Solution to a case involving the interpretation of trace degraded DNA mixtures.

DNA mixture analysis poses a significant challenge in forensic genetics, particularly when dealing with degraded and trace amount DNA samples. Multi-SNPs (MNPs) are genetic markers similar to microhaplotypes but with smaller molecular sizes (< 75 bp), making them theoretically more suitable for analyzing degraded and trace amount samples. In this case report, we investigated a cold case involving a campstool stored for over a decade, aiming to detect and locate the suspect's DNA. We employed both conventional capillary electrophoresis-based short tandem repeat (CE-STR) analysis and next-generation sequencing-based multi-SNP (NGS-MNP) analysis. The typing results and deconvolution of the mixed CE-STR profiles were inconclusive regarding the presence of the suspect's DNA in the mixed samples. However, through NGS-MNP analysis and presence probability calculations, we determined that the suspect's DNA was present in the samples from Sect. 4-1 with a probability of 1-8.41 × 10- 6 (99.999159%). This evidence contradicted the suspect's statement and aided in resolving the case. Our findings demonstrate the significant potential of MNP analysis for examining degraded and trace amount DNA mixtures in forensic investigations.

Application of a newly constructed NGS panel with 45 X-linked microhaplotypes demonstrates the unique value of X-MH for kinship testing and mixture analysis.

X-linked microhaplotypes (X-MHs) have the potential to be a valuable supplementary tool in complex kinship identification or the resolution of DNA mixtures, because they bring together the distinctive genetic pattern of X chromosomal markers and the benefits of microhaplotypes (MHs). In this study, we used the 1000 Genome database to screen and select 63 X-MHs; 18 MHs were filtered out though a batch sequencing assessment of the DNA samples collected from 112 unrelated Chinese Han individuals. The resulting 45-plex panel performed well in comprehensive assessments including repeatability, sensitivity, species specificity, resistance to PCR inhibitors or degradation, mutation rate, and accuracy in detecting DNA mixture samples. The minimum amount of DNA template that can be tested with this panel is 0.5 ng. Additionally, the alleles of the minor contributor can be accurately detected when the mixture rate is larger than 1:9 in female-male mixture or 1:19 in male-male mixture. Then, we calculated population parameters on each MH based on the allele frequency data obtained from the sequence results of the aforementioned 112 unrelated samples. Combining these parameters on each MH, it can be calculated that TDPm, TDPf, CPET, CPEDFM, CPEDFF and CNCEP3 of the 45-plex system were 1-8.99×10-13, 1-1.62×10-19, 0.9999999995, 0.9999981, 0.9955, 0.9999971 and 0.99940, respectively, indicating that the panel is capable in personal identification and parentage testing. To reveal the unique advantage of X-MHs in the analyses of complex kinship and male DNA mixture, further assessments were made. For complex kinship identification, 22 types of individual pairs with different second-degree kinship were simulated and different types of likelihood ratios (LR) were calculated for each. The results revealed that the panel can achieve accuracy of approximately 70 %∼80 % when dividing each of the three types of second-degree kinships into three or four groups. Theoretically, such sub-division cannot be done by using independent autosomal markers. For male DNA mixture analysis without suspects, the maximum likelihood ratio strategy was derived and employed in the estimation of the number of male contributors (NOMC). Simulations were conducted to verify the efficacy of the 45-plex panel in the field and to compare it with autosomal markers by assuming the 45 MHs as autosomal ones. The results showed that X-MHs can achieve higher accuracy in the estimation of NOMC than autosomal ones when the mixed males were unrelated. The results highlighted the unique value of X-linked MHs in complex kinship and male mixture analyses.

A tale of two PG systems: A comparison of the two most widely used continuous probabilistic genotyping systems in the United States.

