Modelling allelic drop-outs in STR sequencing data generated by MPS

A comparison of likelihood ratios calculated from surface DNA mixtures using MPS and CE Technologies

This study evaluates the performance of analysing surface DNA samples using massively parallel sequencing (MPS) compared to traditional capillary electrophoresis (CE). A total of 30 samples were collected from various surfaces in an office environment and were analysed with CE and MPS. These were compared against 60 reference samples (office inhabitants). To identify contributors, likelihood ratios (LRs) were calculated for MPS and CE data using the probabilistic genotyping software MPSproto and EuroForMix respectively. Although a higher number of sequences/peaks were observed per DNA profile in MPS compared to CE, LR values were found to be lower for MPS data formats. This might be the result of the increased complexity of MPS data, along with a possible elevation of unknown alleles and/or artefacts. The study highlights avenues for improving MPS data quality and analysis to facilitate more robust interpretation of challenging casework-like samples.

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.

An overview of autosomal STRs and identity SNPs in a Norwegian population using massively parallel sequencing

In recent years, probabilistic genotyping software has been adapted for the analysis of massively parallel sequencing (MPS) forensic data. Likelihood ratios (LR) are based on allele frequencies selected from populations of interest. This study provides an outline of sequence-based (SB) allele frequencies for autosomal short tandem repeats (aSTRs) and identity single nucleotide polymorphisms (iSNPs) in 371 individuals from Southern Norway. 27 aSTRs and 94 iSNPs were previously analysed with the ForenSeq™ DNA Signature Prep Kit (Verogen). The number of alleles with frequencies less than 0.05 for sequenced-based alleles was 4.6 times higher than for length-based alleles. Consistent with previous studies, it was observed that sequence-based data (both with and without flanks) exhibited higher allele diversity compared to length-based (LB) data; random match probabilities were lower for SB alleles confirming their advantage to discriminate between individuals. Two alleles in markers D22S1045 and Penta D were observed with SNPs in the 3´ flanking region, which have not been reported before. Also, a novel SNP with a minor allele frequency (MAF) of 0.001, was found in marker TH01. The impact of the sample size on minor allele frequency (MAF) values was studied in 88 iSNPs from Southern Norway (n = 371). The findings were then compared to a larger Norwegian population dataset (n = 15,769). The results showed that the smaller Southern Norway dataset provided similar results, and it was a representative sample. Population structure was analyzed for regions within Southern Norway; FST estimates for aSTR and iSNPs did not indicate any genetic structure. Finally, we investigated the genetic differences between Southern Norway and two other populations: Northern Norway and Denmark. Allele frequencies between these populations were compared, and we found no significant frequency differences (p-values > 0.0001). We also calculated the pairwise FST values per marker and comparisons between Southern and Northern Norway showed small differences. In contrast, the comparisons between Southern Norway and Denmark showed higher FST values for some markers, possibly driven by distinct alleles that were present in only one of the populations. In summary, we propose that allele frequencies from each population considered in this study could be used interchangeably to calculate genotype probabilities.

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.

Characterizing the amplification of STR markers in multiplex polymerase chain displacement reaction using massively parallel sequencing

Polymerase chain displacement reaction (PCDR) showed advantages in forensic low-template DNA analysis with improved amplification efficiency, higher allele detection capacity, and lower stutter artifact than PCR. However, characteristics of STR markers after PCDR amplification remain unclarified for the limited resolving power of capillary electrophoresis (CE). This issue can be addressed by massively parallel sequencing (MPS) technology with higher throughput and discriminability. Here, we developed a multiplex PCDR system including 24 STRs and amelogenin. In addition, a PCR reference was established for comparison. After amplification, products were subjected to PCR-free library construction and sequenced on the Illumina NovaSeq system. We implemented a sequence-matching pipeline to separate different amplicon types of PCDR products from the combination of primers. In the sensitivity test, the PCDR multiplex obtained full STR profiles with as low as 125 pg 2800M control DNA. Based on that, single-source DNA samples were tested. First, highly concordant genotypes were observed among the PCDR multiplex, the PCR reference, and CE-based STR kits. Next, read counts of different PCDR amplicon types were investigated, showing a relative abundance of 78:12:12:1 for the shortest amplicon S, the two medium amplicons M1 and M2, and the longest amplicon L. We also analyzed the stutter artifacts for distinct amplicon types, and the results revealed the reduction of N - 1 and N - 2 contraction stutters, and the increase of N + 1 and N + 2 elongation stutters in PCDR samples. Moreover, we confirmed the feasibility of PCDR for amplifying degraded DNA samples and unbalanced DNA mixtures. Compared to the previous proof of principle study, our work took a further step to characterize the complete profile of STR markers in the PCDR context. Our results suggested that the PCDR-MPS workflow is an effective approach for forensic STR analysis. Corresponding findings in this study may help the development of PCDR-based assays and probabilistic methods in future studies.

Modeling the minus two base pair stutter ratio of the D1S1656 locus: A sequence-based mixture distribution model

In this study, we propose a stutter ratio for a minus two base pair stutter (-2bpSR) model of the D1S1656 locus in capillary electrophoresis (CE)-based short tandem repeat (STR) typing. DNA from a total of 108 Japanese individuals was analyzed via massively parallel sequencing to investigate the length of the longest uninterrupted stretch of two base repeat motif (2bpLUS value) within repetitive structures involving the flanking region. Additionally, -2bpSR data was collected using the GlobalFiler Kit on a 3500xL Genetic Analyzer. As a result of sequencing analysis, all alleles were classified into two types by their 2bpLUS values. The -2bpSR differed significantly between the types. Then, we modeled the -2bpSR with a mixture log-normal distribution using the classification of alleles based on the 2bpLUS values. Furthermore, probabilities of the sequence type within each repeat number in the mixture log-normal distribution model were estimated using logistic regression for each of the five major detected populations. This study is expected to enable interpretation of STR typing while considering minus two base pair stutter at the D1S1656 locus.

The impact of common PCR inhibitors on forensic MPS analysis

Massively parallel sequencing holds great promise for new possibilities in the field of forensic genetics, enabling simultaneous analysis of multiple markers as well as offering enhanced short tandem repeat allele resolution. A challenge in forensic DNA analysis is that the samples often contain low amounts of DNA in a background that may interfere with downstream analysis. PCR inhibition mechanisms of some relevant molecules have been studied applying e.g. real-time PCR and digital PCR. However, a detailed understanding of the effects of inhibitory molecules on forensic MPS, including mechanisms and ways to relieve inhibition, is missing. In this study, the effects of two well-characterized PCR inhibitors, humic acid and hematin, have been studied using the ForenSeq DNA Signature Prep kit. Humic acid and hematin resulted in lowered read numbers as well as specific negative effects on certain markers. Quality control of libraries with Fragment analyzer showed that increasing amounts of inhibitors caused a lowered amplicon quantity and that the larger amplicons were more likely to drop out. Further, the inhibitor tolerance could be improved 5-10 times by addition of bovine serum albumin in the initial PCR. On the contrary to the samples with inhibitors, low-template samples resulted in lowered read numbers for all markers. This difference strengthened the conclusion that the inhibitors have a negative effect on the DNA polymerase activity in the initial PCR. Additionally, a common capillary gel electrophoresis-based STR kit was shown to handle at least 200 times more inhibitors than the ForenSeq DNA Signature Prep kit. This suggests that there is room for improvement of the PCR components to ensure analytical success for challenging samples, which is needed for a broad application of MPS for forensic STR analysis.