Improving the Yield of Genetic Diagnosis through Additional Genetic Panel Testing in Hereditary Ophthalmic Diseases.

Numerous hereditary ophthalmic diseases display significant genetic diversity. Consequently, the utilization of gene panel sequencing allows a greater number of patients to receive a genetic diagnosis for their clinical manifestations. We investigated how to improve the yield of genetic diagnosis through additional gene panel sequencing in hereditary ophthalmic diseases. A gene panel sequencing consisting of a customized hereditary retinopathy panel or hereditary retinitis pigmentosa (RP) panel was prescribed and referred to a CAP-accredited clinical laboratory. If no significant mutations associated with hereditary retinopathy and RP were detected in either panel, additional gene panel sequencing was requested for research use, utilizing the remaining panel. After additional gene panel sequencing, a total of 16 heterozygous or homozygous variants were identified in 15 different genes associated with hereditary ophthalmic diseases. Of 15 patients carrying any candidate variants, the clinical symptoms could be tentatively accounted for by genetic mutations in seven patients. However, in the remaining eight patients, given the in silico mutation predictive analysis, variant allele frequency in gnomAD, inheritance pattern, and genotype-phenotype correlation, fully elucidating the clinical manifestations with the identified rare variant was challenging. Our study highlights the utility of gene panel sequencing in achieving accurate diagnoses for hereditary ophthalmic diseases and enhancing the diagnostic yield through additional gene panel sequencing. Thus, gene panel sequencing can serve as a primary tool for the genetic diagnosis of hereditary ophthalmic diseases, even in cases where a single genetic cause is suspected. With a deeper comprehension of the genetic mechanisms underlying these diseases, it becomes feasible.

Population genetic analyses of Eastern Chinese Han nationality using ForenSeq™ DNA Signature Prep Kit.

Currently, the most commonly used method for human identification and kinship analysis in forensic genetics is the detection of length polymorphism in short tandem repeats (STRs) using polymerase chain reaction (PCR) and capillary electrophoresis (CE). However, numerous studies have shown that considerable sequence variations exist in the repeat and flanking regions of the STR loci, which cannot be identified by CE detection. Comparatively, massively parallel sequencing (MPS) technology can capture these sequence differences, thereby enhancing the identification capability of certain STRs. In this study, we used the ForenSeq™ DNA Signature Prep Kit to sequence 58 STRs and 94 individual identification SNPs (iiSNPs) in a sample of 220 unrelated individuals from the Eastern Chinese Han population. Our aim is to obtain MPS-based STR and SNP data, providing further evidence for the study of population genetics and forensic applications. The results showed that the MPS method, utilizing sequence information, identified a total of 486 alleles on autosomal STRs (A-STRs), 97 alleles on X-chromosome STRs (X-STRs), and 218 alleles on Y-chromosome STRs (Y-STRs). Compared with length polymorphism, we observed an increase of 260 alleles (157, 31, and 72 alleles on A-STRs, X-STRs, and Y-STRs, respectively) across 36 STRs. The most substantial increments were observed in DYF387S1 and DYS389II, with increases of 287.5% and 250%, respectively. The most increment in the number of alleles was found at DYF387S1 and DYS389II (287.5% and 250%, respectively). The length-based (LB) and sequence-based (SB) combined random match probability (RMP) of 27 A-STRs were 6.05E-31 and 1.53E-34, respectively. Furthermore, other forensic parameters such as total discrimination power (TDP), cumulative probability of exclusion of trios (CPEtrio), and duos (CPEduo) were significantly improved when using the SB data, and informative data were obtained for the 94 iiSNPs. Collectively, these findings highlight the advantages of MPS technology in forensic genetics, and the Eastern Chinese Han genetic data generated in this study could be used as a valuable reference for future research in this field.

Sequenced-based Rwanda population provides insights into demographic history.

Rwanda is known as the heart of Africa, reflecting the history of the world. Colonization and genocide have led to Rwanda's existing genetic structure. Herein, we used massively parallel sequencing to analyze 296 loci in 185 Rwandans and constructed a database for Rwandan forensic data for the first time. We found the following results: First, forensic parameters demonstrated that all loci were highly informative and could be used for forensic identification and paternity tests in Rwandans. Second, we found that the differences in genetic background between Rwandans and other African populations were similar but slight, as indicated by the massively parallel sequencing panel. Rwandans belonged to the African population and were inseparable from populations from neighboring countries. Also, Rwandans were closer to the European and American populations because of colonization, war, and other reasons. There was no scientific basis for racial classification established by colonization. Further research still needs to be carried out on more loci and larger Rwandan samples.

