Demographic modeling of admixed Latin American populations from whole genomes.

Demographic models of Latin American populations often fail to fully capture their complex evolutionary history, which has been shaped by both recent admixture and deeper-in-time demographic events. To address this gap, we used high-coverage whole-genome data from Indigenous American ancestries in present-day Mexico and existing genomes from across Latin America to infer multiple demographic models that capture the impact of different timescales on genetic diversity. Our approach, which combines analyses of allele frequencies and ancestry tract length distributions, represents a significant improvement over current models in predicting patterns of genetic variation in admixed Latin American populations. We jointly modeled the contribution of European, African, East Asian, and Indigenous American ancestries into present-day Latin American populations. We infer that the ancestors of Indigenous Americans and East Asians diverged ∼30 thousand years ago, and we characterize genetic contributions of recent migrations from East and Southeast Asia to Peru and Mexico. Our inferred demographic histories are consistent across different genomic regions and annotations, suggesting that our inferences are robust to the potential effects of linked selection. In conjunction with published distributions of fitness effects for new nonsynonymous mutations in humans, we show in large-scale simulations that our models recover important features of both neutral and deleterious variation. By providing a more realistic framework for understanding the evolutionary history of Latin American populations, our models can help address the historical under-representation of admixed groups in genomics research and can be a valuable resource for future studies of populations with complex admixture and demographic histories.

Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times.

BACKGROUND: Homoplasy affects demographic inference estimates. This effect has been recognized and corrective methods have been developed. However, no studies so far have defined what homoplasy metrics best describe the effects on demographic inference, or have attempted to estimate such metrics in real data. Here we study how homoplasy in chloroplast microsatellites (cpSSR) affects inference of population expansion time. cpSSRs are popular markers for inferring historical demography in plants due to their high mutation rate and limited recombination. RESULTS: In cpSSRs, homoplasy is usually quantified as the probability that two markers or haplotypes that are identical by state are not identical by descent (Homoplasy index, P). Here we propose a new measure of multi-locus homoplasy in linked SSR called Distance Homoplasy (DH), which measures the proportion of pairwise differences not observed due to homoplasy, and we compare it to P and its per cpSSR locus average, which we call Mean Size Homoplasy (MSH). We use simulations and analytical derivations to show that, out of the three homoplasy metrics analyzed, MSH and DH are more correlated to changes in the population expansion time and to the underestimation of that demographic parameter using cpSSR. We perform simulations to show that Approximate Bayesian Computation (ABC) can be used to obtain reasonable estimates of MSH and DH. Finally, we use ABC to estimate the expansion time, MSH and DH from a chloroplast SSR dataset in Pinus caribaea. To our knowledge, this is the first time that homoplasy has been estimated in population genetic data. CONCLUSIONS: We show that MSH and DH should be used to quantify how homoplasy affects estimates of population expansion time. We also demonstrate how ABC provides a methodology to estimate homoplasy in population genetic data.

Genetic, morphological, geographical and ecological approaches reveal phylogenetic relationships in complex groups, an example of recently diverged pinyon pine species (Subsection Cembroides).

Elucidating phylogenetic relationships and species boundaries within complex taxonomic groups is challenging for intrinsic and extrinsic (i.e., technical) reasons. Mexican pinyon pines are a complex group whose phylogenetic relationships and species boundaries have been widely studied but poorly resolved, partly due to intrinsic ecological and evolutionary features such as low morphological and genetic differentiation caused by recent divergence, hybridization and introgression. Extrinsic factors such as limited sampling and difficulty in selecting informative molecular markers have also impeded progress. Some of the Mexican pinyon pines are of conservation concern but others may remain unprotected because the species boundaries have not been established. In this study we combined approaches to resolve the phylogenetic relationships in this complex group and to establish species boundaries in four recently diverged taxa: P. discolor, P. johannis, P. culminicola and P. cembroides. We performed phylogenetic analyses using the chloroplast markers matK and psbA-trnH as well as complete and partial chloroplast genomes of species of Subsection Cembroides. Additionally, we performed a phylogeographic analysis combining genetic data (18 chloroplast markers), morphological data and geographical data to define species boundaries in four recently diverged taxa. Ecological divergence was supported by differences in climate among localities for distinct genetic lineages. Whereas the phylogenetic analysis inferred with matK and psbA-trnH was unable to resolve the relationships in this complex group, we obtained a resolved phylogeny with the use of the chloroplast genomes. The resolved phylogeny was concordant with a haplotype network obtained using chloroplast markers. In species with potential for recent divergence, hybridization or introgression, nonhierarchical network-based approaches are probably more appropriate to protect against misclassification due to incomplete lineage sorting. The boundaries among genetic lineages were delimited by the inclusion of morphological, geographical and ecological data in the haplotype network. These multiple lines of evidence help to assign species boundaries in this complex group. P. johannis, P. discolor, P. culminicola and P. cembroides are different species based on their genetic, morphological and ecological niche differences. We suggest a reevaluation of the conservation status of these species considering the information generated in this study.

New genes in traditional seed systems: diffusion, detectability and persistence of transgenes in a maize metapopulation.

Gene flow of transgenes into non-target populations is an important biosafety concern. The case of genetically modified (GM) maize in Mexico has been of particular interest because of the country's status as center of origin and landrace diversity. In contrast to maize in the U.S. and Europe, Mexican landraces form part of an evolving metapopulation in which new genes are subject to evolutionary processes of drift, gene flow and selection. Although these processes are affected by seed management and particularly seed flow, there has been little study into the population genetics of transgenes under traditional seed management. Here, we combine recently compiled data on seed management practices with a spatially explicit population genetic model to evaluate the importance of seed flow as a determinant of the long-term fate of transgenes in traditional seed systems. Seed flow between farmers leads to a much wider diffusion of transgenes than expected by pollen movement alone, but a predominance of seed replacement over seed mixing lowers the probability of detection due to a relative lack of homogenization in spatial frequencies. We find that in spite of the spatial complexities of the modeled system, persistence probabilities under positive selection are estimated quite well by existing theory. Our results have important implications concerning the feasibility of long term transgene monitoring and control in traditional seed systems.