Genome-wide association meta-analysis of individuals of European ancestry identifies new loci explaining a substantial fraction of hair color variation and heritability

A novel expectation-maximization approach to infer general diploid selection from time-series genetic data

Detecting and quantifying the strength of selection is a main objective in population genetics. Since selection acts over multiple generations, many approaches have been developed to detect and quantify selection using genetic data sampled at multiple points in time. Such time series genetic data is commonly analyzed using Hidden Markov Models, but in most cases, under the assumption of additive selection. However, many examples of genetic variation exhibiting non-additive mechanisms exist, making it critical to develop methods that can characterize selection in more general scenarios. Thus, we extend a previously introduced expectation-maximization algorithm for the inference of additive selection coefficients to the case of general diploid selection, in which heterozygote and homozygote fitnesses are parameterized independently. We furthermore introduce a framework to identify bespoke modes of diploid selection from given data, as well as a procedure for aggregating data across linked loci to increase power and robustness. Using extensive simulation studies, we find that our method accurately and efficiently estimates selection coefficients for different modes of diploid selection across a wide range of scenarios; however, power to classify the mode of selection is low unless selection is very strong. We apply our method to ancient DNA samples from Great Britain in the last 4,450 years, and detect evidence for selection in six genomic regions, including the well-characterized LCT locus. Our work is the first genome-wide scan characterizing signals of general diploid selection.

Multi-ancestry tandem repeat association study of hair colour using exome-wide sequencing

Hair colour variation is influenced by hundreds of positions across the human genome but this genetic contribution has only been narrowly explored. Genome-wide association studies identified single nucleotide polymorphisms (SNPs) influencing hair colour but the biology underlying these associations is challenging to interpret. We report 16 tandem repeats (TRs) with effects on different models of hair colour plus two TRs associated with hair colour in diverse ancestry groups. Several of these TRs expand or contract amino acid coding regions of their localized protein such that structure, and by extension function, may be altered. We also demonstrate that independent of SNP variation, these TRs can be used to great an additive polygenic score that predicts darker hair colour. This work adds to the growing body of evidence regarding TR influence on human traits with relatively large and independent effects relative to surrounding SNP variation.

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records

BACKGROUND

The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery.

METHODS

We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).

FINDINGS

After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25).

INTERPRETATION

Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.

FUNDING

National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.

Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age

Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.

Skin Phototype and Disease: A Comprehensive Genetic Approach to Pigmentary Traits Pleiotropy Using PRS in the GCAT Cohort

Human pigmentation has largely been associated with different disease prevalence among populations, but most of these studies are observational and inconclusive. Known to be genetically determined, pigmentary traits have largely been studied by Genome-Wide Association Study (GWAS), mostly in Caucasian ancestry cohorts from North Europe, identifying robustly, several loci involved in many of the pigmentary traits. Here, we conduct a detailed analysis by GWAS and Polygenic Risk Score (PRS) of 13 pigmentary-related traits in a South European cohort of Caucasian ancestry (n = 20,000). We observed fair phototype strongly associated with non-melanoma skin cancer and other dermatoses and confirmed by PRS-approach the shared genetic basis with skin and eye diseases, such as melanoma (OR = 0.95), non-melanoma skin cancer (OR = 0.93), basal cell carcinoma (OR = 0.97) and darker phototype with vitiligo (OR = 1.02), cataracts (OR = 1.04). Detailed genetic analyses revealed 37 risk loci associated with 10 out of 13 analyzed traits, and 16 genes significantly associated with at least two pigmentary traits. Some of them have been widely reported, such as MC1R, HERC2, OCA2, TYR, TYRP1, SLC45A2, and some novel candidate genes C1QTNF3, LINC02876, and C1QTNF3-AMACR have not been reported in the GWAS Catalog, with regulatory potential. These results highlight the importance of the assess phototype as a genetic proxy of skin functionality and disease when evaluating open mixed populations.

Advancement in Human Face Prediction Using DNA

The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.

Investigating the morphology and genetics of scalp and facial hair characteristics for phenotype prediction

Microscopic traits and ultrastructure of hair such as cross-sectional shape, pigmentation, curvature, and internal structure help determine the level of variations between and across human populations. Apart from cosmetics and anthropological applications, such as determining species, somatic origin (body area), and biogeographic ancestry, the evidential value of hair has increased with rapid progression in the area of forensic DNA phenotyping (FDP). Individuals differ in the features of their scalp hair (greying, shape, colour, balding, thickness, and density) and facial hair (eyebrow thickness, monobrow, and beard thickness) features. Scalp and facial hair characteristics are genetically controlled and lead to visible inter-individual variations within and among populations of various ethnic origins. Hence, these characteristics can be exploited and made more inclusive in FDP, thereby leading to more comprehensive, accurate, and robust prediction models for forensic purposes. The present article focuses on understanding the genetics of scalp and facial hair characteristics with the goal to develop a more inclusive approach to better understand hair biology by integrating hair microscopy with genetics for genotype-phenotype correlation research.

Genome-Wide Association Study Identifies Two Common Loci Associated with Pigment Dispersion Syndrome/Pigmentary Glaucoma and Implicates Myopia in its Development

PURPOSE

To identify genetic variants associated with pigment dispersion syndrome (PDS) and pigmentary glaucoma (PG) in unrelated patients and to further understand the genetic and potentially causal relationships between PDS and associated risk factors.

DESIGN

A 2-stage genome-wide association meta-analysis with replication and subsequent in silico analyses including Mendelian randomization.

PARTICIPANTS

A total of 574 cases with PG or PDS and 52 627 controls of European descent.

METHODS

Genome-wide association analyses were performed in 4 cohorts and meta-analyzed in 3 stages: (1) a discovery meta-analysis was performed in 3 cohorts, (2) replication was performed in the fourth cohort, and (3) all 4 cohorts were meta-analyzed to increase statistical power. Two-sample Mendelian randomization was used to determine whether refractive error and intraocular pressure exert causal effects over PDS.

