Limits of Performance of Quantitative Polymerase Chain Reaction Systems

Estimation of the DNA copy number in a given biological sample is an important problem in genomics. Quantitative polymerase chain reaction (qPCR) systems detect the target DNA molecules by amplifying their number through a series of thermal cycles and measuring the amount of created amplicons in each cycle. Ideally, the number of target molecules doubles at the end of each cycle. However, in practice, due to biochemical noise the efficiency of the qPCR reaction - defined as the fraction of the target molecules which are successfully copied during a cycle - is always less than 1 . In this paper, we formulate the problem of the joint maximum-likelihood estimation of the qPCR efficiency and the initial DNA copy number. Then, we analytically determine the limits of performance of qPCR by deriving the Cramer-Rao lower bound on the mean-square estimation error. As indicated by simulation studies, the performance of the proposed estimator is superior compared to competing statistical approaches. The proposed approach is validated using experimental data.

[1]  P Kainz,et al.  The PCR plateau phase - towards an understanding of its limitations. , 2000, Biochimica et biophysica acta.

[2]  Marek Kimmel,et al.  Branching processes in biology , 2002 .

[3]  Didier Piau,et al.  Mutation-Replication Statistics of Polymerase Chain Reactions , 2002, J. Comput. Biol..

[4]  J. Peccoud,et al.  Estimation of the parameters of a branching process from migrating binomial observations , 1998, Advances in Applied Probability.

[5]  G Stolovitzky,et al.  Efficiency of DNA replication in the polymerase chain reaction. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[6]  J. Sninsky,et al.  PCR Applications: Protocols for Functional Genomics , 1999 .

[7]  Arjang Hassibi,et al.  A STOCHASTIC MODEL AND SIMULATION ALGORITHM FOR POLYMERASE CHAIN REACTION ( PCR ) SYSTEMS , 2004 .

[8]  Thomas Kailath,et al.  Detection of signals by information theoretic criteria , 1985, IEEE Trans. Acoust. Speech Signal Process..

[9]  C. Wittwer,et al.  Continuous fluorescence monitoring of rapid cycle DNA amplification. , 1997, BioTechniques.

[10]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[11]  R. D. DeGroat,et al.  Exponential parameter estimation In the presence of known components and noise , 1994 .

[12]  Cheng Zhao,et al.  Estimation of the Mutation Rate During Error-prone Polymerase Chain Reaction , 2000, J. Comput. Biol..

[13]  P. Jagers,et al.  Random variation and concentration effects in PCR. , 2003, Journal of theoretical biology.

[14]  Yulei Zhang,et al.  Information theory-based algorithm for in silico prediction of PCR products with whole genomic sequences as templates , 2005, BMC Bioinformatics.

[15]  J. Dion Estimation of the mean and the initial probabilities of a branching process , 1974, Journal of Applied Probability.

[16]  R. Abramson,et al.  Detection of specific polymerase chain reaction product by utilizing the 5'----3' exonuclease activity of Thermus aquaticus DNA polymerase. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Nadia Lalam,et al.  Modelling the PCR amplification process by a size-dependent branching process and estimation of the efficiency , 2004, Advances in Applied Probability.

[18]  K. Mullis,et al.  Specific synthesis of DNA in vitro via a polymerase-catalyzed chain reaction. , 1987, Methods in enzymology.

[19]  Gordon K. Smyth,et al.  A Modified Prony Algorithm for Exponential Function Fitting , 1995, SIAM J. Sci. Comput..