Gill Peter, Curran James, Elliot Keith
Forensic Science Service, Birmingham UK.
Nucleic Acids Res. 2005 Jan 28;33(2):632-43. doi: 10.1093/nar/gki205. Print 2005.
The use of expert systems to interpret short tandem repeat DNA profiles in forensic, medical and ancient DNA applications is becoming increasingly prevalent as high-throughput analytical systems generate large amounts of data that are time-consuming to process. With special reference to low copy number (LCN) applications, we use a graphical model to simulate stochastic variation associated with the entire DNA process starting with extraction of sample, followed by the processing associated with the preparation of a PCR reaction mixture and PCR itself. Each part of the process is modelled with input efficiency parameters. Then, the key output parameters that define the characteristics of a DNA profile are derived, namely heterozygote balance (Hb) and the probability of allelic drop-out p(D). The model can be used to estimate the unknown efficiency parameters, such as pi(extraction). 'What-if' scenarios can be used to improve and optimize the entire process, e.g. by increasing the aliquot forwarded to PCR, the improvement expected to a given DNA profile can be reliably predicted. We demonstrate that Hb and drop-out are mainly a function of stochastic effect of pre-PCR molecular selection. Whole genome amplification is unlikely to give any benefit over conventional PCR for LCN.
随着高通量分析系统产生大量处理耗时的数据,在法医、医学和古DNA应用中使用专家系统来解释短串联重复DNA图谱的情况越来越普遍。特别针对低拷贝数(LCN)应用,我们使用图形模型来模拟与整个DNA过程相关的随机变化,该过程从样本提取开始,接着是与PCR反应混合物制备及PCR本身相关的处理。过程的每个部分都用输入效率参数进行建模。然后,得出定义DNA图谱特征的关键输出参数,即杂合子平衡(Hb)和等位基因缺失概率p(D)。该模型可用于估计未知效率参数,如pi(提取)。“假设”情景可用于改进和优化整个过程,例如通过增加转入PCR的等分试样,可可靠预测对给定DNA图谱的预期改进。我们证明Hb和缺失主要是PCR前分子选择随机效应的函数。对于LCN,全基因组扩增不太可能比传统PCR有任何优势。