STRait Razor v2s: Advancing sequence-based STR allele reporting and beyond to other marker systems

Simultaneous sequencing of 102 Y-STRs on Ion Torrent ™ GeneStudio ™ S5 System

The Precision ID NGS System from Thermo Fisher Scientific is a mainstream next-generation sequencing (NGS) platform used in forensic laboratories to detect almost all commonly used forensic markers, except for Y-chromosomal short tandem repeats (Y-STRs). This study aimed to: 1) develop a Y-STR panel compatible with the automatic workflow of the NGS system using Ion AmpliSeq Technology, 2) evaluate the panel performance following the SWGDAM guidelines, and 3) explore the possibility of using a combination workflow to detect autosomal STRs and Y-STRs (AY-STR NGS workflow). The GrandFiler Y-STR Panel was successfully designed using the 'separating' and 'merging' strategies, including 102 Y-STRs and Amelogenin with an average amplicon length of 133 bp. It is a mega Y-STR multiplex system in which up to 16 samples can be sequenced simultaneously on an Ion 530 ™ Chip. Developmental validation studies of the performance of the NGS platform, species specificity, reproducibility, concordance, sensitivity, degraded samples, case-type samples, and mixtures were conducted to unequivocally determine whether the GrandFiler Y-STR Panel is suitable for real scenarios. The newly developed Y-STR panel showed compelling run metrics and NGS performance, including 92.47% bases with ≥ Q20, 91.80% effective reads, 2106 × depth of coverage (DoC), and 97.09% inter-locus balance. Additionally, it showed high specificity for human males and 99.40% methodological and bioinformatical concordance, generated complete profiles at ≥ 0.1 ng input DNA, and recovered more genetic information from severely degraded and diverse case samples. Although the outcome when used on mixtures was not as expected, more genetic information was obtained compared to that from capillary electrophoresis (CE) methods. The AY-STR NGS workflow was established by combining the GrandFiler Y-STR Panel with the Precision ID GlobalFiler ™ NGS STR Panel v2 at a 2:1 concentration ratio. The combination workflow on NGS performance, reproducibility, concordance, and sensitivity was as stable as the single Y-STR NGS workflow, providing more options for forensic scientists when dealing with different case scenarios. Overall, the GrandFiler Y-STR Panel was confirmed as the first to effectively detect a large number of Y-STR markers on the Precision ID NGS System, which is compatible with 51 Y-STRs in commercial CE kits and 51 Y-STRs in commercial NGS kits and the STRBase. The panel is as robust, reliable, and sensitive as current CE/NGS kits, and is suitable for solving real cases, especially for severely degraded samples (degradation index > 10).

Machine learning applications in forensic DNA profiling: A critical review

Machine learning (ML) is a range of powerful computational algorithms capable of generating predictive models via intelligent autonomous analysis of relatively large and often unstructured data. ML has become an integral part of our daily lives with a plethora of applications, including web, business, automotive industry, clinical diagnostics, scientific research, and more recently, forensic science. In the field of forensic DNA, the manual analysis of complex data can be challenging, time-consuming, and error-prone. The integration of novel ML-based methods may aid in streamlining this process while maintaining the high accuracy and reproducibility required for forensic tools. Due to the relative novelty of such applications, the forensic community is largely unaware of ML capabilities and limitations. Furthermore, computer science and ML professionals are often unfamiliar with the forensic science field and its specific requirements. This manuscript offers a brief introduction to the capabilities of machine learning methods and their applications in the context of forensic DNA analysis and offers a critical review of the current literature in this rapidly developing field.

