Development of a novel forensic STR multiplex for ancestry analysis and extended identity testing

Ancestry analysis using a self-developed 56 AIM-InDel loci and machine learning methods

Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in ancestry analysis. In this study, a self-developed panel consisting of 56 ancestry-informative InDels was used to investigate the genetic structures and genetic relationships between Chinese Inner Mongolia Manchu group and 26 reference populations. The Inner Mongolia Manchu group was closely related in genetic background to East Asian populations, especially the Han Chinese in Beijing. Moreover, populations from northern and southern East Asia displayed obvious variations in ancestral components, suggesting the potential value of this panel in distinguishing the populations from northern and southern East Asia. Subsequently, four machine learning models were performed based on the 56 AIM-InDel loci to evaluate the performance of this panel in ancestry prediction. The random forest model presented better performance in ancestry prediction, with 91.87% and 99.73% accuracy for the five and three continental populations, respectively. The individuals of the Inner Mongolia Manchu group were assigned to the East Asian populations by the random forest model, and they exhibited closer genetic affinities with northern East Asian populations. Furthermore, the random forest model distinguished 87.18% of the Inner Mongolia Manchus from the East Asian populations, suggesting that the random forest model based on the 56 ancestry-informative InDels could be a potential tool for ancestry analysis.

Ancestral Information Analysis of Chinese Korean Ethnic Group via a Novel Multiplex DIP System

Deletion/insertion polymorphism (DIP) is one of the more promising genetic markers in the field of forensic genetics for personal identification and biogeographic ancestry inference. In this research, we used an in-house developed ancestry-informative marker-DIP system, including 56 autosomal diallelic DIPs, three Y-chromosomal DIPs, and an Amelogenin gene, to analyze the genetic polymorphism and ancestral composition of the Chinese Korean group, as well as to explore its genetic relationships with the 26 reference populations. The results showed that this novel panel exhibited high genetic polymorphism in the studied Korean group and could be effectively applied for forensic individual identification in the Korean group. In addition, the results of multiple population genetic analyses indicated that the ancestral component of the Korean group was dominated by northern East Asia. Moreover, the Korean group was more closely related to the East Asian populations, especially to the Japanese population in Tokyo. This study enriched the genetic data of the Korean ethnic group in China and provided information on the ancestry of the Korean group from the perspective of population genetics.

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.

Could routine forensic STR genotyping data leak personal phenotypic information?

The application of forensic genetic markers must comply with privacy rights and legal policies on a premise that the markers do not expose phenotypic information. The most widely-used short tandem repeats (STRs) are generally viewed as 'junk' DNA because most STRs are located in non-coding regions and therefore refrain from leaking phenotypic traits. But with a deepening understanding of phenotypes and underlying genetic structure, whether STRs could potentially reflect any phenotypic information may need re-examining. Therefore, we performed the following analyses. First, we analyzed the association between 15 STRs and three facial characteristics (single or double eyelid, with or without epicanthus, unattached or attached earlobe) on 721 unrelated Han Chinese individuals. Then, we collected 27199 individuals' STRs and geographic data from the literature to investigate the association between STRs and bio-geographic information, and predict geographic information by STRs on additional 1993 unrelated individuals. We found that there was scarcely any association between STRs with studied facial characteristics. Although allele19 in D2S1338 and allele 18 in FGA (P = 0.0032, P = 0.0030, respectively after Bonferroni correction) showed statistical significance, the prediction effectiveness was very low. For the STRs and bio-geographic information, the principal component analysis showed the first three components could explain 87.7% of the variance, but the prediction accuracy only reached 25.2%. We demonstrated that the forensic phenotypes are usually complex traits, it is hardly possible to uncover phenotypic information by testing only dozens of STR loci.

The analysis of ancestry with small-scale forensic panels of genetic markers

In the last 10 years, forensic genetic analysis has been extended beyond identification tests that link a suspect to crime scene evidence using standard DNA profiling, to new supplementary tests that can provide information to investigators about a suspect in the absence of a database hit or eyewitness testimony. These tests now encompass the prediction of physical appearance, ancestry and age. In this review, we give a comprehensive overview of the full range of DNA-based ancestry inference tests designed to work with forensic contact traces, when the level of DNA is often very low or highly degraded. We outline recent developments in the design of ancestry-informative marker sets, forensic assays that use capillary electrophoresis or massively parallel sequencing, and the statistical analysis frameworks that examine the test profile and compares it to reference population variation. Three casework ancestry analysis examples are described which were successfully accomplished in the authors' laboratory, where the ancestry information obtained was critical to the outcome of the DNA analyses made.

