Understanding the genetic diversity within and between populations has important implications for studies of human disease and evolution. This includes identifying associations between genetic variants and disease, detecting genomic regions that have undergone positive selection and highlighting interesting aspects of human population history.
Now, a team of researchers from the UCLA Henry Samueli School of Engineering and Applied Science, UCLA’s Department of Ecology and Evolutionary Biology and Israel’s Tel Aviv University has developed an innovative approach to the study of genetic diversity called spatial ancestry analysis (SPA), which allows for the modeling of genetic variation in two- or three-dimensional space. Their study is published online this week in the journal Nature Genetics.
With SPA, researchers can model the spatial distribution of each genetic variant by assigning a genetic variant’s frequency as a continuous function in geographic space. By doing this, they show that the explicit modeling of the genetic variant frequency — the proportion of individuals who carry a specific variant — allows individuals to be localized on a world map on the basis of their genetic information alone.