Genetic Ancestry Inference: from AIMS to WGS application and challenges in admixed population

Increasingly, the inference of genetic ancestry plays a prominent role in clinical, population and forensic genetics studies. Over the last few decades, several genotyping strategies and analytical methodologies have been developed in order to assign individuals to specific biogeographic regions. However, despite all these efforts, the ancestry inference in populations with a recent history of admixture, such as those in America, is still a challenge. In admixed populations, proportion and components of genetic ancestry vary at different levels: (i) between populations; (ii) between individuals of the same population; (iii) throughout the individual's genome. In the present study we compared and evaluated different sets of markers, from those with small numbers of ancestry informative markers panels (AIMs), to high-density SNPs (HDSNP) and whole-genome-sequence (WGS) data. To this end, we evaluated 1,675 admixed samples from America, using a tetrahybrid admixture model (Native American, European, African and East Asian). Analyses show greater variation in the correlation coefficient of ancestry components within and between admixed populations, especially for minority ancestral components. We also observed, the higher the number of markers in the AIMs panel, the higher the correlation with HDSNP and WGS. In addition, the greater the number of markers, the more robust was the tetrahybrid admixture model.