Ancestry-informative marker (AIM) SNP panel for the Malay population

Ancestry-informative markers (AIMs) can be used to infer the ancestry of an individual to minimize the inaccuracy of self-reported ethnicity in biomedical research. In this study, we describe three methods for selecting AIM SNPs for the Malay population (Malay AIM panel) using different approaches based on pairwise F_ST, informativeness for assignment (I_n), and PCA-correlated SNPs (PCAIMs). These Malay AIM panels were extracted from genotype data stored in SNP arrays hosted by the Malaysian node of the Human Variome Project (MyHVP) and the Singapore Genome Variation Project (SGVP). In particular, genotype data from a total of 165 Malay individuals were analyzed, comprising data on 117 individual genotypes from the Affymetrix SNP-6 SNP array platform and data on 48 individual genotypes from the OMNI 2.5 Illumina SNP array platform. The HapMap phase 3 database (1397 individuals from 11 populations) was used as a reference for comparison with the Malay genotype data. The accuracy of each resulting Malay AIM panel was evaluated using a machine learning "ancestry-predictive model" constructed by using WEKA, a comprehensive machine learning platform written in Java. A total of 1250 SNPs were finally selected, which successfully identified Malay individuals from other world populations with an accuracy of 90%, but the accuracy decreased to 80% using 157 SNPs according to the pairwise F_ST method, while a panel of 200 SNPs selected using I_n and PCAIMs could be used to identify Malay individuals with an accuracy of approximately 80%.

Development and validation of a multiplex insertion/deletion marker panel, SifaInDel 45plex system

In addition to commonly used short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs), insertion and deletion polymorphisms (InDels) have considerable potential in the field of forensic genetics because they combine desirable characteristics of both STRs and SNPs. In the present study, the SifaInDel 45plex system was designed to amplify 45 InDel markers, including 27 autosomal InDels (A-InDels), 16 X chromosome InDels (X-InDels) and two Y chromosome InDels (Y-InDels), simultaneously in a single PCR procedure and then detect products by capillary electrophoresis (CE). We also optimized the PCR conditions for the novel panel and performed several validation studies including repeatability/reproducibility, concordance, accuracy, sensitivity, stability, species specificity and population genetics. The results confirmed that full profiles could be obtained from ≥62.5 pg of input DNA and from a series of challenging samples encountered in routine casework. The SifaInDel 45plex panel could tolerate different concentrations of inhibitors, such as ≤50 μM hematin, ≤20 ng/μL nigrosine and ≤8000 ng/μL urea. In a population investigation, for the 27 A-InDels, the combined power of discrimination (CPD) exceeded 0.999999, and the combined power of exclusion in duos (CPE_D) and trios (CPE_T) was 0.955118 and 0.997754, respectively. For the 16 X-InDels, the combined PD_Male and PD_Female was computed as 0.999845 and 0.999998, respectively, and the combined mean exclusion chance in father/daughter or mother/son duos (MEC_Duo) and mean exclusion chance in standard trios involving daughters (MEC_Trio) was 0.976220 and 0.998163, respectively. In addition, the two Y-InDels could play a role in correctly determining gender. Overall, the established SifaInDel 45plex panel is a well-performing, reliable and robust multiplex system that stands out for combining a considerable number of A-indels, X-indels and Y-indels based on a CE platform. The population study results also demonstrated that the SifaInDel 45plex panel could be a valid complementary approach for human identification and complex kinship analysis.

Developmental validation of the MiSeq FGx Forensic Genomics System for Targeted Next Generation Sequencing in Forensic DNA Casework and Database Laboratories

