DNA Mixtures Research Articles

Temperature-Wise Calibration Increases the Accuracy of DNA Methylation Levels Determined by High-Resolution Melting (HRM)

High-resolution melting (HRM) is a cost-efficient tool for targeted DNA methylation analysis. HRM yields the average methylation status across all CpGs in PCR products. Moreover, it provides information on the methylation pattern, e.g., the occurrence of monoallelic methylation. HRM assays have to be calibrated by analyzing DNA methylation standards of known methylation status and mixtures thereof. In general, DNA methylation levels determined by the classical calibration approach, including the whole temperature range in between normalization intervals, are in good agreement with the mean of the DNA methylation status of individual CpGs determined by pyrosequencing (PSQ), the gold standard of targeted DNA methylation analysis. However, the classical calibration approach leads to highly inaccurate results for samples with heterogeneous DNA methylation since they result in more complex melt curves, differing in their shape compared to those of DNA standards and mixtures thereof. Here, we present a novel calibration approach, i.e., temperature-wise calibration. By temperature-wise calibration, methylation profiles over temperature are obtained, which help in finding the optimal calibration range and thus increase the accuracy of HRM data, particularly for heterogeneous DNA methylation. For explaining the principle and demonstrating the potential of the novel calibration approach, we selected the promoter and two enhancers of MGMT, a gene encoding the repair protein MGMT.

Variability and bias in microbiome metagenomic sequencing: an interlaboratory study comparing experimental protocols.

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

Development and validation of a new multiplex panel using SNaPshot-based DIP-TriSNP markers for forensic DNA mixtures.

Short tandem repeat analysis is challenging when dealing with unbalanced mixtures in forensic cases due to the presence of stutter peaks and large amplicons. In this research, we propose a novel genetic marker called DIP-TriSNP, which combines deletion/insertion polymorphism (DIP) with tri-allelic single nucleotide polymorphism in less than 230bp length of human genome. Based on multiplex PCR and SNaPShot, a panel, including 14 autosomal DIP-TriSNPs and one Y chromosomal DIP-SNP, had been developed and applied to genotyping 102 unrelated Han Chinese individuals in Sichuan of China and simulated a mixture study. The panel sensitivity can reach as low as 0.1ng DNA template, and the minor contributor of DNA can be detected with the highest ratio of 19:1, as indicated by the obtained results. In the Sichuan Han population, the cumulative probability of informative genotypes reached 0.997092, with a combined power of discrimination of 0.999999998801. The panel was estimated to detect more than two alleles in at least one locus in 99.69% of mixtures of the Sichuan Han population. In conclusion, DIP-TriSNPs have shown promising as an innovative DNA marker for identifying the minor contributor in unbalanced DNA mixtures, offering advantages such as short amplifications, increased polymorphism, and heightened sensitivity.

Validation and forensic application of a new 36 X-STR loci multiplex system

Abstract X-chromosomal short tandem repeats (X-STRs) are indispensable in specific cases, distinct from autosomal and Y chromosome genetic markers. SureID® X37 is an innovative six-color fluorescence multiplex detection system that can simultaneously amplify 36 X-STR loci (including DXS6795, DXS7132, DXS8378, DXS10101, DXS10103, DXS10079, DXS10134, GATA172D05, HPRTB, DXS6810, DXS10135, DXS6797, DXS10074, DXS7424, DXS9902, DXS7423, DXS10148, DXS10162, DXS6809, GATA31E08, DXS6803, DXS10075, DXS6807, DXS10164, DXS6789, DXS10146, DXS981, DXS9895, DXS101, DXS6800 DXS907, and DXS8377) and the Amelogenin locus. In this study, we validated its suitability for forensic identification per SWGDAM (Scientific Working Group on DNA analysis methods) guidelines, including PCR conditions, precision, accuracy, case-type samples, sensitivity, repeatability, reproducibility, species specificity, stability, stutter calculation, and DNA mixtures. Additionally, 577 Han Chinese individuals were used to investigate the utility of the system in forensic population genetics. The results indicated that the system is sensitive, stable, and reliable, and is suitable for typical forensic case. Subsequent population investigations confirmed that it serves as a potent supplementary tool in forensic applications.

Genetic Polymorphisms and Forensic Parameters of Thirteen X-Chromosome Markers in the Iraqi Kurdish Population.

