Abstract
The idea of creating a recognizable face from a sample of DNA is moving closer to reality as Oak Ridge National Laboratory (ORNL) researchers employ a novel statistical representation of the face and a genome-wide association study (GWAS) to relate facial characteristics to genetic mutations. The reduction in cost of DNA sequencing and genotyping technology is leading to the availability of massive datasets of human genome sequences and human genotypes representing mutational variation among people. These large-scale data provide for the first time the potential to correlate an individual’s specific genetic code with their physical appearance. Using a specialized statistical method for representing the entire 3D shape of faces, ORNL researchers performed a GWAS to discover associations between genetic mutations and aspects of face shape. Data from 3,556 subjects resulted in the discovery of a very large set of statistically significant associations, which is strong evidence for the viability of predicting faces from DNA.