Genealogies and geography

Genomic insights into the Montseny brook newt (Calotriton arnoldi), a Critically Endangered glacial relict

The Montseny brook newt (Calotriton arnoldi), considered the most endangered amphibian in Europe, is a relict salamandrid species endemic to a small massif located in northeastern Spain. Although conservation efforts should always be guided by genomic studies, those are yet scarce among urodeles, hampered by the extreme sizes of their genomes. Here, we present the third available genome assembly for the order Caudata, and the first genomic study of the species and its sister taxon, the Pyrenean brook newt (Calotriton asper), combining whole-genome and ddRADseq data. Our results reveal significant demographic oscillations which accurately mirrored Europe's climatic history. Although severe bottlenecks have led to depauperate genomic diversity and long runs of homozygosity along a gigantic genome, inbreeding might have been avoided by assortative mating strategies. Other life history traits, however, seem to have been less advantageous, and the lack of land dispersal has driven to exceptional levels of population fragmentation.

The era of the ARG: An introduction to ancestral recombination graphs and their significance in empirical evolutionary genomics

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

Fine scale genetics reveals the subtle negative effects of roads on an endangered bat

The effective management of species with small and fragmented populations requires an in-depth understanding of how the effects of human-induced habitat disturbance shape the structure and gene flow at fine spatial scales. Identification of putative environmental barriers that affect individual exchange among subpopulations is imperative to prevent extinction risks. Here, we investigated how landscape affects the gene flow and relatedness structure of a population of the endangered lesser horseshoe bat (Rhinolophus hipposideros). We also assessed the effects of sexbiased dispersal on genetic relatedness. We genotyped 287 bat samples collected across southern Portugal and developed resistance surfaces for landscape variables hypothesized to affect gene flow. Then, we used spatially explicit models to fit relatedness distance through the resistance surfaces. We found genetic evidence of sex-biased dispersal and identified a significant fine scale structuring in the relatedness regarding females, the philopatric sex. Males displayed uniform levels of relatedness throughout the landscape. The results indicated less relatedness between the female´ from roosts located on proximity of roads than in roosts away from roads. Also, when analysing the sexes together the relatedness on roosts separated by highway were subtly less related in comparison to those occurring on the same side. Roads seem to be major shapers of the contemporary population structure of females, regardless of being relatively recent structures in the landscape. Furthermore, the relatedness patterns detected suggested that high tree density among roosts and continuity of forest patches in broader surrounding areas, promotes the relatedness among individuals. Landscape heterogeneity among roosts slightly decreases genetic relatedness. Nevertheless, those relationships are still weak, suggesting that population structuring driven by those factors is slowly ongoing. Thus, effective management measures should focus on issues for promoting safe road passages and suitable habitat corridors, allowing for the exchange of individuals and gene flow among lesser horseshoe bat roosts.

Isolation by distance in populations with power-law dispersal

Limited dispersal of individuals between generations results in isolation by distance, in which individuals further apart in space tend to be less related. Classic models of isolation by distance assume that dispersal distances are drawn from a thin-tailed distribution and predict that the proportion of the genome that is identical by descent between a pair of individuals should decrease exponentially with the spatial separation between them. However, in many natural populations, individuals occasionally disperse over very long distances. In this work, we use mathematical analysis and coalescent simulations to study the effect of long-range (power-law) dispersal on patterns of isolation by distance. We find that it leads to power-law decay of identity-by-descent at large distances with the same exponent as dispersal. We also find that broad power-law dispersal produces another, shallow power-law decay of identity-by-descent at short distances. These results suggest that the distribution of long-range dispersal events could be estimated from sequencing large population samples taken from a wide range of spatial scales.