X-chromosome short tandem repeat (X-STR) tools are crucial in forensic genetics and human population fields. This study presents the development and validation of a multiplex STR system consisting of thirteen X-STR loci and amelogenin specific to the human X chromosome. The system was optimized and tested for species specificity, sensitivity, stability, and DNA mixture using 9947A female and 9948 male control genomic DNA. The amplified products of nine loci were sequenced to determine the correct amplicon length. Allele frequencies, forensic parameters, mean exclusion chance (MEC), linkage disequilibrium (LD), and allelic patterns were investigated using DNA samples from 225 (159 male, 66 female) unrelated Kurdish individuals who live in Sulaymaniyah province in the Kurdistan region of Iraq. The most informative locus in the Kurdish population was GATA172D05, while the least informative locus was DXS10164. The results demonstrated that the 13 X-STR system is highly polymorphic and sensitive for forensic DNA identification. Genetic distance-based clustering, metric multidimensional scaling (MDS), and correlation matrix were analyzed for 19 ethnic groups and populations. The phylogenetic tree showed that populations clustered according to their ethnogeographic relationships. The findings revealed genetic links between the Iraqi Kurds, Caucasians, Iraqi Arabs, United States (U.S.) ethnic groups, and Chinese populations.

PCR-based detection for the quarantine fungus Colletotrichum kahawae, a biosecurity threat to the coffee (Coffea arabica) industry worldwide.

Coffee berry disease (CBD) is caused by Colletotrichum kahawae, a quarantine fungus still absent from most coffee-producing countries. Given the potential adverse effects on coffee berry production, it is a severe worldwide threat to farmers and industry. Current biosecurity management focuses on exclusion by applying quarantine measures, including certification of coffee plants and their products. However, methods for detecting C. kahawae by the NPPO (National Plant Protection Organization) laboratories still need approval. This research aims to functionally demonstrate, standardize, and validate a method for detecting and discriminating C. kahawae from other Colletotrichum species that may be present in coffee plant samples. The method proposes to use an end-point PCR marker for the mating type gene (MAT1-2-1) and a confirmatory test with a qPCR marker developed on the glutamine synthetase (GS) gene. The C. kahawae amplicons for the Cen-CkM10 marker exhibited specific melting temperature (Tm) values that could be readily differentiated from other tested species, including their relatives. Given the fungus's quarantine status, specificity was tested using artificial mixtures of DNA of C. kahawae with other Colletotrichum species and coffee plant DNA. The described method will enable NPPOs in coffee producing and exporting countries, especially Colombia, to prevent this pathogen's entry, establishment, and spread.

NSPlex: an efficient method to analyze non-specific peaks amplified using commercial STR kits.

Commercial short tandem repeat (STR) kits exclusively contain human-specific primers; however, various non-human organisms with high homology to the STR kit's primer sequences can cause cross-reactivity. Owing to the proprietary nature of the primers in STR kits, the origins and sequences of most non-specific peaks (NSPs) remain unclear. Such NSPs can complicate data interpretation between the casework and reference samples; thus, we developed "NSPlex", an efficient method to discover the biological origins of NSPs. We used leftover STR kit amplicons after capillary electrophoresis and performed advanced bioinformatics analyses using next-generation sequencing followed by BLAST nucleotide searches. Using our method, we could successfully identify NSP generated from PCR amplicons of a sample mixture of human DNA and DNA extracted from matcha powder (finely ground powder of green tea leaves and previously known as a potential source of NSP). Our results showed our method is efficient for NSP analysis without the need for the primer information as in commercial STR kits.

Quantification of total human DNA using qPCR in mixture samples of Crimes Against Sexual Freedom to estimate the success of analysis with autosomal STRs and Y-STRs

ABSTRACT In this study, 241 mixed autosomal STR genetic profiles (swabs − 172, slides − 69) from processed casework samples were analysed. From these samples, DNA was extracted and quantified by qPCR; the results were analysed with the PowerQuant Analysis Software. The extracted DNA samples were amplified with the Investigator 24Plex QS and VeriFiler kits and separated and detected in an ABI 3500 Genetic Analyzer. A quantification correlation was observed between the total autosomal DNA targets [Auto] and the Y chromosome target [Y] in mixed samples in which the success of amplification of the male autosomal STRs markers was associated with high values of the quantification of the target of [Y] and low DNA ratio values [Auto]/[Y] (p = 0.00 < 0.05). Samples with [Auto]/[Y] ratio values much higher than the estimated value required analysis with Y-STR markers. The study herein, which assessed a relatively large number of sexual assault samples, demonstrates that quantitation ratio values of DNA mixtures effectively contribute to the decision-making process on whether and what genetic marker system should be selected for analysis of a male component in unknown casework samples.

