In and out of refugia: historical patterns of diversity and demography in the North American Caesar's mushroom species complex

Some of the effects of past climate dynamics on plant and animal diversity make‐up have been relatively well studied, but to less extent in fungi. Pleistocene refugia are thought to harbour high biological diversity (i.e. phylogenetic lineages and genetic diversity), mainly as a product of increased reproductive isolation and allele conservation. In addition, high extinction rates and genetic erosion are expected in previously glaciated regions. Some of the consequences of past climate dynamics might involve changes in range and population size that can result in divergence and incipient or cryptic speciation. Many of these dynamic processes and patterns can be inferred through phylogenetic and coalescent methods. In this study, we first delimit species within a group of closely related edible ectomycorrhizal Amanita from North America (the American Caesar's mushrooms species complex) using multilocus coalescent‐based approaches; and then address questions related to effects of Pleistocene climate change on the diversity and genetics of the group. Our study includes extensive geographical sampling throughout the distribution range, and DNA sequences from three nuclear protein‐coding genes. Results reveal cryptic diversity and high speciation rates in refugia. Population sizes and expansions seem to be larger at midrange latitudes (Mexican highlands and SE USA). Range shifts are proportional to population size expansions, which were overall more common during the Pleistocene. This study documents responses to past climate change in fungi and also highlights the applicability of the multispecies coalescent in comparative phylogeographical analyses and diversity assessments that include ancestral species.     

Is Niagara Falls a barrier to gene flow in riverine fishes? A test using genome‐wide SNP data from seven native species

Since the early Holocene, fish population genetics in the Laurentian Great Lakes have been shaped by the dual influences of habitat structure and post‐glacial dispersal. Riverscape genetics theory predicts that longitudinal habitat corridors and unidirectional downstream water‐flow drive the downstream accumulation of genetic diversity, whereas post‐glacial dispersal theory predicts that fish genetic diversity should decrease with increasing distance from glacial refugia. This study examines populations of seven native fish species codistributed above and below the 58 m high Niagara Falls – a hypothesized barrier to gene flow in aquatic species. A better understanding of Niagara Falls’ role as a barrier to gene flow and dispersal is needed to identify drivers of Great Lakes genetic diversity and guide strategies to limit exotic species invasions. We used genome‐wide SNPs and coalescent models to test whether populations are: (a) genetically distinct, consistent with the Niagara Falls barrier hypothesis; (b) more genetically diverse upstream, consistent with post‐glacial expansion theory, or downstream, consistent with the riverscape habitat theory; and (c) have migrated either upstream or downstream past Niagara Falls. We found that genetic diversity is consistently greater below Niagara Falls and the falls are an effective barrier to migration, but two species have probably dispersed upstream past the falls after glacial retreat yet before opening of the Welland Canal. Models restricting migration to after opening of the Welland Canal were generally rejected. These results help explain how river habitat features affect aquatic species’ genetic diversity and highlight the need to better understand post‐glacial dispersal pathways.     

Ancestral processes in population genetics-the coalescent

A special stochastic process, called the coalescent, is of fundamental interest in population genetics. For a large class of population models this process is the appropriate tool to analyse the ancestral structure of a sample of n individuals or genes, if the total number of individuals in the population is sufficiently large. A corresponding convergence theorem was first proved by Kingman in 1982 for the Wright-Fisher model and the Moran model. Generalizations to a large class of exchangeable population models and to models with overlying mutation processes followed shortly later. One speaks of the "robustness of the coalescent, as this process appears in many models as the total population size tends to infinity. This publication can be considered as an introduction to the theory of the coalescent as well as a review of the most important "convergence-to-the-coalescent-theorems. Convergence theorems are not only presented for the classical exchangeable haploid case but also for larger classes of population models, for example for diploid, two-sex or non-exchangeable models. A review-like summary of further examples and applications of convergence to the coalescent is given including the most important biological forces like mutation, recombination and selection. The general coalescent process allows for simultaneous multiple mergers of ancestral lines.     

