The genetic study of diverging, closely related populations is required for basic questions on demography and speciation, as well as for biodiversity and conservation research. However, it is often unclear whether divergence is due simply to separation or whether populations have also experienced gene flow. These questions can be addressed with a full model of population separation with gene flow, by applying a Markov chain Monte Carlo method for estimating the posterior probability distribution of model parameters. We have generalized this method and made it applicable to data from multiple unlinked loci. These loci can vary in their modes of inheritance, and inheritance scalars can be implemented either as constants or as parameters to be estimated. By treating inheritance scalars as parameters it is also possible to address variation among loci in the impact via linkage of recurrent selective sweeps or background selection. These methods are applied to a large multilocus data set from Drosophila pseudoobscura and D. persimilis. The species are estimated to have diverged ‫000,005ف‬ years ago. Several loci have nonzero estimates of gene flow since the initial separation of the species, with considerable variation in gene flow estimates among loci, in both directions between the species.

In 1988, Felsenstein described a framework for assessing the likelihood of a genetic data set in which all of the possible genealogical histories of the data are considered, each in proportion to their probability. Although not analytically solvable, several approaches, including Markov chain Monte Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint posterior density of the model parameters. For many purposes, this function can be treated as a likelihood, thereby permitting likelihood-based analyses, including likelihood ratio tests of nested models. Several examples, including an application to the divergence of chimpanzee subspecies, are provided.speciation ͉ population structure ͉ divergence P opulation genetic and phylogenetic models that take a genealogical (i.e., gene tree) approach suffer two nested levels of ambiguity. First, the uncertainty of an estimate of a genealogy can be large and difficult to quantify, and second, it can be difficult to interpret a genealogy estimate explicitly in terms of an evolutionary or population genetics model. In his 1988 review, Felsenstein (1) conceptualized a way thru these uncertainties by positioning the genealogy as a nuisance variable in the definition of the likelihood of the parameters given the data (proportional to the sampling probability of the data):

A method for studying the divergence of multiple closely related populations is described and assessed. The approach of Hey and Nielsen (2007, Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc Natl Acad Sci USA. 104:2785-2790) for fitting an isolation-with-migration model was extended to the case of multiple populations with a known phylogeny. Analysis of simulated data sets reveals the kinds of history that are accessible with a multipopulation analysis. Necessarily, processes associated with older time periods in a phylogeny are more difficult to estimate; and histories with high levels of gene flow are particularly difficult with more than two populations. However, for histories with modest levels of gene flow, or for very large data sets, it is possible to study large complex divergence problems that involve multiple closely related populations or species.

The domestication of all major crop plants occurred during a brief period in human history about 10,000 years ago. During this time, ancient agriculturalists selected seed of preferred forms and culled out seed of undesirable types to produce each subsequent generation. Consequently, favoured alleles at genes controlling traits of interest increased in frequency, ultimately reaching fixation. When selection is strong, domestication has the potential to drastically reduce genetic diversity in a crop. To understand the impact of selection during maize domestication, we examined nucleotide polymorphism in teosinte branched1, a gene involved in maize evolution. Here we show that the effects of selection were limited to the gene's regulatory region and cannot be detected in the protein-coding region. Although selection was apparently strong, high rates of recombination and a prolonged domestication period probably limited its effects. Our results help to explain why maize is such a variable crop. They also suggest that maize domestication required hundreds of years, and confirm previous evidence that maize was domesticated from Balsas teosinte of southwestern Mexico.

The divergence of Drosophila pseudoobscura from its close relatives, D. persimilis and D. pseudoobscura bogotana, was examined using the pattern of DNA sequence variation in a common set of 50 inbred lines at 11 loci from diverse locations in the genome. Drosophila pseudoobscura and D. persimilis show a marked excess of low-frequency variation across loci, consistent with a model of recent population expansion in both species. The different loci vary considerably, both in polymorphism levels and in the levels of polymorphisms that are shared by different species pairs. A major question we address is whether these patterns of shared variation are best explained by gene flow or by persistence since common ancestry. A new test of gene flow, based on patterns of linkage disequilibrium, is developed. The results from these, and other tests, support a model in which D. pseudoobscura and D. persimilis have exchanged genes at some loci. However, the pattern of variation suggests that most gene flow, although occurring after speciation began, was not recent. There is less evidence of gene flow between D. pseudoobscura and D. p. bogotana. The results are compared with recent work on the genomic locations of genes that contribute to reproductive isolation between D. pseudoobscura and D. persimilis. We show that there is a good correspondence between the genomic regions associated with reproductive isolation and the regions that show little or no evidence of gene flow.