MAIN OUTCOME MEASURES

The association of genetic variants with PDS and whether myopia exerts causal effects over PDS.

RESULTS

Significant association was present at 2 novel loci for PDS/PG. These loci and follow-up analyses implicate the genes gamma secretase activator protein (GSAP) (lead single nucleotide polymorphism [SNP]: rs9641220, P = 6.0×10-10) and glutamate metabotropic receptor 5 (GRM5)/TYR (lead SNP: rs661177, P = 3.9×10-9) as important factors in disease risk. Mendelian randomization showed significant evidence that negative refractive error (myopia) exerts a direct causal effect over PDS (P = 8.86×10-7).

CONCLUSIONS

Common SNPs relating to the GSAP and GRM5/TYR genes are associated risk factors for the development of PDS and PG. Although myopia is a known risk factor, this study uses genetic data to demonstrate that myopia is, in part, a cause of PDS and PG.

The Skin We Live in: Pigmentation Traits and Tanning Behaviour in British Young Adults, an Observational and Genetically-Informed Study

Skin cancer incidence has been increasing worldwide, representing a particularly high burden for populations of European ancestry. Outdoor and indoor tanning using ultraviolet (UV) radiation devices are major risk factors for skin cancer. While tanning behaviours can be modified by targeted interventions to reduce skin cancer rates, there is insufficient evidence on the motivations for tanning preferences and their relationship with pigmentation phenotypes. The present observational and genetically-informed study investigates motives for tanning and the role that pigmentation phenotypes play on outdoor and indoor tanning behaviour in British young adults. This study included 3722 participants from the Avon Longitudinal Study of Parents and Children in South West England, with data on pigmentation features, tanning ability and preferences, and SNP genotypes. Liking to tan and outdoor tanning were strongly influenced by pigmentary traits and tanning ability. However, the association of these phenotypes with UV indoor tanning was weaker. Our results provide evidence to support the implementation of skin cancer preventative interventions that consider individual biological characteristics and motives for undergoing outdoor and indoor tanning.

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.

Direct detection of natural selection in Bronze Age Britain

We developed a novel method for efficiently estimating time-varying selection coefficients from genome-wide ancient DNA data. In simulations, our method accurately recovers selective trajectories and is robust to misspecification of population size. We applied it to a large data set of ancient and present-day human genomes from Britain and identified seven loci with genome-wide significant evidence of selection in the past 4500 yr. Almost all of them can be related to increased vitamin D or calcium levels, suggesting strong selective pressure on these or related phenotypes. However, the strength of selection on individual loci varied substantially over time, suggesting that cultural or environmental factors moderated the genetic response. Of 28 complex anthropometric and metabolic traits, skin pigmentation was the only one with significant evidence of polygenic selection, further underscoring the importance of phenotypes related to vitamin D. Our approach illustrates the power of ancient DNA to characterize selection in human populations and illuminates the recent evolutionary history of Britain.

Bayesian model comparison for rare-variant association studies

Whole-genome sequencing studies applied to large populations or biobanks with extensive phenotyping raise new analytic challenges. The need to consider many variants at a locus or group of genes simultaneously and the potential to study many correlated phenotypes with shared genetic architecture provide opportunities for discovery not addressed by the traditional one variant, one phenotype association study. Here, we introduce a Bayesian model comparison approach called MRP (multiple rare variants and phenotypes) for rare-variant association studies that considers correlation, scale, and direction of genetic effects across a group of genetic variants, phenotypes, and studies, requiring only summary statistic data. We apply our method to exome sequencing data (n = 184,698) across 2,019 traits from the UK Biobank, aggregating signals in genes. MRP demonstrates an ability to recover signals such as associations between PCSK9 and LDL cholesterol levels. We additionally find MRP effective in conducting meta-analyses in exome data. Non-biomarker findings include associations between MC1R and red hair color and skin color, IL17RA and monocyte count, and IQGAP2 and mean platelet volume. Finally, we apply MRP in a multi-phenotype setting; after clustering the 35 biomarker phenotypes based on genetic correlation estimates, we find that joint analysis of these phenotypes results in substantial power gains for gene-trait associations, such as in TNFRSF13B in one of the clusters containing diabetes- and lipid-related traits. Overall, we show that the MRP model comparison approach improves upon useful features from widely used meta-analysis approaches for rare-variant association analyses and prioritizes protective modifiers of disease risk.

A large Canadian cohort provides insights into the genetic architecture of human hair colour

Hair colour is a polygenic phenotype that results from differences in the amount and ratio of melanins located in the hair bulb. Genome-wide association studies (GWAS) have identified many loci involved in the pigmentation pathway affecting hair colour. However, most of the associated loci overlap non-protein coding regions and many of the molecular mechanisms underlying pigmentation variation are still not understood. Here, we conduct GWAS meta-analyses of hair colour in a Canadian cohort of 12,741 individuals of European ancestry. By performing fine-mapping analyses we identify candidate causal variants in pigmentation loci associated with blonde, red and brown hair colour. Additionally, we observe colocalization of several GWAS hits with expression and methylation quantitative trait loci (QTLs) of cultured melanocytes. Finally, transcriptome-wide association studies (TWAS) further nominate the expression of EDNRB and CDK10 as significantly associated with hair colour. Our results provide insights on the mechanisms regulating pigmentation biology in humans.

GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically plausible connections. We applied the framework to seventeen phenotypes and found well-replicated genes such as HERC2 and OCA2 for hair and eye color, and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases.

van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Cell-type-specific meQTLs extend melanoma GWAS annotation beyond eQTLs and inform melanocyte gene-regulatory mechanisms

Although expression quantitative trait loci (eQTLs) have been powerful in identifying susceptibility genes from genome-wide association study (GWAS) findings, most trait-associated loci are not explained by eQTLs alone. Alternative QTLs, including DNA methylation QTLs (meQTLs), are emerging, but cell-type-specific meQTLs using cells of disease origin have been lacking. Here, we established an meQTL dataset by using primary melanocytes from 106 individuals and identified 1,497,502 significant cis-meQTLs. Multi-QTL colocalization with meQTLs, eQTLs, and mRNA splice-junction QTLs from the same individuals together with imputed methylome-wide and transcriptome-wide association studies identified candidate susceptibility genes at 63% of melanoma GWAS loci. Among the three molecular QTLs, meQTLs were the single largest contributor. To compare melanocyte meQTLs with those from malignant melanomas, we performed meQTL analysis on skin cutaneous melanomas from The Cancer Genome Atlas (n = 444). A substantial proportion of meQTL probes (45.9%) in primary melanocytes is preserved in melanomas, while a smaller fraction of eQTL genes is preserved (12.7%). Integration of melanocyte multi-QTLs and melanoma meQTLs identified candidate susceptibility genes at 72% of melanoma GWAS loci. Beyond GWAS annotation, meQTL-eQTL colocalization in melanocytes suggested that 841 unique genes potentially share a causal variant with a nearby methylation probe in melanocytes. Finally, melanocyte trans-meQTLs identified a hotspot for rs12203592, a cis-eQTL of a transcription factor, IRF4, with 131 candidate target CpGs. Motif enrichment and IRF4 ChIP-seq analysis demonstrated that these target CpGs are enriched in IRF4 binding sites, suggesting an IRF4-mediated regulatory network. Our study highlights the utility of cell-type-specific meQTLs.

The use of negative control outcomes in Mendelian randomization to detect potential population stratification

A key assumption of Mendelian randomization (MR) analysis is that there is no association between the genetic variants used as instruments and the outcome other than through the exposure of interest. One way in which this assumption can be violated is through population stratification, which can introduce confounding of the relationship between the genetic variants and the outcome and so induce an association between them. Negative control outcomes are increasingly used to detect unobserved confounding in observational epidemiological studies. Here we consider the use of negative control outcomes in MR studies to detect confounding of the genetic variants and the exposure or outcome. As a negative control outcome in an MR study, we propose the use of phenotypes which are determined before the exposure and outcome but which are likely to be subject to the same confounding as the exposure or outcome of interest. We illustrate our method with a two-sample MR analysis of a preselected set of exposures on self-reported tanning ability and hair colour. Our results show that, of the 33 exposures considered, genome-wide association studies (GWAS) of adiposity and education-related traits are likely to be subject to population stratification that is not controlled for through adjustment, and so any MR study including these traits may be subject to bias that cannot be identified through standard pleiotropy robust methods. Negative control outcomes should therefore be used regularly in MR studies to detect potential population stratification in the data used.

NNT mediates redox-dependent pigmentation via a UVB- and MITF-independent mechanism

Ultraviolet (UV) light and incompletely understood genetic and epigenetic variations determine skin color. Here we describe an UV- and microphthalmia-associated transcription factor (MITF)-independent mechanism of skin pigmentation. Targeting the mitochondrial redox-regulating enzyme nicotinamide nucleotide transhydrogenase (NNT) resulted in cellular redox changes that affect tyrosinase degradation. These changes regulate melanosome maturation and, consequently, eumelanin levels and pigmentation. Topical application of small-molecule inhibitors yielded skin darkening in human skin, and mice with decreased NNT function displayed increased pigmentation. Additionally, genetic modification of NNT in zebrafish alters melanocytic pigmentation. Analysis of four diverse human cohorts revealed significant associations of skin color, tanning, and sun protection use with various single-nucleotide polymorphisms within NNT. NNT levels were independent of UVB irradiation and redox modulation. Individuals with postinflammatory hyperpigmentation or lentigines displayed decreased skin NNT levels, suggesting an NNT-driven, redox-dependent pigmentation mechanism that can be targeted with NNT-modifying topical drugs for medical and cosmetic purposes.

Searching for improvements in predicting human eye colour from DNA

Increasing understanding of human genome variability allows for better use of the predictive potential of DNA. An obvious direct application is the prediction of the physical phenotypes. Significant success has been achieved, especially in predicting pigmentation characteristics, but the inference of some phenotypes is still challenging. In search of further improvements in predicting human eye colour, we conducted whole-exome (enriched in regulome) sequencing of 150 Polish samples to discover new markers. For this, we adopted quantitative characterization of eye colour phenotypes using high-resolution photographic images of the iris in combination with DIAT software analysis. An independent set of 849 samples was used for subsequent predictive modelling. Newly identified candidates and 114 additional literature-based selected SNPs, previously associated with pigmentation, and advanced machine learning algorithms were used. Whole-exome sequencing analysis found 27 previously unreported candidate SNP markers for eye colour. The highest overall prediction accuracies were achieved with LASSO-regularized and BIC-based selected regression models. A new candidate variant, rs2253104, located in the ARFIP2 gene and identified with the HyperLasso method, revealed predictive potential and was included in the best-performing regression models. Advanced machine learning approaches showed a significant increase in sensitivity of intermediate eye colour prediction (up to 39%) compared to 0% obtained for the original IrisPlex model. We identified a new potential predictor of eye colour and evaluated several widely used advanced machine learning algorithms in predictive analysis of this trait. Our results provide useful hints for developing future predictive models for eye colour in forensic and anthropological studies.

Evolutionary genetics of skin pigmentation in African populations

Skin color is a highly heritable human trait, and global variation in skin pigmentation has been shaped by natural selection, migration and admixture. Ethnically diverse African populations harbor extremely high levels of genetic and phenotypic diversity, and skin pigmentation varies widely across Africa. Recent genome-wide genetic studies of skin pigmentation in African populations have advanced our understanding of pigmentation biology and human evolutionary history. For example, novel roles in skin pigmentation for loci near MFSD12 and DDB1 have recently been identified in African populations. However, due to an underrepresentation of Africans in human genetic studies, there is still much to learn about the evolutionary genetics of skin pigmentation. Here, we summarize recent progress in skin pigmentation genetics in Africans and discuss the importance of including more ethnically diverse African populations in future genetic studies. In addition, we discuss methods for functional validation of adaptive variants related to skin pigmentation.