Comparative analysis of SNaPshot and massively parallel sequencing for body fluid-specific DNA methylation markers.

The identification of tissue-specific differentially methylated regions has significantly contributed to the field of forensic genetics, particularly in body fluid identification crucial for linking evidence to crimes. Among the various approaches to analyzing DNA methylation, the SNaPshot assay has been popularly studied in numerous researches. However, there is a growing interest in exploring alternative methods such as the use of massively parallel sequencing (MPS), which can process a large number of samples simultaneously. This study compares SNaPshot and MPS multiplex assays using nine cytosine-phosphate-guanine markers for body fluid identification. As a result of analyzing 112 samples, including blood, saliva, vaginal fluid, menstrual blood, and semen, both methods demonstrated high sensitivity and specificity, indicating their reliability in forensic investigations. A total of 92.0% samples were correctly identified by both methods. Although both methods accurately identified all blood, saliva, and semen samples, some vaginal fluid samples showed unexpected methylation signals at nontarget loci in addition to the target loci. In the case of menstrual blood samples, due to their complexity, independent typing criteria were applied, and successful menstrual blood typing was possible, whereas a few samples showed profiles similar to vaginal fluid. The MPS method worked better in vaginal fluid samples, and the SNaPshot method performed better in menstrual blood samples. This study offers valuable insights into body fluid identification based on the characteristics of the SNaPshot and MPS methods, which may help in more efficient forensic applications.

Developmental validation of the STRSeqTyper122 kit for massively parallel sequencing of forensic STRs.

Massively parallel sequencing allows for integrated genotyping of different types of forensic markers, which reduces DNA consumption, simplifies experimental processes, and provides additional sequence-based genetic information. The STRseqTyper122 kit genotypes 63 autosomal STRs, 16 X-STRs, 42 Y-STRs, and the Amelogenin locus. Amplicon sizes of 117 loci were below 300 bp. In this study, MiSeq FGx sequencing metrics for STRseqTyper122 were presented. The genotyping accuracy of this kit was examined by comparing to certified genotypes of NIST standard reference materials and results from five capillary electrophoresis-based kits. The sensitivity of STRseqTyper122 reached 125 pg, and > 80% of the loci were correctly called with 62.5 pg and 31.25 pg input genomic DNA. Repeatability, species specificity, and tolerance for DNA degradation and PCR inhibitors of this kit were also evaluated. STRseqTyper122 demonstrated reliable performance with routine case-work samples and provided a powerful tool for forensic applications.

Genetic Evaluation for Monogenic Disorders of Low Bone Mass and Increased Bone Fragility: What Clinicians Need to Know.

PURPOSE OF REVIEW: The purpose of this review is to outline the principles of clinical genetic testing and to provide practical guidance to clinicians in navigating genetic testing for patients with suspected monogenic forms of osteoporosis. RECENT FINDINGS: Heritability assessments and genome-wide association studies have clearly shown the significant contributions of genetic variations to the pathogenesis of osteoporosis. Currently, over 50 monogenic disorders that present primarily with low bone mass and increased risk of fractures have been described. The widespread availability of clinical genetic testing offers a valuable opportunity to correctly diagnose individuals with monogenic forms of osteoporosis, thus instituting appropriate surveillance and treatment. Clinical genetic testing may identify the appropriate diagnosis in a subset of patients with low bone mass, multiple or unusual fractures, and severe or early-onset osteoporosis, and thus clinicians should be aware of how to incorporate such testing into their clinical practices.

The Development and Characterisation of ssDNA Aptamers via a Modified Cell-SELEX Methodology for the Detection of Human Red Blood Cells.

Blood is one of the most commonly found biological fluids at crime scenes, with the detection and identification of blood holding a high degree of evidential value. It can provide not only information about the nature of the crime but can also lead to identification via DNA profiling. Presumptive tests for blood are usually sensitive but not specific, so small amounts of the substrate can be detected, but false-positive results are often encountered, which can be misleading. Novel methods for the detection of red blood cells based on aptamer-target interactions may be able to overcome these issues. Aptamers are single-stranded DNA or RNA sequences capable of undergoing selective antigen association due to three-dimensional structure formation. The use of aptamers as a target-specific moiety poses several advantages and has the potential to replace antibodies within immunoassays. Aptamers are cheaper to produce, display no batch-to-batch variation and can allow for a wide range of chemical modifications. They can help limit cross-reactivity, which is a hindrance to current forensic testing methods. Within this study, a modified Systematic Evolution of Ligands by Exponential Enrichment (SELEX) process was used to generate aptamers against whole red blood cells. Obtained aptamer pools were analysed via massively parallel sequencing to identify viable sequences that demonstrate a high affinity for the target. Using bioinformatics platforms, aptamer candidates were identified via their enrichment profiles. Binding characterisation was also conducted on two selected aptamer candidates via fluorescent microscopy and qPCR to visualise and quantify aptamer binding. The potential for these aptamers is broad as they can be utilised within a range of bioassays for not only forensic applications but also other analytical science and medical applications. Potential future work includes the incorporation of developed aptamers into a biosensing platform that can be used at crime scenes for the real-time detection of human blood.

Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks.

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) is a central genome-wide method for in vivo analyses of DNA-protein interactions in various cellular conditions. Numerous studies have demonstrated the complex contextual organization of ChIP-seq peak sequences and the presence of binding sites for transcription factors in them. We assessed the dependence of the ChIP-seq peak score on the presence of different contextual signals in the peak sequences by analyzing these sequences from several ChIP-seq experiments using our fully enumerative GPU-based de novo motif discovery method, Argo_CUDA. Analysis revealed sets of significant IUPAC motifs corresponding to the binding sites of the target and partner transcription factors. For these ChIP-seq experiments, multiple regression models were constructed, demonstrating a significant dependence of the peak scores on the presence in the peak sequences of not only highly significant target motifs but also less significant motifs corresponding to the binding sites of the partner transcription factors. A significant correlation was shown between the presence of the target motifs FOXA2 and the partner motifs HNF4G, which found experimental confirmation in the scientific literature, demonstrating the important contribution of the partner transcription factors to the binding of the target transcription factor to DNA and, consequently, their important contribution to the peak score.

Age prediction using DNA methylation of Y-chromosomal CpGs in semen samples.

In cases of sexual assault, the evidence often exists as a mixture of female and male body fluids, and in many cases, contains a higher proportion of female body fluids than males. In these cases, Y-STR, rather than autosomal STRs, can provide useful information. It becomes very difficult to identify the true suspect if there is no match among known suspects or if a match exists for two or more suspects, e.g. two suspects from the same paternal lineage. However, age prediction using the DNA methylation of Y-chromosomal CpGs can help narrow the search for unknown suspects and discriminate between older and younger suspects. Therefore, the DNA methylation profiles of semen samples from 56 healthy Korean males were generated using Illumina's Infinium MethylationEPIC BeadChip Array. Among the ten identified age-associated CpG markers located in the Y-chromosome, nine were used to construct age prediction models. The identified markers were further investigated in the MPS analysis of 147 semen samples, and the multiplex assay was validated with the reliability, reproducibility and sensitivity tests. Several age prediction models were constructed using the MPS data with the multiple linear regression, stepwise linear regression, ridge linear regression, lasso regression, elastic net linear regression and support vector machine analyses, and all showed MAEs of 5 to 7 years in the test set samples. Six single-source female samples were also subjected to MPS analysis but showed very low coverage that could not affect the analysis of the mixed samples. Therefore, the age prediction models of the present study are expected to provide useful investigative leads, especially in mixed male and female samples from sexual assault cases.

Unique molecular identifier-based amplicon sequencing of microhaplotypes for background noise mitigation.

Microhaplotypes (MHs), comprising two or more single-nucleotide polymorphisms in a short fragment, are promising forensic markers owing to their remarkable polymorphic nature. Several studies have demonstrated the utility of MHs through massively parallel sequencing (MPS). Nevertheless, the background noise level associated with MHs in MPS, which imposes a practical detection limit for the system, remains uninvestigated. Currently, unique molecular identifier (UMI) systems are known to effectively mitigate background noise by tracking original DNA molecules and facilitating PCR and MPS error corrections. Hence, this study aimed to design a UMI-based amplicon sequencing system, designated MH-UMIseq, which can amplify 46 MHs simultaneously and generate MPS libraries in four steps: barcoding PCR, nuclease reaction, boosting PCR, and indexing PCR. The performance of the MH-UMIseq system was evaluated using the Illumina NextSeq 550 and MiniSeq systems with 31 sets for 5 ng, 1 ng, and 200 pg of input DNA. The fgbio toolkit was used in conjunction with STRait Razor 3.0 and Visual Microhap to analyze the UMI data on MHs. The corresponding average not suppressed noise proportion of MH-UMIseq were 0.1 %, 0.3 %, and 0.7 % for 5 ng, 1 ng, and 200 pg of DNA, respectively, which substantially suppressed the background noise for more than 1 ng of DNA. Interestingly, the proportion of not suppressed noise in MH-UMIseq notably decreased as the amount of input DNA increased. The number of UMI families was proportional to the copy number of the template DNA and closely correlated with the system resolution. Therefore, the resolution of MH-UMIseq system is expected to be higher than that of conventional MPS for the deconvolution of mixtures containing more than 1 ng of DNA.

