The Chromatin Organization Close to SNP rs12913832, Involved in Eye Color Variation, Is Evolutionary Conserved in Vertebrates.

The most significant genetic influence on eye color pigmentation is attributed to the intronic SNP rs12913832 in the HERC2 gene, which interacts with the promoter region of the contiguous OCA2 gene. This interaction, through the formation of a chromatin loop, modulates the transcriptional activity of OCA2, directly affecting eye color pigmentation. Recent advancements in technology have elucidated the precise spatial organization of the genome within the cell nucleus, with chromatin architecture playing a pivotal role in regulating various genome functions. In this study, we investigated the organization of the chromatin close to the HERC2/OCA2 locus in human lymphocyte nuclei using fluorescence in situ hybridization (FISH) and high-throughput chromosome conformation capture (Hi-C) data. The 3 Mb of genomic DNA that belonged to the chromosomal region 15q12-q13.1 revealed the presence of three contiguous chromatin loops, which exhibited a different level of compaction depending on the presence of the A or G allele in the SNP rs12913832. Moreover, the analysis of the genomic organization of the genes has demonstrated that this chromosomal region is evolutionarily highly conserved, as evidenced by the analysis of syntenic regions in species from other Vertebrate classes. Thus, the role of rs12913832 variant is relevant not only in determining the transcriptional activation of the OCA2 gene but also in the chromatin compaction of a larger region, underscoring the critical role of chromatin organization in the proper regulation of the involved genes. It is crucial to consider the broader implications of this finding, especially regarding the potential regulatory role of similar polymorphisms located within intronic regions, which do not influence the same gene by modulating the splicing process, but they regulate the expression of adjacent genes. Therefore, caution should be exercised when utilizing whole-exome sequencing for diagnostic purposes, as intron sequences may provide valuable gene regulation information on the region where they reside. Thus, future research efforts should also be directed towards gaining a deeper understanding of the precise mechanisms underlying the role and mode of action of intronic SNPs in chromatin loop organization and transcriptional regulation.

Skin pigmentation and genetic variants in an admixed Brazilian population of primarily European ancestry.

Although many genes have been shown to be associated with human pigmentary traits and forensic prediction assays exist (e.g. HIrisPlex-S), the genetic knowledge about skin colour remains incomplete. The highly admixed Brazilian population is an interesting study population for investigation of the complex genotype-phenotype architecture of human skin colour because of its large variation. Here, we compared variants in 22 pigmentary genes with quantitative skin pigmentation levels on the buttock, arm, and forehead areas of 266 genetically admixed Brazilian individuals. The genetic ancestry of each individual was estimated by typing 46 AIM-InDels. The mean proportion of genetic ancestry was 68.8% European, 20.8% Sub-Saharan African, and 10.4% Native American. A high correlation (adjusted R2 = 0.65, p < 0.05) was observed between nine SNPs and quantitative skin pigmentation using multiple linear regression analysis. The correlations were notably smaller between skin pigmentation and biogeographic ancestry (adjusted R2 = 0.45, p < 0.05), or markers in the leading forensic skin colour prediction system, the HIrisPlex-S (adjusted R2 = 0.54, p < 0.05). Four of the nine SNPs, OCA2 rs1448484 (rank 2), APBA2 rs4424881 (rank 4), MFSD12 rs10424065 (rank 8), and TYRP1 1408799 (rank 9) were not investigated as part of the HIrisPlex-S selection process, and therefore not included in the HIrisPlex-S model. Our results indicate that these SNPs account for a substantial part of the skin colour variation in individuals of admixed ancestry. Hence, we suggest that these SNPs are considered when developing future skin colour prediction models.

Ethical, legal and social implications of forensic molecular phenotyping in South Africa.

Conventional forensic DNA analysis involves a matching principle, which compares DNA profiles from evidential samples to those from reference samples of known origin. In casework, however, the accessibility to a reference sample is not guaranteed which limits the use of DNA as an investigative tool. This has led to the development of phenotype prediction, which uses SNP analysis to estimate the physical appearance of the sample donor. Physical traits, such as eye, hair and skin colour, have been associated with certain alleles within specific genes involved in the melanogenesis pathways. These genetic markers are also associated with ancestry and their trait prediction ability has mainly been assessed in European and North American populations. This has prompted research investigating the discriminatory power of these markers in other populations, especially those exhibiting admixture. South Africa is well known for its diversity, and the viability of these particular SNPs still needs to be assessed within this population. South African law currently restricts the use of DNA for molecular phenotyping, and there are also numerous ethical and social considerations, all of which are discussed.

