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使用定量聚合酶链反应进行测量的理论不确定性

Theoretical uncertainty of measurements using quantitative polymerase chain reaction.

作者信息

Peccoud J, Jacob C

机构信息

TIMC-IMAG, Institut Albert Bonniot, Faculté de médecine de Grenoble, La Tronche,

出版信息

Biophys J. 1996 Jul;71(1):101-8. doi: 10.1016/S0006-3495(96)79205-6.

DOI:10.1016/S0006-3495(96)79205-6
PMID:8804593
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1233461/
Abstract

Current quantitative polymerase chain reaction (PCR) protocols are only indicative of the quantity of a target sequence relative to a standard, because no means of estimating the amplification rate is yet available. The variability of PCR performed on isolated cells has already been reported by several authors, but it could not be extensively studied, because of lack of a system for doing kinetic data acquisition and of statistical methods suitable for analyzing this type of data. We used the branching process theory to simulate and analyze quantitative kinetic PCR data. We computed the probability distribution of the offspring of a single molecule. We demonstrated that the rate of amplication has a severe influence on the shape of this distribution. For high values of the amplification rate, the distribution has several maxima of probability. A single amplification trajectory is used to estimate the initial copy number of the target sequence as well as its confidence interval, provided that the amplification is done over more than 20 cycles. The consequence of possible molecular fluctuations in the early stage of amplification is that small copy numbers result in relatively larger intervals than large initial copy numbers. The confidence interval amplitude is the theoretical uncertainty of measurements using quantitative PCR. We expect these results to be applicable to the data produced by the next generation of thermocyclers for quantitative applications.

摘要

目前的定量聚合酶链反应(PCR)方案仅能表明目标序列相对于标准的数量,因为尚无估计扩增率的方法。几位作者已经报道了对分离细胞进行PCR的变异性,但由于缺乏进行动力学数据采集的系统以及适合分析此类数据的统计方法,无法对其进行广泛研究。我们使用分支过程理论来模拟和分析定量动力学PCR数据。我们计算了单个分子后代的概率分布。我们证明扩增率对该分布的形状有严重影响。对于高扩增率值,分布有几个概率最大值。只要扩增超过20个循环,单个扩增轨迹就可用于估计目标序列的初始拷贝数及其置信区间。扩增早期可能的分子波动的结果是,小拷贝数导致的区间相对大于大的初始拷贝数。置信区间幅度是使用定量PCR测量的理论不确定性。我们期望这些结果适用于下一代用于定量应用的热循环仪产生的数据。