Digital quantification of human eye color highlights genetic association of three new loci

Evolutionary insights into Felidae iris color through ancestral state reconstruction

Few studies have explored eye (iris) color evolution beyond humans and domesticated animals. Felids exhibit significant eye color diversity, unlike their brown-eyed relatives, making them an ideal model to study the evolution of eye color in natural populations. Through machine learning analysis of public photographs, five felid eye colors were identified: brown, green, yellow, gray, and blue. The presence or absence of these colors was reconstructed on a phylogeny, as well as their specific quantitative shades. The ancestral felid population likely had brown-eyed and gray-eyed individuals, the latter color being pivotal for the diversification of eye color seen in modern felids. Additionally, yellow eyes are highly associated with and may be necessary for, the evolution of round pupils in felids. These findings enhance the understanding of eye color evolution, and the methods presented in this work are widely applicable and will facilitate future research into the phylogenetic reconstruction of color beyond irises.

Exploring Eye, Hair, and Skin Pigmentation in a Spanish Population: Insights from Hirisplex-S Predictions

BACKGROUND/OBJECTIVES

Understanding and predicting human pigmentation traits is crucial for individual identification. Genome-wide association studies have revealed numerous pigmentation-associated SNPs, indicating genetic overlap among pigmentation traits and offering the potential to develop predictive models without the need for analyzing large numbers of SNPs.

METHODS

In this study, we assessed the performance of the HIrisPlex-S system, which predicts eye, hair, and skin color, on 412 individuals from the Spanish population. Model performance was calculated using metrics including accuracy, area under the curve, sensitivity, specificity, and positive and negative predictive value.

RESULTS

Our results showed high prediction accuracies (70% to 97%) for blue and brown eyes, brown hair, and intermediate skin. However, challenges arose with the remaining categories. The model had difficulty distinguishing between intermediate eye colors and similar shades of hair and exhibited a significant percentage of individuals with incorrectly predicted dark and pale skin, emphasizing the importance of careful interpretation of final predictions. Future studies considering quantitative pigmentation may achieve more accurate predictions by not relying on categories. Furthermore, our findings suggested that not all previously established SNPs showed a significant association with pigmentation in our population. For instance, the number of markers used for eye color prediction could be reduced to four while still maintaining reasonable predictive accuracy within our population.

CONCLUSIONS

Overall, our results suggest that it may be possible to reduce the number of SNPs used in some cases without compromising accuracy. However, further validation in larger and more diverse populations is essential to draw firm conclusions and make broader generalizations.

Predictive accuracy of genetic variants for eye color in a Kazakh population using the IrisPlex system

OBJECTIVE

This study assesses the accuracy of the IrisPlex system, a genetic eye color prediction tool for forensic analysis, in the Kazakh population. The study compares previously published genotypes of 515 Kazakh individuals from varied geographical and ethnohistorical contexts with phenotypic data on their eye color, introduced for the first time in this research.

RESULTS

The IrisPlex panel's effectiveness in predicting eye color in the Kazakh population was validated. It exhibited slightly lower accuracy than in Western European populations but was higher than in Siberian populations. The sensitivity was notably high for brown-eyed individuals (0.99), but further research is needed for blue and intermediate eye colors. This study establishes IrisPlex as a useful predictive tool in the Kazakh population and provides a basis for future investigations into the genetic basis of phenotypic variations in this diverse population.

Photosensitivity and self-induction in patients aged 50 and older

OBJECTIVE

Photosensitivity is known to occur predominantly in children and adolescents and with a clear female predominance. Little is known on the prevalence of photosensitivity in older patients (50+) and its phenotypical appearance.

METHODS

A retrospective observational study was performed investigating the prevalence of a photoparoxysmal EEG response (PPR) on at least one EEG during the period 2015-2021. Data were gathered from patients aged 50 years and older by retrieving clinical and EEG characteristics from existing medical records. Data on photosensitivity-related symptoms in daily life were gathered with telephone interviewing.

RESULTS

In 248 patients a PPR had been elicited, of whom 16 patients (6.5%) were 50 years or older. In older patients, photosensitivity was a persistent feature of childhood-onset epilepsy (n = 8), of adult-onset epilepsy (n = 7), or an incidental finding (n = 1). In the 50+ group, 56% of photosensitive patients was female, whereas 72% in the total PPR-group. In six of 16 older patients, eye closure sensitivity was observed; two of these patients reported self-induction. Symptoms of photosensitivity in daily life were present in eight out of nine patients who consented in a telephone interview. For seven of these patients, wearing sunglasses was helpful.

SIGNIFICANCE

Female preponderance for photosensitivity was not found in epilepsy patients of 50 years and older. In 44% of the older photosensitive patients in this series, the PPR was a feature of adult-onset epilepsy. Symptoms of photosensitivity in daily life in older patients with epilepsy seem comparable to those in younger patients, and thus worthwhile to diagnose and treat them equally.

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this "simulation mis-specification" problem can be framed as a "domain adaptation" problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods-SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using the domain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this "simulation mis-specification" problem can be framed as a "domain adaptation" problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods-SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using the domain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.

Competing endogenous RNA analysis identified lncRNA DSCR9 as a novel prognostic biomarker associated with metastasis and tumor microenvironment in renal cell carcinoma

Distant metastasis is the main cause of death in patients with clear cell renal carcinoma (ccRCC). The dysregulation of the tumor microenvironment is responsible for tumorigenesis and metastasis in ccRCC. The role of long non-coding RNAs in the tumor immune of ccRCC remains unclear. The present study screened differentially expressed protein-coding genes and non-coding genes between ccRCC and normal tissues based on three datasets. The commonly deregulated genes were used to identify distant metastasis-related long non-coding RNAs (lncRNAs) and prognostic lncRNAs. Pearson correlation analysis was used to identify immune-related lncRNAs. A competing endogenous RNA network was constructed and hub lncRNAs were identified. A total of 1650 coding genes, 821 lncRNAs and 62 miRNAs were commonly deregulated in the three datasets. A total of 408 lncRNAs associated with the overall survival of patients with ccRCC were identified. Among them, 82 lncRNAs were distant metastasis-related. Further analysis identified 52 lncRNAs associated with the immune pathway. Functional analyses concordantly demonstrated the role of the 52 lncRNAs in metastasis and tumor immunology. The ceRNA network analysis indicated lncRNA DSCR9 as the key lncRNA regulator. Univariate and multivariate analysis in two independent cohorts validated that DSCR9 could be an independent risk factor for the progression-free survival of patients with ccRCC. Further analyses indicated that DSCR9 might be associated with the immunotherapeutic response. reverse transcription-quantitative PCR demonstrated that the RNA expression level of DSCR9 was upregulated in ccRCC compared with normal kidney samples. The present study demonstrated the potential of LncRNA DSCR9 in assessing the prognosis and developing future immunotherapy for patients with metastatic ccRCC.