The development of probabilistic genotyping (PG) systems to quantitatively analyze DNA mixture samples has been transformative in forensic science. TrueAllele® Casework (TA) and STRmix™ (STRmix) are the two most widely used PG systems in the United States. The two systems were challenged with 48 two-, three-, and four-person mock casework samples, for a total of 152 likelihood ratio (LR) comparisons. TA and STRmix converged on the same result (supportive, non-supportive, or inconclusive) for ~91% of contributor-specific comparisons. Where moderate or substantial differences in log(LR) values were observed, 9% affected the conclusion of the reference association to the mixture. The PG systems exhibited high correlations for estimated contributor-specific template quantities (~92%) and log(LR)s produced (>88%). When the log(LR)s for only low-template contributors (<100 pg) were compared, the R2 value dropped to ~68% and the difference became statistically significant. Of the 14 contributor comparisons where the conclusion differed, two were contradictory (supportive vs. non-supportive) and 12 were either inconclusive versus non-supportive or inconclusive versus supportive. The differing results were likely due to dissimilarities in the mixture input file as STRmix uses a lab-defined analytical threshold (AT) and TA models to 10 RFUs for each electropherogram. When 7 of the 14 mixtures were reanalyzed by STRmix using a 10 RFU AT, the log(LR)s for the low-template contributors became more similar to TAs. This study shows that while both systems may produce accurate and calibrated LRs, their results can deviate, especially for low-template, degraded contributors, and the deviation is generally predictable.

Improved individual identification in DNA mixtures of unrelated or related contributors through massively parallel sequencing.

DNA mixtures are a common sample type in forensic genetics, and we typically assume that contributors to the mixture are unrelated when calculating the likelihood ratio (LR). However, scenarios involving mixtures with related contributors, such as in family murder or incest cases, can also be encountered. Compared to the mixtures with unrelated contributors, the kinship within the mixture would bring additional challenges for the inference of the number of contributors (NOC) and the construction of probabilistic genotyping models. To evaluate the influence of potential kinship on the individual identification of the person of interest (POI), we conducted simulations of two-person (2 P) and three-person (3 P) DNA mixtures containing unrelated or related contributors (parent-child, full-sibling, and uncle-nephew) at different mixing ratios (for 2 P: 1:1, 4:1, 9:1, and 19:1; for 3 P: 1:1:1, 2:1:1, 5:4:1, and 10:5:1), and performed massively parallel sequencing (MPS) using MGIEasy Signature Identification Library Prep Kit on MGI platform. In addition, in silico simulations of mixtures with unrelated and related contributors were also performed. In this study, we evaluated 1): the MPS performance; 2) the influence of multiple genetic markers on determining the presence of related contributors and inferring the NOC within the mixture; 3) the probability distribution of MAC (maximum allele count) and TAC (total allele count) based on in silico mixture profiles; 4) trends in LR values with and without considering kinship in mixtures with related and unrelated contributors; 5) trends in LR values with length- and sequence-based STR genotypes. Results indicated that multiple numbers and types of genetic markers positively influenced kinship and NOC inference in a mixture. The LR values of POI were strongly dependent on the mixing ratio. Non- and correct-kinship hypotheses essentially did not affect the individual identification of the major POI; the correct kinship hypothesis yielded more conservative LR values; the incorrect kinship hypothesis did not necessarily lead to the failure of POI individual identification. However, it is noteworthy that these considerations could lead to uncertain outcomes in the identification of minor contributors. Compared to length-based STR genotyping, using sequence-based STR genotype increases the individual identification power of the POI, concurrently improving the accuracy of mixing ratio inference using EuroForMix. In conclusion, the MGIEasy Signature Identification Library Prep kit demonstrated robust individual identification power, which is a viable MPS panel for forensic DNA mixture interpretations, whether involving unrelated or related contributors.

A preliminary study on identification of the blood donor in a body fluid mixture using a novel compound genetic marker blood-specific methylation-microhaplotype.