High-resolution genotyping of 58 STRs in 635 Northern Han Chinese with MiSeq FGx ® Forensic Genomics System

Sequence polymorphisms were characterized at 27 autosomal STRs (A-STRs), 7 X chromosomal STRs (X-STRs), and 24 Y chromosomal STRs (Y-STRs) in 635 Northern Han Chinese with the ForenSeq DNA Signature Prep Kit on the MiSeq FGx Forensic Genomics System. Since repeat region (RR) and flanking region (FR) variation can be detected by massively parallel sequencing (MPS), the increase in the number of unique alleles and the average of gene diversity was 78.18% and 3.51% between sequence and length, respectively. A total of 74 novel RR variants were identified at 33 STRs compared with STRSeq and previous studies, and 13 FR variants (rs1770275883, rs2053373277, rs2082557941, rs1925525766, rs1926380862, rs1569322793, rs2051848492, rs2051848696, rs2016239814, rs2053269960, rs2044518192, rs2044536444, and rs2089968964) were first submitted to dbSNP. Also, 99.94% of alleles were concordant between the ForenSeq DNA Signature Prep Kit and commercial CE kits. Discordance resulted from the low performance at D22S1045 and occasionally at DYS392, flanking region deletions at D7S820 and DXS10074, and the strict alignment algorithm at DXS7132. Null alleles at DYS505 and DYS448 and multialleles at DYS387S1a/b, DYS385a/b, DYS448, DYS505, DXS7132, and HPRTB were validated with other MPS and CE kits. Thus, a high-resolution sequence-based (SB) and length-based (LB) allele frequencies dataset from Northern Han Chinese has been established already. As expected, forensic parameters increased significantly on combined power of discrimination (PD) and combined power of exclusion (PE) at A-STRs, mildly on combined PD and combined mean exclusion chance (MEC) at X-STRs, and barely on discrimination capacity (DC) at Y-STRs. Additionally, MiSeq FGx quality metrics and MPS performance were evaluated in this study, which presented the high-quality of the dataset at 20 consecutive runs, such as ≥ 60% bases with a quality score of 20 or higher (%≥ Q20), > 60% of effective reads, > 2000 × of depth of coverage (DoC), ≥ 60% of allele coverage ratio (ACR) or heterozygote balance, ≥ 70% of inter-locus balance, and ≤ 0.4 of the absolute value of observed minus expected heterozygosity (|H_exp - H_obs|). In conclusion, MiSeq FGx can help us generate a high-resolution and high-quality dataset for human identification and population genetic studies.

Developmental validation of the ForenSeq MainstAY kit, MiSeq FGx sequencing system and ForenSeq Universal Analysis Software

For human identification purposes, forensic genetics has primarily relied upon a core set of autosomal (and to a lesser extent Y chromosome) short tandem repeat (STR) markers that are enriched by amplification using the polymerase chain reaction (PCR) that are subsequently separated and detected using capillary electrophoresis (CE). While STR typing conducted in this manner is well-developed and robust, advances in molecular biology that have occurred over the last 15 years, in particular massively parallel sequencing (MPS) [1-7], offer certain advantages as compared to CE-based typing. First and foremost is the high throughput capacity of MPS. Current bench top high throughput sequencers enable larger batteries of markers to be multiplexed and multiple samples to be sequenced simultaneously (e.g., millions to billions of nucleotides can be sequenced in one run). Second, compared to the length-based CE approach, sequencing STRs increases discrimination power, enhances sensitivity of detection, reduces noise due to instrumentation, and improves mixture interpretation [4,8-23]. Third, since detection of STRs is based on sequence and not fluorescence, amplicons can be designed that are shorter in length and of similar lengths among loci, where possible, which can improve amplification efficiency and analysis of degraded samples. Lastly, MPS offers a single format approach that can be applied to analysis of a wide variety of genetic markers of forensic interest (e.g., STRs, mitochondrial DNA, single nucleotide polymorphisms, insertion/deletions). These features make MPS a desirable technology for casework [14,15,24,25-48]. The developmental validation of the ForenSeq MainstAY library preparation kit with the MiSeq FGx Sequencing System and ForenSeq Universal Software is reported here to assist with validation of this MPS system for casework [49]. The results show that the system is sensitive, accurate and precise, specific, and performs well with mixtures and mock case-type samples.

