Anthropological genomics researcher Mark Shriver at Penn State has teamed up with scientists in the university’s forensics department to leverage big data, DNA, and 3D imaging to translate a drop of blood into a facial recognition tool.
Shriver’s lab conducts various studies using a method known as “admixture mapping,” which helps them identify ancestral genes linked to facial traits, combined with population genomics to understand those genes’ evolutionary histories. Summarizing their peer-reviewed paper, published in PLOS Genetics last week, Shriver and his team explained:
“… features such as the strength of the brow ridge, the spacing between the eyes, the width of the nose, and the shape of the philtrum are largely scientifically unexplained. Here, we use a novel method to measure face shape in population samples with mixed West African and European ancestry from three locations (United States, Brazil, and Cape Verde). We show that facial variation with regard to sex, ancestry, and genes can be systematically studied with our methods, allowing us to lay the foundation for predictive modeling of faces.”
The scientists collected data on skin pigmentation, gender, ancestry, height, and weight from each of 592 subjects, aged 18-40. They also collected a DNA blood sample from each, and used 3dMDface system technology to obtain an image of each subject bearing a neutral expression. By examining a set of 20 genes that have been shown to have significant effects on facial features, the researchers were able to show how genetic markers in a subject’s DNA could enable a predictive model of his or her facial appearance.
The scientists explained that the tool could be useful in diagnostic tools, in forensics —”DNA left at crime scenes could be tested and faces predicted in order to help to narrow the pool of potential suspects”—and in predicting “facial features of descendants, deceased ancestors, and even extinct human species.”