A genomic evaluation of taxonomic trends through time in coast horned lizards (genus Phrynosoma)

Determining the boundaries between species and deciding when to describe new species are challenging practices that are particularly difficult in groups with high levels of geographic variation. The coast horned lizards (Phrynosoma blainvillii, Phrynosoma cerroense and P. coronatum) have an extensive geographic distribution spanning many distinctive ecological regions ranging from northern California to the Cape Region of Baja California, Mexico, and populations differ substantially with respect to external morphology across much of this range. The number of taxa recognized in the group has been reevaluated by herpetologists over 20 times during the last 180 years, and typically without the aid of explicit species delimitation methods, resulting in a turbulent taxonomy containing anywhere from one to seven taxa. In this study, we evaluate taxonomic trends through time by ranking 15 of these species delimitation models (SDMs) using coalescent analyses of nuclear loci and SNPs in a Bayesian model comparison framework. Species delimitation models containing more species were generally favoured by Bayesian model selection; however, several three‐species models outperformed some four‐ and five‐species SDMs, and the top‐ranked model, which contained five species, outperformed all SDMs containing six species. Model performance peaked in the 1950s based on marginal likelihoods estimated from nuclear loci and SNPs. Not surprisingly, SDMs based on genetic data outperformed morphological taxonomies when using genetic data alone to evaluate models. The de novo estimation of population structure favours a three‐population model that matches the currently recognized integrative taxonomy containing three species. We discuss why Bayesian model selection might favour models containing more species, and why recognizing more than three species might be warranted.     

SEX LINKAGE,SEX‐SPECIFIC SELECTION,AND THE ROLE OF RECOMBINATION IN THE EVOLUTION OF SEXUALLY DIMORPHIC GENE EXPRESSION

Sex‐biased genes—genes that are differentially expressed within males and females—are nonrandomly distributed across animal genomes, with sex chromosomes and autosomes often carrying markedly different concentrations of male‐ and female‐biased genes. These linkage patterns are often gene‐ and lineage‐dependent, differing between functional genetic categories and between species. Although sex‐specific selection is often hypothesized to shape the evolution of sex‐linked and autosomal gene content, population genetics theory has yet to account for many of the gene‐ and lineage‐specific idiosyncrasies emerging from the empirical literature. With the goal of improving the connection between evolutionary theory and a rapidly growing body of genome‐wide empirical studies, we extend previous population genetics theory of sex‐specific selection by developing and analyzing a biologically informed model that incorporates sex linkage, pleiotropy, recombination, and epistasis, factors that are likely to vary between genes and between species. Our results demonstrate that sex‐specific selection and sex‐specific recombination rates can generate, and are compatible with, the gene‐ and species‐specific linkage patterns reported in the genomics literature. The theory suggests that sexual selection may strongly influence the architectures of animal genomes, as well as the chromosomal distribution of fixed substitutions underlying sexually dimorphic traits.     

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis

The Kingman coalescent and its developments are often considered among the most important advances in population genetics of the last decades. Demographic inference based on coalescent theory has been used to reconstruct the population dynamics and evolutionary history of several species, including Mycobacterium tuberculosis (MTB), an important human pathogen causing tuberculosis. One key assumption of the Kingman coalescent is that the number of descendants of different individuals does not vary strongly, and violating this assumption could lead to severe biases caused by model misspecification. Individual lineages of MTB are expected to vary strongly in reproductive success because 1) MTB is potentially under constant selection due to the pressure of the host immune system and of antibiotic treatment, 2) MTB undergoes repeated population bottlenecks when it transmits from one host to the next, and 3) some hosts show much higher transmission rates compared with the average (superspreaders).Here, we used an approximate Bayesian computation approach to test whether multiple-merger coalescents (MMC), a class of models that allow for large variation in reproductive success among lineages, are more appropriate models to study MTB populations. We considered 11 publicly available whole-genome sequence data sets sampled from local MTB populations and outbreaks and found that MMC had a better fit compared with the Kingman coalescent for 10 of the 11 data sets. These results indicate that the null model for analyzing MTB outbreaks should be reassessed and that past findings based on the Kingman coalescent need to be revisited.     

