A paleogenetic perspective of the Sabana de Bogotá (Northern South America) population history over the Holocene (9000 – 550 cal BP)

On the basis of distinct lines of evidence, detailed reconstructions of the Holocene population history of the Sabana de Bogotá (SB) region, Northern South America, have been performed. Currently, there exist two competing models that support temporal continuity or, alternatively, divergence. Despite recent research that lends support to the population discontinuity model, several discrepancies remain, calling for other kinds of evidences to be explored for a more detailed picture of Holocene biocultural evolution. In this study, we analyze the mitochondrial genetic diversity of 30 individuals (including 15 newly reported complete mitochondrial genomes) recovered from several archaeological sites spanning from the late Pleistocene (12,164 cal BP) until the final late Holocene (2,751 cal BP) along with published data from the region dating ∼9,000-550 cal BP in order to investigate diachronic genetic change. Genetic diversity and distance indices were calculated, and demographic models tested in an approximate Bayesian computation (ABC) framework to evaluate whether patterns of genetic affinities of the SB prehispanic populations support genetic continuity or discontinuity. The results show that mitochondrial genomes of the complete dataset fall within the Native American haplogroups A2, B2, C1b, D1 and D4h3a. Haplotype and nucleotide diversity declined over time with further evidence of genetic drift and remarkable reduction of genetic diversity during the final late Holocene. Inter-population distances and the exact test of population differentiation, as well as demographic simulations show no population differentiation and population continuity over time. Consequently, based on the analyzed data, we cannot reject the genetic continuity in the SB region as a plausible population history scenario. However, the restriction of the analyses to the Hyper Variable Region 1 of the mitochondrial genome, and the very low sample size both constitute significant limitations to infer evolutionary history.