Human genetic history on the Tibetan Plateau in the past 5100 years

Using genome-wide data of 89 ancient individuals dated to 5100 to 100 years before the present (B.P.) from 29 sites across the Tibetan Plateau, we found plateau-specific ancestry across plateau populations, with substantial genetic structure indicating high differentiation before 2500 B.P. Northeastern plateau populations rapidly showed admixture associated with millet farmers by 4700 B.P. in the Gonghe Basin. High genetic similarity on the southern and southwestern plateau showed population expansion along the Yarlung Tsangpo River since 3400 years ago. Central and southeastern plateau populations revealed extensive genetic admixture within the plateau historically, with substantial ancestry related to that found in southern and southwestern plateau populations. Over the past ~700 years, substantial gene flow from lowland East Asia further shaped the genetic landscape of present-day plateau populations. The high-altitude adaptive EPAS1 allele was found in plateau populations as early as in a 5100-year-old individual and showed a sharp increase over the past 2800 years.

Increased histological tumour pigmentation in Uveal Melanoma is related to eye colour and loss of chromosome 3/BAP1

Purpose

Heavy pigmentation is known to be a prognostic risk factor in uveal melanoma (UM). We analyzed whether genetic tumor parameters were associated with tumor pigmentation and whether pigmentation should be included in prognostic tests.

Design

Retrospective comparison of clinical, histopathological, and genetic features and survival in UM with different pigmentation.

Participants

A total of 1058 patients with UM from a White European population with diverse eye colors enucleated between 1972 and 2021.

Methods

Cox regression and log-rank tests were used for survival analysis; the chi-square test and Mann-Whitney U test were used for correlation analysis.

Main Outcome Measures

Uveal melanoma-related survival based on tumor pigmentation and chromosome status, correlation of tumor pigmentation with prognostic factors.

Results

The 5-year UM-related mortality was 8% in patients with nonpigmented tumors (n = 54), 25% with lightly pigmented tumors (n = 489), 41% with moderately pigmented tumors (n = 333), and 33% with dark tumors (n = 178) (P < 0.001). The percentage of tumors with monosomy 3 (M3) or 8q gain increased with increasing pigmentation (31%, 46%, 62%, and 70% having M3 [P < 0.001], and 19%, 43%, 61%, and 63% having 8q gain [P < 0.001] in the 4 increasing pigment groups, respectively). BRCA-associated protein 1 (BAP1) loss (known for 204 cases) was associated with increased tumor pigmentation (P = 0.001). Cox regression analysis on survival showed that when chromosome status and pigmentation were both included, pigmentation was not an independent prognostic indicator. Preferentially expressed antigen in melanoma (PRAME) expression was a significant prognostic marker in light tumors (P = 0.02) but not in dark tumors (P = 0.85).

Conclusions

Patients with moderately and heavily pigmented tumors showed a significantly higher UM-related mortality than patients with unpigmented and light tumors (P < 0.001), supporting prior reports on the relation between increased tumor pigmentation and a worse prognosis. Although we previously showed that a dark eye color was associated with tumor pigmentation, we now show that the tumor's genetic status (chromosome 3 and 8q/BAP1 status) is also related to tumor pigmentation. When pigmentation and chromosome 3 status are both included in a Cox regression analysis, pigmentation is not an independent prognostic factor. However, evidence from this and previous studies shows that chromosome changes and PRAME expression have a stronger association with survival when they occur in light tumors than in dark ones. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

Mendelian randomization analyses in ocular disease: a powerful approach to causal inference with human genetic data

Ophthalmic epidemiology is concerned with the prevalence, distribution and other factors relating to human eye disease. While observational studies cannot avoid confounding factors from interventions, human eye composition and structure are unique, thus, eye disease pathogenesis, which greatly impairs quality of life and visual health, remains to be fully explored. Notwithstanding, inheritance has had a vital role in ophthalmic disease. Mendelian randomization (MR) is an emerging method that uses genetic variations as instrumental variables (IVs) to avoid confounders and reverse causality issues; it reveals causal relationships between exposure and a range of eyes disorders. Thus far, many MR studies have identified potentially causal associations between lifestyles or biological exposures and eye diseases, thus providing opportunities for further mechanistic research, and interventional development. However, MR results/data must be interpreted based on comprehensive evidence, whereas MR applications in ophthalmic epidemiology have some limitations worth exploring. Here, we review key principles, assumptions and MR methods, summarise contemporary evidence from MR studies on eye disease and provide new ideas uncovering aetiology in ophthalmology.

Applicability of the IrisPlex system for eye color prediction in an admixed population from Argentina

Eye color prediction based on an individual's genetic information is of interest in the field of forensic genetics. In recent years, researchers have studied different genes and markers associated with this externally visible characteristic and have developed methods for its prediction. The IrisPlex represents a validated tool for homogeneous populations, though its applicability in populations of mixed ancestry is limited, mainly regarding the prediction of intermediate eye colors. With the aim of validating the applicability of this system in an admixed population from Argentina (n = 302), we analyzed the six single nucleotide variants used in that multiplex for eye color and four additional SNPs, and evaluated its prediction ability. We also performed a genotype-phenotype association analysis. This system proved to be useful when dealing with the extreme ends of the eye color spectrum (blue and brown) but presented difficulties in determining the intermediate phenotypes (green), which were found in a large proportion of our population. We concluded that these genetic tools should be used with caution in admixed populations and that more studies are required in order to improve the prediction of intermediate phenotypes.

