Discrimination of relationships with the same degree of kinship using chromosomal sharing patterns estimated from high-density SNPs. (March 2018)

• Record Type: Journal Article
• Authors: Morimoto, Chie; Manabe, Sho; Fujimoto, Shuntaro; Hamano, Yuya; Tamaki, Keiji
• Is Part Of: Forensic science international. Volume 33(2018)
• Page Start: 10
• Page End: 16
• Publication Date: 2018-03
• Subjects: Kinship analysis -- Single nucleotide polymorphisms -- Same degree of kinship -- Chromosomal sharing -- DNA microarray; Forensic genetics -- Periodicals; Génétique légale -- Périodiques; Forensic genetics; Electronic journals; Periodicals; 614.1
• DOI: 10.1016/j.fsigen.2017.11.010
• Languages: English
• ISSNs: 1872-4973

Abstract

Highlights: We developed a method for discerning relationships with the same degree of kinship. Chromosomal sharing patterns of relative pairs were estimated by high-density SNPs. The number of shared chromosomal segments tended to be larger in collateral pairs. Logistic regression was used for the probabilistic determination of kinship. Relationships between actual sample pairs were mostly correctly judged. Abstract: Distinguishing relationships with the same degree of kinship (e.g., uncle–nephew and grandfather–grandson) is generally difficult in forensic genetics by using the commonly employed short tandem repeat loci. In this study, we developed a new method for discerning such relationships between two individuals by examining the number of chromosomal shared segments estimated from high-density single nucleotide polymorphisms (SNPs). We computationally generated second-degree kinships (i.e., uncle–nephew and grandfather–grandson) and third-degree kinships (i.e., first cousins and great-grandfather–great-grandson) for 174, 254 autosomal SNPs considering the effect of linkage disequilibrium and recombination for each SNP. We investigated shared chromosomal segments between two individuals that were estimated based on identity by state regions. We then counted the number of segments in each pair. Based on our results, the number of shared chromosomal segments in collateral relationships was larger than that in lineal relationships with both the second-degree and third-degree kinships. This was probably caused by differences involving chromosomal transitions and recombination between relationships. As we probabilistically evaluated the relationships between simulated pairs based on the number of shared segments using logistic regression, we could determine accurate relationships in >90% of second-degree relatives and >70% of third-degree relatives, using a probability criterion for the relationship ≥0.9. Furthermore, we could judge the true relationships of actual sample pairs from volunteers, as well as simulated data. Therefore, this method can be useful for discerning relationships between two individuals with the same degree of kinship.