The joint allele frequency spectrum of multiple populations: a coalescent theory approach

The allele frequency spectrum is a series of statistics that describe genetic polymorphism, and is commonly used for inferring population genetic parameters and detecting natural selection. Population genetic theory on the allele frequency spectrum for a single population has been well studied using both coalescent theory and diffusion equations. Recently, the theory was extended to the joint allele frequency spectrum (JAFS) for three populations using diffusion equations and was shown to be very useful in inferring human demographic history. In this paper, I show that the JAFS can be analytically derived with coalescent theory for a basic model of two isolated populations and then extended to multiple populations and various complex scenarios, such as those involving population growth and bottleneck, migration, and positive selection. Simulation study is used to demonstrate the accuracy and applicability of the theoretical model. The coalescent theory-based approach for the JAFS can characterize the demographic history with comprehensive statistical models as the diffusion approach does, and in addition gains several novel advantages: the computational complexity of calculating the JAFS with coalescent theory is reduced, and thus it is feasible to analytically obtain the JAFS for multiple populations; the hitchhiking effect can be efficiently modeled in coalescent theory, enabling the development of methodologies for detecting selection via multi-population polymorphism data. As an alternative to the diffusion approximation approach, the coalescent theory for the JAFS also provides a foundation for population genetic inference with the advent of large-scale genomic polymorphism data.     

Did natural selection make the Dutch taller? A cautionary note on the importance of quantification in understanding evolution

One of the main achievements of the modern synthesis is a rigorous mathematical theory for evolution by natural selection. Combining this theory with statistical models makes it possible to estimate the relevant parameters so as to quantify selection and evolution in nature. Although quantification is a sign of a mature science, statistical models are unfortunately often interpreted independently of the motivating mathematical theory. Without a link to theory, numerical results do not represent proper quantifications, because they lack the connections that designate their biological meaning. Here, we want to raise awareness and exemplify this problem by examining a recent study on natural selection in a contemporary human population. Stulp et al. (2015) concluded that natural selection may partly explain the increasing stature of the Dutch population. This conclusion was based on a qualitative assessment of the presence of selection on height. Here, we provide a quantitative interpretation of these results using standard evolutionary theory to show that natural selection has had a minuscule effect.     

Robust Estimates of Divergence Times and Selection with a Poisson Random Field Model: A Case Study of Comparative Phylogeographic Data

Mutation frequencies can be modeled as a Poisson random field (PRF) to estimate speciation times and the degree of selection on newly arisen mutations. This approach provides a quantitative theory for comparing intraspecific polymorphism with interspecific divergence in the presence of selection and can be used to estimate population genetic parameters. Although the original PRF model has been extended to more general biological settings to make statistical inference about selection and divergence among model organisms, it has not been incorporated into phylogeographic studies that focus on estimating population genetic parameters for nonmodel organisms. Here, we modified a recently developed time-dependent PRF model to independently estimate genetic parameters from a nuclear and mitochondrial DNA data set of 22 sister pairs of birds that have diverged across a biogeographic barrier. We found that species that inhabit humid habitats had more recent divergence times and larger effective population sizes than those that inhabit drier habitats, and divergence time estimated from the PRF model were similar to estimates from a coalescent species-tree approach. Selection coefficients were higher in sister pairs that inhabited drier habitats than in those in humid habitats, but overall the mitochondrial DNA was under weak selection. Our study indicates that PRF models are useful for estimating various population genetic parameters and serve as a framework for incorporating estimates of selection into comparative phylogeographic studies.     