Microsatellite Genome-Wide Database Development for the Commercial Blackhead Seabream (Acanthopagrus schlegelii)

Simple sequence repeats (SSRs), the markers with the highest polymorphism and co-dominance degrees, offer a crucial genetic research resource. Limited SSR markers in blackhead seabream have been reported. The availability of the blackhead seabream genome assembly provided the opportunity to carry out genome-wide identification for all microsatellite markers, and bioinformatic analyses open the way for developing a microsatellite genome-wide database in blackhead seabream. In this study, a total of 412,381 SSRs were identified in the 688.08 Mb genome by Krait software. Whole-genome sequences (10×) of 42 samples were aligned against the reference genome and genotyped using the HipSTR tools by comparing and counting repeat number variation across the SSR loci. A total of 156,086 SSRs with a 2–4 bp repeat were genotyped by HipSTR tools, which accounted for 55.78% of the 2–4 bp SSRs in the reference genome. High accuracy of genotyping was observed by comparing HipSTR tools and PCR amplification. A set of 109,131 loci with a number of alleles ≥ 3 and with a number of genotyped individuals ≥ 6 were reserved to constitute the polymorphic SSR database. Fifty-one polymorphic SSR loci were identified through PCR amplification. This strategy to develop polymorphic SSR markers not only obtained a large set of polymorphic SSRs but also eliminated the need for laborious experimental screening. SSR markers developed in this study may facilitate blackhead seabream research, which lays a certain foundation for further gene tagging and genetic linkage analysis, such as marker-assisted selection, genetic mapping, as well as comparative genomic analysis.

Exploring STR sequencing for forensic DNA intelligence databasing using the Austrian National DNA Database as an example

Here, we present the results from a population study that evaluated the performance of massively parallel sequencing (MPS) of short tandem repeats (STRs) with a particular focus on DNA intelligence databasing purposes. To meet this objective, 247 randomly selected reference samples, earlier being processed with conventional capillary electrophoretic (CE) STR sizing from the Austrian National DNA Database, were reanalyzed with the PowerSeq 46Y kit (Promega). This sample set provides MPS-based population data valid for the Austrian population to increase the body of sequence-based STR variation. The study addressed forensically relevant parameters, such as concordance and backward compatibility to extant amplicon-based genotypes, sequence-based stutter ratios, and relative marker performance. Of the 22 autosomal STR loci included in the PowerSeq 46GY panel, 99.98% of the allele calls were concordant between MPS and CE. Moreover, 25 new sequence variants from 15 markers were found in the Austrian dataset that are yet undescribed in the STRSeq online catalogue and were submitted for inclusion. Despite the high degree of concordance between MPS and CE derived genotypes, our results demonstrate the need for a harmonized allele nomenclature system that is equally applicable to both technologies, but at the same time can take advantage of the increased information content of MPS. This appears to be particularly important with regard to database applications in order to prevent false exclusions due to varying allele naming based on different analysis platforms and ensures backward compatibility.

An Introductory Overview of Open-Source and Commercial Software Options for the Analysis of Forensic Sequencing Data

The top challenges of adopting new methods to forensic DNA analysis in routine laboratories are often the capital investment and the expertise required to implement and validate such methods locally. In the case of next-generation sequencing, in the last decade, several specifically forensic commercial options became available, offering reliable and validated solutions. Despite this, the readily available expertise to analyze, interpret and understand such data is still perceived to be lagging behind. This review gives an introductory overview for the forensic scientists who are at the beginning of their journey with implementing next-generation sequencing locally and because most in the field do not have a bioinformatics background may find it difficult to navigate the new terms and analysis options available. The currently available open-source and commercial software for forensic sequencing data analysis are summarized here to provide an accessible starting point for those fairly new to the forensic application of massively parallel sequencing.