A new approach to broaden the range of eye colour identifiable by IrisPlex in DNA phenotyping

IrisPlex system represents the most popular model for eye colour prediction. Based on six polymorphisms this model provides very accurate predictions that strongly depend on the definition of eye colour phenotypes. The aim of the present study was to introduce a new approach to improve eye colour prediction using the well-validated IrisPlex system. A sample of 238 individuals from a Southern Italian population was collected and for each of them a high-resolution image of eye was obtained. By quantifying eye colour variation into CIELAB space several clustering algorithms were applied for eye colour classification. Predictions with the IrisPlex model were obtained using eye colour categories defined by both visual inspection and clustering algorithms. IrisPlex system predicted blue and brown eye colour with high accuracy while it was inefficient in the prediction of intermediate eye colour. Clustering-based eye colour resulted in a significantly increased accuracy of the model especially for brown eyes. Our results confirm the validity of the IrisPlex system for forensic purposes. Although the quantitative approach here proposed for eye colour definition slightly improves its prediction accuracy, further research is still required to improve the model particularly for the intermediate eye colour prediction.

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.

MITF in Normal Melanocytes, Cutaneous and Uveal Melanoma: A Delicate Balance

Microphthalmia-associated transcription factor (MITF) is an important regulator of melanogenesis and melanocyte development. Although it has been studied extensively in cutaneous melanoma, the role of MITF in uveal melanoma (UM) has not been explored in much detail. We review the literature about the role of MITF in normal melanocytes, in cutaneous melanoma, and in UM. In normal melanocytes, MITF regulates melanocyte development, melanin synthesis, and melanocyte survival. The expression profile and the behaviour of MITF-expressing cells suggest that MITF promotes local proliferation and inhibits invasion, inflammation, and epithelial-to-mesenchymal (EMT) transition. Loss of MITF expression leads to increased invasion and inflammation and is more prevalent in malignant cells. Cutaneous melanoma cells switch between MITF-high and MITF-low states in different phases of tumour development. In UM, MITF loss is associated with loss of BAP1 protein expression, which is a marker of poor prognosis. These data indicate a dual role for MITF in benign and malignant melanocytic cells.

Investigating the genetic architecture of eye colour in a Canadian cohort

Eye color is highly variable in populations with European ancestry, ranging from low to high quantities of melanin in the iris. Polymorphisms in the HERC2/OCA2 locus have the largest effect on eye color in these populations, although other genomic regions also influence eye color. We performed genome-wide association studies of eye color in a Canadian cohort of European ancestry (N = 5,641) and investigated candidate causal variants. We uncovered several candidate causal signals in the HERC2/OCA2 region, whereas other loci likely harbor a single causal signal. We observed colocalization of eye color signals with the expression or methylation profiles of cultured primary melanocytes. Genetic correlations of eye and hair color suggest high genome-wide pleiotropy, but locus-level differences in the genetic architecture of both traits. Overall, we provide a better picture of the polymorphisms underpinning eye color variation, which may be a consequence of specific molecular processes in the iris melanocytes.

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Genome-wide association studies of eye color in 5,641 participants

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Multiple independent candidate causal variants were identified across HERC2/OCA2

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Single candidate causal variants observed on or near IRF4, SLC24A4, TYR, and TYRP1

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Colocalization of eye color signals with expression and methylation profiles

What colour are your eyes? Teaching the genetics of eye colour & colour vision. Edridge Green Lecture RCOphth Annual Congress Glasgow May 2019

Eye colour and colour perception are excellent examples to use when teaching genetics as they encompass not simply the basic Mendelian genetics of dominant, recessive and X-linked disorders, but also many of the new concepts such as non-allelic diseases, polygenic disease, phenocopies, genome-wide association study (GWAS), founder effects, gene-environment interaction, evolutionary drivers for variations, copy number variation, insertions deletions, methylation and gene inactivation. Beyond genetics, colour perception touches on concepts involving optics, physics, physiology and psychology and can capture the imagination of the population, as we saw with social media trend of "#the dress". Television shows such as Game of Thrones focused attention on the eye colour of characters, as well as their Dire-wolves and Dragons. These themes in popular culture can be leveraged as tools to teach and engage everyone in genetics, which is now a key component in all eye diseases. As the explosion of data from genomics, big data and artificial intelligence transforms medicine, ophthalmologists need to be genetically literate. Genetics is relevant, not just for Inherited Retinal Diseases and congenital abnormalities but also for the leading causes of blindness: age-related macular degeneration, glaucoma, myopia, diabetic retinopathy and cataract. Genetics should be part of the armamentarium of every practicing ophthalmologist. We need to ask every patient about their family history. In the near future, patients will attend eye clinics with genetic results showing they are at high risk of certain eye diseases and ophthalmologists will need to know how to screen, follow and treat these patients.

A Deep-Learning Approach for Inference of Selective Sweeps from the Ancestral Recombination Graph

Detecting signals of selection from genomic data is a central problem in population genetics. Coupling the rich information in the ancestral recombination graph (ARG) with a powerful and scalable deep-learning framework, we developed a novel method to detect and quantify positive selection: Selection Inference using the Ancestral recombination graph (SIA). Built on a Long Short-Term Memory (LSTM) architecture, a particular type of a Recurrent Neural Network (RNN), SIA can be trained to explicitly infer a full range of selection coefficients, as well as the allele frequency trajectory and time of selection onset. We benchmarked SIA extensively on simulations under a European human demographic model, and found that it performs as well or better as some of the best available methods, including state-of-the-art machine-learning and ARG-based methods. In addition, we used SIA to estimate selection coefficients at several loci associated with human phenotypes of interest. SIA detected novel signals of selection particular to the European (CEU) population at the MC1R and ABCC11 loci. In addition, it recapitulated signals of selection at the LCT locus and several pigmentation-related genes. Finally, we reanalyzed polymorphism data of a collection of recently radiated southern capuchino seedeater taxa in the genus Sporophila to quantify the strength of selection and improved the power of our previous methods to detect partial soft sweeps. Overall, SIA uses deep learning to leverage the ARG and thereby provides new insight into how selective sweeps shape genomic diversity.