Development of high‐density SNP genotyping arrays for white spruce (Picea glauca) and transferability to subtropical and nordic congeners

High‐density SNP genotyping arrays can be designed for any species given sufficient sequence information of high quality. Two high‐density SNP arrays relying on the Infinium iSelect technology (Illumina) were designed for use in the conifer white spruce (Picea glauca). One array contained 7338 segregating SNPs representative of 2814 genes of various molecular functional classes for main uses in genetic association and population genetics studies. The other one contained 9559 segregating SNPs representative of 9543 genes for main uses in population genetics, linkage mapping of the genome and genomic prediction. The SNPs assayed were discovered from various sources of gene resequencing data. SNPs predicted from high‐quality sequences derived from genomic DNA reached a genotyping success rate of 64.7%. Nonsingleton in silico SNPs (i.e. a sequence polymorphism present in at least two reads) predicted from expressed sequenced tags obtained with the Roche 454 technology and Illumina GAII analyser resulted in a similar genotyping success rate of 71.6% when the deepest alignment was used and the most favourable SNP probe per gene was selected. A variable proportion of these SNPs was shared by other nordic and subtropical spruce species from North America and Europe. The number of shared SNPs was inversely proportional to phylogenetic divergence and standing genetic variation in the recipient species, but positively related to allele frequency in P. glauca natural populations. These validated SNP resources should open up new avenues for population genetics and comparative genetic mapping at a genomic scale in spruce species.     

Evidence for sympatric speciation in a Wallacean ancient lake

Sympatric speciation has been demonstrated in few empirical case studies, despite intense searches, because of difficulties in testing the criteria for this mode of speciation. Here, we report a possible case of sympatric speciation in ricefishes of the genus Oryzias on Sulawesi, an island of Wallacea. Three species of Oryzias are known to be endemic to Lake Poso, an ancient tectonic lake in central Sulawesi. Phylogenetic analyses using RAD‐seq‐derived single nucleotide polymorphisms (SNPs) revealed that these species are monophyletic. We also found that the three species are morphologically distinguishable and clearly separated by population‐structure analyses based on the SNPs, suggesting that they are reproductively isolated from each other. A mitochondrial DNA chronogram suggested that their speciation events occurred after formation of the tectonic lake, and existence of a historical allopatric phase was not supported by coalescent‐based demographic inference. Demographic inference also suggested introgressive hybridization from an outgroup population. However, differential admixture among the sympatric species was not supported by any statistical tests. These results all concur with criteria necessary to demonstrate sympatric speciation. Ricefishes in this Wallacean lake provide a promising new model system for the study of sympatric speciation.     

Multiplex restriction amplicon sequencing: a novel next‐generation sequencing‐based marker platform for high‐throughput genotyping

To enable rapid selection of traits in marker‐assisted breeding, markers must be technically simple, low‐cost, high‐throughput and randomly distributed in a genome. We developed such a technology, designated as Multiplex Restriction Amplicon Sequencing (MRASeq), which reduces genome complexity by polymerase chain reaction (PCR) amplification of amplicons flanked by restriction sites. The first PCR primers contain restriction site sequences at 3’‐ends, preceded by 6‐10 bases of specific or degenerate nucleotide sequences and then by a unique M13‐tail sequence which serves as a binding site for a second PCR that adds sequencing primers and barcodes to allow sample multiplexing for sequencing. The sequences of restriction sites and adjacent nucleotides can be altered to suit different species. Physical mapping of MRASeq SNPs from a biparental population of allohexaploid wheat (Triticum aestivum L.) showed a random distribution of SNPs across the genome. MRASeq generated thousands of SNPs from a wheat biparental population and natural populations of wheat and barley (Hordeum vulgare L.). This novel, next‐generation sequencing‐based genotyping platform can be used for linkage mapping to screen quantitative trait loci (QTL), background selection in breeding and many other genetics and breeding applications of various species.     

Habitat association in two genetic groups of the insect-pathogenic fungus metarhizium anisopliae: uncovering cryptic species?

