Source: Cell Press A collection of photographs of genetically unrelated conspecifics, along with DNA analysis, revealed that the striking facial resemblance is associated with shared genetic variations. The work appears Aug. 23 in the journal Cell Reports. “Our study provides a rare insight into human similarity, showing that people with extremely similar faces share common genotypes while being discordant at the epigenome and microbiome levels,” says senior author Manel Esteller of the Josep Carreras Leukemia Institute in Barcelona . , Spain. “Genomics brings them together and the rest separates them.” The number of people identified online as virtual twins or non-genetically related twins has increased due to the expansion of the World Wide Web and the ability to share images of people across the planet. In the new study, Esteller and his team set out to characterize, at the molecular level, random human beings who objectively share facial features. To do this, they recruited human doubles from the photographic work of François Brunelle, a Canadian artist who has been collecting lookalike photos around the world since 1999. They received photos of 32 lookalike couples. The researchers determined an objective similarity measure for the pairs using three different facial recognition algorithms. In addition, participants completed a comprehensive biometric and lifestyle questionnaire and provided saliva DNA for polyomic analysis. “This unique set of samples allowed us to study how genomics, epigenomics and microbiomics can contribute to human similarity,” says Esteller. Overall, the results revealed that these individuals share similar genotypes but differ in DNA methylation and microbiome landscapes. Half of the identical pairs were clustered by all three algorithms. Genetic analysis revealed that 9 of these 16 pairs clustered together, based on 19,277 common single nucleotide polymorphisms. Photographic examples of conspecifics used in this study. Realization: François Brunelle In addition, physical characteristics such as weight and height, as well as behavioral characteristics such as smoking and education, were correlated in matched pairs. Taken together, the results suggest that shared genetic variation is not only associated with similar physical appearance, but may also influence shared habits and behavior. “We have provided a unique insight into the molecular features that potentially influence the construction of the human face,” says Esteller. “We propose that these same determinants correlate with both the physical and behavioral characteristics that constitute human beings.” Some limitations of the study include the small sample size, the use of 2D black and white images, and the predominance of European participants. Despite these caveats, the findings may provide a molecular basis for future applications in fields as diverse as biomedicine, evolution and forensics. “These results will have future implications in forensics – reconstructing a criminal’s face from DNA – and in genetic diagnostics – a picture of a patient’s face will already give you clues as to which genome they have,” says Esteller. “Through collaborative efforts, the ultimate challenge would be to predict the structure of the human face based on the individual’s polyomic landscape.”
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Author: Press Office Source: Cell PressContact: Press Office – Cell PressImage: Image attributed to François Brunelle See also Original Research: Open Access. “Self-Looking People Recognized by Facial Recognition Algorithms Show Genetic Similarities” by François Brunelle et al. Cell references Abstract People who look alike and are recognized by facial recognition algorithms show genetic similarities
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Facial recognition algorithms identify ‘lookalike’ people for polyomics studies Identicals between pairs share common genetic sequences, such as variations in facial features DNA methylation and microbiome profiles contribute only modestly to human similarity The identified SNPs influence physical and behavioral phenotypes beyond facial features
Summary
The human face is one of the most visible features of our unique identity as individuals. Interestingly, monozygotic twins share almost identical facial features and the same DNA sequence, but could show differences in other biometric parameters. The expansion of the world wide web and the ability to share images of people across the planet has increased the number of people identified online as virtual twins or non-familial twins. Here, we have characterized in detail a set of people “look-alikes” with facial recognition algorithms, for their polyomic landscape. We report that these individuals share similar genotypes and differ in DNA methylation and microbiome landscape. These results not only provide information about the genetics that determine our face, but may also have implications for the establishment of other human anthropometric properties and even personality traits.
