Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions.
Bayesian statistical methods for the estimation of hidden genetic structure of populations have gained considerable popularity in the recent years. Utilizing molecular marker data, Bayesian mixture models attempt to identify a hidden population structure by clustering individuals into genetically divergent groups, whereas admixture models target at separating the ancestral sources of the alleles observed in different individuals. We discuss the difficulties involved in the simultaneous estimation of the number of ancestral populations and the levels of admixture in studied individuals' genomes. To resolve this issue, we introduce a computationally efficient method for the identification of admixture events in the population history. Our approach is illustrated by analyses of several challenging real and simulated data sets. The software (baps), implementing the methods introduced here, is freely available at http://www.rni.helsinki.fi/~jic/bapspage.html.
Enterococcus faecium, natively a gut commensal organism, emerged as a leading cause of multidrug-resistant hospital-acquired infection in the 1980s. As the living record of its adaptation to changes in habitat, we sequenced the genomes of 51 strains, isolated from various ecological environments, to understand how E. faecium emerged as a leading hospital pathogen. Because of the scale and diversity of the sampled strains, we were able to resolve the lineage responsible for epidemic, multidrug-resistant human infection from other strains and to measure the evolutionary distances between groups. We found that the epidemic hospital-adapted lineage is rapidly evolving and emerged approximately 75 years ago, concomitant with the introduction of antibiotics, from a population that included the majority of animal strains, and not from human commensal lines. We further found that the lineage that included most strains of animal origin diverged from the main human commensal line approximately 3,000 years ago, a time that corresponds to increasing urbanization of humans, development of hygienic practices, and domestication of animals, which we speculate contributed to their ecological separation. Each bifurcation was accompanied by the acquisition of new metabolic capabilities and colonization traits on mobile elements and the loss of function and genome remodeling associated with mobile element insertion and movement. As a result, diversity within the species, in terms of sequence divergence as well as gene content, spans a range usually associated with speciation.
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