Evaluation of Promega PowerSeq™ Auto/Y systems prototype on an admixed sample of Rio de Janeiro, Brazil: Population data, sensitivity, stutter and mixture studies

Forensic DNA typing typically relies on the length-based (LB) separation of PCR products containing short tandem repeat loci (STRs). Massively parallel sequencing (MPS) elucidates an additional level of STR motif and flanking region variation. Also, MPS enables simultaneous analysis of different marker-types - autosomal STRs, SNPs for lineage and identification purposes, reducing both the amount of sample used and the turn-around-time of analysis. Therefore, MPS methodologies are being considered as an additional tool in forensic genetic casework. The PowerSeq™ Auto/Y System (Promega Corp), a multiplex forensic kit for MPS, enables analysis of the 22 autosomal STR markers (plus Amelogenin) from the PowerPlex® Fusion 6C kit and 23 Y-STR markers from the PowerPlex® Y23 kit. Population data were generated from 140 individuals from an admixed sample from Rio de Janeiro, Brazil. All samples were processed according to the manufacturers' recommended protocols. Raw data (FastQ) were generated for each indexed sample and analyzed using STRait Razor v2s and PowerSeqv2.config file. The subsequent population data showed the largest increase in expected heterozygosity (23%), from LB to sequence-based (SB) analyses at the D5S818 locus. Unreported allele was found at the D21S11 locus. The random match probability across all loci decreased from 5.9 × 10^-28 to 7.6 × 10^-33. Sensitivity studies using 1, 0.25, 0.062 and 0.016 ng of DNA input were analyzed in triplicate. Full Y-STR profiles were detected in all samples, and no autosomal allele drop-out was observed with 62 pg of input DNA. For mixture studies, 1 ng of genomic DNA from a male and female sample at 1:1, 1:4, 1:9, 1:19 and 1:49 proportions were analyzed in triplicate. Clearly resolvable alleles (i.e., no stacking or shared alleles) were obtained at a 1:19 male to female contributor ratio. The minus one stutter (-1) increased with the longest uninterrupted stretch (LUS) allele size reads and according to simple or compound/complex repeats. The haplotype-specific stutter rates add more information for mixed samples interpretation. These data support the use of the PowerSeq^TM Auto/Y systems prototype kit (22 autosomal STR loci, 23 Y-STR loci and Amelogenin) for forensic genetics applications.

Autosomal STR and SNP characterization of populations from the Northeastern Peruvian Andes with the ForenSeq™ DNA Signature Prep Kit

Autosomal DNA data from Peru for human identity testing purposes are scarce in the scientific literature, which hinders obtaining an appropriate portrait of the genetic variation of the resident populations. In this study we genetically characterize five populations from the Northeastern Peruvian Andes (Chachapoyas, Awajún, Wampís, Huancas and Cajamarca). Autosomal short tandem repeat (aSTR) and identity informative single nucleotide polymorphism (iiSNP) data from a total of 233 unrelated individuals are provided, and forensic genetic parameters are calculated for each population and for the combined set Northeastern Peruvian Andes. After correction for multiple testing in the whole dataset of the Northeastern Peruvian Andes, the only departure from Hardy-Weinberg equilibrium was observed in locus rs2111980. Twenty one out of 27 aSTR loci exhibited an increased number of alleles due to sequence variation in the repeat motif and flanking regions. For iiSNPs 33% of the loci displayed flanking region variation. The combined random match probability (RMP), assuming independence of all loci (aSTRs and iiSNPs), in the Chachapoyas, the population with the largest samples size (N = 172), was 8.14 × 10^-62 for length-based data while for sequence-based was 4.15 × 10^-67. In the merged dataset (Northeastern Peruvian Andes; N = 233), the combined RMP when including all markers were 2.96 × 10^-61 (length-based) and 3.21 × 10^-66 (sequence-based). These new data help to fill up some of the gaps in the genetic canvas of South America and provide essential length- and sequence-based background information for other forensic genetic studies in Peru.