Estimating dispersal using close kin dyads: The kindisperse R package

Investigating dispersal in animal populations can be difficult, particularly for taxa that are hard to directly observe such as those that are small or rare. A promising solution may come from new approaches that use genome-wide sequence data to detect close kin dyads and estimate dispersal parameters from the distribution of these dyads. These methods have so far only been applied to mosquito populations. However, they should have broad applicability to a range of taxa, although no assessment has yet been made on their performance under different dispersal conditions and study designs. Here we develop an R package and shiny app, kindisperse, that can be used to estimate dispersal parameters from the spatial distribution of close kin. kindisperse can handle study designs that target different life stages and allows for a range of dispersal kernel shapes and organismal life histories; we provide implementation examples for a vertebrate (Antechinus) and an invertebrate (Aedes). We use simulations run in kindisperse to compare the performance of two published close kin methodologies, showing that one method produces unbiased estimates whereas the other produces downward-biased estimates. We also use kindisperse simulations to investigate how study design affects dispersal estimates, and we provide guidelines for the size and shape of sample sites as well as the number of close kin needed for accurate estimates. kindisperse is easily adaptable for application to a variety of research contexts ranging from invasive pests to threatened species where noninvasive DNA sampling can be used to detect close kin.

Spatial Population Genetics: It's About Time

Many important questions about the history and dynamics of organisms have a geographical component: How many are there, and where do they live? How do they move and interbreed across the landscape? How were they moving a thousand years ago, and where were the ancestors of a particular individual alive today? Answers to these questions can have profound consequences for our understanding of history, ecology, and the evolutionary process. In this review, we discuss how geographic aspects of the distribution, movement, and reproduction of organisms are reflected in their pedigree across space and time. Because the structure of the pedigree is what determines patterns of relatedness in modern genetic variation, our aim is to thus provide intuition for how these processes leave an imprint in genetic data. We also highlight some current methods and gaps in the statistical toolbox of spatial population genetics.

Are populations like a circuit? Comparing isolation by resistance to a new coalescent-based method

A number of methods commonly used in landscape genetics use an analogy to electrical resistance on a network to describe and fit barriers to movement across the landscape using genetic distance data. These are motivated by a mathematical equivalence between electrical resistance between two nodes of a network and the 'commute time', which is the mean time for a random walk on that network to leave one node, visit the other, and return. However, genetic data are more accurately modelled by a different quantity, the coalescence time. Here, we describe the differences between resistance distance and coalescence time, and explore the consequences for inference. We implemented a Bayesian method to infer effective movement rates and population sizes under both these models, and found that inference using commute times could produce misleading results in the presence of biased gene flow. We then used forwards-time simulation with continuous geography to demonstrate that coalescence-based inference remains more accurate than resistance-based methods on realistic data, but difficulties highlight the need for methods that explicitly model continuous, heterogeneous geography.

The IICR and the non-stationary structured coalescent: towards demographic inference with arbitrary changes in population structure

In the last years, a wide range of methods allowing to reconstruct past population size changes from genome-wide data have been developed. At the same time, there has been an increasing recognition that population structure can generate genetic data similar to those produced under models of population size change. Recently, Mazet et al. (Heredity 116:362-371, 2016) showed that, for any model of population structure, it is always possible to find a panmictic model with a particular function of population size changes, having exactly the same distribution of T₂ (the coalescence time for a sample of size two) as that of the structured model. They called this function IICR (Inverse Instantaneous Coalescence Rate) and showed that it does not necessarily correspond to population size changes under non-panmictic models. Besides, most of the methods used to analyse data under models of population structure tend to arbitrarily fix that structure and to minimise or neglect population size changes. Here, we extend the seminal work of Herbots (PhD thesis, University of London, 1994) on the structured coalescent and propose a new framework, the Non-Stationary Structured Coalescent (NSSC) that incorporates demographic events (changes in gene flow and/or deme sizes) to models of nearly any complexity. We show how to compute the IICR under a wide family of stationary and non-stationary models. As an example we address the question of human and Neanderthal evolution and discuss how the NSSC framework allows to interpret genomic data under this new perspective.