Further insight into the global variability of the OCA2-HERC2 locus for human pigmentation from multiallelic markers

The OCA2-HERC2 locus is responsible for the greatest proportion of eye color variation in humans. Numerous studies extensively described both functional SNPs and associated patterns of variation over this region. The goal of our study is to examine how these haplotype structures and allelic associations vary when highly variable markers such as microsatellites are used. Eleven microsatellites spanning 357 Kb of OCA2-HERC2 genes are analyzed in 3029 individuals from worldwide populations. We found that several markers display large differences in allele frequency (10% to 35% difference) among Europeans, East Asians and Africans. In Europe, the alleles showing increased frequency can also discriminate individuals with (IrisPlex) predicted blue and brown eyes. Distinct haplotypes are identified around the variants C and T of the functional SNP rs12913832 (associated to blue eyes), with linkage disequilibrium r² values significant up to 237 Kb. The haplotype carrying the allele rs12913832 C has high frequency (76%) in blue eye predicted individuals (30% in brown eye predicted individuals), while the haplotype associated to the allele rs12913832 T is restricted to brown eye predicted individuals. Finally, homozygosity values reach levels of 91% near rs12913832. Odds ratios show values of 4.2, 7.4 and 10.4 for four markers around rs12913832 and 7.1 for their core haplotype. Hence, this study provides an example on the informativeness of multiallelic markers that, despite their current limited potential contribution to forensic eye color prediction, supports the use of microsatellites for identifying causing variants showing similar genetic features and history.

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.

Genetic variation affects morphological retinal phenotypes extracted from UK Biobank optical coherence tomography images

Optical Coherence Tomography (OCT) enables non-invasive imaging of the retina and is used to diagnose and manage ophthalmic diseases including glaucoma. We present the first large-scale genome-wide association study of inner retinal morphology using phenotypes derived from OCT images of 31,434 UK Biobank participants. We identify 46 loci associated with thickness of the retinal nerve fibre layer or ganglion cell inner plexiform layer. Only one of these loci has been associated with glaucoma, and despite its clear role as a biomarker for the disease, Mendelian randomisation does not support inner retinal thickness being on the same genetic causal pathway as glaucoma. We extracted overall retinal thickness at the fovea, representative of foveal hypoplasia, with which three of the 46 SNPs were associated. We additionally associate these three loci with visual acuity. In contrast to the Mendelian causes of severe foveal hypoplasia, our results suggest a spectrum of foveal hypoplasia, in part genetically determined, with consequences on visual function.

Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology

For centuries, ecologists and evolutionary biologists have used images such as drawings, paintings and photographs to record and quantify the shapes and patterns of life. With the advent of digital imaging, biologists continue to collect image data at an ever-increasing rate. This immense body of data provides insight into a wide range of biological phenomena, including phenotypic diversity, population dynamics, mechanisms of divergence and adaptation, and evolutionary change. However, the rate of image acquisition frequently outpaces our capacity to manually extract meaningful information from images. Moreover, manual image analysis is low-throughput, difficult to reproduce, and typically measures only a few traits at a time. This has proven to be an impediment to the growing field of phenomics – the study of many phenotypic dimensions together. Computer vision (CV), the automated extraction and processing of information from digital images, provides the opportunity to alleviate this longstanding analytical bottleneck. In this review, we illustrate the capabilities of CV as an efficient and comprehensive method to collect phenomic data in ecological and evolutionary research. First, we briefly review phenomics, arguing that ecologists and evolutionary biologists can effectively capture phenomic-level data by taking pictures and analyzing them using CV. Next we describe the primary types of image-based data, review CV approaches for extracting them (including techniques that entail machine learning and others that do not), and identify the most common hurdles and pitfalls. Finally, we highlight recent successful implementations and promising future applications of CV in the study of phenotypes. In anticipation that CV will become a basic component of the biologist’s toolkit, our review is intended as an entry point for ecologists and evolutionary biologists that are interested in extracting phenotypic information from digital images.

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.

Genetic loci associated with skin pigmentation in African Americans and their effects on vitamin D deficiency

A recent genome-wide association study (GWAS) in African descent populations identified novel loci associated with skin pigmentation. However, how genomic variations affect skin pigmentation and how these skin pigmentation gene variants affect serum 25(OH) vitamin D variation has not been explored in African Americans (AAs). In order to further understand genetic factors that affect human skin pigmentation and serum 25(OH)D variation, we performed a GWAS for skin pigmentation with 395 AAs and a replication study with 681 AAs. Then, we tested if the identified variants are associated with serum 25(OH) D concentrations in a subset of AAs (n = 591). Skin pigmentation, Melanin Index (M-Index), was measured using a narrow-band reflectometer. Multiple regression analysis was performed to identify variants associated with M-Index and to assess their role in serum 25(OH)D variation adjusting for population stratification and relevant confounding variables. A variant near the SLC24A5 gene (rs2675345) showed the strongest signal of association with M-Index (P = 4.0 x 10-30 in the pooled dataset). Variants in SLC24A5, SLC45A2 and OCA2 together account for a large proportion of skin pigmentation variance (11%). The effects of these variants on M-Index was modified by sex (P for interaction = 0.009). However, West African Ancestry (WAA) also accounts for a large proportion of M-Index variance (23%). M-Index also varies among AAs with high WAA and high Genetic Score calculated from top variants associated with M-Index, suggesting that other unknown genomic factors related to WAA are likely contributing to skin pigmentation variation. M-Index was not associated with serum 25(OH)D concentrations, but the Genetic Score was significantly associated with vitamin D deficiency (serum 25(OH)D levels less than 12 ng/mL) (OR, 1.30; 95% CI, 1.04-1.64). The findings support the hypothesis suggesting that skin pigmentation evolved responding to increased demand for subcutaneous vitamin D synthesis in high latitude environments.

