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通过大规模并行测序,改善了不相关或相关贡献者的DNA混合物中的个体识别
Zhiyong Liu1, Enlin Wu1, Ran Li2
1Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China; Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou 510080, China.
Forensic science international. Genetics
|June 18, 2024
概括
研究与相关贡献者的DNA混合物揭示了亲属关系不会阻碍主要贡献者识别,但基于序列的基因型定型可以提高准确性. 这项研究验证了大规模并行测序 (MPS) 面板用于法医DNA混合分析.
科学领域:
- 法医遗传学 法医遗传学
- 分子生物学分子生物学
- 生物统计学 生物统计学
背景情况:
- 法医DNA混合分析通常在计算概率比率 (LR) 时假定不相关的贡献者.
- 在DNA混合物中的相关贡献者在确定贡献者数量 (NOC) 和构建概率基因型化模型方面存在挑战.
- 了解亲属关系对个人识别的影响对于复杂的法医案件至关重要.
研究的目的:
- 评估潜在亲属关系对DNA混合物中感兴趣的人 (POI) 个体识别的影响.
- 评估大规模并行测序 (MPS) 使用MGIEasy签名识别库准备包在分析相关和非相关DNA混合物的性能.
- 为了比较基于长度和基于序列的短并列重复 (STR) 基因型鉴定在混合物解释中的有效性.
主要方法:
- 模拟两个和三个人的DNA混合物,不同比例的无关和相关的贡献者 (父母-孩子,兄弟姐妹,叔叔-子).
- 在MGI平台上使用MGIEasy签名识别库准备套件进行了大规模并行测序 (MPS).
- 在模拟中进行并分析了多个遗传标记,亲属假设和STR基因定型方法对LR值和NOC推断的影响.
主要成果:
- 多个遗传标记在DNA混合物中改善了亲属关系和NOC推断.
- 对感兴趣的人 (POI) 的概率比率 (LR) 值高度依赖混合比率.
- 亲属关系考虑没有显著影响主要POI识别,尽管正确的亲属关系产生了保守的LR,而不正确的亲属关系并不能保证识别失败;小贡献者识别显示不确定性.
- 基于序列的STR基因型定型增强了POI识别能力,与基于长度的基因型定型相比,改进了混合比率推断准确度.
结论:
- MGIEasy签名识别库准备套件是用于法医DNA混合物解释的强大的MPS面板.
- 该套件证明了与无关和相关贡献者的混合物分析的可行性.
- 基于序列的STR基因型定型为法医DNA混合分析提供了准确性和识别能力的优势.
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