Genomic insights on the ethno-history of the Maya and the 'Ladinos' from Guatemala.

BACKGROUND: Guatemala is a multiethnic and multilingual country located in Central America. The main population groups separate 'Ladinos' (mixed Native American-African-Spanish), and Native indigenous people of Maya descent. Among the present-day Guatemalan Maya, there are more than 20 different ethnic groups separated by different languages and cultures. Genetic variation of these communities still remains largely unexplored. The principal aim of this study is to explore the genetic variability of the Maya and 'Ladinos' from Guatemala by means of uniparental and ancestry informative markers (AIMs). RESULTS: Analyses of uniparental genetic markers indicate that Maya have a dominant Native American ancestry (mitochondrial DNA [mtDNA]: 100%; Y-chromosome: 94%). 'Ladino', however, show a clear gender-bias as indicated by the large European ancestry observed in the Y-chromosome (75%) compared to the mtDNA (0%). Autosomal polymorphisms (AIMS) also mirror this marked gender-bias: (i) Native American ancestry: 92% for the Maya vs. 55% for the 'Ladino', and (ii) European ancestry: 8% for the Maya vs. 41% for the 'Ladino'. In addition, the impact of the Trans-Atlantic slave trade on the present-day Guatemalan population is very low (and only occurs in the 'Ladino'; mtDNA: 9%; AIMS: 4%), in part mirroring the fact that Guatemala has a predominant orientation to the Pacific Ocean instead of a Caribbean one. Sequencing of entire Guatemalan mitogenomes has led to improved Native American phylogeny via the addition of new haplogroups that are mainly observed in Mesoamerica and/or the North of South America. CONCLUSIONS: The data reveal the existence of a fluid gene flow in the Mesoamerican area and a predominant unidirectional flow towards South America, most likely occurring during the Pre-Classic (1800 BC-200 AD) and the Classic (200-1000 AD) Eras of the Mesoamerican chronology, coinciding with development of the most distinctive and advanced Mesoamerican civilization, the Maya. Phylogenetic features of mtDNA data also suggest a demographic scenario that is compatible with moderate local endogamy and isolation in the Maya combined with episodes of gene exchange between ethnic groups, suggesting an ethno-genesis in the Guatemalan Maya that is recent and supported on a cultural rather than a biological basis.

Exploration of SNP variants affecting hair colour prediction in Europeans.

DNA profiling is a key tool for forensic analysis; however, current methods identify a suspect either by direct comparison or from DNA database searches. In cases with unidentified suspects, prediction of visible physical traits e.g. pigmentation or hair distribution of the DNA donors can provide important probative information. This study aimed to explore single nucleotide polymorphism (SNP) variants for their effect on hair colour prediction. A discovery panel of 63 SNPs consisting of already established hair colour markers from the HIrisPlex hair colour phenotyping assay as well as additional markers for which associations to human pigmentation traits were previously identified was used to develop multiplex assays based on SNaPshot single-base extension technology. A genotyping study was performed on a range of European populations (n = 605). Hair colour phenotyping was accomplished by matching donor's hair to a graded colour category system of reference shades and photography. Since multiple SNPs in combination contribute in varying degrees to hair colour predictability in Europeans, we aimed to compile a compact marker set that could provide a reliable hair colour inference from the fewest SNPs. The predictive approach developed uses a naïve Bayes classifier to provide hair colour assignment probabilities for the SNP profiles of the key SNPs and was embedded into the Snipper online SNP classifier ( http://mathgene.usc.es/snipper/ ). Results indicate that red, blond, brown and black hair colours are predictable with informative probabilities in a high proportion of cases. Our study resulted in the identification of 12 most strongly associated SNPs to hair pigmentation variation in six genes.

Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness.

Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans.