Operationalisation of the ForenSeq® Kintelligence Kit for Australian unidentified and missing persons casework.

Single nucleotide polymorphism (SNP) genotyping technologies can generate investigative leads for human remains identification, including estimation of biological sex, biogeographical ancestry (BGA), externally visible characteristics (EVCs), identity, uniparental lineage and extended kinship. The ForenSeq® Kintelligence Kit provides forensic laboratories with the ability to apply this suite of genetic tools to forensic samples using one panel targeting 10,230 SNPs (including 56 ancestry-informative, 24 phenotype-informative, 94 identity-informative, 106 X chromosome, 85 Y chromosome and 9867 kinship-informative SNPs) sequenced on the MiSeq FGx® Sequencing System. The ForenSeq® Kintelligence Kit has been internally validated, optimised and operationalised by the Australian Federal Police National DNA Program for Unidentified and Missing Persons (AFP Program) for coronial casework. The internal validation was conducted according to the Scientific Working Group on DNA Analysis Methods guidelines (excluding mixture analysis), focussing on sample types typically encountered in human remains identification casework, such as bones, teeth, nail, blood and hair. The workflow was optimised for a high throughput library preparation and sequencing workflow, and additional analytical thresholds were developed to improve genotyping accuracy for low DNA input samples. Additionally, the genetic intelligence generated from the kit was compared to the self-declared biological sex, EVCs and BGA of the DNA donors to assess concordance. The kit was able to produce high quality SNP profiles from 1.0 ng down to 0.1 ng of DNA, with high repeatability and reproducibility, and minimal background noise. The prediction accuracy for biological sex (95%), hair colour (58%), eye colour (74%) and BGA inferences (consistent: 74%; partially consistent: 10%; inconclusive: 16%) was determined based on self-declared data. Additionally, SNP profiles from a volunteer family group of ten related individuals were uploaded to GEDmatch PRO™ to assess kinship accuracy. The kit was capable of detecting (97%) and accurately classifying (90%) genetic relationships spanning from first to fifth degree. The Kintelligence Kit provides the AFP Program with a robust and reliable genetic intelligence tool for unidentified and missing persons investigations, which has been designed to sequence multiple challenging samples in a single multiplexed assay using existing laboratory instrumentation.

Forensic prediction of sex, age, height, body mass index, hip-to-waist ratio, smoking status and lipid lowering drugs using epigenetic markers and plasma proteins.

The prediction of human characteristics from blood using molecular markers would be very helpful in forensic science. Such information can be particularly important in providing investigative leads in police casework from, for example, blood found at crime scenes in cases without a suspect. Here, we investigated the possibilities and limitations of predicting seven phenotypic traits (sex, age, height, body mass index [BMI], hip-to-waist [WTH] ratio, smoking status and lipid-lowering drug use) using either DNA methylation or plasma proteins separately or in combination. We developed a prediction pipeline starting with the prediction of sex followed by sex-specific, stepwise, individual age, sex-specific anthropometric traits and, finally, lifestyle-related traits. Our data revealed that age, sex and smoking status can be accurately predicted from DNA methylation alone, while the use of plasma proteins was highly accurate for prediction of the WTH ratio, and a combined analysis of the best predictions for BMI and lipid-lowering drug use. In unseen individuals, age was predicted with a standard error of 3.3 years for women and 6.5 years for men, while the accuracy in smoking prediction across both men and women was 0.86. In conclusion, we have developed a stepwise approach for the de-novo prediction of individual characteristics from plasma proteins and DNA methylation markers. These models are accurate and may provide valuable information and investigative leads in future forensic casework.

Additional predictions for forensic DNA phenotyping of externally visible characteristics using the ForenSeq and Imagen kits.

