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微单倍型和 Y-SNP/STR(MY):一种基于 MPS 的新型系统,用于在两人混合 DNA 中进行基因型模式识别。

Microhaplotype and Y-SNP/STR (MY): A novel MPS-based system for genotype pattern recognition in two-person DNA mixtures.

机构信息

Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, Guangdong, China; Institute of Archaeological Science, Fudan University, Shanghai 200433, China; School of Basic Medicine and Life Science, Hainan Medical University, Haikou 571199, Hainan, China.

Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, Guangdong, China.

出版信息

Forensic Sci Int Genet. 2022 Jul;59:102705. doi: 10.1016/j.fsigen.2022.102705. Epub 2022 Apr 13.

DOI:10.1016/j.fsigen.2022.102705
PMID:35462161
Abstract

BACKGROUNDS

Y-chromosomal haplotypes based on Y-short tandem repeats (STRs) and Y-single nucleotide polymorphisms/insertion and deletion polymorphisms (SNPs/InDels) are used to characterize paternal lineages of unknown male trace donors. However, Y-chromosomal genetic markers are not currently sufficient for precise individual identification. Microhaplotype (MH), generally < 200 bp on autosomes and consisting of two or more SNPs, was recently introduced in forensic genetics with the development of massive parallel sequencing technology and may facilitate identification and DNA mixture deconvolution. Therefore, combining the two kinds of genetic markers may be beneficial in many forensic scenarios, especially crime scenes with male suspects, such as sexual assault cases.

METHODS

In the present study, we developed a novel MPS-based panel, Microhaplotype and Y-SNP/STR (MY), by multiplex PCR and 150-bp paired-end sequencing, including 114 Y-SNPs (twelve dominant Y-DNA haplogroups), 45 Y-STRs (N-1 stutter < 0.09; estimated mutation rate < 5 × 10), and 22 MHs (allele coverage ratio > 0.91; pairwise distance > 10 Mb). Additionally, MY system-based genotype pattern recognition (GPR), a regression-based method to identify the genotype pattern for each MH locus, is proposed for two-person DNA mixture deconvolution. We integrated 26 two-person genotype combinations into nine genotype patterns and validated the application range of GPR based on DNA profiles of ten sets of simulated male-male DNA mixtures (1:10-1:2).

RESULTS

The effective number of alleles (A) ranged from 3.62 to 14.72, with an average of 7.17, in 100 Chinese Guangdong Han individuals. The cumulative discrimination power was 1-5.00 × 10, and the cumulative power of exclusion was 1-5.00 × 10 and 1-4.85 × 10 for duo and trio paternity testing, respectively. Furthermore, the actual mixing ratio-depth of coverage (DoC) ratio (R) regression relationships were established for different genetic markers and genotype patterns. In five overlapping areas, genotype differentiation of the major and minor contributors required likelihood ratio methods. In nonoverlapping areas, the genotype pattern could be recognized by comparing the observed R and R ranges.

CONCLUSION

The GPR can be used to deconvolute two-person DNA mixtures (application range: 1:10-1:2) for individual identification.

摘要

背景

基于 Y 短串联重复序列(STRs)和 Y 单核苷酸多态性/插入和缺失多态性(SNPs/InDels)的 Y 染色体单倍型可用于描述未知男性痕迹供体的父系血统。然而,Y 染色体遗传标记目前还不足以进行精确的个体识别。微单倍型(MH)通常在常染色体上小于 200bp,由两个或多个 SNPs 组成,随着大规模平行测序技术的发展,最近在法医遗传学中引入,可能有助于识别和 DNA 混合物的解卷积。因此,结合这两种遗传标记在许多法医场景中可能是有益的,特别是在有男性嫌疑人的犯罪现场,如性侵犯案件。

方法

在本研究中,我们通过多重 PCR 和 150-bp 配对末端测序开发了一种新的基于 MPS 的面板,即微单倍型和 Y-SNP/STR(MY),包括 114 个 Y-SNPs(十二个主导的 Y-DNA 单倍群)、45 个 Y-STRs(N-1 突峰<0.09;估计突变率<5×10)和 22 个 MHs(等位基因覆盖率>0.91;成对距离>10Mb)。此外,还提出了基于 MY 系统的基因型模式识别(GPR),这是一种基于回归的方法,用于识别每个 MH 位点的基因型模式,用于两人 DNA 混合物的解卷积。我们将 26 种两人基因型组合整合到 9 种基因型模式中,并基于 10 组模拟男性-男性 DNA 混合物(1:10-1:2)的 DNA 图谱验证了 GPR 的应用范围。

结果

100 名中国广东汉族个体中,有效等位基因数(A)范围为 3.62-14.72,平均值为 7.17。累积鉴别力为 1-5.00×10,双亲鉴定的累积排除力分别为 1-5.00×10和 1-4.85×10。此外,还建立了不同遗传标记和基因型模式的实际混合比-深度覆盖率(DoC)比(R)回归关系。在五个重叠区域,需要使用似然比方法来区分主要和次要供体的基因型分化。在非重叠区域,可以通过比较观察到的 R 和 R 范围来识别基因型模式。

结论

GPR 可用于解卷积两人 DNA 混合物(应用范围:1:10-1:2)进行个体识别。

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