Blood-containing mixtures are frequently encountered at crime scenes involving violence and murder. However, the presence of blood, and the association of blood with a specific donor within these mixtures present significant challenges in forensic analysis. In light of these challenges, this study sought to address these issues by leveraging blood-specific methylation sites and closely linked microhaplotype sites, proposing a novel composite genetic marker known as "blood-specific methylation-microhaplotype". This marker was designed to the detection of blood and the determination of blood donor within blood-containing mixtures. According to the selection criteria mentioned in the Materials and Methods section, we selected 10 blood-specific methylation-microhaplotype loci for inclusion in this study. Among these loci, eight exhibited blood-specific hypomethylation, while the remaining two displayed blood-specific hypermethylation. Based on data obtained from 124 individual samples in our study, the combined discrimination power (CPD) of these 10 successfully sequenced loci was 0.999999298. The sample allele methylation rate (Ram) was obtained from massive parallel sequencing (MPS), which was defined as the proportion of methylated reads to the total clustered reads that were genotyped to a specific allele. To develop an allele type classification model capable of identifying the presence of blood and the blood donor, we used the Random Forest algorithm. This model was trained and evaluated using the Ram distribution of individual samples and the Ram distribution of simulated shared alleles. Subsequently, we applied the developed allele type classification model to predict alleles within actual mixtures, trying to exclude non-blood-specific alleles, ultimately allowing us to identify the presence of blood and the blood donor in the blood-containing mixtures. Our findings demonstrate that these blood-specific methylation-microhaplotype loci have the capability to not only detect the presence of blood but also accurately associate blood with the true donor in blood-containing mixtures with the mixing ratios of 1:29, 1:19, 1:9, 1:4, 1:2, 2:1, 7:1, 8:1, 31:1 and 36:1 (blood:non-blood) by DNA mixture interpretation methods. In addition, the presence of blood and the true blood donor could be identified in a mixture containing four body fluids (blood:vaginal fluid:semen:saliva = 1:1:1:1). It is important to note that while these loci exhibit great potential, the impact of allele dropouts and alleles misidentification must be considered when interpreting the results. This is a preliminary study utilising blood-specific methylation-microhaplotype as a complementary tool to other well-established genetic markers (STR, SNP, microhaplotype, etc.) for the analysis in blood-containing mixtures.

DEPArray™ single-cell technology: A validation study for forensic applications.

In forensics investigations, it is common to encounter biological mixtures consisting of homogeneous or heterogeneous components from multiple individuals and with different genetic contributions. One promising mixture deconvolution strategy is the DEPArray™ technology, which enables the separation of cell populations before genetic analysis. While technological advances are fundamental, their reliable validation is crucial for successful implementation and use for casework. Thus, this study aimed to 1) systematically validate the DEPArray™ system concerning specificity, sensitivity, repeatability, and contamination occurrences for blood, epithelial, and sperm cells, and 2) evaluate its potential for single-cell analysis in the field of forensic science. Our findings confirmed the effective identification of different cell types and the correct assignment of successfully genotyped single cells to their respective donor(s). Using the NGM Detect™ Amplification Kit, the average profile completeness for diploid cells was approximately 80%, with ∼ 290 RFUs. In contrast, haploid sperm analysis yielded an average completeness of 51% referring to the haploid reference profile, accompanied by mean peak heights of ∼ 176 RFUs. Although certain alleles of heterozygous loci in diploid cells showed strong imbalances, the overall peak balances yielded acceptable values above ≥ 60% with a mean value of 72% ± 0.21, a median of 77%, but with a maximum imbalance of 9% between heterozygous peaks. Locus dropouts were considered stochastic events, exhibiting variations among donors and cell types, with a notable failure incidence observed for TH01. Within the wet-lab experimentation with >500 single cells for the validation, profiling was performed using the consensus approach, where profiles were selected randomly from all data to better mirror real casework results. Nevertheless, complete profiles could be achieved with as few as three diploid cells, while the average success rate increased to 100% when using profiles of 6-10 cells. For sperms, however, a consensus profile with completeness >90% of the autosomal diploid genotype could be attained using ≥15 cells. In addition, the robustness of the consensus approach was evaluated in the absence of the respective reference profile without severe deterioration. Here, increased stutter peaks (≥ 15%) were found as the main artifact in single-cell profiles, while contamination and drop-ins were ascertained as rare events. Lastly, the technique's potential and limitations are discussed, and practical guidance is provided, particularly valuable for cold cases, multiple perpetrator rapes, and analyses of homogeneous mixed evidence.

