Inferring population histories using cultural data

The question as to whether cultures evolve in a manner analogous to that of genetic evolution can be addressed by attempting to reconstruct population histories using cultural data. As others have argued, this can only succeed if cultures are isolated enough to maintain and pass on a central core of traditions that can be modified over time. In this study we used a set of cultural data (canoe design traits from Polynesia) to look for the kinds of patterns and relationships normally found in population genetic studies. After developing new techniques to accommodate the peculiarities of cultural data, we were able to infer an ancestral region (Fiji) and a sequence of cultural origins for these Polynesian societies. In addition, we found evidence of cultural exchange, migration and a serial founder effect. Results were stronger when analyses were based on functional traits (presumably subject to natural selection and convergence) rather than symbolic or stylistic traits (probably subject to cultural selection for rapid divergence). These patterns strongly suggest that cultural evolution, while clearly affected by cultural exchange, is also subject to some of the same processes and constraints as genetic evolution.     

Inference of bacterial microevolution using multilocus sequence data

We describe a model-based method for using multilocus sequence data to infer the clonal relationships of bacteria and the chromosomal position of homologous recombination events that disrupt a clonal pattern of inheritance. The key assumption of our model is that recombination events introduce a constant rate of substitutions to a contiguous region of sequence. The method is applicable both to multilocus sequence typing (MLST) data from a few loci and to alignments of multiple bacterial genomes. It can be used to decide whether a subset of isolates share common ancestry, to estimate the age of the common ancestor, and hence to address a variety of epidemiological and ecological questions that hinge on the pattern of bacterial spread. It should also be useful in associating particular genetic events with the changes in phenotype that they cause. We show that the model outperforms existing methods of subdividing recombinogenic bacteria using MLST data and provide examples from Salmonella and Bacillus. The software used in this article, ClonalFrame, is available from http://bacteria.stats.ox.ac.uk/.     

Inference of population structure using multilocus genotype data

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.     

Calculating bootstrap probabilities of phylogeny using multilocus sequence data

Phylogeny estimation is extremely crucial in the study of molecular evolution. The increase in the amount of available genomic data facilitates phylogeny estimation from multilocus sequence data. Although maximum likelihood and Bayesian methods are available for phylogeny reconstruction using multilocus sequence data, these methods require heavy computation, and their application is limited to the analysis of a moderate number of genes and taxa. Distance matrix methods present suitable alternatives for analyzing huge amounts of sequence data. However, the manner in which distance methods can be applied to multilocus sequence data remains unknown. Here, we suggest new procedures to estimate molecular phylogeny using multilocus sequence data and evaluate its significance in the framework of the distance method. We found that concatenation of the multilocus sequence data may result in incorrect phylogeny estimation with an extremely high bootstrap probability (BP), which is due to incorrect estimation of the distances and intentional ignorance of the intergene variations. Therefore, we suggest that the distance matrices for multilocus sequence data be estimated separately and these matrices be subsequently combined to reconstruct phylogeny instead of phylogeny reconstruction using concatenated sequence data. To calculate the BPs of the reconstructed phylogeny, we suggest that 2-stage bootstrap procedures be adopted; in this, genes are resampled followed by resampling of the sequence columns within the resampled genes. By resampling the genes during calculation of BPs, intergene variations are properly considered. Via simulation studies and empirical data analysis, we demonstrate that our 2-stage bootstrap procedures are more suitable than the conventional bootstrap procedure that is adopted after sequence concatenation.     

Estimating selfing rates from reconstructed pedigrees using multilocus genotype data

Several methods have been developed to estimate the selfing rate of a population from a sample of individuals genotyped for several marker loci. These methods can be based on homozygosity excess (or inbreeding), identity disequilibrium, progeny array (PA) segregation or population assignment incorporating partial selfing. Progeny array-based method is generally the best because it is not subject to some assumptions made by other methods (such as lack of misgenotyping, absence of biparental inbreeding and presence of inbreeding equilibrium), and it can reveal other facets of a mixed-mating system such as patterns of shared paternity. However, in practice, it is often difficult to obtain PAs, especially for animal species. In this study, we propose a method to reconstruct the pedigree of a sample of individuals taken from a monoecious diploid population practicing mixed mating, using multilocus genotypic data. Selfing and outcrossing events are then detected when an individual derives from identical parents and from two distinct parents, respectively. Selfing rate is estimated by the proportion of selfed offspring in the reconstructed pedigree of a sample of individuals. The method enjoys many advantages of the PA method, but without the need of a priori family structure, although such information, if available, can be utilized to improve the inference. Furthermore, the new method accommodates genotyping errors, estimates allele frequencies jointly and is robust to the presence of biparental inbreeding and inbreeding disequilibrium. Both simulated and empirical data were analysed by the new and previous methods to compare their statistical properties and accuracies.     