Prediction of eye, hair and skin colour in Latin Americans

Here we evaluate the accuracy of prediction for eye, hair and skin pigmentation in a dataset of > 6500 individuals from Mexico, Colombia, Peru, Chile and Brazil (including genome-wide SNP data and quantitative/categorical pigmentation phenotypes - the CANDELA dataset CAN). We evaluated accuracy in relation to different analytical methods and various phenotypic predictors. As expected from statistical principles, we observe that quantitative traits are more sensitive to changes in the prediction models than categorical traits. We find that Random Forest or Linear Regression are generally the best performing methods. We also compare the prediction accuracy of SNP sets defined in the CAN dataset (including 56, 101 and 120 SNPs for eye, hair and skin colour prediction, respectively) to the well-established HIrisPlex-S SNP set (including 6, 22 and 36 SNPs for eye, hair and skin colour prediction respectively). When training prediction models on the CAN data, we observe remarkably similar performances for HIrisPlex-S and the larger CAN SNP sets for the prediction of hair (categorical) and eye (both categorical and quantitative), while the CAN sets outperform HIrisPlex-S for quantitative, but not for categorical skin pigmentation prediction. The performance of HIrisPlex-S, when models are trained in a world-wide sample (although consisting of 80% Europeans, https://hirisplex.erasmusmc.nl), is lower relative to training in the CAN data (particularly for hair and skin colour). Altogether, our observations are consistent with common variation of eye and hair colour having a relatively simple genetic architecture, which is well captured by HIrisPlex-S, even in admixed Latin Americans (with partial European ancestry). By contrast, since skin pigmentation is a more polygenic trait, accuracy is more sensitive to prediction SNP set size, although here this effect was only apparent for a quantitative measure of skin pigmentation. Our results support the use of HIrisPlex-S in the prediction of categorical pigmentation traits for forensic purposes in Latin America, while illustrating the impact of training datasets on its accuracy.

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.

Association Between Alopecia Areata and Natural Hair Color Among White Individuals

IMPORTANCE

Alopecia areata (AA) is a complex immune-mediated disorder that causes nonscarring hair loss. Previous reports have documented preferential targeting of pigmented hair follicles with sparing of gray, nonpigmented hair follicles in alopecia lesions. Thus, immune targeting of melanogenesis-associated proteins in melanocytes and keratinocytes represents a potential mechanism for the inflammation that targets anagen hairs in alopecia areata.

OBJECTIVE

To investigate the association of alopecia areata with hair color among White residents of the UK.

DESIGN, SETTING, AND PARTICIPANTS

This matched, case-control study conducted in October 2020 used a large prospectively acquired cohort and included data that were collected from the UK Biobank, a large-scale prospective resource designed to study phenotypic and genotypic determinants in adults. A total of 502 510 UK Biobank participants were reviewed for inclusion. Among these individuals, 1673 cases of alopecia areata with reported hair color were captured and matched by age and sex to 6692 controls without alopecia areata using 1:4 matching.

MAIN OUTCOMES AND MEASURES

Conditional logistic regression analysis was performed, in which the outcome variable was alopecia areata and the main predictor was natural hair color before graying. The variables considered included diabetes, hypothyroidism, hyperthyroidism, and vitiligo.

RESULTS

Of 464 353 participants, 254 505 (54.8%) were women, and the mean (SD) age for those with alopecia areata was 46.9 (16.5) years. Alopecia areata was significantly more common in individuals with black (adjusted odds ratio [aOR], 2.97; 95% CI, 2.38-3.71) and dark brown hair (aOR, 1.26; 95% CI, 1.11-1.42) compared with light brown hair. In contrast, blond individuals exhibited significantly decreased alopecia areata compared with those with light brown hair (aOR, 0.69; 95% CI, 0.56-0.85). Red hair color was not significantly different from light brown hair.

CONCLUSIONS AND RELEVANCE

The findings of this matched case-control study seem to indicate that alopecia areata is modulated by natural hair color, preferentially targeting darker hair. Our results support a previously proposed model of alopecia areata in which immunity is directed against melanogenesis-associated proteins in the anagen hair follicles. However, further study is needed to more precisely understand the immunopathogenic association between alopecia areata and hair color.

The constraints of racialization: How classification and valuation hinder scientific research on human variation

Human biological variation has historically been studied through the lens of racialization. Despite a general shift away from the use of overt racial terminologies, the underlying racialized frameworks used to describe and understand human variation still remain. Even in relatively recent anthropological and biomedical work, we can observe clear manifestations of such racial thinking. This paper shows how classification and valuation are two specific processes which facilitate racialization and hinder attempts to move beyond such frameworks. The bias induced by classification distorts descriptions of phenotypic variation in a way that erroneously portrays European populations as more variable than others. Implicit valuation occurs in tandem with classification and produces narratives of superiority/inferiority for certain phenotypic variants without an objective biological basis. The bias of racialization is a persistent impediment stemming from the inheritance of scientific knowledge developed under explicitly racial paradigms. It is also an internalized cognitive distortion cultivated through socialization in a world where racialization is inescapable. Though undeniably challenging, this does not present an insurmountable barrier, and this bias can be mitigated through the critical evaluation of past work, the active inclusion of marginalized perspectives, and the direct confrontation of institutional structures enforcing racialized paradigms.

Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

Investigative genetic genealogy: Current methods, knowledge and practice

Investigative genetic genealogy (IGG) has emerged as a new, rapidly growing field of forensic science. We describe the process whereby dense SNP data, commonly comprising more than half a million markers, are employed to infer distant relationships. By distant we refer to degrees of relatedness exceeding that of first cousins. We review how methods of relationship matching and SNP analysis on an enlarged scale are used in a forensic setting to identify a suspect in a criminal investigation or a missing person. There is currently a strong need in forensic genetics not only to understand the underlying models to infer relatedness but also to fully explore the DNA technologies and data used in IGG. This review brings together many of the topics and examines their effectiveness and operational limits, while suggesting future directions for their forensic validation. We further investigated the methods used by the major direct-to-consumer (DTC) genetic ancestry testing companies as well as submitting a questionnaire where providers of forensic genetic genealogy summarized their operation/services. Although most of the DTC market, and genetic genealogy in general, has undisclosed, proprietary algorithms we review the current knowledge where information has been discussed and published more openly.

Mapping of cis-acting expression quantitative trait loci in human scalp hair follicles

BACKGROUND

The association of molecular phenotypes, such as gene transcript levels, with human common genetic variation can help to improve our understanding of interindividual variability of tissue-specific gene regulation and its implications for disease.

METHODS

With the aim to capture the spectrum of biological processes affected by regulatory common genetic variants (minor allele frequency ≥ 1%) in healthy hair follicles (HFs) from scalp tissue, we performed a genome-wide mapping of cis-acting expression quantitative trait loci (eQTLs) in plucked HFs, and applied these eQTLs to help further explain genomic findings for hair-related traits.

RESULTS

We report 374 high-confidence eQTLs found in occipital scalp tissue, whose associated genes (eGenes) showed enrichments for metabolic, mitotic and immune processes, as well as responses to steroid hormones. We were able to replicate 68 of these associations in a smaller, independent dataset, in either frontal and/or occipital scalp tissue. Furthermore, we found three genomic regions overlapping reported genetic loci for hair shape and hair color. We found evidence to confirm the contributions of PADI3 to human variation in hair traits and suggest a novel potential candidate gene within known loci for androgenetic alopecia.

CONCLUSIONS

Our study shows that an array of basic cellular functions relevant for hair growth are genetically regulated within the HF, and can be applied to aid the interpretation of interindividual variability on hair traits, as well as genetic findings for common hair disorders.

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.

Genetics of facial telangiectasia in the Rotterdam Study: a genome-wide association study and candidate gene approach

BACKGROUND

The severity of facial telangiectasia or red veins is associated with many lifestyle factors. However, the genetic predisposition remains unclear.

OBJECTIVES

We performed a genome-wide association study (GWAS) on facial telangiectasia in the Rotterdam Study (RS) and tested for replication in two independent cohorts. Additionally, a candidate gene approach with known pigmentation genes was performed.

METHODS

Facial telangiectasia were extracted from standardized facial photographs (collected from 2010-2013) of 2842 northwestern European participants (median age 66.9, 56.8% female) from the RS. Our GWAS top hits (P-value <10^-6 ) were tested for replication in 460 elderly women of the SALIA cohort and in 576 additional men and women of the RS. Associations of top single nucleotide polymorphisms (SNPs) with expression quantitative trait loci (eQTL) in various tissues were reviewed (GTEx database) alongside phenotype associations in the UK biobank database. SNP-based associations between known pigmentation genes and facial telangiectasia were tested. Conditional analysis on skin colour was additionally performed.

RESULTS

Our most significant GWAS signal was rs4417318 (P-value 5.38*10^-7 ), an intergenic SNP on chromosome 12 mapping to the SLC16A7 gene. Other suggestive SNPs tagged genes ZNF211, ZSCAN4, ICOS and KCNN3; SNP eQTLs and phenotype associations tagged links to the vascular system. However, the top signals did not pass significance in the two replication cohorts. The pigmentation genes KIAA0930, SLCA45A2 and MC1R, were significantly associated with telangiectasia in a candidate gene approach but not independently of skin colour.

CONCLUSION

In this GWAS on telangiectasia in a northwestern European population, no genome-wide significant SNPs were found, although suggestive signals indicate genes involved in the vascular system might be involved in telangiectasia. Significantly associated pigmentation genes underline the link between skin colour and telangiectasia.

The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits

Predicting appearance phenotypes from genotypes is relevant for various areas of human genetic research and applications such as genetic epidemiology, human history, anthropology, and particularly in forensics. Many appearance phenotypes, and thus their underlying genotypes, are highly correlated, with pigmentation traits serving as primary examples. However, all available genetic prediction models, including those for pigmentation traits currently used in forensic DNA phenotyping, ignore phenotype correlations. Here, we investigated the impact of appearance phenotype correlations on genetic appearance prediction in the exemplary case of three pigmentation traits. We used data for categorical eye, hair and skin colour as well as 41 DNA markers utilized in the recently established HIrisPlex-S system from 762 individuals with complete phenotype and genotype information. Based on these data, we performed genetic prediction modelling of eye, hair and skin colour via three different strategies, namely the established approach of predicting phenotypes solely based on genotypes while not considering phenotype correlations, and two novel approaches that considered phenotype correlations, either incorporating truly observed correlated phenotypes or DNA-predicted correlated phenotypes in addition to the DNA predictors. We found that using truly observed correlated pigmentation phenotypes as additional predictors increased the DNA-based prediction accuracies for almost all eye, hair and skin colour categories, with the largest increase for intermediate eye colour, brown hair colour, dark to black skin colour, and particularly for dark skin colour. Outcomes of dedicated computer simulations suggest that this prediction accuracy increase is due to the additional genetic information that is implicitly provided by the truly observed correlated pigmentation phenotypes used, yet not covered by the DNA predictors applied. In contrast, considering DNA-predicted correlated pigmentation phenotypes as additional predictors did not improve the performance of the genetic prediction of eye, hair and skin colour, which was in line with the results from our computer simulations. Hence, in practical applications of DNA-based appearance prediction where no phenotype knowledge is available, such as in forensic DNA phenotyping, it is not advised to use DNA-predicted correlated phenotypes as predictors in addition to the DNA predictors. In the very least, this is not recommended for the pigmentation traits and the established pigmentation DNA predictors tested here.