Comprehensive landscape of non-CODIS STRs in global populations provides new insights into challenging DNA profiles.

The worldwide implementation of short tandem repeats (STR) profiles in forensic genetics necessitated establishing and expanding the CODIS core loci set to facilitated efficient data management and exchange. Currently, the mainstay CODIS STRs are adopted in most general-purpose forensic kits. However, relying solely on these loci failed to yield satisfactory results for challenging tasks, such as bio-geographical ancestry inference, complex DNA mixture profile interpretation, and distant kinship analysis. In this context, non-CODIS STRs are potent supplements to enhance the systematic discriminating power, particularly when combined with the high-throughput next-generation sequencing (NGS) technique. Nevertheless, comprehensive evaluation on non-CODIS STRs in diverse populations was scarce, hindering their further application in routine caseworks. To address this gap, we investigated genetic variations of 178 historically available non-CODIS STRs from ethnolinguistically different worldwide populations and studied their characteristics and forensic potentials via high-coverage whole genome sequencing (WGS) data. Initially, we delineated the genomic properties of these non-CODIS markers through sequence searching, repeat structure scanning, and manual inspection. Subsequent population genetics analysis suggested that these non-CODIS STRs had comparable polymorphism levels and forensic utility to CODIS STRs. Furthermore, we constructed a theoretical next-generation sequencing (NGS) panel comprising 108 STRs (20 CODIS STRs and 88 non-CODIS STRs), and evaluated its performance in inferring bio-geographical ancestry origins, deconvoluting complex DNA mixtures, and differentiating distant kinships using real and simulated datasets. Our findings demonstrated that incorporating supplementary non-CODIS STRs enabled the extrapolation of multidimensional information from a single STR profile, thereby facilitating the analysis of challenging forensic tasks. In conclusion, this study presents an extensive genomic landscape of forensic non-CODIS STRs among global populations, and emphasized the imperative inclusion of additional polymorphic non-CODIS STRs in future NGS-based forensic systems.

A complete pipeline enables haplotyping and phasing macrohaplotype in long sequencing reads for polyploidy samples and a multi-source DNA mixture.

Macrohaplotype combines multiple types of phased DNA variants, increasing forensic discrimination power. High-quality long-sequencing reads, for example, PacBio HiFi reads, provide data to detect macrohaplotypes in multiploidy and DNA mixtures. However, the bioinformatics tools for detecting macrohaplotypes are lacking. In this study, we developed a bioinformatics software, MacroHapCaller, in which targeted loci (i.e., short TRs [STRs], single nucleotide polymorphisms, and insertion and deletions) are genotyped and combined with novel algorithms to call macrohaplotypes from long reads. MacroHapCaller uses physical phasing (i.e., read-backed phasing) to identify macrohaplotypes, and thus it can detect multi-allelic macrohaplotypes for a given sample. MacroHapCaller was validated with data generated from our designed targeted PacBio HiFi sequencing pipeline, which sequenced ∼8-kb amplicon regions harboring 20 core forensic STR loci in human benchmark samples HG002 and HG003. MacroHapCaller also was validated in whole-genome long-read sequencing data. Robust and accurate genotyping and phased macrohaplotypes were obtained with MacroHapCaller compared with the known ground truth. MacroHapCaller achieved a higher or consistent genotyping accuracy and faster speed than existing tools HipSTR and DeepVar. MacroHapCaller enables efficient macrohaplotype analysis from high-throughput sequencing data and supports applications using discriminating macrohaplotypes.

