Forensic evaluation of the Asia Pacific ancestry-informative MAPlex assay

DNA intelligence, and particularly the inference of biogeographical ancestry (BGA) is increasing in interest, and relevance within the forensic genetics community. The majority of current MPS-based forensic ancestry-informative assays focus on the differentiation of major global populations. The recently published MAPlex (Multiplex for the Asia Pacific) panel contains 144 SNPs and 20 microhaplotypes and aims to improve the differentiation of populations in the Asia Pacific region. This study reports the first forensic evaluation of the MAPlex panel using AmpliSeq technology and Ion S5 sequencing. This study reports on the overall performance of MAPlex including the assay’s sequence coverage distribution and stability, baseline noise and description of problematic SNPs. Dilution series, artificially degraded and mixed DNA samples were also analysed to evaluate the sensitivity of the panel with challenging or compromised forensic samples. As the first panel to combine biallelic SNPs, multiple-allele SNPs and microhaplotypes, the MAPlex assay demonstrated an enhanced capacity for mixture detection, not easily performed with common binary SNPs. This performance evaluation indicates that MAPlex is a robust, stable and highly sensitive assay that is applicable to forensic casework for the prediction of BGAMdlP is supported by a postdoctoral fellowship awarded by the Consellería de Cultura, Educación e Ordenación Universitaria and the Consellería de Economía, Emprego e Industria from Xunta de Galicia (Modalidade A, ED481B 2017/088). CP, AFA, AMM, MdlP, MVL are supported by MAPA, Multiple Allele Polymorphism Analysis (BIO2016-78525-R), a research project funded by the Spanish Research State Agency (AEI), and co-financed with ERDF funds. AFA is supported by a post-doctorate grant funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (Modalidade B, ED481B 2018/010). The 1000 Genomes high coverage sequence data were generated at the New York Genome Center with funds provided by NHGRI Grant 3UM1HG008901-03S1S

Epigenetic age estimation in saliva and in buccal cells

Age estimation based on epigenetic markers is a DNA intelligence tool with the potential to provide relevant information for criminal investigations, as well as to improve the inference of age-dependent physical characteristics such as male pattern baldness or hair color. Age prediction models have been developed based on different tissues, including saliva and buccal cells, which show different methylation patterns as they are composed of different cell populations. On many occasions in a criminal investigation, the origin of a sample or the proportion of tissues is not known with certainty, for example the provenance of cigarette butts, so use of combined models can provide lower prediction errors. In the present study, two tissue-specific and seven age-correlated CpG sites were selected from publicly available data from the Illumina HumanMethylation 450 BeadChip and bibliographic searches, to help build a tissue-dependent, and an age-prediction model, respectively. For the development of both models, a total of 184 samples (N = 91 saliva and N = 93 buccal cells) ranging from 21 to 86 years old were used. Validation of the models was performed using either k-fold cross-validation and an additional set of 184 samples (N = 93 saliva and N = 91 buccal cells, 21–86 years old). The tissue prediction model was developed using two CpG sites (HUNK and RUNX1) based on logistic regression that produced a correct classification rate for saliva and buccal swab samples of 88.59 % for the training set, and 83.69 % for the testing set. Despite these high success rates, a combined age prediction model was developed covering both saliva and buccal cells, using seven CpG sites (cg10501210, LHFPL4, ELOVL2, PDE4C, HOXC4, OTUD7A and EDARADD) based on multivariate quantile regression giving a median absolute error (MAE): ± 3.54 years and a correct classification rate ( %CP±PI) of 76.08 % for the training set, and an MAE of ± 3.66 years and a %CP±PI of 71.19 % for the testing set. The addition of tissue-of origin as a co-variate to the model was assessed, but no improvement was detected in age predictions. Finally, considering the limitations usually faced by forensic DNA analyses, the robustness of the model and the minimum recommended amount of input DNA for bisulfite conversion were evaluated, considering up to 10 ng of genomic DNA for reproducible results. The final multivariate quantile regression age predictor based on the models we developed has been placed in the open-access Snipper forensic classification websiteThis project was funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (Modalidade B, ED481B 2018/010) by a postdoctorate grant awarded to AFA. MVL is supported by the Ministerio de Educación, Cultura y Ciencia, Spain (PID2019-107876RB-I00).M.d.l.P. is supported by a post-doctorate grant funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (ED481D-2021-008). J.R. is supported by the “Programa de axudas á etapa predoutoral” funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (ED481A-2020/039)S

Development of the VISAGE enhanced tool and statistical models for epigenetic age estimation in blood, buccal cells and bones

DNA methylation is known as a biomarker for age with applications in forensics. Here we describe the VISAGE (VISible Attributes through GEnomics) Consortium’s enhanced tool for epigenetic age estimation in somatic tissues. The tool is based on eight DNA methylation markers (44 CpGs), bisulfite multiplex PCR followed by sequencing on the MiSeq FGx platform, and three statistical prediction models for blood, buccal cells and bones. The model for blood is based on six CpGs from ELOVL2, MIR29B2CHG, KLF14, FHL2, TRIM59 and PDE4C, and predicts age with a mean absolute error (MAE) of 3.2 years, while the model for buccal cells includes five CpGs from PDE4C, MIR29B2CHG, ELOVL2, KLF14 and EDARADD and predicts age with MAE of 3.7 years, and the model for bones has six CpGs from ELOVL2, KLF14, PDE4C and ASPA and predicts age with MAE of 3.4 years. The VISAGE enhanced tool for age estimation in somatic tissues enables reliable collection of DNA methylation data from small amounts of DNA using a sensitive multiplex MPS assay that provides accurate estimation of age in blood, buccal swabs, and bones using the statistical model tailored to each tissue