Utilizing Massively Parallel Sequencing (MPS) of Human Leukocyte Antigen (HLA) Gene Polymorphism to Assess Relatedness in Deficiency Parentage Testing.

In the realm of DNA testing with legal implications, the reliability and precision of genetic markers play a pivotal role in confirming or negating paternity claims. This study aimed to assess the potential utility of human leukocyte antigen (HLA) gene polymorphism through massively parallel sequencing (MPS) technology as robust forensic markers for parentage testing involving genetic deficiencies. It sought to redefine the significance of HLA genes in this context. Data on autosomal short tandem repeat (aSTR) mutational events across 18 paternity cases involving 16 commonly employed microsatellite loci were presented. In instances where traditional aSTR analysis failed to establish statistical certainty, kinship determination was pursued via HLA genotyping, encompassing the amplification of 17 linked HLA loci. Within the framework of this investigation, phase-resolved genotypes for HLA genes were meticulously generated, resulting in the definition of 34 inherited HLA haplotypes. An impressive total of 274 unique HLA alleles, which were classified at either the field 3 or 4 level, were identified, including the discovery of four novel HLA alleles. Likelihood ratio (LR) values, which indicated the likelihood of the observed data under a true biological relationship versus no relationship, were subsequently calculated. The analysis of the LR values demonstrated that the HLA genes significantly enhanced kinship determination compared with the aSTR analysis. Combining LR values from aSTR markers and HLA loci yielded conclusive outcomes in duo paternity cases, showcasing the potential of HLA genes and MPS technology for deeper insights and diversity in genetic testing. Comprehensive reference databases and high-resolution HLA typing across diverse populations are essential. Reintegrating HLA alleles into forensic identification complements existing markers, creating a potent method for future forensic analysis.

Identifying distant relatives using benchtop-scale sequencing.

The genetic component of forensic genetic genealogy (FGG) is an estimate of kinship, often conducted at genome scales between a great number of individuals. The promise of FGG is substantial: in concert with genealogical records and other nongenetic information, it can indirectly identify a person of interest. A downside of FGG is cost, as it is currently expensive and requires chemistries uncommon to forensic genetic laboratories (microarrays and high throughput sequencing). The more common benchtop sequencers can be coupled with a targeted PCR assay to conduct FGG, though such approaches have limited resolution for kinship. This study evaluates low-pass sequencing, an alternative strategy that is accessible to benchtop sequencers and can produce resolutions comparable to high-pass sequencing. Samples from a three-generation pedigree were augmented to include up to 7th degree relatives (using whole genome pedigree simulations) and the ability to recover the true kinship coefficient was assessed using algorithms qualitatively similar to those found in GEDmatch. We show that up to 7th degree relatives can be reliably inferred from 1 × whole genome sequencing obtainable from desktop sequencers.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study.

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

An exploratory view into allelic drop-out of sequenced autosomal STRs.

As massively parallel sequencing is implemented in forensic genetics, an understanding of sequence data must accompany these advancements, that is, accurate modeling of data for proper statistical analysis. Allelic drop-out, a common stochastic effect seen in genetic data, is often modeled in statistical analysis of STR results. This proof-of-concept study sequenced several serial dilutions of a standard sample ranging from 4 ng to 7.82 pg to evaluate allelic drop-out trends on a select panel of autosomal STRs using the ForenSeq™ DNA Signature Prep Kit, Primer Set A on the Illumina MiSeq FGx. Parameters assessed included locus, profile, and run specific information. A majority of the allelic drop-out occurred in DNA concentrations less than 31.25 pg. Statistical results indicated a need for locus-specific modeling based on STR descriptors, like simple versus compound repeat patterns. No correlation was seen between average read count of scored alleles and allelic drop-out at a locus. A statistical correlation was observed between the amount of allelic drop-out and the starting amount of DNA in a sample, average read count of a sample, and total read count generated on a flow cell. This study supports using common allelic drop-out factors used in fragment length analysis on sequenced STRs while including additional locus, sample, and run specific information. Results demonstrate multiple factors that can be considered when developing probability of allelic drop-out models for sequenced autosomal STRs including locus-specific analysis, total read count of a profile, and total read count sequenced on a flow cell.