Inferring species-level phylogenies and taxonomic distinctiveness using multilocus data in Sistrurus rattlesnakes

Phylogenetic relationships and taxonomic distinctiveness of closely related species and subspecies are most accurately inferred from data derived from multiple independent loci. Here, we apply several approaches for understanding species-level relationships using data from 18 nuclear DNA loci and 1 mitochondrial DNA locus within currently described species and subspecies of Sistrurus rattlesnakes. Collectively, these methods provide evidence that a currently described species, the massasauga rattlesnake (Sistrurus catenatus), consists of two well-supported clades, one composed of the two western subspecies (S. c. tergeminus and S. c. edwardsii) and the other the eastern subspecies (S. c. catenatus). Within pigmy rattlesnakes (S. miliarius), however, there is not strong support across methods for any particular grouping at the subspecific level. Monophyly based tests for taxonomic distinctiveness show evidence for distinctiveness of all subspecies but this support is strongest by far for the S. c. catenatus clade. Because support for the distinctiveness of S. c. catenatus is both strong and consistent across methods, and due to its morphological distinctiveness and allopatric distribution, we suggest that this subspecies be elevated to full species status, which has significant conservation implications. Finally, most divergence time estimates based upon a fossil-calibrated species tree are > 50% younger than those from a concatenated gene tree analysis and suggest that an active period of speciation within Sistrurus occurred within the late Pliocene/Pleistocene eras.     

A model-based method for identifying species hybrids using multilocus genetic data

We present a statistical method for identifying species hybrids using data on multiple, unlinked markers. The method does not require that allele frequencies be known in the parental species nor that separate, pure samples of the parental species be available. The method is suitable for both markers with fixed allelic differences between the species and markers without fixed differences. The probability model used is one in which parentals and various classes of hybrids (F(1)'s, F(2)'s, and various backcrosses) form a mixture from which the sample is drawn. Using the framework of Bayesian model-based clustering allows us to compute, by Markov chain Monte Carlo, the posterior probability that each individual belongs to each of the distinct hybrid classes. We demonstrate the method on allozyme data from two species of hybridizing trout, as well as on two simulated data sets.     

Test of colonisation scenarios reveals complex invasion history of the red tomato spider mite Tetranychus evansi

The spider mite Tetranychus evansi is an emerging pest of solanaceous crops worldwide. Like many other emerging pests, its small size, confusing taxonomy, complex history of associations with humans, and propensity to start new populations from small inocula, make the study of its invasion biology difficult. Here, we use recent developments in Approximate Bayesian Computation (ABC) and variation in multi-locus genetic markers to reconstruct the complex historical demography of this cryptic invasive pest. By distinguishing among multiple pathways and timing of introductions, we find evidence for the "bridgehead effect", in which one invasion serves as source for subsequent invasions. Tetranychus evansi populations in Europe and Africa resulted from at least three independent introductions from South America and involved mites from two distinct sources in Brazil, corresponding to highly divergent mitochondrial DNA lineages. Mites from southwest Brazil (BR-SW) colonized the African continent, and from there Europe through two pathways in a "bridgehead" type pattern. One pathway resulted in a widespread invasion, not only to Europe, but also to other regions in Africa, southern Europe and eastern Asia. The second pathway involved the mixture with a second introduction from BR-SW leading to an admixed population in southern Spain. Admixture was also detected between invasive populations in Portugal. A third introduction from the Brazilian Atlantic region resulted in only a limited invasion in Europe. This study illustrates that ABC methods can provide insights into, and distinguish among, complex invasion scenarios. These processes are critical not only in understanding the biology of invasions, but also in refining management strategies for invasive species. For example, while reported observations of the mite and outbreaks in the invaded areas were largely consistent with estimates of geographical expansion from the ABC approach, historical observations failed to recognize the complex pathways involved and the corresponding effects on genetic diversity.     

Inference of population structure using multilocus genotype data: dominant markers and null alleles

Dominant markers such as amplified fragment length polymorphisms (AFLPs) provide an economical way of surveying variation at many loci. However, the uncertainty about the underlying genotypes presents a problem for statistical analysis. Similarly, the presence of null alleles and the limitations of genotype calling in polyploids mean that many conventional analysis methods are invalid for many organisms. Here we present a simple approach for accounting for genotypic ambiguity in studies of population structure and apply it to AFLP data from whitefish. The approach is implemented in the program structure version 2.2, which is available from http://pritch.bsd.uchicago.edu/structure.html.     

