Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

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. RESULTS: We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. CONCLUSION: The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at

Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach

The evolution of bacterial populations has recently become considerably better understood due to large-scale sequencing of population samples. It has become clear that DNA sequences from a multitude of genes, as well as a broad sample coverage of a target population, are needed to obtain a relatively unbiased view of its genetic structure and the patterns of ancestry connected to the strains. However, the traditional statistical methods for evolutionary inference, such as phylogenetic analysis, are associated with several difficulties under such an extensive sampling scenario, in particular when a considerable amount of recombination is anticipated to have taken place. To meet the needs of large-scale analyses of population structure for bacteria, we introduce here several statistical tools for the detection and representation of recombination between populations. Also, we introduce a model-based description of the shape of a population in sequence space, in terms of its molecular variability and affinity towards other populations. Extensive real data from the genus Neisseria are utilized to demonstrate the potential of an approach where these population genetic tools are combined with an phylogenetic analysis. The statistical tools introduced here are freely available in BAPS 5.2 software, which can be downloaded from http://web.abo.fi/fak/mnf/mate/jc/software/baps.html

Local Population Structure and Patterns of Western Hemisphere Dispersal for Coccidioides spp., the Fungal Cause of Valley Fever.

UnlabelledCoccidioidomycosis (or valley fever) is a fungal disease with high morbidity and mortality that affects tens of thousands of people each year. This infection is caused by two sibling species, Coccidioides immitis and C. posadasii, which are endemic to specific arid locales throughout the Western Hemisphere, particularly the desert southwest of the United States. Recent epidemiological and population genetic data suggest that the geographic range of coccidioidomycosis is expanding, as new endemic clusters have been identified in the state of Washington, well outside the established endemic range. The genetic mechanisms and epidemiological consequences of this expansion are unknown and require better understanding of the population structure and evolutionary history of these pathogens. Here we performed multiple phylogenetic inference and population genomics analyses of 68 new and 18 previously published genomes. The results provide evidence of substantial population structure in C. posadasii and demonstrate the presence of distinct geographic clades in central and southern Arizona as well as dispersed populations in Texas, Mexico, South America, and Central America. Although a smaller number of C. immitis strains were included in the analyses, some evidence of phylogeographic structure was also detected in this species, which has been historically limited to California and Baja, Mexico. Bayesian analyses indicated that C. posadasii is the more ancient of the two species and that Arizona contains the most diverse subpopulations. We propose a southern Arizona-northern Mexico origin for C. posadasii and describe a pathway for dispersal and distribution out of this region.ImportanceCoccidioidomycosis, or valley fever, is caused by the pathogenic fungi Coccidioides posadasii and C. immitis The fungal species and disease are primarily found in the American desert southwest, with spotted distribution throughout the Western Hemisphere. Initial molecular studies suggested a likely anthropogenic movement of C. posadasii from North America to South America. Here we comparatively analyze eighty-six genomes of the two Coccidioides species and establish local and species-wide population structures to not only clarify the earlier dispersal hypothesis but also provide evidence of likely ancestral populations and patterns of dispersal for the known subpopulations of C. posadasii

Colonization and dispersal patterns of the invasive American brine shrimp Artemia franciscana (Branchiopoda: Anostraca) in the Mediterranean region

Cysts of the brine shrimp Artemia franciscana are harvested from the Great Salt Lake (GSL) and San Francisco Bay (SFB) saltworks in the USA, and marketed worldwide to provide live food for aquaculture. This species has become invasive across several countries. We investigated (1) if the introduced populations in the Mediterranean region could have originated from these USA populations, (2) how the genetic diversity of Mediterranean compares to that at GSL and SFB, and (3) if genetic patterns in the Mediterranean can shed light on colonization routes. We sequenced a fragment of the cytochrome c oxidase subunit I and screened microsatellites loci from Mediterranean populations and the two putative USA sources. Haplotypes from Mediterranean populations were identical or closely related to those from SFB and GSL, and not related to other available American populations. Microsatellite analyses showed a reduced population diversity for most Mediterranean populations suggesting bottleneck effects, but few populations were showing similar or higher genetic diversity than native ones, which are likely to be admixed from both GSL and SFB because of multiple introductions. Results suggest natural dispersal, potentially via flamingos, between two Spanish populations. Our analyses show that all invaded populations could have originated from those commercialized USA populations. © 2013 Springer Science+Business Media Dordrecht

Genetic Assignment Methods for Gaining Insight into the Management of Infectious Disease by Understanding Pathogen, Vector, and Host Movement

For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease

Genetic structure of the threatened West-Pannonian population of Great Bustard (Otis tarda).

The genetic diversity, population structure and gene flow of the Great Bustards (Otis tarda) living in Austria-Slovakia-West Hungary (West-Pannonian region), one of the few populations of this globally threatened species that survives across the Palaearctic, has been assessed for the first time in this study. Fourteen recently developed microsatellite loci identified one single population in the study area, with high values of genetic diversity and gene flow between two different genetic subunits. One of these subunits (Heideboden) was recognized as a priority for conservation, as it could be crucial to maintain connectivity with the central Hungarian population and thus contribute to keeping contemporary genetic diversity. Current conservation efforts have been successful in saving this threatened population from extinction two decades ago, and should continue to guarantee its future survival

Genetic structure of the Mon-Khmer speaking groups and their affinity to the neighbouring Tai populations in Northern Thailand

<p>Abstract</p> <p>Background</p> <p>The Mon-Khmer speaking peoples inhabited northern Thailand before the arrival of the Tai speaking people from southern China in the thirteenth century A.D. Historical and anthropological evidence suggests a close relationship between the Mon-Khmer groups and the present day majority northern Thai groups. In this study, mitochondrial and Y-chromosomal DNA polymorphisms in more than 800 volunteers from eight Mon-Khmer and ten Tai speaking populations were investigated to estimate the degree of genetic divergence between these major linguistic groups and their internal structure.</p> <p>Results</p> <p>A large fraction of genetic variation is observed within populations (about 80% and 90% for mtDNA and the Y-chromosome, respectively). The genetic divergence between populations is much higher in Mon-Khmer than in Tai speaking groups, especially at the paternally inherited markers. The two major linguistic groups are genetically distinct, but only for a marginal fraction (1 to 2%) of the total genetic variation. Genetic distances between populations correlate with their linguistic differences, whereas the geographic distance does not explain the genetic divergence pattern.</p> <p>Conclusions</p> <p>The Mon-Khmer speaking populations in northern Thailand exhibited the genetic divergence among each other and also when compared to Tai speaking peoples. The different drift effects and the post-marital residence patterns between the two linguistic groups are the explanation for a small but significant fraction of the genetic variation pattern within and between them.</p