Evaluation of a custom GeneRead™ massively parallel sequencing assay with 210 ancestry informative SNPs using the Ion S5™ and MiSeq platforms

Forensic biogeographical ancestry inference: recent insights and current trends

BACKGROUND

As a powerful complement to the paradigmatic DNA profiling strategy, biogeographical ancestry inference (BGAI) plays a significant part in human forensic investigation especially when a database hit or eyewitness testimony are not available. It indicates one's biogeographical profile based on known population-specific genetic variations, and thus is crucial for guiding authority investigations to find unknown individuals. Forensic biogeographical ancestry testing exploits much of the recent advances in the understanding of human genomic variation and improving of molecular biology.

OBJECTIVE

In this review, recent development of prospective ancestry informative markers (AIMs) and the statistical approaches of inferring biogeographic ancestry from AIMs are elucidated and discussed.

METHODS

We highlight the research progress of three potential AIMs (i.e., single nucleotide polymorphisms, microhaplotypes, and Y or mtDNA uniparental markers) and discuss the prospects and challenges of two methods that are commonly used in BGAI.

CONCLUSION

While BGAI for forensic purposes has been thriving in recent years, important challenges, such as ethics and responsibilities, data completeness, and ununified standards for evaluation, remain for the use of biogeographical ancestry information in human forensic investigations. To address these issues and fully realize the value of BGAI in forensic investigation, efforts should be made not only by labs/institutions around the world independently, but also by inter-lab/institution collaborations.

Biogeographical ancestry, variable selection, and PLS-DA method: a new panel to assess ancestry in forensic samples via MPS technology

As evidenced by the large number of articles recently published in the literature, forensic scientists are making great efforts to infer externally visible features and biogeographical ancestry (BGA) from DNA analysis. Just as phenotypic, ancestry information obtained from DNA can provide investigative leads to identify the victims (missing/unidentified persons, crime/armed conflict/mass disaster victims) or trace their perpetrators when no matches were found with the reference profile or in the database. Recently, the advent of Massively Parallel Sequencing technologies associated with the possibility of harnessing high-throughput genetic data allowed us to investigate the associations between phenotypic and genomic variations in worldwide human populations and develop new BGA forensic tools capable of simultaneously analyzing up to millions of markers if for example the ancient DNA approach of hybridization capture was adopted to target SNPs of interest. In the present study, a selection of more than 3000 SNPs was performed to create a new BGA panel and the accuracy of the new panel to infer ancestry from unknown samples was evaluated by the PLS-DA method. Subsequently, the panel created was assessed using three variable selection techniques (Backward variable elimination, Genetic Algorithm and Regularized elimination procedure), and the best SNPs in terms of inferring bio-geographical ancestry at inter- and intra-continental level were selected to obtain panels to predict BGA with a reduced number of selected markers to be applied in routine forensic cases where PCR amplification is the best choice to target SNPs.

Evaluation of a SNP-STR haplotype panel for forensic genotype imputation

Short tandem repeat polymorphism (STR)-based individual identification is a popular and reliable method in many forensic applications. However, STRs still frequently fail to find any matched records. In such cases, if known STRs could provide more information, it would be very helpful to solve specific problems. Genotype imputation has long been used in the study of single nucleotide polymorphisms (SNPs) and has recently been introduced into forensic fields. The idea is that, through a reference haplotype panel containing SNPs and STRs, we can obtain unknown genetic information through genotype imputation based on known STR or SNP genotypes. Several recent studies have already demonstrated this exciting idea, and a 1000 Genomes SNP-STR haplotype panel has also been released. To further study the performance of genotype imputation in forensic fields, we collected STR, microhaplotype (MH) and SNP array genotypes from Chinese Han population individuals and then performed genotype imputation analysis based on the released reference panel. As a result, the average locus imputation accuracy was ∼83 % (or ∼70 %) when SNPs in the SNP array (or MH SNPs) were imputed from STRs, and was ∼30 % when highly polymorphic markers (STRs and MHs) were imputed from each other. When STRs were imputed from SNP array, the average locus imputation accuracy increased to ∼48 %. After analyzing the match scores between real STRs and the STRs imputed from SNPs, ∼80 % of studied STR records can be connected to corresponding SNP records, which may help for individual identification. Our results indicate that genotype imputation has great potential for forensic applications.

Study on Gaseous Chlorobenzene Treatment by a Bio-Trickling Filter: Degradation Mechanism and Microbial Community

Large-flow waste gas generated from the pharmaceutical and chemical industry usually contains low concentrations of VOCs (volatile organic compounds), and it is also the key factor that presents challenges in terms of disposal. To date, due to the limitations of mass transfer rate and microbial degradation ability, the degradation performance of VOCs using the biological method has not been ideal. Therefore, in this study, the sludge from a chlorobenzene-containing wastewater treatment plant was inoculated into our experimental bio-trickling filter (BTF) to explore the feasibility of domestication and degradation of gaseous chlorobenzene by highly active microorganisms. The kinetics of its mass transfer reaction and microbial community dynamics were also discussed. Moreover, the main process parameters of BTF for chlorobenzene degradation were optimized. The results showed that the degradation effect of chlorobenzene reached more than 85% at an inlet concentration of chlorobenzene 700 mg·m−3, oxygen concentration of 10%, and an empty bed retention time (EBRT) of 80 s. The mass transfer kinetic analysis indicated that the process of chlorobenzene degradation in the BTF occurred between the zero-stage reaction and the first-stage reaction. This BTF contributed significantly to the biodegradability of chlorobenzene, overcoming the limitation of gas-to-liquid/solid mass transfer of chlorobenzene. The analysis of the species diversity showed that Thermomonas, Petrimona, Comana, and Ottowia were typical organic-matter-degrading bacteria that degraded chlorobenzene efficiently with xylene present.

Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field

The biogeographical ancestry (BGA) of a trace or a person/skeleton refers to the component of ethnicity, constituted of biological and cultural elements, that is biologically determined. Nowadays, many individuals are interested in exploring their genealogy, and the capability to distinguish biogeographic information about population groups and subgroups via DNA analysis plays an essential role in several fields such as in forensics. In fact, for investigative and intelligence purposes, it is beneficial to inference the biogeographical origins of perpetrators of crimes or victims of unsolved cold cases when no reference profile from perpetrators or database hits for comparative purposes are available. Current approaches for biogeographical ancestry estimation using SNPs data are usually based on PCA and Structure software. The present study provides an alternative method that involves multivariate data analysis and machine learning strategies to evaluate BGA discriminating power of unknown samples using different commercial panels. Starting from 1000 Genomes project, Simons Genome Diversity Project and Human Genome Diversity Project datasets involving African, American, Asian, European and Oceania individuals, and moving towards further and more geographically restricted populations, powerful multivariate techniques such as Partial Least Squares-Discriminant Analysis (PLS-DA) and machine learning techniques such as XGBoost were employed, and their discriminating power was compared. PLS-DA method provided more robust classifications than XGBoost method, showing that the adopted approach might be an interesting tool for forensic experts to infer BGA information from the DNA profile of unknown individuals, but also highlighting that the commercial forensic panels could be inadequate to discriminate populations at intra-continental level.

Development and validation of a novel 133-plex forensic STR panel (52 STRs and 81 Y-STRs) using single-end 400 bp massive parallel sequencing

Short tandem repeats (STRs) are the preferred genetic markers in forensic DNA analysis, routinely measured by capillary electrophoresis (CE) method based on the fragment length features. While, the massive parallel sequencing (MPS) technology could simultaneously target a large number of intriguing forensic STRs, bypassing the intrinsic limitations of amplicon size separation and accessible fluorophores in CE, which is efficient and promising for enabling the identification of forensic biological evidence. Here, we developed a novel MPS-based Forensic Analysis System Multiplecues SetB Kit of 133-plex forensic STR markers (52 STRs and 81 Y-STRs) and one Y-InDel (M175) based on multiplex PCR and single-end 400 bp sequencing strategy. This panel was subjected to developmental validation studies according to the SWGDAM Validation Guidelines. Approximately 2185 MPS-based reactions using 6 human DNA standards and 8 male donors were conducted for substrate studies (filter paper, gauze, cotton swab, four different types of FTA cards, peripheral venous blood, saliva, and exfoliated cells), sensitivity studies (from 2 ng down to 0.0625 ng), mixture studies (two-person DNA mixtures), PCR inhibitor studies (seven commonly encountered PCR inhibitors), species specificity studies (11 non-human species), and repeatability studies. Results of concordance studies (413 Han males and 6 human DNA standards) generated by STRait Razor and in-house Python scripts indicated 99.98% concordance rate in STR calling relative to CE for STRs between 41,900 genotypes at 100 STR markers. Moreover, the limitations of present studies, the nomenclature rules and forensic MPS applications were also described. In conclusion, the validation studies based on ~ 2200 MPS-based and ~ 2500 CE-based DNA profiles demonstrated that the novel MPS-based panel meets forensic DNA quality assurance guidelines with robust, reliable, and reproducible performance on samples of various quantities and qualities, and the STR nomenclature rules should be further regulated to integrate the inconformity between MPS-based and CE-based methods.

Evaluation of a custom QIAseq targeted DNA panel with 164 ancestry informative markers sequenced with the Illumina MiSeq

Introduction of new methods requires meticulous evaluation before they can be applied to forensic genetic case work. Here, a custom QIAseq Targeted DNA panel with 164 ancestry informative markers was assessed using the MiSeq sequencing platform. Concordance, sensitivity, and the capability for analysis of mixtures were tested. The assay gave reproducible and nearly concordant results with an input of 10 and 2 ng DNA. Lower DNA input led to an increase in both locus and allele drop-outs, and a higher variation in heterozygote balance. Locus or allele drop-outs in the samples with less than 2 ng DNA input were not necessarily associated with the overall performance of a locus. Thus, the QIAseq assay will be difficult to implement in a forensic genetic setting where the sample material is often scarce and of poor quality. With equal or near equal mixture ratios, the mixture DNA profiles were easily identified by an increased number of imbalanced heterozygotes. For more skewed mixture ratios, the mixture DNA profiles were identified by an increased noise level. Lastly, individuals from Great Britain and the Middle East were investigated. The Middle Eastern individuals showed a greater affinity with South European populations compared to North European populations.