The ancestry of the Colombian population comprises a large number of well differentiated Native communities belonging to diverse linguistic groups. In the late fifteenth century, a process of admixture was initiated with the arrival of the Europeans, and several years later, Africans also became part of the Colombian population. Therefore, the genepool of the current Colombian population results from the admixture of Native Americans, Europeans and Africans. This admixture occurred differently in each region of the country, producing a clearly stratified population. Considering the importance of population substructure in both clinical and forensic genetics, we sought to investigate and compare patterns of genetic ancestry in Colombia by studying samples from Native and non-Native populations living in its 5 continental regions: the Andes, Caribe, Amazonia, Orinoquía, and Pacific regions. For this purpose, 46 AIM-Indels were genotyped in 761 non-related individuals from current populations. Previously published genotype data from 214 Colombian Natives from five communities were used for population comparisons. Significant differences were observed between Native and non-Native populations, among non-Native populations from different regions and among Native populations from different ethnic groups. The Pacific was the region with the highest African ancestry, Amazonia harboured the highest Native ancestry and the Andean and Orinoquían regions showed the highest proportion of European ancestry. The Andean region was further sub-divided into 6 sub-regions: North East, Central West, Central East, West, South West and South East. Among these regions, the South West region showed a significantly lower European admixture than the other regions. Hardy-Weinberg equilibrium and variance values of ancestry among individuals within populations showed a potential stratification of the Pacific population.
Pubmed ID: 27736937 RIS Download
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A software tool for maximum likelihood estimation of individual ancestries from multilocus SNP genotype datasets. It uses the same statistical model as STRUCTURE but calculates estimates much more rapidly using a fast numerical optimization algorithm. It uses a block relaxation approach to alternately update allele frequency and ancestry fraction parameters. Each block update is handled by solving a large number of independent convex optimization problems, which are tackled using a fast sequential quadratic programming algorithm. Convergence of the algorithm is accelerated using a novel quasi-Newton acceleration method.
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