As modern humans ventured out of Africa and dispersed around the world, they faced novel environmental challenges that led to geographic adaptations including skin colour. Over the long history of human evolution, skin colour has changed dramatically, showing tremendous diversity across different geographical regions, for example, the majority of individuals from the expansive lands of Africa have darker skin, whereas the majority of people from Eurasia exhibit lighter skin. What adaptations did lighter skin confer upon modern humans as they migrated from Africa to Eurasia? What genetic mechanisms underlie the diversity of skin colour observed in different populations? In recent years, scientists have gradually gained a deeper understanding of the interactions between pigmentation gene and skin colour through population-based genomic studies of different groups around the world, particularly in East Asia and Africa. In this review, we summarize our current understanding of 26 skin colour-related pigmentation genes and 48 SNPs that influence skin colour. Important pigmentation genes across three major populations are described in detail: MFSD12, SLC24A5, PDPK1 and DDB1/CYB561A3/TMEM138 influence skin colour in African populations; OCA2, KITLG, SLC24A2, GNPAT and PAH are key to the evolution of skin pigmentation in East Asian populations; and SLC24A5, SLC45A2, TYR, TYRP1, ASIP, MC1R and IRF4 significantly contribute to the lightening of skin colour in European populations. We summarized recent findings in genomic studies of skin colour in populations that implicate diverse geographic environments, local adaptation among populations, gene flow and multi-gene interactions as factors influencing skin colour diversity.

Various facial colour cues were identified as valid predictors of facial attractiveness, yet the conventional univariate approach has simplified the complex nature of attractiveness judgement for real human faces. Predicting attractiveness from colour cues is difficult due to the high number of candidate variables and their inherent correlations. Using datasets from Chinese subjects, this study proposed a novel analytic framework for modelling attractiveness from various colour characteristics. One hundred images of real human faces were used in experiments and an extensive set of 65 colour features were extracted. Two separate attractiveness evaluation sets of data were collected through psychophysical experiments in the UK and China as training and testing datasets, respectively. Eight multivariate regression strategies were compared for their predictive accuracy and simplicity. The proposed methodology achieved a comprehensive assessment of diverse facial colour features and their role in attractiveness judgements of real faces; improved the predictive accuracy (the best-fit model achieved an out-of-sample accuracy of 0.66 on a 7-point scale) and significantly mitigated the issue of model overfitting; and effectively simplified the model and identified the most important colour features. It can serve as a useful and repeatable analytic tool for future research on facial impression modelling using high-dimensional datasets.

Facial skin colour, a key factor related to impressions, is widely used by CG character designers to build characters with different storylines. The previous research provided essential suggestions for creating an attractive facial image. However, the suggestions of the prior research are insufficient for building the characters to resonate with the current public, especially young people. The present study investigates the influence of skin colour (whiteness and hue angle) on the femininity, masculinity and likableness perception of Chinese female and male images. A psychophysical experiment was carried out to investigate these relationships. The categorical judgement results reveal that whiteness significantly impacted the feminine-masculine perception of the Chinese male image and the likableness perception of the Chinese female and male image. This connection between the whiteness and likability of the male facial image could be related to the beauty trends in the last decade. The hue angle only significantly influenced the likability perception of the Chinese female image. This result is agreed with past research in the same area.