Multiplex DNA typing methods using massively parallel sequencing can be used to predict externally visible characteristics (EVCs) in forensic DNA phenotyping through the analysis of single-nucleotide polymorphisms. The focus of EVC determination has focused on hair color, eye color, and skin tone as well as visible biogeographical ancestry features. In this study, we researched off-label applications beyond what is currently marketed by the manufacturer of the Verogen ForenSeq kit primer set B and Imagen primer set E SNP loci. We investigated additional EVC predictions by examining published genome wide sequencing studies and reported allele-specific gene expression and predictive values. We have identified 15 SNPs included in the ForenSeq kit panel and Imagen kits that have additional EVC prediction capabilities beyond what is published in the Verogen manuals. The additional EVCs that can be predicted include hair graying, ephelides hyperpigmented spots, dermatoheliosis, facial pigmented spots, standing height, pattern balding, helix-rolling ear morphology, hair shape, hair thickness, facial morphology, eyebrow thickness, sarcoidosis, obesity, vitiligo, and tanning propensity. The loci can be used to augment and refine phenotype predictions with software such as MetaHuman for missing persons, cold case, and historic case investigations.

Forensic DNA Phenotyping: Genes and Genetic Variants for Eye Color Prediction.

In recent decades, the use of genetic polymorphisms related to specific phenotypes, such as eye color, has greatly contributed to the development of the research field called forensic DNA phenotyping (FDP), enabling the investigators of crime cases to reduce the number of suspects, making their work faster and more precise. Eye color is a polygenic phenotype, and many genetic variants have been highlighted, with the major contributor being the HERC2-OCA2 locus, where many single nucleotide variations (SNPs) were identified. Interestingly, the HERC2-OCA2 locus, containing the intronic SNP rs12913832, the major eye color determinant, shows a high level of evolutionary conservation across many species of vertebrates. Currently, there are some genetic panels to predict eye color by genomic DNA analysis, even if the exact role of the SNP variants in the formation of eye color is still poorly understood, with a low level of predictivity in the so-called intermediate eye color. Many variants in OCA2, HERC2, and other genes lie in introns or correspond to synonymous variants, highlighting greater complexity in the mechanism of action of such genes than a simple missense variation. Here, we show the main genes involved in oculocutaneous pigmentation and their structural and functional features, as well as which genetic variants show the highest level of eye color predictivity in currently used FDP assays. Despite the great recent advances and impact of FDP in criminal cases, it is necessary to enhance scientific research to better understand the mechanism of action behind each genetic variant involved in eye color, with the goal of obtaining higher levels of prediction.

Forensic DNA phenotyping: Inferring phenotypic traits from crime scene DNA.

INTRODUCTION: Forensic DNA Phenotyping (FDP) has provided better understanding of various phenotypic features (e.g., height, skin colour, eye colour, structure and shape of scalp hair, baldness, facial features etc.) and associated genetic variations. The current study was designed to investigate the genetic variants and their potential contribution towards accurate phenotype prediction systems. Short Tandem Repeat (STR) based DNA typing method can be uninformative or with little potential to solve a crime in absence of suspect DNA profile in the database. Forensic DNA Phenotyping (FDP), prediction of externally visible characteristics (EVCs) from the crime scene DNA would certainly provide a new dimension to personal identification. The aim of this review paper is to highlight the significance and future prospects of FDP. RESULTS: A comprehensive literature review was conducted using PubMed and similar e-databases with keywords from two main components-phenotype and the associated genetic variants. To ensure a thorough literature review, searches were extended using the snowballing technique from reference lists. Key data extracted were type of study, sample characteristics (sample size, age, geographical location and ancestry), details of SNPs studied and prediction accuracies. CONCLUSION: Phenotyping tools based on genotyping and statistical analysis for the prediction of human pigmentation are propitious in solving cold cases. This indicates the inevitability of future studies for the identification of new genetic markers for accurate prediction of phenotype or EVCs via genome-wide association study (GWAS) in diverse global populations.

Haplotype distribution in a forensic full mtDNA genome database of admixed Southern Brazilians and its association with self-declared ancestry and pigmentation traits.

