Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
School of Basic Medical Sciences, Anhui Medical University, Hefei, 230031, Anhui, China.
Hereditas. 2023 Mar 29;160(1):14. doi: 10.1186/s41065-023-00271-2.
Dongxiang group, as an important minority, resides in Gansu province which is located at the northwest China, forensic detection system with more loci needed to be studied to improve the application efficiency of forensic case investigation in this group.
A 60-plex system including 57 autosomal deletion/insertion polymorphisms (A-DIPs), 2 Y chromosome DIPs (Y-DIPs) and the sex determination locus (Amelogenin) was explored to evaluate the forensic application efficiencies of individual discrimination, kinship analysis and biogeographic origin prediction in Gansu Dongxiang group based on the 60-plex genotype results of 233 unrelated Dongxiang individuals. The 60-plex genotype results of 4582 unrelated individuals from 33 reference populations in five different continents were also collected to analyze the genetic background of Dongxiang group and its genetic relationships with other continental populations.
The system showed high individual discrimination power, as the cumulative power of discrimination (CPD), cumulative power of exclusion (CPE) for trio and cumulative match probability (CMP) values were 0.99999999999999999999997297, 0.999980 and 2.7029E, respectively. The system could distinguish 98.12%, 93.78%, 82.18%, 62.35% and 39.32% of full sibling pairs from unrelated individual pairs, when the likelihood ratio (LR) limits were set as 1, 10, 100, 1000 and 10,000 based on the simulated family samples, respectively. Additionally, Dongxiang group had the close genetic distances with populations in East Asia, especially showed the intimate genetic relationships with Chinese Han populations, which were concluded from the genetic affinities and genetic background analyses of Dongxiang group and 33 reference populations. In terms of the effectiveness of biogeographic origin inference, different artificial intelligent algorithms possessed different efficacies. Among them, the random forest (RF) and extreme gradient boosting (XGBoost) algorithm models could accurately predict the biogeographic origins of 99.7% and 90.59% of three and five continental individuals, respectively.
This 60-plex system had good performance for individual discrimination, kinship analysis and biogeographic origin prediction in Dongxiang group, which could be used as a powerful tool for case investigation.
东乡族作为中国的一个重要少数民族，居住在中国西北部的甘肃省。为了提高法医学在该群体中进行案件调查的应用效率，需要研究更多的遗传标记。
本研究开发了一个包含 57 个常染色体缺失/插入多态性（A-DIPs）、2 个 Y 染色体 DIPs（Y-DIPs）和性别决定基因座（Amelogenin）的 60 plex 系统，以评估该系统在甘肃东乡族个体识别、亲缘关系分析和生物地理起源预测方面的法医学应用效率。本研究基于 233 名无关东乡个体的 60 plex 基因型结果，对该系统进行了评价。此外，还收集了来自五个不同大陆的 33 个参考人群的 4582 名无关个体的 60 plex 基因型结果，以分析东乡族的遗传背景及其与其他大陆人群的遗传关系。
该系统具有较高的个体识别能力，累积鉴别力（CPD）、累积排除力（CPE）和累积匹配概率（CMP）值分别为 0.99999999999999999999997297、0.999980 和 2.7029E。当似然比（LR）限值分别设定为 1、10、100、1000 和 10000 时，该系统可以从无关个体对中区分出 98.12%、93.78%、82.18%、62.35%和 39.32%的全同胞对，这是基于模拟家庭样本得出的结果。此外，东乡族与东亚人群具有较近的遗传距离，尤其是与中国汉族人群具有密切的遗传关系，这是从东乡族和 33 个参考人群的遗传关系和遗传背景分析中得出的结论。在生物地理起源推断的有效性方面，不同的人工智能算法具有不同的效果。其中，随机森林（RF）和极端梯度增强（XGBoost）算法模型可以分别准确预测三个和五个大陆个体的 99.7%和 90.59%的生物地理起源。
该 60 plex 系统在东乡族个体识别、亲缘关系分析和生物地理起源预测方面具有良好的性能，可作为案件调查的有力工具。