STRait Razor Online: An enhanced user interface to facilitate interpretation of MPS data

Since 2013, STRait Razor has enabled analysis of massively parallel sequencing (MPS) data from various marker systems such as short tandem repeats, single nucleotide polymorphisms, insertion/deletions, and mitochondrial DNA. In this paper, STRait Razor Online (SRO), available at https://www.unthsc.edu/straitrazor, is introduced as an interactive, Shiny-based user interface for primary analysis of MPS data and secondary analysis of STRait Razor haplotype pileups. This software can be accessed from any common browser via desktop, tablet, or smartphone device. SRO is available also as a standalone application and open-source R script available at https://github.com/ExpectationsManaged/STRaitRazorOnline. The local application is capable of batch processing of both fastq files and primary analysis output. Processed batches generate individual report folders and summary reports at the locus- and haplotype-level in a matter of minutes. For example, the processing of data from ∼700 samples generated with the ForenSeq Signature Preparation Kit from allsequences.txt to a final table can be performed in ∼40 min whereas the Excel-based workbooks can take 35-60 h to compile a subset of the tables generated by SRO. To facilitate analysis of single-source, reference samples, a preliminary triaging system was implemented that calls potential alleles and flags loci suspected of severe heterozygote imbalance. When compared to published, manually curated data sets, 98.72 % of software-assigned allele calls without manual interpretation were consistent with curated data sets, 0.99 % loci were presented to the user for interpretation due to heterozygote imbalance, and the remaining 0.29 % of loci were inconsistent due to the analytical thresholds used across the studies.

Genetic assessment reveals no population substructure and divergent regional and sex-specific histories in the Chachapoyas from northeast Peru

Many native populations in South America have been severely impacted by two relatively recent historical events, the Inca and the Spanish conquest. However decisive these disruptive events may have been, the populations and their gene pools have been shaped markedly also by the history prior to the conquests. This study focuses mainly on the Chachapoya peoples that inhabit the montane forests on the eastern slopes of the northern Peruvian Andes, but also includes three distinct neighboring populations (the Jívaro, the Huancas and the Cajamarca). By assessing mitochondrial, Y-chromosomal and autosomal diversity in the region, we explore questions that have emerged from archaeological and historical studies of the regional culture (s). These studies have shown, among others, that Chachapoyas was a crossroads for Coast-Andes-Amazon interactions since very early times. In this study, we examine the following questions: 1) was there pre-Hispanic genetic population substructure in the Chachapoyas sample? 2) did the Spanish conquest cause a more severe population decline on Chachapoyan males than on females? 3) can we detect different patterns of European gene flow in the Chachapoyas region? and, 4) did the demographic history in the Chachapoyas resemble the one from the Andean area? Despite cultural differences within the Chachapoyas region as shown by archaeological and ethnohistorical research, genetic markers show no significant evidence for past or current population substructure, although an Amazonian gene flow dynamic in the northern part of this territory is suggested. The data also indicates a bottleneck c. 25 generations ago that was more severe among males than females, as well as divergent population histories for populations in the Andean and Amazonian regions. In line with previous studies, we observe high genetic diversity in the Chachapoyas, despite the documented dramatic population declines. The diverse topography and great biodiversity of the northeastern Peruvian montane forests are potential contributing agents in shaping and maintaining the high genetic diversity in the Chachapoyas region.