The color of normal: How a Eurocentric focus erases pigmentation complexity

OBJECTIVES

Skin pigmentation is both a highly variable and highly visible human phenotypic trait. Investigations into the biology and origins of this variation have been the focus of research in the fields of dermatology, anthropology, and forensic science, among others. This manuscript explores how much of what we know about the biology, genetics, and evolutionary origins of pigmentation has been strongly influenced by investigations and applications that focus on lighter skin.

METHODS

I reviewed literature from the fields of dermatology, anthropology and evolutionary genetics, and forensic science to assess how perceptions of lighter skin as the "normal" state in humans can shape the ways that knowledge is gathered and applied in these fields.

RESULTS

This normalization of lighter skin has impacted common tools used in dermatology and shaped the framework of dermatological education. A strong Eurocentric bias has shaped our understanding of the genetic architecture of pigmentary traits, which influences the ways in we understand the evolutionary processes leading to modern pigmentation diversity. Finally, I discuss how these biases in pigmentation genetics work in combination with phenotypic systems that privilege predicting lighter pigmentation variation to impede accurate prediction of intermediate phenotypes, particularly in individuals with ancestry from multiple populations. This can lead to a disproportionate targeting of already over-policed populations with darker skin.

CONCLUSIONS

Potential changes to how we conceptualize clinical and basic pigmentation research may help to reduce existing health disparities and improve understanding of pigmentation genetic architecture and how this knowledge is applied in forensic contexts.

Comparison of Genome-Wide Association Scans for Quantitative and Observational Measures of Human Hair Curvature

Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10-09; observational measure lead SNP rs11803731, p = 2.1 × 10-17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures.

Genetic Heritability of Pigmentary Glaucoma and Associations With Other Eye Phenotypes

Importance

Mechanisms behind pigmentary glaucoma, a form of early-onset glaucoma that may potentially lead to severe visual impairment or blindness, are poorly understood.

Objective

To calculate the single-nucleotide polymorphism (SNP) heritability of pigmentary glaucoma and identify genetic associations with the disease.

Design, Setting and Participants

This genome-wide association study included affected individuals from Germany and control participants from the United Kingdom. Genome-wide information was obtained for patients with pigmentary glaucoma and control participants free of glaucoma by using the Illumina Human Omni Express Exome 8v1-2 chip and genomic imputation. The SNP heritability of pigmentary glaucoma was estimated through a restricted maximum likelihood analysis. Associations between the genetic variants and pigmentary glaucoma obtained from age, sex, and principal component-adjusted logistic regression models were compared with those of SNPs previously associated with other eye phenotypes using Pearson product-moment correlations. Data were collected from November 2008 to January 2018, and analysis was completed between April 2018 and August 2019.

Main Outcomes and Measures

An estimate of SNP-explained heritability for pigmentary glaucoma; correlations of effect sizes between pigmentary glaucoma and iris pigmentation and myopia; and correlations of effect sizes between pigmentary glaucoma and other eye phenotypes.

Results

A total of 227 affected individuals (mean [SD] age, 58.7 [13.3] years) and 291 control participants (mean [SD] age, 80.2 [4.9] years) were included; all were of European ancestry. The SNP heritability of pigmentary glaucoma was 0.45 (SE, 0.22; P = 6.15 × 10-10). Twelve SNPs previously reported with genome-wide significant associations with eye pigmentation were associated with pigmentary glaucoma's SNP heritability (4.9% SNP heritability; 0.022; P = 6.0 × 10-4). Pigmentary glaucoma SNP effect sizes were correlated moderately for myopia (r, 0.42 [95% CI, 0.14-0.63]; P = 4.3 × 10-3) and more strongly with those for iris pigmentation (r = -0.69 [95% CI, -0.91 to -0.20]; P = .01), although this was nonsignificant per a strict adjusted significance threshold (P < .01).

Conclusions and Relevance

These findings support the conclusion that pigmentary glaucoma may have a genetic basis and be highly heritable. Variants associated with lighter eye color and myopia appear to be associated with increased risk of pigmentary glaucoma, but no shared genetic basis with primary open-angle glaucoma (or its quantitative endophenotype of cup-disc ratio) was observed.

Iris Colour and the Risk of Developing Uveal Melanoma

Uveal melanoma (UM) is a global disease which especially occurs in elderly people. Its incidence varies widely between populations, with the highest incidence among Caucasians, and a South-to-North increase in Europe. As northern Europeans often have blond hair and light eyes, we wondered whether iris colour may be a predisposing factor for UM and if so, why. We compared the distribution of iris colour between Dutch UM patients and healthy Dutch controls, using data from the Rotterdam Study (RS), and reviewed the literature regarding iris colour. We describe molecular mechanisms that might explain the observed associations. When comparing a group of Dutch UM patients with controls, we observed that individuals from Caucasian ancestry with a green/hazel iris colour (Odds Ratio (OR) = 3.64, 95% Confidence Interval (CI) 2.57-5.14) and individuals with a blue/grey iris colour (OR = 1.38, 95% CI 1.04-1.82) had a significantly higher crude risk of UM than those with brown eyes. According to the literature, this may be due to a difference in the function of pheomelanin (associated with a light iris colour) and eumelanin (associated with a brown iris colour). The combination of light-induced stress and aging may affect pheomelanin-carrying melanocytes in a different way than eumelanin-carrying melanocytes, increasing the risk of developing a malignancy.

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.

Insights on hair, skin and eye color of ancient and contemporary Native Americans

Over the past few years, tools capable of predicting pigmentation phenotypes have been developed aiming to contribute for criminal and anthropological investigations. In this study, we used eight genetic systems to infer eye, hair, and skin color of ancient and contemporary Native Americans. To achieve this goal, we retrieved 61 SNPs from 42 samples available in free online repositories of DNA sequences. We performed pigmentation predictions using two freely available tools, HIrisPlex-S and Snipper, in addition to two other published models. This workflow made possible to predict all three phenotypes with at least one tool for 29 out of the 42 samples. Considering these 29 individuals, predictions for eye, hair, and skin color were obtained with HIrisPlex-S for 27, 28 and 27 individuals, respectively, while 24, 25 and 25 individuals had such predictions with Snipper. In general, ancient and contemporary Native Americans were predicted to have intermediate/brown eyes, black hair, and intermediate/darker skin pigmentation.

