring mean in a supercritical or near-critical size-dependent branching process. Adv. Appl. Prob. 36, 582--601.
Lalam, N. and Jacob, C. (2003). Modelling the PCR amplification process with size-dependent branching processes and estimation of the efficiency. Tech. Rep., Applied Mathematics and Informatics, INRA, Jouy-en-Josas.
Mackay, I. M., Arden, K. E. and Nitsche, A. (2002). Real-time PCR in virology. Nucleic Acids Res. 30, 1292--1305.
Mullis, K. B. and Faloona, F. (1987). Specific synthesis of DNA in vitro via a polymerase-catalysed chain reaction. Methods Enzymol. 155, 335--350.
Mullis, K. B., Ferré, F. and Gibbs, R. A. (1994). The Polymerase Chain Reaction. Birkhäuser, Boston.
Nedelman, J., Heagerty, P. and Lawrence, C. (1992). Quantitative PCR: procedures and precision. Bull. Math. Biol. 54, 477--502.
Peccoud, J. and Jacob, C. (1996). Theoretical uncertainty of measurements using quantitative polymerase chain reaction. Biophys. J. 71, 101--108.
Peccoud, J. and Jacob, C. (1998). Statistical estimations of PCR amplification rates. In Gene Quantification, ed. F. Ferré, Birkhäuser, Boston.
Piau, D. (2001). Processus de branchement et champ moyen. Adv. Appl. Prob. 33, 391--403.
Raeymakers, L. (1995). A commentary on the practical applications of competitive PCR. Genome Res. 5, 91--94.
Saiki, R. K. et al. (1988). Primer-directed enzymatic amplification of DNA with a thermostable DNA polymerase. Science 239, 487--491.
Schnell, S. and Mendoza, C. (1997). Enzymological considerations for a theoretical description of the quantitative competitive polymerase chain reaction. J. Theoret. Biol. 184, 433--440.
Stolovitzky, G. and Cecchi, G. (1996). Efficiency of DNA replication in the polymerase chain reaction. Biophysics 93, 12947--12952.
Sun, G. (1995). The PCR and branching processes. J. Comput. Biol. 2, 63--86.
Vandenbroucke, I. I., Vandesempele, J., De Paepe, A. and Messiaen, L. (2001). Quantification of splice variants using real-time PCR. Nucleic Acids Res. 29, e68.
Weiss, G. and Von Haeseler, A. (1995). Modeling the PCR. J. Comput. Biol. 2, 49--61.