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Finding valid indicators of emotional states is one of the biggest challenges in animal welfare science. Here, we investigated in horses whether variation in the expression of eye wrinkles caused by contraction of the inner eyebrow raiser reflects emotional valence. By confronting horses with positive and negative conditions, we aimed to induce positive and negative emotional states, hypothesising that positive emotions would reduce whereas negative emotions would increase eye wrinkle expression. Sixteen horses were individually exposed in a balanced order to two positive (grooming, food anticipation) and two negative conditions (food competition, waving a plastic bag). Each condition lasted for 60 seconds and was preceded by a 60 second control phase. Throughout both phases, pictures of the eyes were taken, and for each horse four pictures per condition and phase were randomly selected. Pictures were scored in random order and by two experimenters blind to condition and phase for six outcome measures: qualitative impression, eyelid shape, markedness of the wrinkles, presence of eye white, number of wrinkles, and the angle between the line through the eyeball and the highest wrinkle. The angle decreased during grooming and increased during food competition compared to control phases, whereas the two phases did not differ during food anticipation and the plastic bag condition. No effects on the other outcome measures were detected. Taken together, we have defined a set of measures to assess eye wrinkle expression reliably, of which one measure was affected by the conditions the horses were exposed to. Variation in eye wrinkle expression might provide valuable information on horse welfare but further validation of specific measures across different conditions is needed.

Forensic DNA phenotyping (FDP) is a technique used to predict an individual’s physical appearance traits based on DNA. Eye color, a highly heritable genetic trait, is one of the most obvious and distinguishable externally visible characteristics (EVCs) employed in human identification. Genotype-phenotype association studies have focused on detecting single nucleotide polymorphisms (SNPs) located in and nearby genes directly or indirectly involved in pigment synthesis. In this study, we investigated 66 SNPs related to pigment production and their efficacy in predicting eye color for forensic purposes. Using bioinformatics and machine learning techniques, we analyzed these SNPs in 438 admixed individuals with diverse phenotypes from Southern Brazil. We introduce BR-FDP-EYE, a system for phenotype prediction from DNA. This eye color predictor utilizes five to seven SNPs to classify phenotypes, achieving an overall accuracy of up to 85%. Users can select from four classification methods. The first option is a five-class classifier (BR-FDP-EYE-5), distinguishing Blue, Green, Hazel, Light Brown, and Dark Brown eye colors. While this classifier demonstrates high sensitivity for the Blue and Dark Brown classes (81%–87%), it exhibits lower sensitivity for the remaining three classes (up to 33%). Alternatively, users can choose one of three three-class classifiers, depending on their specific needs: BR-FDP-EYE-3-I for Blue, Intermediate (Green ＋ Hazel ＋ Light Brown), and Dark Brown; BR-FDP-EYE-3-II for Light (Blue ＋ Green), Hazel, and Brown (Light Brown ＋ Dark Brown); and BR-FDP-EYE-3-III for Blue, Intermediate (Green ＋ Hazel), and Brown (Light Brown ＋ Dark Brown). These three-class classifiers improve overall accuracy and enhance per-class metrics, providing a more balanced performance for targeted applications. BR-FDP-EYE offers a simple, user-friendly interface suitable for genetics and anthropological research, educational purposes, and potentially, law enforcement investigations. •BR-FDP-EYE is a simple-to-use system for eye phenotype prediction through DNA.•With 5–7 SNPs, ML models can predict eye color in an admixed population.•Population-specific approaches in the development of predictive methods are needed.