Developmental validation of a custom-designed Multi-InDel panel: A five-dye multiplex amplification system for challenging DNA samples.

The continual investigation of novel genetic markers has yielded promising solutions for addressing the challenges encountered in forensic DNA analysis. In this study, we have introduced a custom-designed panel capable of simultaneously amplifying 41 novel Multi-insertion/deletion (Multi-InDel) markers and an amelogenin locus using the capillary electrophoresis platform. Through a developmental validation study conducted in accordance with guidelines recommended by the Scientific Working Group on DNA Analysis Methods, we demonstrated that the new Multi-InDel system exhibited the sensitivity to produce reliable genotyping profiles with as little as 62.5 pg of template DNA. Accurate and complete genotyping profiles could be obtained even in the presence of specific concentrations of PCR inhibitors. Furthermore, the maximum amplicon size for this system was limited to under 220 bp in the genotyping profile, resulting in its superior efficiency compared to commercially available short tandem repeat kits for both naturally and artificially degraded samples. In the context of mixed DNA analysis, the Multi-InDel system was proved informative in the identification of two-person DNA mixture, even when the template DNA of the minor contributor was as low as 50 pg. In conclusion, a series of performance evaluation studies have provided compelling evidence that the new Multi-InDel system holds promise as a valuable tool for forensic DNA analysis.

Improving DNA mixtures analysis using compound markers composed of InDels and SNPs screened from the whole genome with next-generation sequencing.

Next-generation sequencing (NGS) allows for better identification of insertion and deletion polymorphisms (InDels) and their combination with adjacent single nucleotide polymorphisms (SNPs) to form compound markers. These markers can improve the polymorphism of microhaplotypes (MHs) within the same length range, and thus, boost the efficiency of DNA mixture analysis. In this study, we screened InDels and SNPs across the whole genome and selected highly polymorphic markers composed of InDels and/or SNPs within 300 bp. Further, we successfully developed and evaluated an NGS-based panel comprising 55 loci, of which 24 were composed of both SNPs and InDels. Analysis of 124 unrelated Southern Han Chinese revealed an average effective number of alleles (Ae ) of 7.52 for this panel. The cumulative power of discrimination and cumulative probability of exclusion values of the 55 loci were 1-2.37 × 10-73 and 1-1.19 × 10-28 , respectively. Additionally, this panel exhibited high allele detection rates of over 97% in each of the 21 artificial mixtures involving from two to six contributors at different mixing ratios. We used EuroForMix to calculate the likelihood ratio (LR) and evaluate the evidence strength provided by this panel, and it could assess evidence strength with LR, distinguishing real and noncontributors. In conclusion, our panel holds great potential for detecting and analyzing DNA mixtures in forensic applications, with the capability to enhance routine mixture analysis.

Carrying out common DNA donor analysis using DBLR™ on two or five-cell mini-mixture subsamples for improved discrimination power in complex DNA mixtures.

Probabilistic genotyping systems are able to analyse complex mixed DNA profiles and show good power to discriminate contributors from non-contributors. However, the abilities of the statistical analyses are still unavoidably bound by the quality of information being analysed. If a profile has a high number of contributors, or a contributor that is present in trace amounts, then the amount of information about those individuals in the DNA profile is limited. Recent work has shown the ability to gain better resolution of the genotypes of contributors to complex profiles using cell subsampling. This is the process of taking many sets of a limited number of cells and individually profiling each set. These 'mini-mixtures' can provide greater information about the genotypes of underlying contributors. In our work we take the resulting profiles from multiple subsamplings of complex DNA profiles in equal amounts and show how testing for, and then assuming, a common DNA donor can further improve the ability to resolve the genotypes of contributors. Using direct cell sub-sampling and statistical analysis software DBLR™, we were able to recover single source profiles of uploadable quality from five out of the six contributors of an equally proportioned mixture. Through the analysis of mixtures in this work we provide a template for carrying out common donor analysis for maximum effect.

