Identification of missing persons through kinship analysis by microhaplotype sequencing of single-source DNA and two-person DNA mixtures

Abstract

In forensic applications, there is an increasing demand for the analysis of DNA profiles arising from missing person identification (MPI) cases. A specific DNA profile may originate from a single source or more than one contributor (i.e., a DNA mixture). When direct references are not available, indirect relative references can be used to identify missing persons by kinship analysis. As a novel kind of multiallelic marker, microhaplotypes have proven promising for relatedness determination and mixture deconvolution. Herein, we developed a large panel of 185 microhaplotype markers and demonstrated its application in different scenarios of relationship inference through a simulation study and real pedigree analysis, combined with probabilistic genotyping models for data interpretation. Based on single-source profiles, it was shown that the present microhaplotype panel was sufficient for pairwise close relative testing (parent/child, full-sibling and 2nd-degree relative). For more distant relatives (3rd-degree relatives), there was a clear improvement when data from one well-chosen extra relative were available. We further sought to evaluate the theoretical systematic effectiveness and actual performance of microhaplotype markers in identifying the contribution of a missing pedigree member to a two-person mixture (as a minor donor). It was observed that 100% correct assignments were made in the balanced mixtures (with no dropout) when referenced to close relatives. When the mixture profiles suffered from dropout, incorrect assignments of minor donors were markedly associated with relatedness and the dropout level. Meanwhile, the studied scenarios generally exhibited zero or very low false-positive rates, indicating a low probability of incorrectly assigning an unrelated contributor as a close relative of the reference. Our results indicate that microhaplotype data can be reliably interpreted for identifying missing persons through kinship analysis based on DNA profiles of single-source samples or two-person mixtures. Furthermore, this study could be extended to more complex scenarios, such as determining the relatedness of contributors in (or among) mixed DNA profiles, if combined with different statistical frameworks.