The eye color of birds, generally referring to the color of the iris, results from both pigmentation and structural coloration. Avian iris colors exhibit striking interspecific and intraspecific variations that correspond to unique evolutionary and ecological histories. Here, we identified the genetic basis of pearl (white) iris color in domestic pigeons ( Columba livia ) to explore the largely unknown genetic mechanism underlying the evolution of avian iris coloration. Using a genome-wide association study (GWAS) approach in 92 pigeons, we mapped the pearl iris trait to a 9 kb region containing the facilitative glucose transporter gene SLC2A11B . A nonsense mutation (W49X) leading to a premature stop codon in SLC2A11B was identified as the causal variant. Transcriptome analysis suggested that SLC2A11B loss of function may downregulate the xanthophore-differentiation gene CSF1R and the key pteridine biosynthesis gene GCH1 , thus resulting in the pearl iris phenotype. Coalescence and phylogenetic analyses indicated that the mutation originated approximately 5,400 years ago, coinciding with the onset of pigeon domestication, while positive selection was likely associated with artificial breeding. Within Aves, potentially impaired SLC2A11B was found in six species from six distinct lineages, four of which associated with their signature brown or blue eyes and lack of pteridine. Analysis of vertebrate SLC2A11B orthologs revealed relaxed selection in the avian clade, consistent with the scenario that during and after avian divergence from the reptilian ancestor, the SLC2A11B-involved development of dermal chromatophores likely degenerated in the presence of feather coverage. Our findings provide new insight into the mechanism of avian iris color variations and the evolution of pigmentation in vertebrates.

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.

One of the greatest strengths of Drosophila genetics is its easily observable and selectable phenotypic markers. The mini-white marker has been widely used as a transgenic marker for Drosophila transgenesis. Flies carrying a mini-white construct can exhibit various eye colors ranging from pale orange to intense red, depending on the insertion site and gene dosage. Because the two copies of the mini-white marker show a stronger orange color, this is often used for selecting progenies carrying two transgenes together in a single chromosome after chromosomal recombination. However, some GAL4 lines available in the fly community originally have very strong red eyes. Without employing another marker, such as GFP, generating a recombinant chromosome with the strong red-eyed GAL4 and a desired UAS-transgene construct may be difficult. Therefore, we decided to change the red eyes of GAL4 lines to orange color. To change the eye color of the fly, we tested the CRISPR/Cas9 method with a guide RNA targeting the white gene with OK371-GAL4 and elav-GAL4. After a simple screening, we have successfully obtained multiple lines of orange-eyed OK371-GAL4 and elav-GAL4 that still maintain their original expression patterns. All of these simple experiments were performed by undergraduate students, allowing them to learn about a variety of different genetic experiments and genome editing while contributing to the fly research community by creating fruit fly lines that will be used in real-world research.

Phenotypic trait prediction in ancient DNA analysis can provide information about the external appearance of individuals from past human populations. Some studies predicting eye and hair color in ancient adult skeletons have been published, but not for ancient subadult skeletons, which are more prone to decay. In this study, eye and hair color were predicted for an early medieval adult skeleton and a subadult skeleton that was anthropologically characterized as a middle-aged man and a subadult of unknown sex about 6 years old. When processing the petrous bones, precautions were taken to prevent contamination with modern DNA. The MillMix tissue homogenizer was used for grinding, 0.5 g of bone powder was decalcified, and DNA was purified in Biorobot EZ1. The PowerQuant System was used for quantification and a customized version of the HIrisPlex panel for massive parallel sequencing (MPS) analysis. Library preparation and templating were performed on the HID Ion Chef Instrument and sequencing on the Ion GeneStudio S5 System. Up to 21 ng DNA/g of powder was obtained from ancient petrous bones. Clean negative controls and no matches with elimination database profiles confirmed no contamination issue. Brown eyes and dark brown or black hair were predicted for the adult skeleton and blue eyes and brown or dark brown hair for the subadult skeleton. The MPS analysis results obtained proved that it is possible to predict hair and eye color not only for an adult from the Early Middle Ages, but also for a subadult skeleton dating to this period.

