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通过对二项式采样的激光捕获细胞群体进行概率计算机解释来进行DNA混合物基因分型:结合定量数据以获取更多识别信息。

DNA mixture genotyping by probabilistic computer interpretation of binomially-sampled laser captured cell populations: combining quantitative data for greater identification information.

作者信息

Ballantyne Jack, Hanson Erin K, Perlin Mark W

机构信息

National Center for Forensic Science, Orlando, FL, USA.

出版信息

Sci Justice. 2013 Jun;53(2):103-14. doi: 10.1016/j.scijus.2012.04.004. Epub 2012 May 16.

Abstract

Two person DNA admixtures are frequently encountered in criminal cases and their interpretation can be challenging, particularly if the amount of DNA contributed by both individuals is approximately equal. Due to an inevitable degree of uncertainty in the constituent genotypes, reduced statistical weight is given to the mixture evidence compared to that expected from the constituent single source contributors. The ultimate goal of mixture analysis, then, is to precisely discern the constituent genotypes and here we posit a novel strategy to accomplish this. We hypothesised that LCM-mediated isolation of multiple groups of cells ('binomial sampling') from the admixture would create separate cell sub-populations with differing constituent weight ratios. Furthermore we predicted that interpreting the resulting DNA profiling data by the quantitative computer-based TrueAllele® interpretation system would result in an efficient recovery of the constituent genotypes due to newfound abilities to compute a maximum LR from sub-samples with skewed weight ratios, and to jointly interpret all possible pairings of sub-samples using a joint likelihood function. As a proof of concept, 10 separate cell samplings of size 20 recovered by LCM from each of two 1:1 buccal cell mixtures were DNA-STR profiled using a specifically developed LCN methodology, with the data analyzed by the TrueAllele® Casework system. In accordance with the binomial sampling hypothesis, the sub-samples exhibited weight ratios that were well dispersed from the 50% center value (50±35% at the 95% level). The maximum log(LR) information for a genotype inferred from a single 20 cell sample was 18.5 ban, with an average log(LR) information of 11.7 ban. Co-inferring genotypes using a joint likelihood function with two sub-samples essentially recovered the full genotype information. We demonstrate that a similar gain in genotype information can be obtained with standard (28-cycle) PCR conditions using the same joint interpretation methods. Finally, we discuss the implications of this work for routine forensic practice.

摘要

两人DNA混合样本在刑事案件中经常遇到,对其进行解读可能具有挑战性,特别是当两人贡献的DNA量大致相等时。由于组成基因型存在不可避免的不确定性,与单个来源样本相比,混合样本证据的统计权重有所降低。因此,混合样本分析的最终目标是精确识别组成基因型,在此我们提出一种新策略来实现这一目标。我们假设通过激光捕获显微切割(LCM)从混合样本中分离多组细胞(“二项式采样”)将产生具有不同组成权重比的单独细胞亚群。此外,我们预测,使用基于计算机的定量TrueAllele®解读系统解读所得的DNA分型数据,将能够有效恢复组成基因型,因为该系统具备从权重比不均衡的子样本中计算最大似然比(LR),以及使用联合似然函数共同解读所有可能子样本配对的新能力。作为概念验证,使用专门开发的低拷贝数(LCN)方法对通过LCM从两个1:1口腔细胞混合物中分别回收的10个大小为20的细胞样本进行DNA-STR分型,并使用TrueAllele®案例分析系统对数据进行分析。根据二项式采样假设,子样本的权重比在95%水平上从50%中心值(50±35%)有很好的分散。从单个20细胞样本推断出的基因型的最大对数似然比(log(LR))信息为18.5 ban,平均对数似然比信息为11.7 ban。使用联合似然函数对两个子样本共同推断基因型基本上恢复了完整的基因型信息。我们证明,使用相同的联合解读方法,在标准(28个循环)PCR条件下也可以获得类似的基因型信息增益。最后,我们讨论了这项工作对常规法医实践的影响。

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