Postadmixture Selection on Chileans Targets Haplotype Involved in Pigmentation, Thermogenesis and Immune Defense against Pathogens

Detection of positive selection signatures in populations around the world is helping to uncover recent human evolutionary history as well as the genetic basis of diseases. Most human evolutionary genomic studies have been performed in European, African, and Asian populations. However, populations with Native American ancestry have been largely underrepresented. Here, we used a genome-wide local ancestry enrichment approach complemented with neutral simulations to identify postadmixture adaptations underwent by admixed Chileans through gene flow from Europeans into local Native Americans. The top significant hits (P = 2.4×10-7) are variants in a region on chromosome 12 comprising multiple regulatory elements. This region includes rs12821256, which regulates the expression of KITLG, a well-known gene involved in lighter hair and skin pigmentation in Europeans as well as in thermogenesis. Another variant from that region is associated with the long noncoding RNA RP11-13A1.1, which has been specifically involved in the innate immune response against infectious pathogens. Our results suggest that these genes were relevant for adaptation in Chileans following the Columbian exchange.

Evaluation of the VISAGE Basic Tool for Appearance and Ancestry Prediction Using PowerSeq Chemistry on the MiSeq FGx System

The study of DNA to predict externally visible characteristics (EVCs) and the biogeographical ancestry (BGA) from unknown samples is gaining relevance in forensic genetics. Technical developments in Massively Parallel Sequencing (MPS) enable the simultaneous analysis of hundreds of DNA markers, which improves successful Forensic DNA Phenotyping (FDP). The EU-funded VISAGE (VISible Attributes through GEnomics) Consortium has developed various targeted MPS-based lab tools to apply FDP in routine forensic analyses. Here, we present an evaluation of the VISAGE Basic tool for appearance and ancestry prediction based on PowerSeq chemistry (Promega) on a MiSeq FGx System (Illumina). The panel consists of 153 single nucleotide polymorphisms (SNPs) that provide information about EVCs (41 SNPs for eye, hair and skin color from HIrisPlex-S) and continental BGA (115 SNPs; three overlap with the EVCs SNP set). The assay was evaluated for sensitivity, repeatability and genotyping concordance, as well as its performance with casework-type samples. This targeted MPS assay provided complete genotypes at all 153 SNPs down to 125 pg of input DNA and 99.67% correct genotypes at 50 pg. It was robust in terms of repeatability and concordance and provided useful results with casework-type samples. The results suggest that this MPS assay is a useful tool for basic appearance and ancestry prediction in forensic genetics for users interested in applying PowerSeq chemistry and MiSeq for this purpose.

An Independent Locus Upstream of ASIP Controls Variation in the Shade of the Bay Coat Colour in Horses

Novel coat colour phenotypes often emerge during domestication, and there is strong evidence of genetic selection for the two main genes that control base coat colour in horses-ASIP and MC1R. These genes direct the type of pigment produced, red pheomelanin (MC1R) or black eumelanin (ASIP), as well as the relative concentration and the temporal-spatial distribution of melanin pigment deposits in the skin and hair coat. Here, we describe a genome-wide association study (GWAS) to identify novel genic regions involved in the determination of the shade of bay. In total, 126 horses from five different breeds were ranked according to the extent of the distribution of eumelanin: spanning variation in phenotype from black colour restricted only to the extremities to the presence of some black pigment across nearly all the body surface. We identified a single region associated with the shade of bay ranking spanning approximately 0.5 MB on ECA22, just upstream of the ASIP gene (p = 9.76 × 10-15). This candidate region encompasses the distal 5' end of the ASIP transcript (as predicted from other species) as well as the RALY gene. Both loci are viable candidates based on the presence of similar alleles in other species. These results contribute to the growing understanding of coat colour genetics in the horse and to the mapping of genetic determinants of pigmentation on a molecular level. Given pleiotropic phenotypes in behaviour and obesity for ASIP alleles, especially those in the 5' regulatory region, improved understanding of this new Shade allele may have implications for health management in the horse.

An Assessment of Environmental Health Measures in the Deepwater Horizon Research Consortia

Research consortia play a key role in our understanding of how environmental exposures influence health and wellbeing, especially in the case of catastrophic events such as the Deepwater Horizon oil spill. A common challenge that prevents the optimal use of these data is the difficulty of harmonizing data regarding the environmental exposures and health effects across the studies within and among consortia. A review of the measures used by members of the Deepwater Horizon Research Consortia highlights the challenges associated with balancing timely implementation of a study to support disaster relief with optimizing the long-term value of the data. The inclusion of common, standard measures at the study design phase and a priori discussions regarding harmonization of study-specific measures among consortia members are key to overcoming this challenge. As more resources become available to support the use of standard measures, researchers now have the tools needed to rapidly coordinate their studies without compromising research focus or timely completion of the original study goals.

Ancient genomes from present-day France unveil 7,000 years of its demographic history

Genomic studies conducted on ancient individuals across Europe have revealed how migrations have contributed to its present genetic landscape, but the territory of present-day France has yet to be connected to the broader European picture. We generated a large dataset comprising the complete mitochondrial genomes, Y-chromosome markers, and genotypes of a number of nuclear loci of interest of 243 individuals sampled across present-day France over a period spanning 7,000 y, complemented with a partially overlapping dataset of 58 low-coverage genomes. This panel provides a high-resolution transect of the dynamics of maternal and paternal lineages in France as well as of autosomal genotypes. Parental lineages and genomic data both revealed demographic patterns in France for the Neolithic and Bronze Age transitions consistent with neighboring regions, first with a migration wave of Anatolian farmers followed by varying degrees of admixture with autochthonous hunter-gatherers, and then substantial gene flow from individuals deriving part of their ancestry from the Pontic steppe at the onset of the Bronze Age. Our data have also highlighted the persistence of Magdalenian-associated ancestry in hunter-gatherer populations outside of Spain and thus provide arguments for an expansion of these populations at the end of the Paleolithic Period more northerly than what has been described so far. Finally, no major demographic changes were detected during the transition between the Bronze and Iron Ages.