Human DNA profiling using PCR at polymorphic short tandem repeat (STR) loci followed by capillary electrophoresis (CE) size separation and length-based allele typing has been the standard in the forensic community for over 20 years. Over the last decade, Next-Generation Sequencing (NGS) matured rapidly, bringing modern advantages to forensic DNA analysis. The MiSeq FGx™ Forensic Genomics System, comprised of the ForenSeq™ DNA Signature Prep Kit, MiSeq FGx™ Reagent Kit, MiSeq FGx™ instrument and ForenSeq™ Universal Analysis Software, uses PCR to simultaneously amplify up to 231 forensic loci in a single multiplex reaction. Targeted loci include Amelogenin, 27 common, forensic autosomal STRs, 24 Y-STRs, 7 X-STRs and three classes of single nucleotide polymorphisms (SNPs). The ForenSeq™ kit includes two primer sets: Amelogenin, 58 STRs and 94 identity informative SNPs (iiSNPs) are amplified using DNA Primer Set A (DPMA; 153 loci); if a laboratory chooses to generate investigative leads using DNA Primer Set B, amplification is targeted to the 153 loci in DPMA plus 22 phenotypic informative (piSNPs) and 56 biogeographical ancestry SNPs (aiSNPs). High-resolution genotypes, including detection of intra-STR sequence variants, are semi-automatically generated with the ForenSeq™ software. This system was subjected to developmental validation studies according to the 2012 Revised SWGDAM Validation Guidelines. A two-step PCR first amplifies the target forensic STR and SNP loci (PCR1); unique, sample-specific indexed adapters or "barcodes" are attached in PCR2. Approximately 1736 ForenSeq™ reactions were analyzed. Studies include DNA substrate testing (cotton swabs, FTA cards, filter paper), species studies from a range of nonhuman organisms, DNA input sensitivity studies from 1ng down to 7.8pg, two-person human DNA mixture testing with three genotype combinations, stability analysis of partially degraded DNA, and effects of five commonly encountered PCR inhibitors. Calculations from ForenSeq™ STR and SNP repeatability and reproducibility studies (1ng template) indicate 100.0% accuracy of the MiSeq FGx™ System in allele calling relative to CE for STRs (1260 samples), and >99.1% accuracy relative to bead array typing for SNPs (1260 samples for iiSNPs, 310 samples for aiSNPs and piSNPs), with >99.0% and >97.8% precision, respectively. Call rates of >99.0% were observed for all STRs and SNPs amplified with both ForenSeq™ primer mixes. Limitations of the MiSeq FGx™ System are discussed. Results described here demonstrate that the MiSeq FGx™ System meets forensic DNA quality assurance guidelines with robust, reliable, and reproducible performance on samples of various quantities and qualities.

Multi-InDel Analysis for Ancestry Inference of Sub-Populations in China

Ancestry inference is of great interest in diverse areas of scientific researches, including the forensic biology, medical genetics and anthropology. Various methods have been published for distinguishing populations. However, few reports refer to sub-populations (like ethnic groups) within Asian populations for the limitation of markers. Several InDel loci located very tightly in physical positions were treated as one marker by us, which is multi-InDel. The multi-InDel shows potential as Ancestry Inference Marker (AIM). In this study, we performed a genome-wide scan for multi-InDels as AIM. After examining the F_ST distributions in the 1000 Genomes Database, 12 candidates were selected and validated for eastern Asian populations. A multiplexed assay was developed as a panel to genotype 12 multi-InDel markers simultaneously. Ancestry component analysis with STRUCTURE and principal component analysis (PCA) were employed to estimate its capability for ancestry inference. Furthermore, ancestry assignments of trial individuals were conducted. It proved to be very effective when 210 samples from Han and Tibetan individuals in China were tested. The panel consisting of multi-InDel markers exhibited considerable potency in ancestry inference, and was suggested to be applied in forensic practices and genetic population studies.

Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome

Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects' DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European-American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.

Inference of Ancestry in Forensic Analysis I: Autosomal Ancestry-Informative Marker Sets

An expanding choice of ancestry-informative marker single nucleotide polymorphisms (AIM-SNPs) is becoming available for the forensic user in the form of sensitive SNaPshot-based tests or in alternative single-base extension genotyping systems (e.g., Sequenom iPLEX) that can be adapted for analysis with SNaPshot. In addition, alternative ancestry-informative variation: Indels and STRs can be analyzed using direct PCR-to-CE techniques that offer the possibility to detect mixed profiles. We review the current forensically viable AIM panels, their optimized PCR multiplexes, and the population differentiation power they offer. We also describe how improved population divergence balance can be achieved with the enlarged multiplex scales of next-generation sequencing approaches to enable analysis of admixed individuals without biased estimation of co-ancestry proportions.