DNA-based prediction of hair morphology, defined as straight, curly or wavy hair, could contribute to an improved description of an unknown offender and allow more accurate forensic reconstructions of physical appearance in the field of forensic DNA phenotyping. Differences in scalp hair morphology are significant at the worldwide scale and within Europe. The only genome-wide association study made to date revealed the Trichohyalin gene (TCHH) to be significantly associated with hair morphology in Europeans and reported weaker associations for WNT10A and FRAS1 genes. We conducted a study that centered on six SNPs located in these three genes with a sample of 528 individuals from Poland. The predictive capacity of the candidate DNA variants was evaluated using logistic regression; classification and regression trees; and neural networks, by applying a 10-fold cross validation procedure. Additionally, an independent test set of 142 males from six European populations was used to verify performance of the developed prediction models. Our study confirmed association of rs11803731 (TCHH), rs7349332 (WNT10A) and rs1268789 (FRAS1) SNPs with hair morphology. The combined genotype risk score for straight hair had an odds ratio of 2.7 and these predictors explained ∼ 8.2% of the total variance. The selected three SNPs were found to predict straight hair with a high sensitivity but low specificity when a 10-fold cross validation procedure was applied and the best results were obtained using the neural networks approach (AUC=0.688, sensitivity=91.2%, specificity=23.0%). Application of the neural networks model with 65% probability threshold on an additional test set gave high sensitivity (81.4%) and improved specificity (50.0%) with a total of 78.7% correct calls, but a high non-classification rate (66.9%). The combined TTGGGG SNP genotype for rs11803731, rs7349332, rs1268789 (European frequency=4.5%) of all six straight hair-associated alleles was identified as the best predictor, giving >80% probability of straight hair. Finally, association testing of 44 SNPs previously identified to be associated with male pattern baldness revealed a suggestive association with hair morphology for rs4679955 on 3q25.1. The study results reported provide the starting point for the development of a predictive test for hair morphology in Europeans. More studies are now needed to discover additional determinants of hair morphology to improve the predictive accuracy of this trait in forensic analysis.

Development of a forensic skin colour predictive test.

There is growing interest in skin colour prediction in the forensic field. However, a lack of consensus approaches for recording skin colour phenotype plus the complicating factors of epistatic effects, environmental influences such as exposure to the sun and unidentified genetic variants, present difficulties for the development of a forensic skin colour predictive test centred on the most strongly associated SNPs. Previous studies have analysed skin colour variation in single unadmixed population groups, including South Asians (Stokowski et al., 2007, Am. J. Hum. Genet, 81: 1119-32) and Europeans (Jacobs et al., 2013, Hum Genet. 132: 147-58). Nevertheless, a major challenge lies in the analysis of skin colour in admixed individuals, where co-ancestry proportions do not necessarily dictate any one person's skin colour. Our study sought to analyse genetic differences between African, European and admixed African-European subjects where direct spectrometric measurements and photographs of skin colour were made in parallel. We identified strong associations to skin colour variation in the subjects studied from a pigmentation SNP discovery panel of 59 markers and developed a forensic online classifier based on naïve Bayes analysis of the SNP profiles made. A skin colour predictive test is described using the ten most strongly associated SNPs in 8 genes linked to skin pigmentation variation.

Collaborative EDNAP exercise on the IrisPlex system for DNA-based prediction of human eye colour.

The IrisPlex system is a DNA-based test system for the prediction of human eye colour from biological samples and consists of a single forensically validated multiplex genotyping assay together with a statistical prediction model that is based on genotypes and phenotypes from thousands of individuals. IrisPlex predicts blue and brown human eye colour with, on average, >94% precision accuracy using six of the currently most eye colour informative single nucleotide polymorphisms (HERC2 rs12913832, OCA2 rs1800407, SLC24A4 rs12896399, SLC45A2 (MATP) rs16891982, TYR rs1393350, and IRF4 rs12203592) according to a previous study, while the accuracy in predicting non-blue and non-brown eye colours is considerably lower. In an effort to vigorously assess the IrisPlex system at the international level, testing was performed by 21 laboratories in the context of a collaborative exercise divided into three tasks and organised by the European DNA Profiling (EDNAP) Group of the International Society of Forensic Genetics (ISFG). Task 1 involved the assessment of 10 blood and saliva samples provided on FTA cards by the organising laboratory together with eye colour phenotypes; 99.4% of the genotypes were correctly reported and 99% of the eye colour phenotypes were correctly predicted. Task 2 involved the assessment of 5 DNA samples extracted by the host laboratory from simulated casework samples, artificially degraded, and provided to the participants in varying DNA concentrations. For this task, 98.7% of the genotypes were correctly determined and 96.2% of eye colour phenotypes were correctly inferred. For Tasks 1 and 2 together, 99.2% (1875) of the 1890 genotypes were correctly generated and of the 15 (0.8%) incorrect genotype calls, only 2 (0.1%) resulted in incorrect eye colour phenotypes. The voluntary Task 3 involved participants choosing their own test subjects for IrisPlex genotyping and eye colour phenotype inference, while eye photographs were provided to the organising laboratory and judged; 96% of the eye colour phenotypes were inferred correctly across 100 samples and 19 laboratories. The high success rates in genotyping and eye colour phenotyping clearly demonstrate the reproducibility and the robustness of the IrisPlex assay as well as the accuracy of the IrisPlex model to predict blue and brown eye colour from DNA. Additionally, this study demonstrates the ease with which the IrisPlex system is implementable and applicable across forensic laboratories around the world with varying pre-existing experiences.