A new approach to the study of genetic diversity called spatial ancestry analysis (SPA) could open up new avenues of genetic exploration.
The new approach allows for the modelling of genetic variation in two- or three-dimensional space. This could allow researchers to gain a clearer understanding of the genetic diversity within and between populations, which has important implications for studies of human disease and evolution.
Researchers from the University of California, Los Angeles Henry Samueli School of Engineering and Applied Science and Tel Aviv University developed the new approach which allows for the modelling of genetic variation in two- or three-dimensional space.

SPA Genetic Mapping Colors represent the true country of origin of the individual (also represented by country internet code). (a–d) A map generated by SPA. Iteration 1 starts with random positioning of individuals (a). By iteration 4, the northern and southern populations are separated (b). By iteration 7, the positioning of individuals is close to convergence (c). In iteration 10, individuals have reached their final positions (d). (e) A map generated by PCA9. (f) Map of Europe.
Using the new technique, researchers are able to model the spatial distribution of each genetic variant by assigning it as a continuous function in geographic space. Using this technique, they show that the explicit modelling of the genetic variant frequency allows individuals to be localised on a world map on the basis of their genetic information alone.
Eleazar Eskin, an associate professor of computer science at UCLA Engineering, said: “If we know from where each individual in our study originated, what we observe is that some variation is more common in one part of the world and less common in another part of the world.
“In this study, we think of the frequency of variation as being defined by a specific location. This gives us a different way to think about populations, which are usually thought of as being discrete. Instead, we think about the variant frequencies changing in different locations. If you think about a person’s ancestry, it is no longer about being from a specific population — but instead, each person’s ancestry is defined by the location they’re from. Now ancestry is a continuum.”
The model can actually infer geographic locations of an individual, if even it is previously unknown. They can create a geographic ancestry of an individual’s parents, even if those parents differ in ancestry.



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