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.

The genomics of coloration provides insights into adaptive evolution

Coloration is an easily quantifiable visual trait that has proven to be a highly tractable system for genetic analysis and for studying adaptive evolution. The application of genomic approaches to evolutionary studies of coloration is providing new insight into the genetic architectures underlying colour traits, including the importance of large-effect mutations and supergenes, the role of development in shaping genetic variation and the origins of adaptive variation, which often involves adaptive introgression. Improved knowledge of the genetic basis of traits can facilitate field studies of natural selection and sexual selection, making it possible for strong selection and its influence on the genome to be demonstrated in wild populations.

Objectives, design and main findings until 2020 from the Rotterdam Study

The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.

The challenge of predicting human pigmentation traits in degraded bone samples with the MPS-based HIrisPlex-S system

Identification of human remains is an important part of human DNA analysis studies. STR and mitochondrial DNA markers are well suited for the analysis of degraded biological samples including bone material. However, these DNA markers may be useless when reference material is not available. In these cases, predictive DNA analysis can support the process of human identification by providing investigative leads. Forensic DNA phenotyping has progressed significantly by offering new methods based on massively parallel sequencing technology, but the frequent degradation processes observed in skeletal remains can make analysis of such samples challenging. In this study, we demonstrate the usefulness of a recently established Ion AmpliSeq^TM HIrisPlex-S panel using Ion Torrent technology for analyzing bone samples that show different levels of DNA degradation. In total, 63 bone samples at post-mortem intervals up to almost 80 years were genotyped and eye, hair and skin colour predictions were performed using the HIrisPlex-S models. Following the recommended coverage thresholds, it was possible to establish full DNA profiles comprising of 41 DNA variants for 35 samples (55.6%). For 5 samples (7.9%) no DNA profiles were generated. The remaining 23 samples (36.5%) produced partial profiles and showed a clear underperformance of 3 HIrisPlex-S SNPs - rs1545397 (OCA2), rs1470608 (OCA2) and rs10756819 (BNC2), all used for skin colour prediction only. None of the 23 samples gave complete genotypes needed for skin colour prediction was obtained, and in 7 of them (25.9%) the 3 underperformed SNPs were the cause. At the same time, the prediction of eye and hair colour using complete IrisPlex and HIrisPlex profiles could be made for these 23 samples in 20 (87.0%) and 12 cases (52.2%), respectively. Complete HIrisPlex-S profiles were generated from as little as 49 pg of template DNA. Five samples for which the HIrisPlex-S analysis failed, consistently failed in standard STR analysis. Importantly, the 3 underperforming SNPs produced significantly lower number of reads in good quality samples. Nonetheless, the AUC loss resulting from missing data for these 3 SNPs is not considered large (≤0.004) and the prediction of pigmentation from partial profiles is also available in the current HPS tool. The study shows that DNA degradation and the resulting loss of data are the most serious challenge to DNA phenotyping of skeletal remains. Although the newly developed HIrisPlex-S panel has been successfully validated in the current research, primer redesign for the 3 underperforming SNPs in the MPS design should be considered in the future.

Meta-analysis of 542,934 subjects of European ancestry identifies new genes and mechanisms predisposing to refractive error and myopia

Refractive errors, in particular myopia, are a leading cause of morbidity and disability worldwide. Genetic investigation can improve understanding of the molecular mechanisms that underlie abnormal eye development and impaired vision. We conducted a meta-analysis of genome-wide association studies (GWAS) that involved 542,934 European participants and identified 336 novel genetic loci associated with refractive error. Collectively, all associated genetic variants explain 18.4% of heritability and improve the accuracy of myopia prediction (area under the curve (AUC) = 0.75). Our results suggest that refractive error is genetically heterogeneous, driven by genes that participate in the development of every anatomical component of the eye. In addition, our analyses suggest that genetic factors controlling circadian rhythm and pigmentation are also involved in the development of myopia and refractive error. These results may enable the prediction of refractive error and the development of personalized myopia prevention strategies in the future.

Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan

The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes.

A study in scarlet: MC1R as the main predictor of red hair and exemplar of the flip-flop effect

Genetic variation in melanocortin-1 receptor (MC1R) is a known contributor to disease-free red hair in humans. Three loss-of-function single-nucleotide variants (rs1805007, rs1805008 and rs1805009) have been established as strongly correlated with red hair. The contribution of other loss-of-function MC1R variants (in particular rs1805005, rs2228479 and rs885479) and the extent to which other genetic loci are involved in red hair colour is less well understood. Here, we used the UK Biobank cohort to capture a comprehensive list of MC1R variants contributing to red hair colour. We report a correlation with red hair for both strong-effect variants (rs1805007, rs1805008 and rs1805009) and weak-effect variants (rs1805005, rs2228479 and rs885479) and show that their coefficients differ by two orders of magnitude. On the haplotype level, both strong- and weak-effect variants contribute to the red hair phenotype, but when considered individually, weak-effect variants show a reverse, negative association with red hair. The reversal of association direction in the single-variant analysis is facilitated by a distinguishing structure of MC1R, in which loss-of-function variants are never found to co-occur on the same haplotype. The other previously reported hair colour genes' variants do not substantially improve the MC1R red hair colour predictive model. Our best model for predicting red versus other hair colours yields an unparalleled area under the receiver operating characteristic of 0.96 using only MC1R variants. In summary, we present a comprehensive statistically derived characterization of the role of MC1R variants in red hair colour and offer a powerful, economical and parsimonious model that achieves unsurpassed performance.