Development and evaluations of the ancestry informative markers of the VISAGE Enhanced Tool for Appearance and Ancestry

The VISAGE Enhanced Tool for Appearance and Ancestry (ET) has been designed to combine markers for the prediction of bio-geographical ancestry plus a range of externally visible characteristics into a single massively parallel sequencing (MPS) assay. We describe the development of the ancestry panel markers used in ET, and the enhanced analyses they provide compared to previous MPS-based forensic ancestry assays. As well as established autosomal single nucleotide polymorphisms (SNPs) that differentiate sub-Saharan African, European, East Asian, South Asian, Native American, and Oceanian populations, ET includes autosomal SNPs able to efficiently differentiate populations from Middle East regions [...]The study was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 740580 within the framework of the VISible Attributes through GEnomics (VISAGE) Project and Consortium. M.d.l.P. is supported by a post-doctorate grant funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (ED481D-2021–008). J.R. is supported by the “Programa de axudas á etapa predoutoral” funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (ED481A-2020/039). C.P., A.F.A., A.M.M., M.d.l.P., M.V.L. and the work to compile ancestry informative tri-allelic SNPs and microhaplotypes are supported by MAPA, ‘Multiple Allele Polymorphism Analysis’ (BIO2016–78525-R), a research project funded by the Spanish Research State Agency (AEI) and co-financed with ERDF funds. The population studies by S.O. at University of Santiago de Compostela, were financed by the Fundação de Apoio a Pesquisa do Distrito Federal (FAPDF), BrazilS

Impact of genetic ancestry on chronological age prediction using DNA methylation analysis

Several forensic age predictors based on DNA methylation have been developed, reporting a considerable number of CpG loci highly correlated with chronological age. Most of the published age prediction models so far were based on European samples, and therefore there is a need to explore additional worldwide populations. We performed a comprehensive analysis of methylation profiles from buccal mucosa samples of three independent population groups from Middle East, West Africa and Central Europe. For each population approx. 50 samples with an equal distribution of donor ages were collected. Using bisulfite pyrosequencing we analyzed the age dependent methylation changes at five CpG sites in the genes of ASPA, ITGA2B, PDE4C and ELOVL2 and predicted the donor ages using two previously reported age prediction models. Our results display significantly lower dispersions of methylations and thus errors of predicted ages in the Middle East population compared to the Central Europe and West African populations. Interestingly, the overall methylation variation was highly similar between the three populations at all investigated CpGs

Eurasiaplex-2: Shifting the focus to SNPs with high population specificity increases the power of forensic ancestry marker sets

To compile a new South Asian-informative panel of forensic ancestry SNPs, we changed the strategy for selecting the most powerful markers for this purpose by targeting polymorphisms with near absolute specificity – when the South Asian-informative allele identified is absent from all other populations or present at frequencies below 0.001 (one in a thousand). More than 120 candidate SNPs were identified from 1000 Genomes datasets satisfying an allele frequency screen of ≥ 0.1 (10 % or more) allele frequency in South Asians, and ≤ 0.001 (0.1 % or less) in African, East Asian, and European populations. From the candidate pool of markers, a final panel of 36 SNPs, widely distributed across most autosomes, were selected that had allele frequencies in the five 1000 Genomes South Asian populations ranging from 0.4 to 0.15. Slightly lower average allele frequencies, but consistent patterns of informativeness were observed in gnomAD South Asian datasets used to validate the 1000 Genomes variant annotations. We named the panel of 36 South Asian-specific SNPs Eurasiaplex-2, and the informativeness of the panel was evaluated by compiling worldwide population data from 4097 samples in four genome variation databases that largely complement the global sampling of 1000 Genomes. Consistent patterns of allele frequency distribution, which were specific to South Asia, were observed in all populations in, or closely sited to, the Indian sub-continent. Pakistani populations from the HGDP-CEPH panel had markedly lower allele frequencies, highlighting the need to develop a statistical system to evaluate the ancestry inference value of counting the number of population-specific alleles present in an individualM.d.l.P. is supported by a post-doctorate grant funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (ED481D-2021-008). J.R. is supported by the “Programa de axudas á etapa predoutoral” funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (ED481A-2020-039)S

Dog breed affiliation with a forensically validated canine STR set

We tested a panel of 13 highly polymorphic canine short tandem repeat (STR) markers for dog breed assignment using 392 dog samples from the 23 most popular breeds in Austria, Germany, and Switzerland. This STR panel had originally been selected for canine identification. The dog breeds sampled in this study featured a population frequency ≥1% and accounted for nearly 57% of the entire pedigree dog population in these three countries. Breed selection was based on a survey comprising records for nearly 1.9 million purebred dogs belonging to more than 500 different breeds. To derive breed membership from STR genotypes, a range of algorithms were used. These methods included discriminant analysis of principal components (DAPC), STRUCTURE, GeneClass2, and the adegenet package for R. STRUCTURE analyses suggested 21 distinct genetic clusters. Differentiation between most breeds was clearly discernable. Fourteen of 23 breeds (61%) exhibited maximum mean cluster membership proportions of more than 0.70 with a highest value of 0.90 found for Cavalier King Charles Spaniels. Dogs of only 6 breeds (26%) failed to consistently show only one major cluster. The DAPC method yielded the best assignment results in all 23 declared breeds with 97.5% assignment success. The frequency-based assignment test also provided a high success rate of 87%. These results indicate the potential viability of dog breed prediction using a well-established and sensitive set of 13 canine STR markers intended for forensic routine use