Comparison of STR profiling from low template DNA extracts with and without the consensus profiling method.

Kelly S Grisedale, Angela van Daal
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引用次数: 31

Abstract

Background: The consensus profiling method was introduced to overcome the exaggerated stochastic effects associated with low copy number DNA typing. However, little empirical evidence has been provided which shows that a consensus profile, derived from dividing a sample into separate aliquots and including only alleles seen at least twice, gives the most informative profile, compared to a profile obtained by amplifying the entire low template DNA extract in one reaction. Therefore, this study aimed to investigate the quality of consensus profiles compared to profiles obtained using the whole low template extract for amplification.

Methods: A total of 100 pg and 25 pg DNA samples were amplified with the PowerPlex® ESI 16 Kits using 30 or 34 PCR cycles. A total of 100 pg and 25 pg DNA samples were then divided into three aliquots for a 34-cycle PCR and a consensus profile derived that included alleles that appeared in at least two of the replicates. Profiles from the non-split samples were compared to the consensus profiles focusing on peak heights, allele drop out, locus drop out and allele drop in.

Results: Performing DNA profiling on non-split extracts produced profiles with a higher percentage of correct loci compared to the consensus profiling technique. Consensus profiling did eliminate any spurious alleles from the final profile. However, there was a notable increase in allele and locus drop out when a LTDNA sample was divided prior to amplification.

Conclusions: The loss of information that occurs when a sample is split for amplification indicates that consensus profiling may not be producing the most informative DNA profile for samples where the template amount is limited.

采用与不采用共识分析方法的低模板DNA提取STR分析比较。
背景:为了克服与低拷贝数DNA分型相关的夸张的随机效应,引入了共识分析方法。然而,很少有经验证据表明,与在一次反应中扩增整个低模板DNA提取物获得的图谱相比,将样本分成单独的等分并仅包括至少两次的等位基因获得的共识图谱提供了最丰富的信息图谱。因此,本研究旨在探讨共识档案的质量与使用整个低模板提取扩增获得的档案相比。方法:使用PowerPlex®ESI 16试剂盒扩增100 pg和25 pg的DNA样本,分别进行30或34个PCR循环。然后将总共100 pg和25 pg的DNA样本分成三个等份,进行34个周期的PCR,并得出共识的图谱,其中包括至少两个重复中出现的等位基因。将非分裂样本的图谱与关注峰高、等位基因缺失、位点缺失和等位基因缺失的共识图谱进行比较。结果:与共识分析技术相比,对非分裂提取物进行DNA分析产生的正确位点百分比更高。共识分析确实消除了最终侧写中的任何虚假等位基因。然而,当LTDNA样本在扩增前进行分裂时,等位基因和位点缺失明显增加。结论:当样本分离扩增时发生的信息丢失表明,对于模板数量有限的样本,共识分析可能无法产生最具信息量的DNA图谱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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