Reducing noise and stutter in short tandem repeat loci with unique molecular identifiers

Unique molecular identifiers (UMIs) are a promising approach to contend with errors generated during PCR and massively parallel sequencing (MPS). With UMI technology, random molecular barcodes are ligated to template DNA molecules prior to PCR, allowing PCR and sequencing error to be tracked and corrected bioinformatically. UMIs have the potential to be particularly informative for the interpretation of short tandem repeats (STRs). Traditional MPS approaches may simply lead to the observation of alleles that are consistent with the hypotheses of stutter, while with UMIs stutter products bioinformatically may be re-associated with their parental alleles and subsequently removed. Herein, a bioinformatics pipeline named strumi is described that is designed for the analysis of STRs that are tagged with UMIs. Unlike other tools, strumi is an alignment-free machine learning driven algorithm that clusters individual MPS reads into UMI families, infers consensus super-reads that represent each family and provides an estimate the resulting haplotype's accuracy. Super-reads, in turn, approximate independent measurements not of the PCR products, but of the original template molecules, both in terms of quantity and sequence identity. Provisional assessments show that naïve threshold-based approaches generate super-reads that are accurate (∼97 % haplotype accuracy, compared to ∼78 % when UMIs are not used), and the application of a more nuanced machine learning approach increases the accuracy to ∼99.5 % depending on the level of certainty desired. With these features, UMIs may greatly simplify probabilistic genotyping systems and reduce uncertainty. However, the ability to interpret alleles at trace levels also permits the interpretation, characterization and quantification of contamination as well as somatic variation (including somatic stutter), which may present newfound challenges.

Identification of sequence polymorphisms at 58 STRs and 94 iiSNPs in a Tibetan population using massively parallel sequencing

Massively parallel sequencing (MPS) has rapidly become a promising method for forensic DNA typing, due to its ability to detect a large number of markers and samples simultaneously in a single reaction, and sequence information can be obtained directly. In the present study, two kinds of forensic genetic markers, short tandem repeat (STR) and identity-informative single nucleotide polymorphism (iiSNP) were analyzed simultaneously using ForenSeq DNA Signature Prep Kit, a commercially available kit on MPS platform. A total of 152 DNA markers, including 27 autosomal STR (A-STR) loci, 24 Y chromosomal STR (Y-STR) loci, 7 X chromosomal STR (X-STR) loci and 94 iiSNP loci were genotyped for 107 Tibetan individuals (53 males and 54 females). Compared with length-based STR typing methods, 112 more A-STR alleles, 41 more Y-STR alleles, and 24 more X-STR alleles were observed at 17 A-STRs, 9 Y-STRs, and 5 X-STRs using sequence-based approaches. Thirty-nine novel sequence variations were observed at 20 STR loci. When the flanking regions were also analyzed in addition to target SNPs at the 94 iiSNPs, 38 more alleles were identified. Our study provided an adequate genotype and frequencies data of the two types of genetic markers for forensic practice. Moreover, we also proved that this panel is highly polymorphic and informative in Tibetan population, and should be efficient in forensic kinship testing and personal identification cases.

Forensic STR allele extraction using a machine learning paradigm

We present a machine learning approach to short tandem repeat (STR) sequence detection and extraction from massively parallel sequencing data called Fragsifier. Using this approach, STRs are detected on each read by first locating the longest repeat stretches followed by locus prediction using k-mers in a machine learning sequence model. This is followed by reference flanking sequence alignment to determine precise STR boundaries. We show that Fragsifier produces genotypes that are concordant with profiles obtained using capillary electrophoresis (CE), and also compared the results with that of STRait Razor and the ForenSeq UAS. The data pre-processing and training of the sequence classifier is readily scripted, allowing the analyst to experiment with different thresholds, datasets and loci of interest, and different machine learning models.