An inter-laboratory comparison of probabilistic genotyping parameters and evaluation of performance on DNA mixtures from different laboratories

Probabilistic genotyping (PG) is becoming the preferred standard for evidence interpretation, amongst forensic DNA laboratories, especially those in the United States.Various groups have expressed concern about reliability of PG systems, especially for mixtures beyond two contributors.Studies involving interlaboratory testing of known mixtures have been identified as ways to evaluate the reliability of PG systems. Reliability means different things in different contexts. However, it suffices here to think about it as a mixture of precision and accuracy. We might also consider whether a system is prone to producing misleading results – for example large likelihood ratios (LRs) when the POI is truly not a contributor, or small LRs when the POI is a truly a contributor.In this paper we show that the PG system STRmix™ is relatively unaffected by differences in parameter settings. That is, a DNA mixture that is analyzed in different laboratories using STRmix™ will result in different LRs, but less than 0.05% of these LRs would result in a different, or misleading conclusion as long as the LR is greater than 50. For the purposes of this study, we define LRs assigned using different parameters for the same mixtures as similar if the LR of the true POI is greater than the LRs generated for 99.9% of the general population.These findings are based on an interlaboratory study involving eight laboratories that provided twenty known DNA mixtures of two to four contributors and their individual laboratory STRmix™ parameters. The eight sets of laboratory parameters included differences in STR kits and PCR cycles as well as the peak, stutter, and locus specific amplification efficiency variances.

Targeted recovery of male cells in a male and female same-cell mixture.

DNA mixture deconvolution in the forensic DNA community has been addressed in a variety of ways. "Front-end" methods that separate the cellular components of mixtures can provide a significant benefit over computational methods as there is no need to rely on models with inherent uncertainty to generate conclusions. Historically, cell separation methods have been investigated but have been largely ineffective due to high cost, unreliability, and the lack of proper instrumentation. However, the last decade has given rise to more innovative technology that can target and recover cells more effectively. This study focuses on the development and optimization of a method to selectively label and recover male cells in a mixture of male and female epithelial cells using a Y-chromosome labeling kit with DEPArray™ technology, whereby male cells are labeled and recovered into a single extraction-ready tube. Labeling efficiency was tested using freshly collected and aged buccal swabs where 70%-75% and 38% of male cells were labeled, respectively, with less than 1% false positives. DEPArray™ detection was assessed using single buccal epithelial cells where approximately 80% of labeled cells were identified as male. Mixtures (1:1, 1:10, male to female) yielded profiles that were predominantly single source male or those in which the male component was more easily interpreted. The male-specific labeling method was demonstrated to be both robust and reliable when used on freshly collected cells. While the DEPArray™ meditated detection and recovery had notable limitations, it still improved the interpretation of the male component in same-cell mixtures in more recently collected samples.

Abstract 5017: Analytical performance of contrived samples for validation of liquid biopsy assays