Forensic analysis and sequence variation of 133 STRs in the Hakka population.

Introduction: Short Tandem Repeats (STRs) are highly valuable genetic markers in forensic science. However, the conventional PCR-CE technique has limitations, and the emergence of massively parallel sequencing (MPS) technology presents new opportunities for STR analysis. Yet, there is limited research on Chinese population diversity using MPS. Methods: In this study, we obtained genotype data for 52 A-STRs and 81 Y-STRs from the Hakka population in Meizhou, Guangdong, China, using the Forensic Analysis System Multiplecues SetB Kit on the MGISEQ-2000 platform. Results: Our findings demonstrate that these 133 STRs are highly efficient for forensic applications within the Meizhou Hakka population. Statistical analysis revealed Hobs values ranging from 0.61306 to 0.91083 and Hexp values ranging from 0.59156 to 0.91497 for A-STRs based on length polymorphism. For sequence polymorphism, Hobs values ranged from 0.61306 to 0.94586, and Hexp values fluctuated between 0.59156 and 0.94487. The CPE values were 1-5.0779620E-21 and 1-3.257436E-24 for length and sequence polymorphism, respectively, while the CPD values were 1-1.727007E-59 and 1-5.517015E-66, respectively. Among the 80 Y-STR loci, the HD values for length and sequence polymorphism were 0.99764282 and 0.99894195, respectively. The HMP values stood at 0.00418102 and 0.00288427, respectively, and the DC values were 0.75502742 and 0.83363803, respectively. For the 52 A-STR loci, we identified 554 and 989 distinct alleles based on length and sequence polymorphisms, respectively. For the 81 Y-STR loci, 464 and 652 unique alleles were detected at the length and sequence level, respectively. Population genetic analysis revealed that the Meizhou Hakka population has a close kinship relationship with the Asian populations THI and KOR based on length polymorphism data of A-STRs. Conversely, based on length polymorphism data of Y-STRs, the Meizhou Hakka population has the closest kinship relationship with the Henan Han population. Discussion: Overall, the variation information of repeat region sequences significantly enhances the forensic identification efficacy of STR genetic markers, providing an essential database for forensic individual and paternity testing in this region. Additionally, the data generated by our study will serve as a vital resource for research into the genetic structure and historical origins of the Meizhou Hakka population.

Cytogenetics and genomics of acute myeloid leukemia.

The diversity of genetic and genomic abnormalities observed in acute myeloid leukemia (AML) reflects the complexity of these hematologic neoplasms. The detection of cytogenetic and molecular alterations is fundamental to diagnosis, risk stratification and treatment of AML. Chromosome rearrangements are well established in the diagnostic classification of AML, as are some gene mutations, in several international classification systems. Additionally, the detection of new mutational profiles at relapse and identification of mutations in the pre- and post-transplant settings are illuminating in understanding disease evolution and are relevant to the risk assessment of AML patients. In this review, we discuss recurrent cytogenetic abnormalities, as well as the detection of recurrent mutations, within the context of a normal karyotype, and in the setting of chromosome abnormalities. Two new classification schemes from the WHO and ICC are described, comparing these classifications in terms of diagnostic criteria and entity definition in AML. Finally, we discuss ways in which genomic sequencing can condense the detection of gene mutations and chromosome abnormalities into a single assay.

Biogeographical Ancestry Analyses Using the ForenSeqTM DNA Signature Prep Kit and Multiple Prediction Tools.

The inference of biogeographical ancestry (BGA) can assist in police investigations of serious crime cases and help to identify missing people and victims of mass disasters. In this study, we evaluated the typing performance of 56 ancestry-informative SNPs in 177 samples using the ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system. Furthermore, we compared the prediction accuracy of the tools Universal Analysis Software v1.2 (UAS), the FROG-kb, and GenoGeographer when inferring the ancestry of 503 Europeans, 22 non-Europeans, and 5 individuals with co-ancestry. The kit was highly sensitive with complete aiSNP profiles in samples with as low as 250pg input DNA. However, in line with others, we observed low read depth and occasional drop-out in some SNPs. Therefore, we suggest not using less than the recommended 1ng of input DNA. FROG-kb and GenoGeographer accurately predicted both Europeans (99.6% and 91.8% correct, respectively) and non-Europeans (95.4% and 90.9% correct, respectively). The UAS was highly accurate when predicting Europeans (96.0% correct) but performed poorer when predicting non-Europeans (40.9% correct). None of the tools were able to correctly predict individuals with co-ancestry. Our study demonstrates that the use of multiple prediction tools will increase the prediction accuracy of BGA inference in forensic casework.