Tracking traders' understanding of the market using e-communication data

Tracking the volume of keywords in Internet searches, message boards, or Tweets has provided an alternative for following or predicting associations between popular interest or disease incidences. Here, we extend that research by examining the role of e-communications among day traders and their collective understanding of the market. Our study introduces a general method that focuses on bundles of words that behave differently from daily communication routines, and uses original data covering the content of instant messages among all day traders at a trading firm over a 40-month period. Analyses show that two word bundles convey traders' understanding of same day market events and potential next day market events. We find that when market volatility is high, traders' communications are dominated by same day events, and when volatility is low, communications are dominated by next day events. We show that the stronger the traders' attention to either same day or next day events, the higher their collective trading performance. We conclude that e-communication among traders is a product of mass collaboration over diverse viewpoints that embodies unique information about their weak or strong understanding of the market.     

Inference of hazel grouse population structure using multilocus data: a landscape genetic approach

In conservation and management of species it is important to make inferences about gene flow, dispersal and population structure. In this study, we used 613 georeferenced tissue samples from hazel grouse (Bonasa bonasia) where each individual was genotyped at 12 microsatellite loci to make inference on population genetic structure, gene flow and dispersal in northern Sweden. Observed levels of genetic diversity suggest that Swedish hazel grouse do not suffer loss of genetic diversity compared with other grouse species. We found significant F(IS) (deviation from Hardy-Weinberg expectations) over the entire sample using jack-knifed estimators over loci, which is most likely explained by a Wahlund effect. With the use of spatial autocorrelation methods, we detected significant isolation by distance among individuals. Neighbourhood size was estimated in the order of 62-158 individuals corresponding to a dispersal distance of 950-1500 m. Using a spatial statistical model for landscape genetics to infer the number of populations and the spatial location of genetic discontinuities between these populations we found indications that Swedish hazel grouse are divided into a northern and a southern population. We could not find a sharp border between these two populations and none of the observed borders appeared to coincide with any potential geographical barriers.These results imply that gene flow appears somewhat unrestricted in the boreal taiga forests of northern Sweden and that the two populations of hazel grouse in Sweden may be explained by the post-glacial reinvasion history of the Scandinavian Peninsula.     

Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies

We describe extensions to the method of Pritchard et al. for inferring population structure from multilocus genotype data. Most importantly, we develop methods that allow for linkage between loci. The new model accounts for the correlations between linked loci that arise in admixed populations ("admixture linkage disequilibium"). This modification has several advantages, allowing (1) detection of admixture events farther back into the past, (2) inference of the population of origin of chromosomal regions, and (3) more accurate estimates of statistical uncertainty when linked loci are used. It is also of potential use for admixture mapping. In addition, we describe a new prior model for the allele frequencies within each population, which allows identification of subtle population subdivisions that were not detectable using the existing method. We present results applying the new methods to study admixture in African-Americans, recombination in Helicobacter pylori, and drift in populations of Drosophila melanogaster. The methods are implemented in a program, structure, version 2.0, which is available at http://pritch.bsd.uchicago.edu.     

A method for distinguishing consanguinity and population substructure using multilocus genotype data

We use the patterns of homozygosity at multiple loci to distinguish between excess homozygosity caused by consanguineous mating and that due to undetected population subdivision (the Wahlund effect). Clarification of the underlying causes of excess homozygosity is of practical importance in explaining the occurrence of recessive genetic disorders and in forensic match probability calculations. We calculated a likelihood surface for two parameters: C, the proportion of the population practicing consanguinity, and theta, the genetic correlation due population subdivision. To illustrate the method, we applied it to multilocus genotypic data of two U.K. Asian populations, one practicing a high frequency of cousin marriage, and another in which caste endogamy was suspected. The method was able to successfully distinguish the different patterns of relatedness. The method also returned accurate estimates of C and theta using simulated data sets. We show how our method can be extended to allow for degrees of inbreeding closer than cousin unions, including selfing. With closer inbreeding, the relatedness of recent ancestors beyond the parents becomes an issue.     

Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data

A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation.     

Resolving the phylogenetic relationships and evolutionary history of the Drosophila virilis group using multilocus data

