Precision DNA Mixture Interpretation with Single-Cell Profiling

Abstract

Wet-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.

Validation of Probabilistic Genotyping Software for Single Cell STR Analysis

“…An initial screening of these subsamples was conducted in which samples that provided an inclusionary log(LR) (i.e., log(LR) > 1) for a specific donor were considered for use. An alternative approach to cluster individual subsamples by donor may be to utilize the mixture to mixture and common donor applications in the DBLR software [ 32 , 33 ], or employ classic clustering algorithms such as K-means or EM [ 34 ]. A comparison of the log(LR)s obtained from individual subsamples compared to replicate analysis is provided in Figure 15 (single source) and Figure 16 (two-cell mini-mixtures).…”

“…Perhaps one of the largest impediments to labs considering testing and evaluation of single cell PG applications is the cost associated with preparing and analyzing the hundreds of single cell subsamples needed to develop the PG model. While our manual DSCS protocol is significantly cheaper than other automated single cell sub sampling methods, another approach to potentially decrease cost would be to create in silico models of single cell subsamples [ 34 ]. Other work with standard PG analysis has demonstrated comparable success from various labs when utilizing general PG parameters as opposed to lab specific parameters for comparable workflows (i.e., same amplification kit, reaction volume, PCR cycle number, and capillary electrophoresis model) [ 40 ].…”

New Perspectives for Whole Genome Amplification in Forensic STR Analysis

“…As a way of avoiding mixtures right from the start, methods have been suggested that physically deconvolve mixed trace material by isolating bioparticles (such as skin flakes, and aggregates of a few cells or single cells) that contain the genomic DNA of exactly one donor individual [67,68]. The price to be paid is an extremely low amount of DNA, which necessitates LCN DNA methods entailing stochastic effects, particularly when analyzing replicates.…”

Recent advances in forensic biology and forensic DNA typing: INTERPOL review 2019–2022

“…A number of approaches have been taken and advances made in DNA mixture interpretation [ 259 ]. These include probabilistic genotyping software [ 15 ], using genetic markers beyond traditional autosomal STR typing [ 260 ], or separating contributor cells and performing single-cell analysis [ [261] , [262] , [263] , [264] , [265] , [266] ].…”