Strains of insect-pathogenic fungi with high virulence toward certain pest insects have great potential for commercial biological control applications. Identifying such strains has been a central theme in using fungi for biological control. This theme is supported by a persistent paradigm in insect pathology which suggests that the host insect is the predominant influence on the population genetics of insect-pathogenic fungi. In this study, a population genetics analysis of the insect-pathogenic fungus Metarhizium anisopliae from forested and agricultural habitats in Ontario, Canada, showed a nonrandom association of alleles between two distinct, reproductively isolated groups (index of multilocus association = 1.2). Analyses of the mitochondrial DNA showed no differences between the groups. The two groups were associated with different habitat types, and associations with insect hosts were not found. The group from forested areas showed an ability for cold-active growth (i.e., 8 degrees C), while the group from the agricultural area showed an ability for growth at high temperatures (i.e., 37 degrees C) and resilience to UV exposure. These results represent a significant paradigm shift; habitat selection, not host insect selection, drives the population structure of these insect-pathogenic deuteromycetous fungi. With each group we observed recombining population structures as well as clonally reproducing lineages. We discuss whether these groups may represent cryptic species. Worldwide, M. anisopliae may be an assembly of cryptic species, each adapted to certain environmental conditions. The association of fungal genotypes with habitat but not with host insects has implications on the criteria for utility of this, and perhaps other, fungal biocontrol agents.     

Using coalescent simulations to test the impact of quaternary climate cycles on divergence in an alpine plant-insect association

The Quaternary climate cycles forced species to repeatedly migrate across a continually changing landscape. How these shifts in distribution impacted the evolution of unrelated but ecologically associated taxa has remained elusive due to the stochastic nature of the evolutionary process and variation in species-specific biological characteristics and environmental constraints. To account for the uncertainty in genealogical estimates, we adopted a coalescent approach for testing hypotheses of population divergence in coevolving taxa. We compared genealogies of a specialized herbivorous insect, Parnassius smintheus (Papilionidae), and its host plant, Sedum lanceolatum (Crassulaceae), from the alpine tundra of the Rocky Mountains to null distributions from coalescent simulations to test whether tightly associated taxa shared a common response to the paleoclimatic cycles. Explicit phylogeographic models were generated from geologic and biogeographic data and evaluated over a wide range of divergence times given calibrated mutation rates for both species. Our analyses suggest that the insect and its host plant responded similarly but independently to the climate cycles. By promoting habitat expansion and mixing among alpine populations, glacial periods repeatedly reset the distributions of genetic variation in each species and inhibited continual codivergence among pairs of interacting species.     

Phylogeography’s past,present, and future: 10 years after

Approximately 20 years ago, Avise and colleagues proposed the integration of phylogenetics and population genetics for investigating the connection between micro- and macroevolutionary phenomena. The new field was termed phylogeography. Since the naming of the field, the statistical rigor of phylogeography has increased, in large part due to concurrent advances in coalescent theory which enabled model-based parameter estimation and hypothesis testing. The next phase will involve phylogeography increasingly becoming the integrative and comparative multi-taxon endeavor that it was originally conceived to be. This exciting convergence will likely involve combining spatially-explicit multiple taxon coalescent models, genomic studies of natural selection, ecological niche modeling, studies of ecological speciation, community assembly and functional trait evolution. This ambitious synthesis will allow us to determine the causal links between geography, climate change, ecological interactions and the evolution and composition of taxa across whole communities and assemblages. Although such integration presents analytical and computational challenges that will only be intensified by the growth of genomic data in non-model taxa, the rapid development of “likelihood-free” approximate Bayesian methods should permit parameter estimation and hypotheses testing using complex evolutionary demographic models and genomic phylogeographic data. We first review the conceptual beginnings of phylogeography and its accomplishments and then illustrate how it evolved into a statistically rigorous enterprise with the concurrent rise of coalescent theory. Subsequently, we discuss ways in which model-based phylogeography can interface with various subfields to become one of the most integrative fields in all of ecology and evolutionary biology.     