Variation in assessments of suitability and number of contributors for DNA mixtures.

The interpretation of a DNA mixture (a sample that contains DNA from two or more people) depends on a laboratory/analyst's assessment of the suitability of the sample for comparison/analysis, and an assessment of the number of contributors (NoC) present in the sample. In this study, 134 participants from 67 forensic laboratories provided a total of 2272 assessments of 29 DNA mixtures (provided as electropherograms). The laboratories' responses were evaluated in terms of the variability of suitability assessments, and the accuracy and variability of NoC assessments. Policies and procedures related to suitability and NoC varied notably among labs. We observed notable variation in whether labs would assess a given mixture as suitable or not, predominantly due to differences in lab policies: if two labs following their standard operating procedures (SOPs) were given the same mixture, they agreed on whether the mixture was suitable for comparison 66% of the time. Differences in suitability assessments have a direct effect on variability in interpretations among labs, since mixtures assessed as not suitable would not result in reported interpretations. For labs following their SOPs, 79% of assessments of NoC were correct. When two different labs provided NoC responses, 63% of the time both labs were correct, and 7% of the time both labs were incorrect. Incorrect NoC assessments have been shown to affect statistical analyses in some cases, but do not necessarily imply inaccurate interpretations or conclusions. Most incorrect NoC estimates were overestimates, which previous research has shown have less of an effect on likelihood ratios than underestimates.

Guiding proposition setting in forensic DNA interpretation.

There is a general reluctance to use conditioning profiles when forming propositions for cases where the evidence is a DNA mixture. However, the use of conditioning profiles improves the ability to differentiate true from false donors. There are at least four situations where this decision making is at its most difficult. These are:Rigorous mathematical treatment, given by Slooten and others, appears to offer strong guidance for these situations. This treatment assumes that the prior probabilities for conditioning, or not conditioning, on any individual are not extreme. It is when these prior probabilities appear ambiguous that the decision to condition or not can appear to be problematic. This is often the situation found in casework. In this paper we attempt to show that such situations may benefit most from following such guidance. A lower bound on the Bayes factor can be obtained by finding the highest LR that includes the POI and dividing by the highest LR that does not include the POI. These two highest LRs may be found with and without the disputed conditioning profile. The resultant lower bound is on the BF for the inclusion of the POI without directly assuming the disputed conditioning profile. Adopting this approach would both minimize adventitious inclusions and approximate an exhaustive set of propositions.

Comparison of swab types & elution buffers for collection and analysis of intact cells to aid in deconvolution of complex DNA mixtures.

Heightened sensitivity of forensic DNA techniques has led to an increased variety of samples tested, often yielding complex DNA mixtures, in turn making the interpretation of profiling results more complicated. Currently, there is no prescribed upstream laboratory method to separate complex DNA mixtures by their contributors; therefore, a method is needed that could reduce mixtures into their component parts. Various cell sorting applications have the potential to be this method, if intact cells can be reliably obtained from forensic samples. Here, the effects of elution buffer and swab substrate on the recovery of intact, human, white blood cells from dried blood samples were evaluated. Approximately 328,000 cells per swab were deposited onto cotton, flocked, and dissolvable swabs. The whole-cell elution of the dried samples was evaluated with water, phosphate buffered saline, and AutoMACS® elution buffers. We demonstrate that AutoMACS® buffer is superior for the elution of intact cells, compared to phosphate buffered saline and water. When swab type was considered, the highest yield of intact cells resulted from flocked swabs, as opposed to cotton or dissolvable swabs.

Evaluation of the MHSeqTyper47 kit for forensically challenging DNA samples.