Utility of the Ion S5™ and MiSeq FGx™ sequencing platforms to characterize challenging human remains

Often in missing persons' and mass disaster cases, the samples remaining for analysis are hard tissues such as bones, teeth, nails, and hair. These remains may have been exposed to harsh environmental conditions, which pose challenges for downstream genotyping. Short tandem repeat analysis (STR) via capillary electrophoresis (CE) is still the gold standard for DNA typing; however, a newer technology known as massively parallel sequencing (MPS) could improve upon our current techniques by typing different and more markers in a single analysis, and consequently improving the power of discrimination. In this study, bone and tooth samples exposed to a variety of DNA insults (cremation, embalming, decomposition, thermal degradation, and fire) were assessed and sequenced using the Precision ID chemistry and a custom AmpliSeq™ STR and iiSNP panel on the Ion S5™ System, and the ForenSeq DNA Signature Prep Kit on the MiSeq FGx™ system, as well as the GlobalFiler™ PCR Amplification Kit on the 3500™ Genetic Analyzer. The results demonstrated that using traditional CE-based genotyping performed as expected, producing a partial or full DNA profile for all samples, and that both sequencing chemistries and platforms were able to recover sufficient STR and SNP information from a majority of the same challenging samples. Run metrics including profile completeness and mean read depth produced good results with each system, considering the degree of damage of some samples. Most sample insults (except decomposed) produced similar numbers of alleles for both MPS systems. Comparable markers produced full concordance between the two platforms.

Assessment of impact of DNA extraction methods on analysis of human remain samples on massively parallel sequencing success

Skeletal remains recovered from missing persons' cases are often exposed to harsh environmental conditions resulting in the DNA being damaged, degraded, and/or the samples containing PCR inhibitors. In this study, the efficacy of common extraction methods was evaluated to remove high levels of PCR inhibitors commonly encountered with human remains, and their downstream compatibility with the two leading sequencing chemistries and platforms for human identification purposes. Blood, hair, and bone samples were spiked with high levels of inhibitors commonly identified in each particular substrate in order to test the efficiency of various DNA extraction methods prior to sequencing. Samples were extracted using three commercial extraction kits (DNA IQ™, DNA Investigator, and PrepFiler® BTA), organic (blood and hair only), and two total demineralization protocols (bone only)). Massively parallel sequencing (MPS) was performed using two different systems: Precision ID chemistry and a custom AmpliSeq™ STR and iiSNP panel on the Ion S5™ System and the ForenSeq DNA Signature Prep Kit on the MiSeq FGx™. The overall results showed that all DNA extraction methods were efficient and are fully compatible with both MPS systems. Key performance indicators such as STR and SNP reportable alleles, read depth, and heterozygote balance were comparable for each extraction method. In samples where CE-based STRs yielded partial profiles (bone), MPS-based STRs generated more complete or full profiles. Moreover, MPS panels contain more STR loci than current CE-based STR kits and also include SNPs, which can further increase the power of discrimination obtained from these samples, making MPS a desirable choice for the forensic analysis of such challenging samples.

A review of bioinformatic methods for forensic DNA analyses

Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used.

Flanking Variation Influences Rates of Stutter in Simple Repeats

It has been posited that the longest uninterrupted stretch (LUS) of tandem repeats, as defined by the number of exactly matching repeating motif units, is a better predictor of rates of stutter than the parental allele length (PAL). While there are cases where this hypothesis is likely correct, such as the 9.3 allele in the TH01 locus, there can be situations where it may not apply as well. For example, the PAL may capture flanking indel variations while remaining insensitive to polymorphisms in the repeat, and these haplotypic changes may impact the stutter rate. To address this, rates of stutter were contrasted against the LUS as well as the PAL on different flanking haplotypic backgrounds. This study shows that rates of stutter can vary substantially depending on the flanking haplotype, and while there are cases where the LUS is a better predictor of stutter than the PAL, examples to the contrary are apparent in commonly assayed forensic markers. Further, flanking variation that is 7 bp from the repeat region can impact rates of stutter. These findings suggest that non-proximal effects, such as DNA secondary structure, may be impacting the rates of stutter in common forensic short tandem repeat markers.

Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification

The human skin microbiome is comprised of diverse communities of bacterial, eukaryotic, and viral taxa and contributes millions of additional genes to the repertoire of human genes, affecting human metabolism and immune response. Numerous genetic and environmental factors influence the microbiome composition and as such contribute to individual-specific microbial signatures which may be exploited for forensic applications. Previous studies have demonstrated the potential to associate skin microbial profiles collected from touched items to their individual owner, mainly using unsupervised methods from samples collected over short time intervals. Those studies utilize either targeted 16S rRNA or shotgun metagenomic sequencing to characterize skin microbiomes; however, these approaches have limited species and strain resolution and susceptibility to stochastic effects, respectively. Clade-specific markers from the skin microbiome, using supervised learning, can predict individual identity using skin microbiomes from their respective donors with high accuracy. In this study the hidSkinPlex is presented, a novel targeted sequencing method using skin microbiome markers developed for human identification. The hidSkinPlex (comprised of 286 bacterial (and phage) family-, genus-, species-, and subspecies-level markers), initially was evaluated on three bacterial control samples represented in the panel (i.e., Propionibacterium acnes, Propionibacterium granulosum, and Rothia dentocariosa) to assess the performance of the multiplex. The hidSkinPlex was further evaluated for prediction purposes. The hidSkinPlex markers were used to attribute skin microbiomes collected from eight individuals from three body sites (i.e., foot (Fb), hand (Hp) and manubrium (Mb)) to their host donor. Supervised learning, specifically regularized multinomial logistic regression and 1-nearest-neighbor classification were used to classify skin microbiomes to their hosts with up to 92% (Fb), 96% (Mb), and 100% (Hp) accuracy. All samples (n=72) regardless of body site origin were correctly classified with up to 94% accuracy, and body site origin could be predicted with up to 86% accuracy. Finally, human short tandem repeat and single-nucleotide polymorphism profiles were generated from skin swab extracts from a single subject to highlight the potential to use microbiome profiling in conjunction with low-biomass samples. The hidSkinPlex is a novel targeted enrichment approach to profile skin microbiomes for human forensic identification purposes and provides a method to further characterize the utility of skin microflora for human identification in future studies, such as the stability and diversity of the personal skin microbiome.

Investigation of the STR loci noise distributions of PowerSeq™ Auto System

Aim

To characterize the noise and stutter distribution of 23 short tandem repeats (STRs) included in the PowerSeq^TM Auto System.

Methods

Raw FASTQ files were analyzed using STRait Razor v2s to display alleles and coverage. The sequence noise was divided into several categories: noise at allele position, noise at -1 repeat position, and artifact. The average relative percentages of locus coverage for each noise, stutter, and allele were calculated from the samples used for this locus noise analysis.

Results

Stutter products could be routinely observed at the -2 repeat position, -1 repeat position, and +1 repeat position of alleles. Sequence noise at the allele position ranged from 10.22% to 28.81% of the total locus coverage. At the allele position, individual noise reads were relatively low.

Conclusion

The data indicate that noise generally will be low. In addition, the PowerSeq^TM Auto System could capture nine flanking region single nucleotide polymorphisms (SNPs) that would not be observed by other current kits for massively parallel sequencing (MPS) of STRs.

Fast STR allele identification with STRait Razor 3.0

The short tandem repeat allele identification tool (STRait Razor), a program used to characterize the haplotypes of short tandem repeats (STRs) in massively parallel sequencing (MPS) data, was redesigned. STRait Razor v3.0 performs ∼660× faster allele identification than its previous version (v2s), a speedup that is largely due to a novel indexing strategy used to perform "fuzzy" (approximate) string matching of anchor sequences. Written in a portable compiled language, C++, STRait Razor v3.0 functions on all major operating systems including Microsoft Windows, and it has cross-platform multithreading support. In silico estimates of precision and accuracy of STRait Razor v3.0 were 100% in this evaluation and results were highly concordant with those of Strait Razor v2s. STRait Razor v3.0 adds several key features that simplify the haplotype reporting process, including simple filters to remove low frequency haplotypes as well as merging haplotypes within a locus encoded on opposite strands of the DNA molecule.