Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms

We developed a new approach for pairwise kinship analysis in forensic genetics based on chromosomal sharing between two individuals. Here, we defined “index of chromosome sharing” (ICS) calculated using 174,254 single nucleotide polymorphism (SNP) loci typed by SNP microarray and genetic length of the shared segments from the genotypes of two individuals. To investigate the expected ICS distributions from first- to fifth-degree relatives and unrelated pairs, we used computationally generated genotypes to consider the effect of linkage disequilibrium and recombination. The distributions were used for probabilistic evaluation of the pairwise kinship analysis, such as likelihood ratio (LR) or posterior probability, without allele frequencies and haplotype frequencies. Using our method, all actual sample pairs from volunteers showed significantly high LR values (i.e., ≥ 108); therefore, we can distinguish distant relationships (up to the fifth-degree) from unrelated pairs based on LR. Moreover, we can determine accurate degrees of kinship in up to third-degree relationships with a probability of > 80% using the criterion of posterior probability ≥ 0.90, even if the kinship of the pair is totally unpredictable. This approach greatly improves pairwise kinship analysis of distant relationships, specifically in cases involving identification of disaster victims or missing persons.本研究开发了一种基于两名个体间染色体共享特征的法医遗传学两两亲缘关系分析新方法。本研究定义了染色体共享指数（index of chromosome sharing，ICS），该指数通过SNP芯片分型得到的174254个单核苷酸多态性（single nucleotide polymorphism，SNP）位点，以及两名个体基因型中共享片段的遗传长度计算得到。为探究一级至五级亲缘关系及无关个体对的预期ICS分布，本研究采用计算机模拟生成的基因型数据，以考量连锁不平衡与重组的影响。该分布可用于两两亲缘关系分析的概率推断，无需依赖等位基因频率与单倍型频率即可计算似然比（likelihood ratio，LR）或后验概率等指标。应用本方法时，所有来自志愿者的实际样本对均呈现显著较高的似然比（即≥10⁸），因此可基于似然比将远缘亲缘关系（最高至五级）与无关个体对区分开来。此外，即便待分析样本对的亲缘关系完全未知，以≥0.90的后验概率作为判定标准，本方法仍可在80%以上的概率下准确判定三级及以内亲缘关系的具体等级。该方法极大地提升了远缘亲缘关系的两两亲缘关系分析效能，尤其适用于灾难受害者识别或失踪人员身份鉴定场景。