Extended Kinship Inference Part 2: Evaluation of the Impact of Information Loss on Likelihood Ratios and Haplotype Matching

Abstract

Medium-density single nucleotide polymorphism (SNP) profiles enable law enforcement to infer close and distant genetic relationships. Part one of this study demonstrated that the ForenSeq® Kintelligence Kit, which targets 10,230 SNPs, can facilitate extended kinship inference through kinship likelihood ratio (LR) and identical by descent (IBD) segment matching methods. However, if SNPs are not detected, or are incorrectly called, the ability to detect genetic relatives and accurately classify the relationship may be compromised. The Kintelligence profiles for the central individuals of two pedigrees described in Part One were edited to simulate information loss through locus and allele dropout. LRs were calculated with DBLR™ and SNP profiles were uploaded to GEDmatch PRO™ for database searching or direct comparison. The LRs decreased with increasing information loss but still provided strong statistical support for relatedness. LRs exceeded 100,000 for all full sibling to fifth degree relationships for up to 30% locus and allele dropout. Locus dropout did not significantly impact the ability to infer first to fifth degree relationships with IBD segment matching. Allele dropout had a greater impact, with 30% allele dropout impairing the ability to classify relationships to their correct degree. When allele dropout was greater than 10%, the fifth degree relative was no longer detected in the database search. This study highlights the robustness of LR calculations and the GEDmatch PRO™ IBD segment matching algorithms and the suitability of the Kintelligence Kit for medium-range kinship inference, with the algorithm maintaining the ability to infer relationships despite increasing information loss.