A multiethnic genome-wide analysis of 44,039 individuals identifies 41 new loci associated with central corneal thickness

Central corneal thickness (CCT) is one of the most heritable human traits, with broad-sense heritability estimates ranging between 0.68 to 0.95. Despite the high heritability and numerous previous association studies, only 8.5% of CCT variance is currently explained. Here, we report the results of a multiethnic meta-analysis of available genome-wide association studies in which we find association between CCT and 98 genomic loci, of which 41 are novel. Among these loci, 20 were significantly associated with keratoconus, and one (RAPSN rs3740685) was significantly associated with glaucoma after Bonferroni correction. Two-sample Mendelian randomization analysis suggests that thinner CCT does not causally increase the risk of primary open-angle glaucoma. This large CCT study explains up to 14.2% of CCT variance and increases substantially our understanding of the etiology of CCT variation. This may open new avenues of investigation into human ocular traits and their relationship to the risk of vision disorders.

Genome-wide association studies for iris pigmentation and heterochromia patterns in Large White pigs

Eye colour genetics have been extensively studied in humans since the rediscovery of Mendel's laws. This trait was first interpreted using simplistic genetic models but soon it was realised that it is more complex. In this study, we analysed eye colour variability in a Large White pig population (n = 897) and report the results of GWASs based on several comparisons including pigs having four main eye colour categories (three with both pigmented eyes of different brown grades: pale, 17.9%; medium, 14.8%; and dark, 54.3%; another one with both eyes completely depigmented, 3.8%) and heterochromia patterns (heterochromia iridis - depigmented iris sectors in pigmented irises, 3.2%; heterochromia iridum - one whole eye iris of depigmented phenotype and the other eye with the iris completely pigmented, 5.9%). Pigs were genotyped with the Illumina PorcineSNP60 BeadChip and GEMMA was used for the association analyses. The results indicated that SLC45A2 (on chromosome 16, SSC16), EDNRB (SSC11) and KITLG (SSC5) affect the different grades of brown pigmentation of the eyes, the bilateral eye depigmentation defect and the heterochromia iridis defect recorded in this white pig population respectively. These genes are involved in several mechanisms affecting pigmentation. Significant associations for the eye depigmented patterns were also identified for SNPs on two SSC4 regions (including two candidate genes: NOTCH2 and PREX2) and on SSC6, SSC8 and SSC14 (including COL17A1 as candidate gene). This study provided useful information to understand eye pigmentation mechanisms, further valuing the pig as animal model to study complex phenotypes in humans.

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.

An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data

Most current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. Our method CLUES treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also infer the trajectory of a SNP (EDAR) in Han Chinese, finding evidence that this allele's age is much older than previously claimed. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, including ASIP, KITLG, and TYR. However, selection on OCA2/HERC2 seems to be much older and, in contrast to previous claims, we find no evidence of selection on TYRP1.

Meta-analysis of GWA studies provides new insights on the genetic architecture of skin pigmentation in recently admixed populations

BACKGROUND

Association studies in recently admixed populations are extremely useful to identify the genetic architecture of pigmentation, due to their high genotypic and phenotypic variation. However, to date only four Genome-Wide Association Studies (GWAS) have been carried out in these populations.

RESULTS

We present a GWAS of skin pigmentation in an admixed sample from Cuba (N = 762). Additionally, we conducted a meta-analysis including the Cuban sample, and admixed samples from Cape Verde, Puerto Rico and African-Americans from San Francisco. This meta-analysis is one of the largest efforts so far to characterize the genetic basis of skin pigmentation in admixed populations (N = 2,104). We identified five genome-wide significant regions in the meta-analysis, and explored if the markers observed in these regions are associated with the expression of relevant pigmentary genes in human melanocyte cultures. In three of the regions identified in the meta-analysis (SLC24A5, SLC45A2, and GRM5/TYR), the association seems to be driven by non-synonymous variants (rs1426654, rs16891982, and rs1042602, respectively). The rs16891982 polymorphism is strongly associated with the expression of the SLC45A2 gene. In the GRM5/TYR region, in addition to the rs1042602 non-synonymous SNP located on the TYR gene, variants located in the nearby GRM5 gene have an independent effect on pigmentation, possibly through regulation of gene expression of the TYR gene. We also replicated an association recently described near the MFSD12 gene on chromosome 19 (lead variant rs112332856). Additionally, our analyses support the presence of multiple signals in the OCA2/HERC2/APBA2 region on chromosome 15. A clear causal candidate is the HERC2 intronic variant rs12913832, which has a profound influence on OCA2 expression. This variant has pleiotropic effects on eye, hair, and skin pigmentation. However, conditional and haplotype-based analyses indicate the presence of other variants with independent effects on melanin levels in OCA2 and APBA2. Finally, a follow-up of genome-wide signals identified in a recent GWAS for tanning response indicates that there is a substantial overlap in the genetic factors influencing skin pigmentation and tanning response.

CONCLUSIONS

Our meta-analysis of skin pigmentation GWAS in recently admixed populations provides new insights about the genetic architecture of this complex trait.

A commonly occurring genetic variant within the NPLOC4-TSPAN10-PDE6G gene cluster is associated with the risk of strabismus

Strabismus refers to an abnormal alignment of the eyes leading to the loss of central binocular vision. Concomitant strabismus occurs when the angle of deviation is constant in all positions of gaze and often manifests in early childhood when it is considered to be a neurodevelopmental disorder of the visual system. As such, it is inherited as a complex genetic trait, affecting 2-4% of the population. A genome-wide association study (GWAS) for self-reported strabismus (1345 cases and 65,349 controls from UK Biobank) revealed a single genome-wide significant locus on chromosome 17q25. Approximately 20 variants across the NPLOC4-TSPAN10-PDE6G gene cluster and in almost perfect linkage disequilibrium (LD) were most strongly associated (lead variant: rs75078292, OR = 1.26, p = 2.24E-08). A recessive model provided a better fit to the data than an additive model. Association with strabismus was independent of refractive error, and the degree of association with strabismus was minimally attenuated after adjustment for amblyopia. The association with strabismus was replicated in an independent cohort of clinician-diagnosed children aged 7 years old (116 cases and 5084 controls; OR = 1.85, p = 0.009). The associated variants included 2 strong candidate causal variants predicted to have functional effects: rs6420484, which substitutes tyrosine for a conserved cysteine (C177Y) in the TSPAN10 gene, and a 4-bp deletion variant, rs397693108, predicted to cause a frameshift in TSPAN10. The population-attributable risk for the locus was approximately 8.4%, indicating an important role in conferring susceptibility to strabismus.

Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb

Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods.

Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches

Predicting phenotypes from DNA has recently become extensively studied field in forensic research and is referred to as Forensic DNA Phenotyping. Systems based on single nucleotide polymorphisms for accurate prediction of iris, hair and skin color in global population, independent of bio-geographical ancestry, have recently been introduced. Here, we analyzed 14 SNPs for distinct skin pigmentation traits in a homogeneous cohort of 222 Polish subjects. We compared three different algorithms: General Linear Model based on logistic regression, Random Forest and Neural Network in 18 developed prediction models. We demonstrate Random Forest to be the most accurate algorithm for 3- and 4-category estimations (total of 58.3% correct calls for skin color prediction, 47.2% for tanning prediction, 50% for freckling prediction). Binomial Logistic Regression was the best approach in 2-category estimations (total of 69.4% correct calls, AUC = 0.673 for tanning prediction; total of 52.8% correct calls, AUC = 0.537 for freckling prediction). Our study confirms the association of rs12913832 (HERC2) with all three skin pigmentation traits, but also variants associated solely with certain pigmentation traits, namely rs6058017 and rs4911414 (ASIP) with skin sensitivity to sun and tanning abilities, rs12203592 (IRF4) with freckling and rs4778241 and rs4778138 (OCA2) with skin color and tanning. Finally, we assessed significant differences in allele frequencies in comparison with CEU data and our study provides a starting point for the development of prediction models for homogeneous populations with less internal differentiation than in the global predictive testing.

The contribution of myostatin (MSTN) and additional modifying genetic loci to race distance aptitude in Thoroughbred horses racing in different geographic regions

BACKGROUND

Race distance aptitude in Thoroughbred horses is highly heritable and is influenced largely by variation at the myostatin gene (MSTN).

OBJECTIVES

In addition to MSTN, we hypothesised that other modifying loci contribute to best race distance.

STUDY DESIGN

Using 3006 Thoroughbreds, including 835 'elite' horses, which were >3 years old, had race records and were sampled from Europe/Middle-East, Australia/New Zealand, North America and South Africa, we performed genome-wide association (GWA) tests and separately developed a genomic prediction algorithm to comprehensively catalogue additive genetic variation contributing to best race distance.

METHODS

48,896 single-nucleotide polymorphism (SNP) genotypes were generated from high-density SNP genotyping arrays. Heritability estimates, tests of GWA and genomic prediction models were derived for the phenotypes: average race distance, best race distance for elite, nonelite and all winning horses.

RESULTS

Heritability estimates were high ( h m 2  = 0.51, best race distance - elite; h m 2  = 0.42, best race distance - nonelite; h m 2  = 0.40, best race distance - all) and most of the variation was attributed to the MSTN gene. MSTN locus SNPs were the most strongly associated with the trait and included BIEC2-438999 (ECA18:66913090; P = 4.51 × 10^-110 , average race distance; P = 2.33 × 10^-42 , best race distance - elite). The genomic prediction algorithm enabled the inclusion of variation from all SNPs in a model that partitioned horses into short and long cohorts following assignment of MSTN genotype. Additional genes with minor contributions to best race distance were identified.

MAIN LIMITATIONS

The nongenetic influence of owner/trainer decisions on placement of horses in suitable races could not be controlled.

CONCLUSIONS

MSTN is the single most important genetic contributor to best race distance in the Thoroughbred. Employment of genetic prediction models will lead to more accurate placing of horses in races that are best suited to their inherited genetic potential for distance aptitude.

Genome-wide study of hair colour in UK Biobank explains most of the SNP heritability

Natural hair colour within European populations is a complex genetic trait. Previous work has established that MC1R variants are the principal genetic cause of red hair colour, but with variable penetrance. Here, we have extensively mapped the genes responsible for hair colour in the white, British ancestry, participants in UK Biobank. MC1R only explains 73% of the SNP heritability for red hair in UK Biobank, and in fact most individuals with two MC1R variants have blonde or light brown hair. We identify other genes contributing to red hair, the combined effect of which accounts for ~90% of the SNP heritability. Blonde hair is associated with over 200 genetic variants and we find a continuum from black through dark and light brown to blonde and account for 73% of the SNP heritability of blonde hair. Many of the associated genes are involved in hair growth or texture, emphasising the cellular connections between keratinocytes and melanocytes in the determination of hair colour.

Natural hair colour in Europeans is a complex genetic trait. Here, the authors carry out a genome-wide association study using UK BioBank data, suggesting that in combination with pigmentation genes, variants with roles in hair texture and growth can affect hair colouration or our perception of it.

Off-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: A resource

With recent advances in DNA sequencing technologies it has become feasible and cost effective to genotype larger marker sets for forensic purposes. Two technologies that make use of the larger marker sets have come into focus in forensic research and applications; inference of biogeographic ancestry (BGA) and forensic DNA phenotyping (FDP). These methods hold the promise to reveal information about a yet unknown perpetrator from a DNA sample. In contrast, DNA-profiling, that is a standard practice in case work, relies on matching DNA-profiles between crime scene material and suspects on a database of DNA-profiles. Markers for DNA-profiling were developed under the premise to reveal as little additional information about the human source of the profile as possible, the rationale being that personal privacy rights have to be balanced against the public interest in solving a crime. The same argument holds for markers used in BGA and FDP; these markers might also reveal information on off-target phenotypes (OTPs), that go beyond BGA and the phenotypes targeted in FDP. In particular, health related OTPs might shift the balance between privacy protection and public interest. However, to our knowledge, there is currently no convenient resource available to incorporate knowledge on OTPs in BGA and FDP assay design and application. In order to provide such a resource, we performed a systematic search for OTPs associated with a comprehensive set of markers (1766 SNPs) used or suggested to be used for BGA inference and FDP. In this set, we identified a relatively small number of 27 SNPs (1.53%) that convey information on diverse health related OTPs such as cancer risk, induced asthma, or risk of alcoholism. Some of these SNPs are commonly used for FDP and BGA across different marker sets. We conclude that the effects of SNP markers used in FDP and BGA on OTPs are currently limited, with few exceptions that should be considered in a balanced decision on assay design and application.