Abstract Introduction: Cell-free DNA (cfDNA) extracted from plasma is critical for the analytical validation of liquid biopsy assays. cfDNA is comprised of genetic material from tumor and non-tumor cells, which can be highly variable across tumor types and disease stage. Relative to tumor tissue, cfDNA yield is lower and may not always capture all clinically relevant variants (e.g. gene fusions). Supplementing analytical validation studies with contrived samples prepared from cell line derived DNA to mimic the features of cfDNA allows for more robust testing of rare variants in clinical samples. To determine the commutability of contrived sample DNA to clinical plasma sample cfDNA, a retrospective analysis of sensitivity studies using two methods of contrived sample preparation was performed. Methods: The PGDx elio Plasma Focus assay was used to compare sample base size post library preparation and limit of detection (LoD) of clinically relevant variants. Both methods used fragmented cell line DNA with a variant of interest and for method #1, cell line DNA was spiked into noncancerous donor plasma, which was then extracted resulting in a cfDNA and cell line DNA mixture. This contrived sample was diluted using wild-type (WT) DNA extracted from noncancerous donor plasma to obtain a target variant allele frequency (VAF). Method #2 used fragmented cell line DNA diluted with fragmented WT cell line DNA to obtain a target VAF. This retrospective data analysis will include a minimum of 28 samples run in replicate (3-20) across multiple studies. Results: Data obtained from a DNA fragment analyzer post library preparation show similarities between fragmented cell line DNA spiked into plasma, fragmented cell line DNA, and clinical plasma cfDNA, with fragment peaks ranging from 290-320 base pair (bp). The median LoDs across the three sample types (n=28) were also similar for single nucleotide variants (SNVs) at VAFs of 0.70%, 0.76%, 0.72%, indels at VAFs of 0.70%, 1.0%, 0.78%, amplifications at folds of 1.4, 1.3, 1.5, and translocations at fusion read fractions of 0.5%, 0.61%, 0.55%. When comparing the same variants in a contrived sample functional characterization study, the call rates of various dilution levels were similar. A Fisher’s Exact Test of the Hit Rate showed no significant difference for KRAS G12V SNV, ERBB2 amplification, and RET translocation between cell line DNA and clinical cfDNA. Conclusions: This data demonstrates that contrived samples perform with general equivalence to and may be an appropriate substitute for clinical plasma samples, though certain DNA sources may influence overall performance. Overall, fragmented cell line DNA spiked into plasma and fragmented cell line DNA diluted with WT fragmented cell line DNA performed similarly to clinical cfDNA samples representative of the intended use population. Citation Format: Amanda E. Harvey, Cindy K. Maddox, Sonomi O. Dillon, Omar T. Khawar, Ellen L. Verner, Amy Greer, Kenneth C. Valkenburg, Brian J. Caveney, Shakti Ramkissoon. Analytical performance of contrived samples for validation of liquid biopsy assays [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5017.

A novel 193-plex MPS panel integrating STRs and SNPs highlights the application value of forensic genetics in individual identification and paternity testing.

Massively parallel sequencing (MPS) has emerged as a promising technology for targeting multiple genetic loci simultaneously in forensic genetics. Here, a novel 193-plex panel was designed to target 28 A-STRs, 41 Y-STRs, 21 X-STRs, 3 sex-identified loci, and 100 A-SNPs by employing a single-end 400bp sequencing strategy on the MGISEQ-2000™ platform. In the present study, a series of validations and sequencing of 1642 population samples were performed to evaluate the overall performance of the MPS-based panel and its practicality in forensic application according to the SWGDAM guidelines. In general, the 193-plex markers in our panel showed good performance in terms of species specificity, stability, and repeatability. Compared to commercial kits, this panel achieved 100% concordance for standard gDNA and 99.87% concordance for 14,560 population genotypes. Moreover, this panel detected 100% of the loci from 0.5ng of DNA template and all unique alleles at a 1:4 DNA mixture ratio (0.2ng minor contributor), and the applicability of the proposed approach for tracing and degrading DNA was further supported by case samples. In addition, several forensic parameters of STRs and SNPs were calculated in a population study. High CPE and CPD values greater than 0.9999999 were clearly demonstrated and these results could be useful references for the application of this panel in individual identification and paternity testing. Overall, this 193-plex MPS panel has been shown to be a reliable, repeatable, robust, inexpensive, and powerful tool sufficient for forensic practice.

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.

Insights into non-informative results from non-invasive prenatal screening through gestational age, maternal BMI, and age analyses.

The discovery of cell-free fetal DNA fragments in the maternal plasma initiated a novel testing method in prenatal care, called non-invasive prenatal screening (NIPS). One of the limitations of NIPS is the necessity for a sufficient proportion of fetal fragments in the analyzed circulating DNA mixture (fetal fraction), otherwise, the sample is uninterpretable. We present the effect of gestational age, maternal body mass index (BMI), and maternal age on the fetal fraction (FF) of the sample. We retrospectively analyzed data from 5543 pregnant women with a single male fetus who underwent NIPS from which 189 samples received a repeat testing due to an insufficient FF. We showed the relationship between the failure rate of the samples after the repeated analysis, the FF, and the gestational age at the first sampling. Next, we found that different maternal BMI categories affect the FF and thus the chance of an informative redraw. A better understanding of the factors affecting the FF will reduce the number of non-informative calls from repeated analyzes. In this study, we provide helpful information to clinicians on how to approach non-informative analyses.

