Geolocation prediction from STR genotyping: a pilot study in five geographically distinct global populations

Area of Science:

• Forensic genetics
• Population genetics
• Biometrics

Background:

• Short tandem repeat (STR) profiling is crucial for individual identification.
• Traditional STR analysis requires a reference sample for comparison.
• STR genotypes alone lack geolocation information without a reference.

Purpose of the Study:

• To evaluate the potential of STR-based genotypes for predicting an individual's geolocation.
• To determine if population-specific STR genotype data can be used for geolocation prediction.

Main Methods:

• Collected genotype data from five distinct populations (Caucasian, Hispanic, Asian, Estonian, Bahrainian) from published literature.
• Analyzed genotype frequencies and identified unique and most frequent genotypes within each population.
• Developed and proposed three prediction models for genotype-to-geolocation mapping.

Main Results:

• Significant differences in observed genotypes were found across populations (p < 0.05).
• STR loci D1S1656 and SE33 exhibited substantial variations in genotype frequencies.
• STRs SE33, D12S391, D21S11, D19S433, D18S51, and D1S1656 showed a high occurrence of unique genotypes.
• D12S391 and D13S317 displayed distinct population-specific frequent genotypes.

Conclusions:

• STR genotypes can be utilized for geolocation prediction, especially when no reference sample is available.
• Proposed models (unique genotypes, most frequent genotypes, combinatorial approach) can assist investigations.
• This method offers a valuable tool for forensic agencies in identifying geographic origins from genetic profiles.