The Drosophila virilis group is one of the major lineages of Drosophila previously recognised and it has been used as a model for different types of studies. It comprises 13 species whose phylogenetic relationships are not well resolved. In the present study, six nuclear genes (Adh, fused, Gpdh, NonA, CG9631 and CG7219) and the mitochondrial ribosomal RNA genes (12S-16S) have been used to estimate the evolutionary tree of the group using different methods of phylogenetic reconstruction. Different competing evolutionary hypotheses have also been compared using the Approximately Unbiased test to further evaluate the robustness of the inferred trees. Results are, in general, consistent with previous studies in recovering the four major lineages of the group (D. virilis phylad, Drosophila montana subphylad, Drosophila kanekoi subphylad and Drosophila littoralis subphylad), although D. kanekoi, D. littoralis and Drosophila ezoana are here inferred to be more closely related to the D. virilis phylad than to the D. montana subphylad. The age of the crown group, estimated with a Bayesian method that assumes a relaxed molecular clock, is placed in the late Miocene (～ 10 Mya). The oldest lineages also appeared during this period (～ 7.5 to ～ 8.9 Mya), while the ages of the basal nodes of the montana subphylad and the virilis phylad are located in the early Pliocene (～ 4.9 and ～ 4.1 Mya). Major cladogenesis events correlate to geological and palaeoclimatic occurrences that most likely affected the freshwater and deciduous forests where these species are found. The inferred biogeographical history of the group, based on the statistical dispersal-vicariance analysis, indicates that the last common ancestor of the group had a Holarctic distribution from which the North American and the Eurasian lineages evolved as a result of a vicariant event.     

Ginkgo: spatially-explicit simulator of complex phylogeographic histories

We present Ginkgo, a software package for agent-based, forward-time simulations of genealogies of multiple unlinked loci from diploid populations. Ginkgo simulates the evolution of one or more species on a spatially explicit landscape of cells. The user of the software can specify the geographical and environmental characteristics of the landscape, and these properties can change according to a prespecified schedule. The geographical elements modelled include the arrangement of cells and movement rates between particular cells. Each species has a function that can calculate a fitness score for any combination of an individual organism's phenotype and environmental characteristics. The user can control the number of fitness factors (the dimensionality of the cell-specific fitness factors and the individuals phenotypic vectors) and the weighting of each of these dimensions in the fitness calculation. Cell-specific fitness trait optima can be specified across the landscape to mimic differences in habitat. In addition to their differing fitness functions, species can differ in terms of their vagility and fecundity. Genealogies and occurrence data can be produced at any time during the simulation in NEXUS and ESRI Ascii Grid formats, respectively.     

Global optimal eBURST analysis of multilocus typing data using a graphic matroid approach

Background  

Multilocus Sequence Typing (MLST) is a frequently used typing method for the analysis of the clonal relationships among strains of several clinically relevant microbial species. MLST is based on the sequence of housekeeping genes that result in each strain having a distinct numerical allelic profile, which is abbreviated to a unique identifier: the sequence type (ST). The relatedness between two strains can then be inferred by the differences between allelic profiles. For a more comprehensive analysis of the possible patterns of evolutionary descent, a set of rules were proposed and implemented in the eBURST algorithm. These rules allow the division of a data set into several clusters of related strains, dubbed clonal complexes, by implementing a simple model of clonal expansion and diversification. Within each clonal complex, the rules identify which links between STs correspond to the most probable pattern of descent. However, the eBURST algorithm is not globally optimized, which can result in links, within the clonal complexes, that violate the rules proposed.     

LIAN 3.0: detecting linkage disequilibrium in multilocus data. Linkage Analysis

SUMMARY: LIAN is a program to test the null hypothesis of linkage equilibrium for multilocus data. LIAN incorporates both a Monte Carlo method as well as a novel algebraic method to carry out the hypothesis test. The program further returns the genetic diversity of the sample and the pairwise distances between its members.     

RETRACTED ARTICLE: An analysis of population structure and linkage disequilibrium using multilocus data in 187 maize inbred lines

This study analyzes population structure and linkage disequilibrium (LD) among 187 commonly used Chinese maize inbred lines, representing the genetic diversity among public, commercial and historically important lines for corn breeding. Seventy SSR loci, evenly distributed over 10 chromosomes, were assayed for polymorphism. The identified 290 alleles served to estimate population structure and analyze the genome-wide LD. The population of lines was highly structured, showing 6 subpopulations: BSSS (American BSSS including Reid), PA (group A germplasm derived from modern U.S. hybrids in China), PB (group B germplasm derived from modern U.S. hybrid in China), Lan (Lancaster Surecrop), LRC (derivative lines from Lvda Reb Cob, a Chinese landrace) and SPT (derivative lines from Si-ping-tou, a Chinese landrace). Forty lines, which formerly had an unknown and/or miscellaneous origin and pedigree record, were assigned to the appropriate group. Relationship estimates based on SSR marker data were quantified in a Q matrix, and this information will inform breeder’s decisions regarding crosses. Extensive inter- and intra-chromosomal LD was detected between 70 microsatellite loci for the investigated maize lines (2109 loci pairs in LD with D′ > 0.1 and 93 out of them at P < 0.01).This suggests that rapidly evolving microsatellites may track recent population structure. Interlocus LD decay among the diverse maize germplasm indicated that association studies in QTLs and/or candidate genes might avoid nonfunctional and spurious associations since most of the LD blocks were broken between diverse germplasm. The defined population structure and the LD analysis present the basis for future association mapping. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.