A minimum set of ancestry informative markers for determining admixture proportions in a mixed American population: the Brazilian set

The Brazilian population is considered to be highly admixed. The main contributing ancestral populations were European and African, with Amerindians contributing to a lesser extent. The aims of this study were to provide a resource for determining and quantifying individual continental ancestry using the smallest number of SNPs possible, thus allowing for a cost- and time-efficient strategy for genomic ancestry determination. We identified and validated a minimum set of 192 ancestry informative markers (AIMs) for the genetic ancestry determination of Brazilian populations. These markers were selected on the basis of their distribution throughout the human genome, and their capacity of being genotyped on widely available commercial platforms. We analyzed genotyping data from 6487 individuals belonging to three Brazilian cohorts. Estimates of individual admixture using this 192 AIM panels were highly correlated with estimates using ~370 000 genome-wide SNPs: 91%, 92%, and 74% of, respectively, African, European, and Native American ancestry components. Besides that, 192 AIMs are well distributed among populations from these ancestral continents, allowing greater freedom in future studies with this panel regarding the choice of reference populations. We also observed that genetic ancestry inferred by AIMs provides similar association results to the one obtained using ancestry inferred by genomic data (370 K SNPs) in a simple regression model with rs1426654, related to skin pigmentation, genotypes as dependent variable. In conclusion, these markers can be used to identify and accurately quantify ancestry of Latin Americans or US Hispanics/Latino individuals, in particular in the context of fine-mapping strategies that require the quantification of continental ancestry in thousands of individuals.

Differential nuclear and mitochondrial DNA preservation in post-mortem teeth with implications for forensic and ancient DNA studies

Major advances in genetic analysis of skeletal remains have been made over the last decade, primarily due to improvements in post-DNA-extraction techniques. Despite this, a key challenge for DNA analysis of skeletal remains is the limited yield of DNA recovered from these poorly preserved samples. Enhanced DNA recovery by improved sampling and extraction techniques would allow further advancements. However, little is known about the post-mortem kinetics of DNA degradation and whether the rate of degradation varies between nuclear and mitochondrial DNA or across different skeletal tissues. This knowledge, along with information regarding ante-mortem DNA distribution within skeletal elements, would inform sampling protocols facilitating development of improved extraction processes. Here we present a combined genetic and histological examination of DNA content and rates of DNA degradation in the different tooth tissues of 150 human molars over short-medium post-mortem intervals. DNA was extracted from coronal dentine, root dentine, cementum and pulp of 114 teeth via a silica column method and the remaining 36 teeth were examined histologically. Real time quantification assays based on two nuclear DNA fragments (67 bp and 156 bp) and one mitochondrial DNA fragment (77 bp) showed nuclear and mitochondrial DNA degraded exponentially, but at different rates, depending on post-mortem interval and soil temperature. In contrast to previous studies, we identified differential survival of nuclear and mtDNA in different tooth tissues. Futhermore histological examination showed pulp and dentine were rapidly affected by loss of structural integrity, and pulp was completely destroyed in a relatively short time period. Conversely, cementum showed little structural change over the same time period. Finally, we confirm that targeted sampling of cementum from teeth buried for up to 16 months can provide a reliable source of nuclear DNA for STR-based genotyping using standard extraction methods, without the need for specialised equipment or large-volume demineralisation steps.

Analysis of linkage and linkage disequilibrium for syntenic STRs on 12 chromosomes

The purpose of this study is to evaluate allelic association and linkage of 18 adjacent syntenic short tandem repeat (STR) pairs form out of 30 markers located on 12 different autosomes. Linkage disequilibrium was tested by using the unknown gametic phase genotypes and phased haplotypes from 290 unrelated individuals from Chinese Han population. Genetic linkage analysis between syntenic STRs was performed based on 145 two-generation families which involved 628 meioses. The results showed no significant linkage disequilibrium at any STR pairs and independent inheritance between syntenic STR pairs was indicated. Significant linkage (maximum logarithm of odd (LOD) scores >3.0) was found in 6 out of the 18 adjacent syntenic STR pairs (D1S1627-D1S1677, CSF1PO-D5S818, D6S1017-D6S1043, D6S1043-D6S474, D12S391-vWA, and D19S253-D19S433). These significant linkage marker pairs had a genetic distance ranged from 11.94 to 41.33 cM deduced from HapMap. When recombination fractions determined in families were compared to those derived from Kosambi mapping function based on HapMap data, the latter may have an overestimation. In summary, our results demonstrated that product rule included syntenic STRs can be used for unrelated individual profile probability and the recombination fraction based on family data was superior to the estimation from HapMap for kinship analysis.