Department of Forensic Genetics, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China.
Laboratory of Molecular Translational Medicine, Center for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
Forensic Sci Int Genet. 2020 Nov;49:102371. doi: 10.1016/j.fsigen.2020.102371. Epub 2020 Aug 14.
A set of DNA methylation markers was detected and evaluated to identify body fluids using the amplification refractory mutation system-PCR (ARMS-PCR) and random forest algorithm. In this study, four multiplex DNA methylation reactions composed of 22 promising methylation markers were used to identify regular forensic body fluids, including venous blood, saliva, semen, menstrual blood, and vaginal fluid. The ARMS-specific primers were used to amplify the candidate markers, and then the methylation values of each CpG site were detected through capillary electrophoresis (CE). The DNA methylation patterns of 22 highly informative methylation markers were consistent with previously reported results to a certain extent. To our knowledge, our study is a new method to apply the ARMS-PCR technique and random forest model to detect DNA methylation patterns and identify the type of body fluids in forensic science, thus providing a new method for forensic body fluid identification. Moreover, we proved that this method is robust, applicable and effective for identifying body fluids using the random forest model. The accuracy to predict all body fluids reached up to 0.9966. We firmly believe that this method will have a great potential in the detection of methylation profiles at the molecular level.
采用扩增受阻突变系统-聚合酶链反应（ARMS-PCR）和随机森林算法，检测并评估了一组 DNA 甲基化标记物，以识别体液。在这项研究中，使用了由 22 个有前途的甲基化标记物组成的四个多重 DNA 甲基化反应，以识别常规法医体液，包括静脉血、唾液、精液、月经血和阴道液。ARMS 特异性引物用于扩增候选标记物，然后通过毛细管电泳（CE）检测每个 CpG 位点的甲基化值。22 个高信息量甲基化标记物的 DNA 甲基化模式在一定程度上与先前报道的结果一致。据我们所知，我们的研究是一种新的方法，应用 ARMS-PCR 技术和随机森林模型来检测 DNA 甲基化模式，并识别法医学中的体液类型，从而为法医体液识别提供了一种新方法。此外，我们通过随机森林模型证明了该方法在识别体液方面具有稳健性、适用性和有效性。预测所有体液的准确率高达 0.9966。我们坚信，这种方法在分子水平上检测甲基化谱方面具有巨大的潜力。