BACKGROUND: The advent of massively parallel sequencing (MPS) applications focused on the generation of forensic-quality full mitochondrial genome sequences led to a popularization of the technique on a global scale. However, the lack of forensic-graded population databases has refrained a wider adoption of full genome sequences as the industry standard, despite its better discrimination capacity of individual maternal lineages. PURPOSE: This work describes a forensic-oriented full mtDNA genome database comprised of 480 samples from a Southern Brazilian population. METHODS: A collection of mitochondrial sequences were obtained from low-pass, full genome DNA sequencing results. The complete sample set was evaluated regarding haplotype composition and distribution. Summary statistics and forensic parameters were calculated and are presented for the database, with detailed information concerning the impact of removing genetic information in the form of specific variants or increasingly larger genomic regions. Interpopulational analysis comparing haplotypical diversity in Brazilian and 26 worldwide populations was also performed. The association between mitochondrial genetic variability and phenotypic diversity was also evaluated in populations, with self-declared ancestry and three distinct phenotypic pigmentation traits (eyes, skin and hair colors) as parameters. RESULTS: The presented database can be used to evaluate mitochondrial-related genetic evidence, providing LR values of up to 20,465 for unobserved haplotypes. Haplotype distribution in Southern Brazil seems to be different than the remaining of the country, with a larger contribution of maternal lines with European origin. Despite association can be found between lighter and darker phenotypes or self-declared ancestry and haplotype distribution, prediction models cannot be reliably proposed due to the admixed nature of the Brazilian population. CONCLUSIONS: The proposed database provides a basis for statistical calculation and frequency estimation of full mitochondrial genomes, and can be part of an integrated, representative, national database comprising most of the genetic diversity of maternal lineages in the country.

Forensic genetics through the lens of Lewontin: population structure, ancestry and race.

In his famous 1972 paper, Richard Lewontin used 'classical' protein-based markers to show that greater than 85% of human genetic diversity was contained within, rather than between, populations. At that time, these same markers also formed the basis of forensic technology aiming to identify individuals. This review describes the evolution of forensic genetic methods into DNA profiling, and how the field has accounted for the apportionment of genetic diversity in considering the weight of forensic evidence. When investigative databases fail to provide a match to a crime-scene profile, specific markers can be used to seek intelligence about a suspect: these include inferences on population of origin (biogeographic ancestry) and externally visible characteristics, chiefly pigmentation of skin, hair and eyes. In this endeavour, ancestry and phenotypic variation are closely entangled. The markers used show patterns of inter- and intrapopulation diversity that are very atypical compared to the genome as a whole, and reinforce an apparent link between ancestry and racial divergence that is not systematically present otherwise. Despite the legacy of Lewontin's result, therefore, in a major area in which genetics coincides with issues of public interest, methods tend to exaggerate human differences and could thereby contribute to the reification of biological race. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Analysis of Skin Pigmentation and Genetic Ancestry in Three Subpopulations from Pakistan: Punjabi, Pashtun, and Baloch.

Skin pigmentation is one of the most prominent and variable phenotypes in humans. We compared the alleles of 163 SNPs and indels from the Human Pigmentation (HuPi) AmpliSeq™ Custom panel, and biogeographic ancestry with the quantitative skin pigmentation levels on the upper arm, lower arm, and forehead of 299 Pakistani individuals from three subpopulations: Baloch, Pashtun, and Punjabi. The biogeographic ancestry of each individual was estimated using the Precision ID Ancestry Panel. All individuals were mainly of mixed South-Central Asian and European ancestry. However, the Baloch individuals also had an average proportion of Sub-Saharan African ancestry of approximately 10%, whereas it was <1% in the Punjabi and Pashtun individuals. The pairwise genetic distances between the Pashtun, Punjabi, and Baloch subpopulations based on the ancestry markers were statistically significantly different. Individuals from the Pashtun subpopulation had statistically significantly lower skin pigmentation than individuals from the Punjabi and Baloch subpopulations (p < 0.05). The proportions of European and Sub-Saharan African ancestry and five SNPs (rs1042602, rs10831496, rs1426654, rs16891982, and rs12913832) were statistically significantly associated with skin pigmentation at either the upper arm, lower arm or forehead in the Pakistani population after correction for multiple testing (p < 10-3). A model based on four of these SNPs (rs1426654, rs1042602, rs16891982, and rs12913832) explained 33% of the upper arm skin pigmentation. The four SNPs and the proportions of European and Sub-Saharan African ancestry explained 37% of the upper arm skin pigmentation. Our results indicate that the four likely causative SNPs, rs1426654, rs1042602, rs16891982, and rs12913832 located in SLC24A5, TYR, SLC45A2, and HERC2, respectively, are essential for skin color variation in the admixed Pakistani subpopulations.

Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits.

The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction performance in Bayesian models for eye, hair and skin color as well as hair structure and freckles in comparison to the respective prior-free models. Those prior-free models were either similarly defined either very close to the already established ones by using a reduced predictive marker set. However, these differences in the number of the predictive markers should not affect significantly our main outcomes. We observed that such priors often had a strong effect on the prediction performance, but to varying degrees between different traits and also different trait categories, with some categories barely showing an effect. While we found potential for improving the prediction accuracy of many of the appearance trait categories tested by using priors, our analyses also showed that misspecification of those prior values often severely diminished the accuracy compared to the respective prior-free approach. This emphasizes the importance of accurate specification of prevalence-informed priors in Bayesian prediction modeling of appearance traits. However, the existing literature knowledge on spatial prevalence is sparse for most appearance traits, including those investigated here. Due to the limitations in appearance trait prevalence knowledge, our results render the use of trait prevalence-informed priors in DNA-based appearance trait prediction currently infeasible.

Evaluation of supervised machine-learning methods for predicting appearance traits from DNA.

The prediction of human externally visible characteristics (EVCs) based solely on DNA information has become an established approach in forensic and anthropological genetics in recent years. While for a large set of EVCs, predictive models have already been established using multinomial logistic regression (MLR), the prediction performances of other possible classification methods have not been thoroughly investigated thus far. Motivated by the question to identify a potential classifier that outperforms these specific trait models, we conducted a systematic comparison between the widely used MLR and three popular machine learning (ML) classifiers, namely support vector machines (SVM), random forest (RF) and artificial neural networks (ANN), that have shown good performance outside EVC prediction. As examples, we used eye, hair and skin color categories as phenotypes and genotypes based on the previously established IrisPlex, HIrisPlex, and HIrisPlex-S DNA markers. We compared and assessed the performances of each of the four methods, complemented by detailed hyperparameter tuning that was applied to some of the methods in order to maximize their performance. Overall, we observed that all four classification methods showed rather similar performance, with no method being substantially superior to the others for any of the traits, although performances varied slightly across the different traits and more so across the trait categories. Hence, based on our findings, none of the ML methods applied here provide any advantage on appearance prediction, at least when it comes to the categorical pigmentation traits and the selected DNA markers used here.

A New Robust Epigenetic Model for Forensic Age Prediction.

Forensic DNA phenotyping refers to an emerging field of forensic sciences aimed at the prediction of externally visible characteristics of unknown sample donors directly from biological materials. The aging process significantly affects most of the above characteristics making the development of a reliable method of age prediction very important. Today, the so-called "epigenetic clocks" represent the most accurate models for age prediction. Since they are technically not achievable in a typical forensic laboratory, forensic DNA technology has triggered efforts toward the simplification of these models. The present study aimed to build an epigenetic clock using a set of methylation markers of five different genes in a sample of the Italian population of different ages covering the whole span of adult life. In a sample of 330 subjects, 42 selected markers were analyzed with a machine learning approach for building a prediction model for age prediction. A ridge linear regression model including eight of the proposed markers was identified as the best performing model across a plethora of candidates. This model was tested on an independent sample of 83 subjects providing a median error of 4.5 years. In the present study, an epigenetic model for age prediction was validated in a sample of the Italian population. However, its applicability to advanced ages still represents the main limitation in forensic caseworks.

Eye color prediction using single nucleotide polymorphisms in Saudi population.