Birds exhibit striking variation in eye color that arises from interactions between specialized pigment cells named chromatophores. The types of chromatophores present in the avian iris are lacking from the integument of birds or mammals, but are remarkably similar to those found in the skin of ectothermic vertebrates. To investigate molecular mechanisms associated with eye coloration in birds, we took advantage of a Mendelian mutation found in domestic pigeons that alters the deposition of yellow pterin pigments in the iris. Using a combination of genome-wide association analysis and linkage information in pedigrees, we mapped variation in eye coloration in pigeons to a small genomic region of ~8.5kb. This interval contained a single gene, SLC2A11B , which has been previously implicated in skin pigmentation and chromatophore differentiation in fish. Loss of yellow pigmentation is likely caused by a point mutation that introduces a premature STOP codon and leads to lower expression of SLC2A11B through nonsense-mediated mRNA decay. There were no substantial changes in overall gene expression profiles between both iris types as well as in genes directly associated with pterin metabolism and/or chromatophore differentiation. Our findings demonstrate that SLC2A11B is required for the expression of pterin-based pigmentation in the avian iris. They further highlight common molecular mechanisms underlying the production of coloration in the iris of birds and skin of ectothermic vertebrates.

Background Predicting the eye and hair color from genotype became an established and widely used tool in forensic genetics, as well as in studies of ancient human populations. However, the accuracy of this tool has been verified on the West and Central Europeans only, while populations from border regions between Europe and Asia (like Caucasus and Ural) also carry the light pigmentation phenotypes. Results We phenotyped 286 samples collected across North Eurasia, genotyped them by the standard HIrisPlex-S markers and found that predictive power in Caucasus/Ural/West Siberian populations is reasonable but lower than that in West Europeans. As these populations have genetic ancestries different from that of West Europeans, we hypothesized they may carry a somewhat different allele spectrum. Thus, for all samples we performed the exome sequencing additionally enriched with the 53 genes and intergenic regions known to be associated with the eye/hair color. Our association analysis replicated the importance of the key previously known SNPs but also identified five new markers whose eye color prediction power for the studied populations is compatible with the two major previously well-known SNPs. Four out of these five SNPs lie within the HERС2 gene and the fifth in the intergenic region. These SNPs are found at high frequencies in most studied populations. The released dataset of exomes from Russian populations can be further used for population genetic and medical genetic studies. Conclusions This study demonstrated that precision of the established systems for eye/hair color prediction from a genotype is slightly lower for the populations from the border regions between Europe and Asia that for the West Europeans. However, this precision can be improved if some newly revealed predictive SNPs are added into the panel. We discuss that the replication of these pigmentation-associated SNPs on the independent North Eurasian sample is needed in the future studies.

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.

To document the distribution of iris color in the United States of America. This original investigation is an epidemiologic assessment of eye color data from all 50 states' Department of Motor Vehicles (DMV). All driver's license holders data nationwide (age 16 years and older, both genders) were requested from the Department of Motor Vehicles (DMVs) in each state. Driver's license holders from states whose DMV did not participate in the study due to special state-specific regulations, did not compile iris color information, or did not respond were then excluded. Self reported eye color information was obtained from the DMVs databases of each driver's license applicant self-reported eye color information. All 50 states' Department of Motor Vehicles in the USA were contacted using various methods and the database of driver licenses eye color for current active licenses (without including any personal information) was requested. Any iris color beyond grey, blue, green, hazel, or brown/black was categorized as \"others\". Iris color of 235,423,085 driver's license holders (DLHs) from 31 states was collected. The data show that brown/black iris color was documented in 124,811,254 DLHs (53%), blue in 55,797,458 DLHs (23.7%), hazel in 24,152,854 DLHs (10.3%), green in 21,258,873 DLHs (9%), grey in 1,597,675 DLHs (0.7%), and other iris colors in 7,804,971 DLHs (3.3%). Utilizing information from over 230 million driver's license holders, this report is the largest study of iris color distribution representing the United States of America, thus providing a valuable source for future eye disease and other sociological research. The data show that the most prominent iris color in the United States of America is brown/black, then blue, hazel, green, other iris colors, and grey.