Genetic response to climatic change: insights from ancient DNA and phylochronology

Understanding how climatic change impacts biological diversity is critical to conservation. Yet despite demonstrated effects of climatic perturbation on geographic ranges and population persistence, surprisingly little is known of the genetic response of species. Even less is known over ecologically long time scales pertinent to understanding the interplay between microevolution and environmental change. Here, we present a study of population variation by directly tracking genetic change and population size in two geographically widespread mammal species (Microtus montanus and Thomomys talpoides) during late-Holocene climatic change. We use ancient DNA to compare two independent estimates of population size (ecological and genetic) and corroborate our results with gene diversity and serial coalescent simulations. Our data and analyses indicate that, with population size decreasing at times of climatic change, some species will exhibit declining gene diversity as expected from simple population genetic models, whereas others will not. While our results could be consistent with selection, independent lines of evidence implicate differences in gene flow, which depends on the life history strategy of species.     

Penalized classification for optimal statistical selection of markers from high-throughput genotyping: application in sheep breeds

The identification of individuals’ breed of origin has several practical applications in livestock and is useful in different biological contexts such as conservation genetics, breeding and authentication of animal products. In this paper, penalized multinomial regression was applied to identify the minimum number of single nucleotide polymorphisms (SNPs) from high-throughput genotyping data for individual assignment to dairy sheep breeds reared in Sicily. The combined use of penalized multinomial regression and stability selection reduced the number of SNPs required to 48. A final validation step on an independent population was carried out obtaining 100% correctly classified individuals. The results using independent analysis, such as admixture, F_st, principal component analysis and random forest, confirmed the ability of these methods in selecting distinctive markers. The identified SNPs may constitute a starting point for the development of a SNP based identification test as a tool for breed assignment and traceability of animal products.     

PGEToolbox: A Matlab toolbox for population genetics and evolution

Assessing genetic diversity within populations is vital for understanding the nature of evolutionary processes at the molecular level. PGEToolbox is a Matlab-based open-sourced software package for data analysis in population genetics. The main features of this software are as follows: 1) capability for handling both DNA sequence polymorphisms and single nucleotide polymorphisms (SNPs), which include genotype and haplotype data; 2) exhaustive population genetic analyses and neutrality tests based on the coalescent theory; 3) extendibility and scalability for complex and large genome-wide datasets; 4) simple yet effective graphic user interfaces and sophisticated visualization of data and results. For academic uses, PGEToolbox is available free of charge at http://bioinformatics.org/pgetoolbox.     

MetaPopGen: an r package to simulate population genetics in large size metapopulations

Population genetics simulation models are useful tools to study the effects of demography and environmental factors on genetic variation and genetic differentiation. They allow for studying species and populations with complex life histories, spatial distribution and many other complicating factors that make analytical treatment impracticable. Most simulation models are individual‐based: this poses a limitation to simulation of very large populations because of the limits in computer memory and long computation times. To overcome these limitations, we propose an intermediate approach that allows modelling of very complex demographic scenarios, which would be intractable with analytical models, and removes the limitations imposed by large population size, which affect individual‐based simulation models. We implement this approach in a software package for the r environment, MetaPopGen. The innovative concept of this approach with respect to the other population genetic simulators is that it focuses on genotype numbers rather than on individuals. Genotype numbers are iterated through time by using random number generators for appropriate probabilistic distributions to reproduce the stochasticity inherent to Mendelian segregation, survival, dispersal and reproduction. Features included in the model are age structure, monoecious and dioecious (or separate sexes) life cycles, mutation, dispersal and selection. The model simulates only one locus at a time. All demographic parameters can be genotype‐, sex‐, age‐, deme‐ and time‐dependent. MetaPopGen is therefore indicated to study large populations and very complex demographic scenarios. We illustrate the capabilities of MetaPopGen by applying it to the case of a marine fish metapopulation in the Mediterranean Sea.