BACKGROUND: DNA prediction of eye color represent one application of the externally visible characteristics (EVC), which attained growing interest in the field of DNA forensic phenotyping. This is mainly due to its ability to narrow the pool of suspects without the need to compare any retrieved DNA material from the crime scene to a reference DNA. Several methods and multiplex genetic panel were proposed with variable prediction accuracy between different populations. However, such panel was not previously tested in the Saudi population, nor any populations of the Middle East and North Africa origin. METHOD: A panel of eleven single nucleotide polymorphisms (SNPs) was tested for their association with three eye colors (brown, hazel, and intermediate) in 80 volunteer Saudi individuals. SNPs and haplotype association test with eye colors were performed to identify the top significant SNPs with the three eye colors. Also, multinomial logistic regression was used to construct the prediction model using a training set of 60 subjects, and a validation set of 20 subjects. The goodness of fit parameter of the model to correctly predicts each eye color as compared to the other was performed. RESULTS: Eye color was significantly associated with rs12913832, rs7170852, and rs916977 that are located within HERC2. SNP rs12913832 was the top significant SNP (p-value = 1.78E-15) that accounted for the association in this region, as the other SNPs were not significant after adjusting for rs12913832. A prediction model containing five SNPs showed high prediction accuracy with Area Under the receiver operating characteristic Curves (AUC) equals to 0.95 and 0.83 for brown and intermediate eye colors, respectively. However, the model's performance was very low for predicting the hazel eye color with AUC equals 0.75. DISCUSSION: Despite the small sample size of our study, we reported very significant SNP associations with eye color. Our model to predict eye colors based on DNA material showed high accuracy for brown and intermediate eye colors. The eye color prediction-model underperformed for the hazel eye colors, suggesting that larger sample size, as well as more comprehensive set of SNPs, could improve the model-prediction accuracy.

DNA-based predictive models for the presence of freckles.

Freckles or ephelides are hyperpigmented spots observed on skin surface mainly in European and Asian populations. Easy recognition and external visibility make prediction of ephelides, the potentially useful target in the field of forensic DNA phenotyping. Prediction of freckles would be a step forward in sketching the physical appearance of unknown perpetrators or decomposed cadavers for the forensic DNA intelligence purposes. Freckles are especially common in people with pale skin and red hair and therefore it is expected that predisposition to freckles may partially share the genetic background with other pigmentation traits. The first proposed freckle prediction model was developed based on investigation that involved variation of MC1R and 8 SNPs from 7 genes in a Spanish cohort [19]. In this study we examined 113 DNA variants from 46 genes previously associated with human pigmentation traits and assessed their impact on freckles presence in a group of 960 individuals from Poland. Nineteen DNA variants revealed associations with the freckle phenotype and the study also revealed that females have ∼1.8 higher odds of freckles presence comparing to males (p-value = 9.5 × 10-5). Two alternative prediction models were developed using regression methods. A simplified binomial 12-variable model predicts the presence of ephelides with cross-validated AUC = 0.752. A multinomial 14-variable model predicts one of three categories - non-freckled, medium freckled and heavily freckled. The two extreme categories, non-freckled and heavily freckled were predicted with moderately high accuracy of cross-validated AUC = 0.754 and 0.792, respectively. Prediction accuracy of the intermediate category was lower, AUC = 0.657. The study presents novel DNA models for prediction of freckles that can be used in forensic investigations and emphasizes significance of pigmentation genes and sex in predictive DNA analysis of freckles.

True colors: A literature review on the spatial distribution of eye and hair pigmentation.

DNA-based prediction of externally visible characteristics has become an established approach in forensic genetics, with the aim of tracing individuals who are potentially unknown to the investigating authorities but without using this prediction as evidence in court. While a number of prediction models have been proposed, use of prior probabilities in those models has largely been absent. Here, we aim at compiling information on the spatial distribution of eye and hair coloration in order to use this as prior knowledge to improve prediction accuracy. To this end, we conducted a detailed literature review and created maps showing the eye and hair pigmentation prevalence both by countries with available information and by interpolation in order to obtain prior estimates for populations without available data. Furthermore, we assessed the association between these two traits in a very large data set. A strong limitation was the quite low amount of available data, especially outside Europe. We hope that our results will facilitate the improvement of already existing and of novel prediction methods for pigmentation traits and induce further studies on the spatial distribution of these traits.

Forensic DNA phenotyping: Developing a model privacy impact assessment.

Forensic scientists around the world are adopting new technology platforms capable of efficiently analysing a larger proportion of the human genome. Undertaking this analysis could provide significant operational benefits, particularly in giving investigators more information about the donor of genetic material, a particularly useful investigative lead. Such information could include predicting externally visible characteristics such as eye and hair colour, as well as biogeographical ancestry. This article looks at the adoption of this new technology from a privacy perspective, using this to inform and critique the application of a Privacy Impact Assessment to this emerging technology. Noting the benefits and limitations, the article develops a number of themes that would influence a model Privacy Impact Assessment as a contextual framework for forensic laboratories and law enforcement agencies considering implementing forensic DNA phenotyping for operational use.

Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA.

Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.