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Diego Veliz-Otani

Publications and source records attributed to Diego Veliz-Otani.

2 recordsLinked to original sources

Peruvian Population Genomics: Unraveling the Genetic Landscape and Admixture Dynamics of Urban Populations.

Latin American populations exhibit high genetic and phenotypic diversity shaped by complex admixture histories, yet remain underrepresented in genomic research. Here, we analyze genome-wide data from 432 urban individuals across 13 regions of Peru, including 346 newly genotyped from the Peruvian Genome Project. We revealed fine-scale population structure and demographic patterns shaped by both ancient and recent events. Indigenous American ancestries in urban individuals trace back to ancient north-south interactions consisted with archaeological records, while admixture events occurring within the last 8-10 generations involved sources already admixed between distinct ancestral lineages. Identity-by-descent analyses reveal sustained gene flow in southern Peru, while effective population size trends highlight demographic stability in Lima over the past 25 generations. Sex-biased admixture patterns suggest Indigenous ancestry contribution preferentially mediated by females. These findings offer a comprehensive view of Peru's genetic heritage, advancing our understanding of human genetic diversity and historical demographic processes in Latin America.

Admixture

Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas.

Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.

Humans