Identifying and Communicating Genetic Determinants of Facial Features: Practical Considerations in Forensic Molecular Photofitting

• NCJ Number: 248591
• Author(s): Mark Shriver
• Date Published: July 2013
• Length: 95 pages
• Grant Number(s): 2008-DN-BX-K125
• Agencies: NIJ-Sponsored
• Publication Type: Report (Study/Research); Report (Grant Sponsored)
• Award: Identifying and Communicating Genetic Determinants of Facial Features:Practical Considerations in Forensic Molecular Photofitting

Annotation

This study used spatially dense quasi-landmarks to measure face shape in population samples with mixed West African and European ancestry from three locations (United States, Brazil, and Cape Verde).

Abstract

The study achieved three goals. First, it identified genes underlying variability in facial features within and among European and West African populations. This included population sample collection, phenotype of 3D photos, whole-genome marker genotyping, and gene mapping. Second, researchers assayed independent population samples in order to test for replication of significant mapping results. The replication of whole genome mapping results is important, especially for complex and multifaceted traits like human facial features. Third, the project tested for the ability of human observers to recognize the effects of individual genes on facial features and to match facial photographs with corresponding computer-generated facial reconstructions based on functional locus genotype. Of the three West African/European admixed populations, 154 were from the United States, 191 from Brazil, and 247 from Cape Verde. Each person contributed DNA and 3D facial images. Ancestry informative markers (AIMs) were used to estimate individual genomic ancestry from DNA. This report explains why admixed populations are uniquely suited to the study of the genetics of facial features. By simultaneously modeling facial-shape variation as a function of sex and genomic ancestry along with genetic markers in craniofacial candidate genes, the effects of sex and ancestry can be removed from the model, providing the ability to extract the effects of individual genes. 4 figures and 47 references