Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms.
Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms.
复制标题
DOI：
10.1371/journal.pone.0160287
复制
发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Tamaki K
中科院分区：
文献类型：
--
作者：
Morimoto C;Manabe S;Kawaguchi T;Kawai C;Fujimoto S;Hamano Y;Yamada R;Matsuda F;Tamaki K
我们开发了一种基于两个个体之间染色体共享的法医遗传学成对亲属分析的新方法。在这里，我们定义了“染色体共享指数”（ICS），通过SNP微阵列分型的174,254个单核苷酸多态性（SNP）位点和来自两个个体的基因型共享片段的遗传长度来计算。为了研究从一级到五度亲缘关系和非亲缘关系对的预期ICS分布，我们使用计算生成的基因型来考虑连锁不平衡和重组的影响。在不考虑等位基因频率和单倍型频率的情况下，采用似然比（LR）或后验概率等方法对两两亲属关系分析进行概率评估。使用我们的方法，来自志愿者的所有实际样本对都显示出显著的高LR值（即≥108）；因此，我们可以根据LR区分远距离关系（直到五度）和不相关的关系。此外，即使这对夫妇的亲属关系完全不可预测，我们也可以使用后验概率≥0.90的标准，以bbbb80 %的概率准确确定三度关系中的亲属关系程度。这种方法大大改进了对远亲关系的两两亲属分析，特别是在涉及识别灾害受害者或失踪人员的情况下。
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.
影响因子：
2.9
作者：
Narahara M;Tamaki K;Yamada R
通讯作者：
Yamada R