Genome-wide association studies for corneal and refractive astigmatism in UK Biobank demonstrate a shared role for myopia susceptibility loci

Previous studies have suggested that naturally occurring genetic variation contributes to the risk of astigmatism. The purpose of this investigation was to identify genetic markers associated with corneal and refractive astigmatism in a large-scale European ancestry cohort (UK Biobank) who underwent keratometry and autorefraction at an assessment centre. Genome-wide association studies for corneal and refractive astigmatism were performed in individuals of European ancestry (N = 86,335 and 88,005 respectively), with the mean corneal astigmatism or refractive astigmatism in fellow eyes analysed as a quantitative trait (dependent variable). Genetic correlation between the two traits was calculated using LD Score regression. Gene-based and gene-set tests were carried out using MAGMA. Single marker-based association tests for corneal astigmatism identified four genome-wide significant loci (P < 5 × 10^-8) near the genes ZC3H11B (1q41), LINC00340 (6p22.3), HERC2/OCA2 (15q13.1) and NPLOC4/TSPAN10 (17q25.3). Three of these loci also demonstrated genome-wide significant association with refractive astigmatism: LINC00340, HERC2/OCA2 and NPLOC4/TSPAN10. The genetic correlation between corneal and refractive astigmatism was 0.85 (standard error = 0.068, P = 1.37 × 10^-35). Here, we have undertaken the largest genome-wide association studies for corneal and refractive astigmatism to date and identified four novel loci for corneal astigmatism, two of which were also novel loci for refractive astigmatism. These loci have previously demonstrated association with axial length (ZC3H11B), myopia (NPLOC4), spherical equivalent refractive error (LINC00340) and eye colour (HERC2). The shared role of these novel candidate genes for astigmatism lends further support to the shared genetic susceptibility of myopia and astigmatism.

Genome-wide association studies and CRISPR/Cas9-mediated gene editing identify regulatory variants influencing eyebrow thickness in humans

Hair plays an important role in primates and is clearly subject to adaptive selection. While humans have lost most facial hair, eyebrows are a notable exception. Eyebrow thickness is heritable and widely believed to be subject to sexual selection. Nevertheless, few genomic studies have explored its genetic basis. Here, we performed a genome-wide scan for eyebrow thickness in 2961 Han Chinese. We identified two new loci of genome-wide significance, at 3q26.33 near SOX2 (rs1345417: P = 6.51×10(-10)) and at 5q13.2 near FOXD1 (rs12651896: P = 1.73×10(-8)). We further replicated our findings in the Uyghurs, a population from China characterized by East Asian-European admixture (N = 721), the CANDELA cohort from five Latin American countries (N = 2301), and the Rotterdam Study cohort of Dutch Europeans (N = 4411). A meta-analysis combining the full GWAS results from the three cohorts of full or partial Asian descent (Han Chinese, Uyghur and Latin Americans, N = 5983) highlighted a third signal of genome-wide significance at 2q12.3 (rs1866188: P = 5.81×10(-11)) near EDAR. We performed fine-mapping and prioritized four variants for further experimental verification. CRISPR/Cas9-mediated gene editing provided evidence that rs1345417 and rs12651896 affect the transcriptional activity of the nearby SOX2 and FOXD1 genes, which are both involved in hair development. Finally, suitable statistical analyses revealed that none of the associated variants showed clear signals of selection in any of the populations tested. Contrary to popular speculation, we found no evidence that eyebrow thickness is subject to strong selective pressure.

Assessment of rosacea symptom severity by genome-wide association study and expression analysis highlights immuno-inflammatory and skin pigmentation genes

Rosacea is a common, chronic skin disease of variable severity with limited treatment options. The cause of rosacea is unknown, but it is believed to be due to a combination of hereditary and environmental factors. Little is known about the genetics of the disease. We performed a genome-wide association study (GWAS) of rosacea symptom severity with data from 73 265 research participants of European ancestry from the 23andMe customer base. Seven loci had variants associated with rosacea at the genome-wide significance level (P < 5 × 10-8). Further analyses highlighted likely gene regions or effector genes including IRF4 (P = 1.5 × 10-17), a human leukocyte antigen (HLA) region flanked by PSMB9 and HLA-DMB (P = 2.2 × 10-15), HERC2-OCA2 (P = 4.2 × 10-12), SLC45A2 (P = 1.7 × 10-10), IL13 (P = 2.8 × 10-9), a region flanked by NRXN3 and DIO2 (P = 4.1 × 10-9), and a region flanked by OVOL1and SNX32 (P = 1.2 × 10-8). All associations with rosacea were novel except for the HLA locus. Two of these loci (HERC-OCA2 and SLC45A2) and another precedented variant (rs1805007 in melanocortin 1 receptor) with an association P value just below the significance threshold (P = 1.3 × 10-7) have been previously associated with skin phenotypes and pigmentation, two of these loci are linked to immuno-inflammation phenotypes (IL13 and PSMB9-HLA-DMA) and one has been associated with both categories (IRF4). Genes within three loci (PSMB9-HLA-DMA, HERC-OCA2 and NRX3-DIO2) were differentially expressed in a previously published clinical rosacea transcriptomics study that compared lesional to non-lesional samples. The identified loci provide specificity of inflammatory mechanisms in rosacea, and identify potential pathways for therapeutic intervention.