Determinant genes of craniofacial morphology and their application to the development of a molecular portrait

• Autores: Belén Navarro López
• Directores de la Tesis: Marian Martínez de Pancorbo Gómez (codir. tes.), Íñigo Olalde (codir. tes.)
• Lectura: En la Gobierno Vasco = Eusko Jaurlaritza ( España ) en 2025
• Idioma: español
• Número de páginas: 292
• Enlaces
  • Tesis en acceso abierto en: ADDI
• Resumen

  • The ability to predict an individual's facial appearance from a DNA sample would represent a significant breakthrough in Forensic Science. In cases where no individual is available for DNA profile matching or when witnesses are absent, DNA from a biological trace could generate a facial portrait that would greatly aid the identification process. With this aim, this work focuses on studying previously identified genetic markers within a Spanish population to assess their correlation with facial morphology. The goal is to pinpoint the most significant SNPs shaping facial traits and to develop DNA-based predictive models capable of generating facial portraits. For this purpose, a set of 157 candidate SNPs, 116 previously related to facial morphology and 41 associated with iris, hair and skin pigmentation, have been studied in a cohort of 530 individuals from the Spanish population. This population presents an unexplored yet promising option because of its well-defined biological environment and the extensive genetic contribution of various subpopulations. 3D facial scans were collected, and an anthropological analysis of morphofacial variation was conducted using two approaches: the physical anthropology and the MeshMonk segmentation method. Subsequently, a genetic study of the selected SNPs was performed, followed by an association analysis between these SNPs and the morphological variations. This revealed significant correlations across different facial measurements and regions. Finally, we have developed different DNA-based predictive models for specific facial measurements and indices, yielding promising results. Although not yet definitive, these models support the feasibility of predicting facial features from DNA, suggesting a valuable future role for FDP in aiding human identification.