Attribution 4.0 International (CC BY 4.0)2022-09-162022-09-162021-10-20Ge, J., King, J. L., Smuts, A., & Budowle, B. (2021). Precision DNA Mixture Interpretation with Single-Cell Profiling. Genes, 12(11), 1649. https://doi.org/10.3390/genes121116492073-4425https://hdl.handle.net/20.500.12503/31760Wet-lab based studies have exploited emerging single-cell technologies to address the challenges of interpreting forensic mixture evidence. However, little effort has been dedicated to developing a systematic approach to interpreting the single-cell profiles derived from the mixtures. This study is the first attempt to develop a comprehensive interpretation workflow in which single-cell profiles from mixtures are interpreted individually and holistically. In this approach, the genotypes from each cell are assessed, the number of contributors (NOC) of the single-cell profiles is estimated, followed by developing a consensus profile of each contributor, and finally the consensus profile(s) can be used for a DNA database search or comparing with known profiles to determine their potential sources. The potential of this single-cell interpretation workflow was assessed by simulation with various mixture scenarios and empirical allele drop-out and drop-in rates, the accuracies of estimating the NOC, the accuracies of recovering the true alleles by consensus, and the capabilities of deconvolving mixtures with related contributors. The results support that the single-cell based mixture interpretation can provide a precision that cannot beachieved with current standard CE-STR analyses. A new paradigm for mixture interpretation is available to enhance the interpretation of forensic genetic casework.http://creativecommons.org/licenses/by/4.0/DNA forensicsDNA mixtureclustering algorithmconsensus profilemixture interpretationnumber of contributorssingle-cellAlgorithmsAllelesCluster AnalysisDNA / analysisDNA / chemistryDNA / geneticsDNA ContaminationDNA Fingerprinting / methodsForensic Genetics / methodsForensic Genetics / trendsGenetic TechniquesGenotypeHumansMicrosatellite RepeatsSingle-Cell Analysis / methodsArticle© 2021 by the authors.1211