Forensic Applications of Markers Present on the X Chromosome

The X chromosome is one of the two sex chromosomes found in humans and other mammals. It plays a crucial role in determining an individual's sex and contains genetic information that can be useful in forensic and human identity testing. Unlike autosomal DNA, which is inherited from both parents, the X chromosome is inherited differently in males and females, making it useful in certain types of analyses. In forensic investigations, the X chromosome can be used to determine the sex of an individual, which can be useful in identifying potential suspects or victims. Additionally, X chromosome analysis can be used to link evidence samples to a particular individual or to exclude individuals as potential contributors of the evidence. This can be particularly useful in cases where the evidence sample is a mixture of DNA from multiple individuals. In human identity testing, the X chromosome can be used in situations where other types of DNA analysis are not possible or inconclusive. For example, in cases where a potential parent is unavailable for testing, analysis of the X chromosome can be used to determine if a child is likely to be their biological offspring. Similarly, in cases where traditional autosomal DNA analysis is inconclusive, X chromosome analysis can be used to provide additional information about the biological relationship between individuals. However, there are some limitations to the use of X chromosome analysis in forensic and human identity testing. One limitation is that it is not as informative as autosomal DNA analysis, as it contains less genetic information. Additionally, the inheritance patterns of the X chromosome can be complex, particularly in cases where there are multiple generations involved. Therefore, X chromosome analysis should be interpreted in conjunction with other types of DNA analysis and other forms of evidence to ensure accurate and reliable results. Overall, the use of X chromosome analysis in forensic and human identity testing can provide important information in certain situations, particularly where traditional DNA analysis is not possible or inconclusive. As such, it is an important tool in the fields of forensic science and human identification.

Back Cover: Improving DNA mixtures analysis using compound markers composed of InDels and SNPs screened from the whole genome with next‐generation sequencing

Back Cover: Improving DNA mixtures analysis using compound markers composed of InDels and SNPs screened from the whole genome with next‐generation sequencing

Micropreparative Gel Electrophoresis for Purification of Nanoscale Bioconjugates.

Conventional techniques for purifying macromolecular conjugates often require complex and costly installments that are inaccessible to most laboratories. In this work, we develop a one-step micropreparative method based on a trilayered polyacrylamide gel electrophoresis (MP-PAGE) setup to purify biological samples, synthetic nanoparticles, as well as biohybrid complexes. We apply this method to recover DNA from a ladder mixture with yields of up to 90%, compared to the 58% yield obtained using the conventional crush-and-soak method. MP-PAGE was also able to isolate enhanced yellow fluorescence protein (EYFP) from crude cell extract with 90% purity, which is comparable to purities achieved through a more complex two-step purification procedure involving size exclusion and immobilized metal-ion affinity chromatography. This technique was further extended to demonstrate size-dependent separation of a commercial mixture of graphene quantum dots (GQDs) into three different fractions with distinct optical properties. Finally, MP-PAGE was used to isolate DNA-EYFP and DNA-GQD bioconjugates from their reaction mixture of DNA and EYFP and GQD precursors, samples that otherwise could not be effectively purified by conventional chromatography. MP-PAGE thus offers a rapid and versatile means of purifying biological and synthetic nanomaterials without the need for specialized equipment.

Abstract PR005: Tracing the clonal dynamic of metastatic castration-resistant prostate cancer over immunotherapy using circulating tumor DNA