Forensic DNA Phenotyping (FDP), i.e. the prediction of human externally visible traits from DNA, has become a fast growing subfield within forensic genetics due to the intelligence information it can provide from DNA traces. FDP outcomes can help focus police investigations in search of unknown perpetrators, who are generally unidentifiable with standard DNA profiling. Therefore, we previously developed and forensically validated the IrisPlex DNA test system for eye colour prediction and the HIrisPlex system for combined eye and hair colour prediction from DNA traces. Here we introduce and forensically validate the HIrisPlex-S DNA test system (S for skin) for the simultaneous prediction of eye, hair, and skin colour from trace DNA. This FDP system consists of two SNaPshot-based multiplex assays targeting a total of 41 SNPs via a novel multiplex assay for 17 skin colour predictive SNPs and the previous HIrisPlex assay for 24 eye and hair colour predictive SNPs, 19 of which also contribute to skin colour prediction. The HIrisPlex-S system further comprises three statistical prediction models, the previously developed IrisPlex model for eye colour prediction based on 6 SNPs, the previous HIrisPlex model for hair colour prediction based on 22 SNPs, and the recently introduced HIrisPlex-S model for skin colour prediction based on 36 SNPs. In the forensic developmental validation testing, the novel 17-plex assay performed in full agreement with the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, as previously shown for the 24-plex assay. Sensitivity testing of the 17-plex assay revealed complete SNP profiles from as little as 63 pg of input DNA, equalling the previously demonstrated sensitivity threshold of the 24-plex HIrisPlex assay. Testing of simulated forensic casework samples such as blood, semen, saliva stains, of inhibited DNA samples, of low quantity touch (trace) DNA samples, and of artificially degraded DNA samples as well as concordance testing, demonstrated the robustness, efficiency, and forensic suitability of the new 17-plex assay, as previously shown for the 24-plex assay. Finally, we provide an update to the publically available HIrisPlex website https://hirisplex.erasmusmc.nl/, now allowing the estimation of individual probabilities for 3 eye, 4 hair, and 5 skin colour categories from HIrisPlex-S input genotypes. The HIrisPlex-S DNA test represents the first forensically validated tool for skin colour prediction, and reflects the first forensically validated tool for simultaneous eye, hair and skin colour prediction from DNA.

1. Microphthalmia-associated transcription factor (MITF) plays a pivotal role in melanocyte development by regulating the transcription of major pigmentation enzymes (e.g. TYR, TYRP1 and DCT). A single-nucleotide polymorphism (SNP), c.-638T>C, was identified in the MITF promoter, and genotyping of a population (n = 426) revealed that SNP c.-638T>C was associated with skin colour in black-boned chickens. 2. Individuals with genotypes CC and TC exhibited greater MTIF expression than those with genotype TT. Luciferase assays also revealed that genotype CC and TC promoters had higher activity levels than genotype TT. Expression of melanogenesis-related gene (TYR) was higher in the skin of chickens with the CC and CT genotype compared to TT chickens (P < 0.05). 3. Transcription factor-binding site analyses showed that the c.-638C allele contains a putative binding site for transcription factor sterol regulatory element-binding transcription factor 2, aryl hydrocarbon receptor nuclear translocator, transcription factor binding to IGHM enhancer 3 and upstream transcription factor 2. In contrast, the c.-638T allele contains binding sites for Sp3 transcription factor and Krüppel-like factor 1. 4. It was concluded that MITF promoter polymorphisms affected chicken skin colour. SNP c.-638T>C could be used for the marker-assisted selection of skin colour in black-boned chicken breeding.

BACKGROUND: Accurate skin colour measurements are important for numerous medical applications including the diagnosis and treatment of cutaneous disorders and the provision of maxillofacial soft tissue prostheses.
METHODS: In this study, we obtained accurate skin colour measurements from four different ethnic groups (Caucasian, Chinese, Kurdish, Thai) and at four different body locations (Forehead, cheek, inner arm, back of hand) with a view of establishing a new skin colour database for medical and cosmetic applications. Skin colours are measured using a spectrophotometer and converted to a device-independent standard colour appearance space (CIELAB) where skin colour is expressed as values along the three dimensions: Lightness L*, Redness a* and Yellowness b*. Skin colour differences and variation are then evaluated as a function of ethnicity and body location.
RESULTS: We report three main results: (1) When plotted in a standard colour appearance space (CIELAB), skin colour distributions for the four ethnic groups overlap significantly, although there are systematic mean differences. Between ethnicities, the most significant skin colour differences occur along the yellowness dimension, with Thai skin exhibiting the highest yellowness (b*) value and Caucasian skin the lowest value. Facial redness (a*) is invariant across the four ethnic groups. (2) Between different body locations, there are significant variations in redness (a*), with the forehead showing the highest redness value and the inner arm the lowest. (3) The colour gamut is smallest in the Chinese sample and largest in the Caucasian sample, with the Chinese gamut lying entirely the Caucasian gamut. Similarly, the largest variability in skin tones is found in the Caucasian group, and the smallest in the Chinese group.
CONCLUSIONS: Broadly speaking, skin colour variation can be explained by two main factors: individual differences in lightness and yellowness are mostly due to ethnicity, whereas differences in redness are primarily due to different body locations. Variations in lightness are more idiosyncratic probably reflecting the large influence of environmental factors such as exposure to sun.