Verogen. Verogen Inc., 11111 Flintkote Ave, San Diego, CA 92121, USA.
Fulcrum Genomics, Fulcrum Genomics LLC, 1840 Folsom St Suite 304, Boulder, CO 80302, USA.
Forensic Sci Int Genet. 2022 Nov;61:102769. doi: 10.1016/j.fsigen.2022.102769. Epub 2022 Aug 27.
Forensic genetic genealogy (FGG) has primarily relied upon dense single nucleotide polymorphism (SNP) profiles from forensic samples or unidentified human remains queried against online genealogy database(s) of known profiles generated with SNP microarrays or from whole genome sequencing (WGS). In these queries, SNPs are compared to database samples by locating contiguous stretches of shared SNP alleles that allow for detection of genomic segments that are identical by descent (IBD) among biological relatives (kinship). This segment-based approach, while robust for detecting distant relationships, generally requires DNA quantity and/or quality that are sometimes not available in forensic casework samples. By focusing on SNPs with maximal discriminatory power and using an algorithm designed for a sparser SNP set than those from microarray typing, performance similar to segment matching was reached even in difficult casework samples. This algorithm locates shared segments using kinship coefficients in "windows" across the genome. The windowed kinship algorithm is a modification of the PC-AiR and PC-Relate tools for genetic relatedness inference, referred to here as the "whole genome kinship" approach, that control for the presence of unknown or unspecified population substructure. Simulated and empirical data in this study, using DNA profiles comprised of 10,230 SNPs (10K multiplex) targeted by the ForenSeq™ Kintelligence Kit demonstrate that the windowed kinship approach performs comparably to segment matching for identifying first, second and third degree relationships, reasonably well for fourth degree relationships, and with fewer false kinship associations. Selection criteria for the 10K SNP PCR-based multiplex and functionality of the windowed kinship algorithm are described.
法医遗传基因学（FGG）主要依赖于从法医样本或身份不明的人类遗骸中获取的密集单核苷酸多态性（SNP）图谱，或者从 SNP 微阵列或全基因组测序（WGS）生成的已知图谱的在线家谱数据库中查询。在这些查询中，通过定位连续的共享 SNP 等位基因片段，将 SNPs 与数据库样本进行比较，这些片段允许检测生物亲属（亲属关系）中具有相同遗传来源（IBD）的基因组片段。这种基于片段的方法虽然在检测远距离关系方面非常强大，但通常需要法医工作样本中有时无法获得的 DNA 数量和/或质量。通过关注具有最大区分力的 SNP，并使用专为比微阵列分型 SNP 集合更稀疏的 SNP 集设计的算法，即使在困难的工作样本中，也可以达到类似于片段匹配的性能。该算法使用基因组中“窗口”的亲属系数来定位共享片段。窗口亲缘关系算法是用于遗传相关性推断的 PC-AiR 和 PC-Relate 工具的修改版，在此称为“全基因组亲缘关系”方法，可控制未知或未指定的人口亚结构的存在。本研究使用包含 10,230 个 SNP（10K 多重）的 DNA 图谱的模拟和经验数据（由 ForenSeq ™ Kintelligence 试剂盒靶向）表明，窗口亲缘关系方法在识别第一、第二和第三度关系方面与片段匹配性能相当，在识别第四度关系方面表现相当好，并且假亲属关系关联较少。描述了用于 10K SNP 基于 PCR 的多重分析的选择标准和窗口亲缘关系算法的功能。