Review of SNP assays for disaster victim identification: Cost, time, and performance information for decision-makers.

In mass disaster events, forensic DNA laboratories may be called upon to quickly pivot their operations toward identifying bodies and reuniting remains with family members. Ideally, laboratories have considered this possibility in advance and have a plan in place. Compared with traditional short tandem repeat (STR) typing, single nucleotide polymorphisms (SNPs) may be better suited to these disaster victim identification (DVI) scenarios due to their small genomic target size, resulting in an improved success rate in degraded DNA samples. As the landscape of technology has shifted toward DNA sequencing, many forensic laboratories now have benchtop instruments available for massively parallel sequencing (MPS), facilitating this operational pivot from routine forensic STR casework to DVI SNP typing. Herein, we present the commercially available SNP sequencing assays amenable to DVI, we use data simulations to explore the potential for kinship prediction from SNP panels of varying sizes, and we give an example DVI scenario as context for presenting the matrix of considerations: kinship predictive potential, cost, and throughput of current SNP assay options. This information is intended to assist laboratories in choosing a SNP system for disaster preparedness.

Ultrasensitive sequencing of STR markers utilizing unique molecular identifiers and the SiMSen-Seq method.

Massively parallel sequencing (MPS) is increasingly applied in forensic short tandem repeat (STR) analysis. The presence of stutter artefacts and other PCR or sequencing errors in the MPS-STR data partly limits the detection of low DNA amounts, e.g., in complex mixtures. Unique molecular identifiers (UMIs) have been applied in several scientific fields to reduce noise in sequencing. UMIs consist of a stretch of random nucleotides, a unique barcode for each starting DNA molecule, that is incorporated in the DNA template using either ligation or PCR. The barcode is used to generate consensus reads, thus removing errors. The SiMSen-Seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing) method relies on PCR-based introduction of UMIs and includes a sophisticated hairpin design to reduce unspecific primer binding as well as PCR protocol adjustments to further optimize the reaction. In this study, SiMSen-Seq is applied to develop a proof-of-concept seven STR multiplex for MPS library preparation and an associated bioinformatics pipeline. Additionally, machine learning (ML) models were evaluated to further improve UMI allele calling. Overall, the seven STR multiplex resulted in complete detection and concordant alleles for 47 single-source samples at 1 ng input DNA as well as for low-template samples at 62.5 pg input DNA. For twelve challenging mixtures with minor contributions of 10 pg to 150 pg and ratios of 1-15% relative to the major donor, 99.2% of the expected alleles were detected by applying the UMIs in combination with an ML filter. The main impact of UMIs was a substantially lowered number of artefacts as well as reduced stutter ratios, which were generally below 5% of the parental allele. In conclusion, UMI-based STR sequencing opens new means for improved analysis of challenging crime scene samples including complex mixtures.

Performance of a 74-Microhaplotype Assay in Kinship Analyses.

Microhaplotypes (MHs) consisting of multiple SNPs and indels on short stretches of DNA are new and interesting loci for forensic genetic investigations. In this study, we analysed 74 previously defined MHs in two of the populations that our laboratory provides with forensic genetic services, Danes and Greenlanders. In addition to the 229 SNPs that originally made up the 74 MHs, 66 SNPs and 3 indels were identified in the two populations, and 45 of these variants were included in new definitions of the MHs, whereas 24 SNPs were considered rare and of little value for case work. The average effective number of alleles (Ae) was 3.2, 3.0, and 2.6 in Danes, West Greenlanders, and East Greenlanders, respectively. High levels of linkage disequilibrium were observed in East Greenlanders, which reflects the characteristics of this population that has a small size, and signs of admixture and substructure. Pairwise kinship simulations of full siblings, half-siblings, first cousins, and unrelated individuals were performed using allele frequencies from MHs, STRs and SNPs from Danish and Greenlandic populations. The MH panel outperformed the currently used STR and SNP marker sets and was able to differentiate siblings from unrelated individuals with a 0% false positive rate and a 1.1% false negative rate using an LR threshold of 10,000 in the Danish population. However, the panel was not able to differentiate half-siblings or first cousins from unrelated individuals. The results generated in this study will be used to implement MHs as investigative markers for relationship testing in our laboratory.