Abstract Human cancer tissues are known to release their own DNA into body fluids such as plasma. These DNA molecules derived from tumors, collectively known as circulating tumor DNA (ctDNA), contain genetic information about disease progression at the time of sampling. Importantly, ctDNA has recently been utilized for capturing the whole-body disease profile and when sampled at various time points over the treatment, can inform the dynamic of clonal heterogeneity and its contribution to therapy failures. Metastatic castration-resistant prostate cancer (mCRPC) is a class of cancerous diseases with a high degree of clonal heterogeneity and high mortality which is largely due to the frequent emergence of therapy resistance. Therefore, reconstructing the clonal history for mCRPC diseases using ctDNA has great potential in identification of novel and targetable molecular mechanisms that drive mCRPC progression. To assess this possibility, we hypothesize that tumor clones that are responsible for therapy resistance carry distinct genomic profiles, which are captured in plasma ctDNA and could be computationally resolved through genomic sequencing and clonal reconstruction. To address this question, we obtained plasma cell-free DNA (cfDNA), a mixture of ctDNA and other tissue-derived DNA, from 38 individuals treated with combination PD-L1 and PARP inhibition involved in a recent clinical trial (NCT02484404). Whole-genome sequencing was performed using cfDNA and fragmented buffy coat DNA as germline control. cfDNA samples with a tumor fraction of lower than 10% were excluded. Various computational strategies were used to model the clonal structures of diseases and estimate the temporal order in which small and large structural variants emerged. Through this approach, we observed a negative association between cfDNA tumor fraction and therapy response. Multiple clonal evolutionary patterns leading to therapy failures were observed. For example, both gain and loss of activating androgen receptor mutations were detected in different cases following the treatment, which represents two distinct mechanisms of evading immunotherapy targeting. As a result, changes in the relevant transcriptional activities were also detected through ctDNA fragment-based computational inference. Additionally, clonal persistence was detected in multiple cases that exhibited stable diseases upon the treatment, which involves loss-of-function mutations in p53, ATM, and CDK12. To estimate the potential contribution to plasma ctDNA by metastatic diseases, multi-region whole genome and exome sequencing data of the tumors that are available for some cases prior to the treatment were also analyzed. Clones resolved from analyzing ctDNA were computationally mapped to the primary disease or metastatic tissue with a shared set of mutations in a subset of cases and may explain the patterns of treatment response. Our novel findings from this study will fill in a critical gap of knowledge about the complex genetic mechanisms driving mCRPC immunotherapy resistance. Citation Format: Chennan Li, Anna Baj, Clara C. Y. Seo, Nicholas T. Terrigino, John R. Bright, S. Thomas Hennigan, Isaiah M. King, Scott Wilkinson, Shana Y. Trostel, William D. Figg, William L. Dahut, Jung Min Lee, David Y. Takeda, Fatima Karzai, Adam G. Sowalsky. Tracing the clonal dynamic of metastatic castration-resistant prostate cancer over immunotherapy using circulating tumor DNA [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR005.

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.

Using simulated microhaplotype genotyping data to evaluate the value of machine learning algorithms for inferring DNA mixture contributor numbers

Inferring the number of contributors (NoC) is a crucial step in interpreting DNA mixtures, as it directly affects the accuracy of the likelihood ratio calculation and the assessment of evidence strength. However, obtaining the correct NoC in complex DNA mixtures remains challenging due to the high degree of allele sharing and dropout. This study aimed to analyze the impact of allele sharing and dropout on NoC inference in complex DNA mixtures when using microhaplotypes (MH). The effectiveness and value of highly polymorphic MH for NoC inference in complex DNA mixtures were evaluated through comparing the performance of three NoC inference methods, including maximum allele count (MAC) method, maximum likelihood estimation (MLE) method, and random forest classification (RFC) algorithm. In this study, we selected the top 100 most polymorphic MH from the Southern Han Chinese (CHS) population, and simulated over 40 million complex DNA mixture profiles with the NoC ranging from 2 to 8. These profiles involve unrelated individuals (RM type) and related pairs of individuals, including parent-offspring pairs (PO type), full-sibling pairs (FS type), and second-degree kinship pairs (SE type). Our results indicated that how the number of detected alleles in DNA mixture profiles varied with the markers’ polymorphism, kinship’s involvement, NoC, and dropout settings. Across different types of DNA mixtures, the MAC and MLE methods performed best in the RM type, followed by SE, FS, and PO types, while RFC models showed the best performance in the PO type, followed by RM, SE, and FS types. The recall of all three methods for NoC inference were decreased as the NoC and dropout levels increased. Furthermore, the MLE method performed better at low NoC, whereas RFC models excelled at high NoC and/or high dropout levels, regardless of the availability of a priori information about related pairs of individuals in DNA mixtures. However, the RFC models which considered the aforementioned priori information and were trained specifically on each type of DNA mixture profiles, outperformed RFC_ALL model that did not consider such information. Finally, we provided recommendations for model building when applying machine learning algorithms to NoC inference.