Microhaplotypes have been highly regarded for forensic mixture DNA deconvolution because they do not experience interference from stutters in the same way as short tandem repeat markers, and they tend to be more polymorphic than single nucleotide polymorphism markers. However, forensic microhaplotype kits have not been reported. The MHSeqTyper47 kit genotypes 47 microhaplotype loci. In this study, MiSeq FGx sequencing metrics for MHSeqTyper47 were presented, and the genotyping accuracy of this kit was examined. The sensitivity of MHSeqTyper47 reached 62.5 pg, and full genotyping results were obtained from degraded DNA samples with degradation indexes ≤ 3.00. Full genotypes were obtained in the presence of 100 ng/µL tannin, 50 µM heme, 25 ng/µL humic acid, and 1.25 µg/µL indigo dye. In DNA mixture studies, a minimum of 31 loci of the minor contributor were correctly genotyped at 1:99 or 99:1 mixing ratios, with the cumulative random matching probability of these loci reaching 4.54 × 10-25. Mixing ratios could be reliably predicted from two-donor DNA mixtures based on the loci with four called alleles. Taken together, these data showed that the MHSeqTyper47 kit was effective for forensically challenging DNA analysis.

A New Computational Deconvolution Algorithm for the Analysis of Forensic DNA Mixtures with SNP Markers.

Single nucleotide polymorphisms (SNPs) support robust analysis on degraded DNA samples. However, the development of a systematic method to interpret the profiles derived from the mixtures is less studied, and it remains a challenge due to the bi-allelic nature of SNP markers. To improve the discriminating power of SNPs, this study explored bioinformatic strategies to analyze mixtures. Then, computer-generated mixtures were produced using real-world massively parallel sequencing (MPS) data from the single samples processed with the Precision ID Identity Panel. Moreover, the values of the frequency of major allele reads (FMAR) were calculated and applied as key parameters to deconvolve the two-person mixtures and estimate mixture ratios. Four custom R language scripts (three for autosomes and one for Y chromosome) were designed with the K-means clustering method as a core algorithm. Finally, the method was validated with real-world mixtures. The results indicated that the deconvolution accuracy for evenly balanced mixtures was 100% or close to 100%, which was the same as the deconvolution accuracy of inferring the genotypes of the major contributor of unevenly balanced mixtures. Meanwhile, the accuracy of inferring the genotypes of the minor contributor decreased as its proportion in the mixture decreased. Moreover, the estimated mixture ratio was almost equal to the actual ratio between 1:1 and 1:6. The method proposed in this study provides a new paradigm for mixture interpretation, especially for inferring contributor profiles of evenly balanced mixtures and the major contributor profile of unevenly balanced mixtures.

Microhaplotype and Y-SNP/STR (MY): A novel MPS-based system for genotype pattern recognition in two-person DNA mixtures.

BACKGROUNDS: Y-chromosomal haplotypes based on Y-short tandem repeats (STRs) and Y-single nucleotide polymorphisms/insertion and deletion polymorphisms (SNPs/InDels) are used to characterize paternal lineages of unknown male trace donors. However, Y-chromosomal genetic markers are not currently sufficient for precise individual identification. Microhaplotype (MH), generally < 200 bp on autosomes and consisting of two or more SNPs, was recently introduced in forensic genetics with the development of massive parallel sequencing technology and may facilitate identification and DNA mixture deconvolution. Therefore, combining the two kinds of genetic markers may be beneficial in many forensic scenarios, especially crime scenes with male suspects, such as sexual assault cases. METHODS: In the present study, we developed a novel MPS-based panel, Microhaplotype and Y-SNP/STR (MY), by multiplex PCR and 150-bp paired-end sequencing, including 114 Y-SNPs (twelve dominant Y-DNA haplogroups), 45 Y-STRs (N-1 stutter < 0.09; estimated mutation rate < 5 × 10-3), and 22 MHs (allele coverage ratio > 0.91; pairwise distance > 10 Mb). Additionally, MY system-based genotype pattern recognition (GPR), a regression-based method to identify the genotype pattern for each MH locus, is proposed for two-person DNA mixture deconvolution. We integrated 26 two-person genotype combinations into nine genotype patterns and validated the application range of GPR based on DNA profiles of ten sets of simulated male-male DNA mixtures (1:10-1:2). RESULTS: The effective number of alleles (Ae) ranged from 3.62 to 14.72, with an average of 7.17, in 100 Chinese Guangdong Han individuals. The cumulative discrimination power was 1-5.00 × 10-31, and the cumulative power of exclusion was 1-5.00 × 10-8 and 1-4.85 × 10-12 for duo and trio paternity testing, respectively. Furthermore, the actual mixing ratio-depth of coverage (DoC) ratio (RDoC) regression relationships were established for different genetic markers and genotype patterns. In five overlapping areas, genotype differentiation of the major and minor contributors required likelihood ratio methods. In nonoverlapping areas, the genotype pattern could be recognized by comparing the observed RDoC and RDoC ranges. CONCLUSION: The GPR can be used to deconvolute two-person DNA mixtures (application range: 1:10-1:2) for individual identification.

