Leveraging microhaplotype information from hybridization capture SNP panels to enhance pairwise kinship inference

Hybridization capture-based single nucleotide polymorphism (SNP) panels have been widely adopted for forensic kinship inference, yet conventional analysis treats each captured SNP independently, potentially underutilizing the genetic information embedded within enriched DNA fragments. Here, we present a bioinformatic strategy that transforms dense SNP panels into microhaplotype (MH) panels by extending core SNPs into fragment-level haplotypes, without altering probe design or laboratory workflows. Using a capture panel targeting 5761 autosomal SNPs, we successfully converted 5186 loci into MHs by identifying additional polymorphic sites within captured fragments. The resulting SNP-extended panel exhibited substantially increased allelic diversity and effective allele numbers compared with the original SNP panel, while maintaining stable read depth and heterozygote balance across 69 true samples. Three parent-offspring pairs yielded discordant results at individual loci, each attributable to single-SNP mutations within an MH allele, illustrating the interpretative advantage of haplotype-level data. Performance evaluation using simulated pedigrees encompassing six relationship types demonstrated that the SNP-extended panel consistently outperformed the SNP-only panel in pairwise kinship inference under both likelihood ratio (LR) and maximum-LR frameworks, with the most pronounced improvements observed for third-degree and more distant relationships. Validation with true samples from two extended pedigrees confirmed the practical applicability of the approach. This study provides proof of concept that bioinformatic reinterpretation of capture-based SNP data into MHs offers a scalable and cost-effective pathway to further improve the discriminatory power of existing SNP panels for forensic kinship analysis.