Efficient base editing by RNA-guided cytidine base editors (CBEs) in pigs

Cytidine base editors (CBEs) have been demonstrated to be useful for precisely inducing C:G-to-T:A base mutations in various organisms. In this study, we showed that the BE4-Gam system induced the targeted C-to-T base conversion in porcine blastocysts at an efficiency of 66.7-71.4% via the injection of a single sgRNA targeting a xeno-antigen-related gene and BE4-Gam mRNA. Furthermore, the efficiency of simultaneous three gene base conversion via the injection of three targeting sgRNAs and BE4-Gam mRNA into porcine parthenogenetic embryos was 18.1%. We also obtained beta-1,4-N-acetyl-galactosaminyl transferase 2, alpha-1,3-galactosyltransferase, and cytidine monophosphate-N-acetylneuraminic acid hydroxylase deficient pig by somatic cell nuclear transfer, which exhibited significantly decreased activity. In addition, a new CBE version (termed AncBE4max) was used to edit genes in blastocysts and porcine fibroblasts (PFFs) for the first time. While this new version demonstrated a three genes base-editing rate of 71.4% at the porcine GGTA1, B4galNT2, and CMAH loci, it increased the frequency of bystander edits, which ranged from 17.8 to 71.4%. In this study, we efficiently and precisely mutated bases in porcine blastocysts and PFFs using CBEs and successfully generated C-to-T and C-to-G mutations in pigs. These results suggest that CBEs provide a more simple and efficient method for improving economic traits, reducing the breeding cycle, and increasing disease tolerance in pigs, thus aiding in the development of human disease models.

Integration of eQTL and a Single-Cell Atlas in the Human Eye Identifies Causal Genes for Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a leading cause of vision loss. To better understand disease pathogenesis and identify causal genes in GWAS loci for AMD risk, we present a comprehensive database of human retina and retinal pigment epithelium (RPE). Our database comprises macular and non-macular RNA sequencing (RNA-seq) profiles from 129 donors, a genome-wide expression quantitative trait loci (eQTL) dataset that includes macula-specific retina and RPE/choroid, and single-nucleus RNA-seq (NucSeq) from human retina and RPE with subtype resolution from more than 100,000 cells. Using NucSeq, we find enriched expression of AMD candidate genes in RPE cells. We identify 15 putative causal genes for AMD on the basis of co-localization of genetic association signals for AMD risk and eye eQTL, including the genes TSPAN10 and TRPM1. These results demonstrate the value of our human eye database for elucidating genetic pathways and potential therapeutic targets for ocular diseases.

Novel genetic loci affecting facial shape variation in humans

The human face represents a combined set of highly heritable phenotypes, but knowledge on its genetic architecture remains limited, despite the relevance for various fields. A series of genome-wide association studies on 78 facial shape phenotypes quantified from 3-dimensional facial images of 10,115 Europeans identified 24 genetic loci reaching study-wide suggestive association (p < 5 × 10-8), among which 17 were previously unreported. A follow-up multi-ethnic study in additional 7917 individuals confirmed 10 loci including six unreported ones (padjusted < 2.1 × 10-3). A global map of derived polygenic face scores assembled facial features in major continental groups consistent with anthropological knowledge. Analyses of epigenomic datasets from cranial neural crest cells revealed abundant cis-regulatory activities at the face-associated genetic loci. Luciferase reporter assays in neural crest progenitor cells highlighted enhancer activities of several face-associated DNA variants. These results substantially advance our understanding of the genetic basis underlying human facial variation and provide candidates for future in-vivo functional studies.

MEK inhibition remodels the active chromatin landscape and induces SOX10 genomic recruitment in BRAF(V600E) mutant melanoma cells

Background

The MAPK/ERK signaling pathway is an essential regulator of numerous cell processes that are crucial for normal development as well as cancer progression. While much is known regarding MAPK/ERK signal conveyance from the cell membrane to the nucleus, the transcriptional and epigenetic mechanisms that govern gene expression downstream of MAPK signaling are not fully elucidated.

Results

This study employed an integrated epigenome analysis approach to interrogate the effects of MAPK/ERK pathway inhibition on the global transcriptome, the active chromatin landscape, and protein–DNA interactions in 501mel melanoma cells. Treatment of these cells with the small-molecule MEK inhibitor AZD6244 induces hyperpigmentation, widespread gene expression changes including alteration of genes linked to pigmentation, and extensive epigenomic reprogramming of transcriptionally distinct regulatory regions associated with the active chromatin mark H3K27ac. Regulatory regions with differentially acetylated H3K27ac regions following AZD6244 treatment are enriched in transcription factor binding motifs of ETV/ETS and ATF family members as well as the lineage-determining factors MITF and SOX10. H3K27ac-dense enhancer clusters known as super-enhancers show similar transcription factor motif enrichment, and furthermore, these super-enhancers are associated with genes encoding MITF, SOX10, and ETV/ETS proteins. Along with genome-wide resetting of the active enhancer landscape, MEK inhibition also results in widespread SOX10 recruitment throughout the genome, including increased SOX10 binding density at H3K27ac-marked enhancers. Importantly, these MEK inhibitor-responsive enhancers marked by H3K27ac and occupied by SOX10 are located near melanocyte lineage-specific and pigmentation genes and overlap numerous human SNPs associated with pigmentation and melanoma phenotypes, highlighting the variants located within these regions for prioritization in future studies.

Conclusions

These results reveal the epigenetic reprogramming underlying the re-activation of melanocyte pigmentation and developmental transcriptional programs in 501mel cells in response to MEK inhibition and suggest extensive involvement of a MEK-SOX10 axis in the regulation of these processes. The dynamic chromatin changes identified here provide a rich genomic resource for further analyses of the molecular mechanisms governing the MAPK pathway in pigmentation- and melanocyte-associated diseases.

Electronic supplementary material

The online version of this article (10.1186/s13072-019-0297-2) contains supplementary material, which is available to authorized users.