Probabilistic genotyping of single cell replicates from complex DNA mixtures recovers higher contributor LRs than standard analysis.

DNA mixtures are a common source of crime scene evidence and are often one of the more difficult sources of biological evidence to interpret. With the implementation of probabilistic genotyping (PG), mixture analysis has been revolutionized allowing previously unresolvable mixed profiles to be analyzed and probative genotype information from contributors to be recovered. However, due to allele overlap, artifacts, or low-level minor contributors, genotype information loss inevitably occurs. In order to reduce the potential loss of significant DNA information from donors in complex mixtures, an alternative approach is to physically separate individual cells from mixtures prior to performing DNA typing thus obtaining single source profiles from contributors. In the present work, a simplified micro-manipulation technique combined with enhanced single-cell DNA typing was used to collect one or few cells, referred to as direct single-cell subsampling (DSCS). Using this approach, single and 2-cell subsamples were collected from 2 to 6 person mixtures. Single-cell subsamples resulted in single source DNA profiles while the 2-cell subsamples returned either single source DNA profiles or new mini-mixtures that are less complex than the original mixture due to the presence of fewer contributors. PG (STRmix™) was implemented, after appropriate validation, to analyze the original bulk mixtures, single source cell subsamples, and the 2-cell mini mixture subsamples from the original 2-6-person mixtures. PG further allowed replicate analysis to be employed which, in many instances, resulted in a significant gain of genotype information such that the returned donor likelihood ratios (LRs) were comparable to that seen in their single source reference profiles (i.e., the reciprocal of their random match probabilities). In every mixture, the DSCS approach gave improved results for each donor compared to standard bulk mixture analysis. With the 5- and 6- person complex mixtures, DSCS recovered highly probative LRs (≥1020) from donors that had returned non-probative LRs (<103) by standard methods.

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

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.

Evaluation of microfluidics-based droplet PCR combined with multiplex STR system in forensic science.

Because of its excellent monodispersity, high throughput, and low volume, microfluidics-based droplet PCR has become the core technology of digital PCR, next-generation sequencing, and other technology platforms. This study constructed a microfluidic water-in-oil droplet PCR system and amplified a commercially available forensic 22-plex short tandem repeat detection system. We analyzed the sensitivity, concordance, amplification efficiency of the droplet PCR, and influence factors of the above aspects. The droplet PCR showed high concordance with conventional bulk PCR and had high sensitivity as 0.125 ng. Furthermore, we observed the performance of droplet PCR in high-order mixed DNA. As the mixture ratios from 10:1 to 30:1, droplet PCR presented more mixture proportion (Mx) increased loci from 11 (57.89%) to 17 (89.47%). In the mixture ratios 20:1, 25:1, and 30:1, significant Mx differences between droplet PCR and bulk PCR were observed (p < 0.05). The results showed that the droplet PCR could improve the identification of the minor contributor's DNA in a two-person mixture and alleviate the imbalanced amplification problem. This study provides a reference and basis for the wide application of droplet PCR in forensic science.