Coalescence times andFSTvalues in subdivided populations with symmetric structure

The structured coalescent is a continuous-time Markov chain which describes the genealogy of a sample of homologous genes from a subdivided population. Assuming this model, some results are proved relating to the genealogy of a pair of genes and the extent of subpopulation differentiation, which are valid under certain graph-theoretic symmetry and regularity conditions on the structure of the population. We first review and extend earlier results stating conditions under which the mean time since the most recent common ancestor of a pair of genes from any single subpopulation is independent of the migration rate and equal to that of two genes from an unstructured population of the same total size. Assuming the infinite alleles model of neutral mutation with a small mutation rate, we then prove a simple relationship between the migration rate and the value of Wright's coefficientFSTfor a pair of neighbouring subpopulations, which does not depend on the precise structure of the population provided that this is sufficiently symmetric.

Coalescence times and F ST values in subdivided populations with symmetric structure

The structured coalescent is a continuous-time Markov chain which describes the genealogy of a sample of homologous genes from a subdivided population. Assuming this model, some results are proved relating to the genealogy of a pair of genes and the extent of subpopulation differentiation, which are valid under certain graph-theoretic symmetry and regularity conditions on the structure of the population. We first review and extend earlier results stating conditions under which the mean time since the most recent common ancestor of a pair of genes from any single subpopulation is independent of the migration rate and equal to that of two genes from an unstructured population of the same total size. Assuming the infinite alleles model of neutral mutation with a small mutation rate, we then prove a simple relationship between the migration rate and the value of Wright's coefficient F ST for a pair of neighbouring subpopulations, which does not depend on the precise structure of the population provided that this is sufficiently symmetric.

DNA Barcoding Survey of Anurans across the Eastern Cordillera of Colombia and the Impact of the Andes on Cryptic Diversity

Colombia hosts the second highest amphibian species diversity on Earth, yet its fauna remains poorly studied, especially using molecular genetic techniques. We present the results of the first wide-scale DNA barcoding survey of anurans of Colombia, focusing on a transect across the Eastern Cordillera. We surveyed 10 sites between the Magdalena Valley to the west and the eastern foothills of the Eastern Cordillera, sequencing portions of the mitochondrial 16S ribosomal RNA and cytochrome oxidase subunit 1 (CO1) genes for 235 individuals from 52 nominal species. We applied two barcode algorithms, Automatic Barcode Gap Discovery and Refined Single Linkage Analysis, to estimate the number of clusters or “unconfirmed candidate species” supported by DNA barcode data. Our survey included ~7% of the anuran species known from Colombia. While barcoding algorithms differed slightly in the number of clusters identified, between three and ten nominal species may be obscuring candidate species (in some cases, more than one cryptic species per nominal species). Our data suggest that the high elevations of the Eastern Cordillera and the low elevations of the Chicamocha canyon acted as geographic barriers in at least seven nominal species, promoting strong genetic divergences between populations associated with the Eastern Cordillera.

Covariation of gene frequencies in a stepping-stone lattice of populations

For a one- or two-dimensional lattice of finite length consisting of populations, each of which has the same population size, the classical stepping-stone model has been used to approximate the patterns of variation at neutral loci in geographic regions. In the pioneering papers by Maruyama (1970a, 1970b, 1971) the changes of gene frequency at a locus subject to neutral mutation between two alleles, migration, and random genetic drift were modeled by a vector autoregression model. Maruyama was able to use the spectrum of the migration matrix, but to do this he had to introduce approximations in which there was either extra mutation in the terminal populations, or extra migration from the subterminal population into the terminal population. In this paper a similar vector autoregression model is used, but it proves possible to obtain the eigenvalues and eigenvectors of the migration matrix without those approximations. Approximate formulas for the variances and covariances of gene frequencies in different populations are obtained, and checked by numerical iteration of the exact covariances of the vector autoregression model.

GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans

Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.

Do major roads reduce gene flow in urban bird populations?

BACKGROUND

Although the negative effects of roads on the genetics of animal populations have been extensively reported, the question of whether roads reduce gene flow in volant, urban bird populations has so far not been addressed. In this study, we assess whether highways decreased gene flow and genetic variation in a small passerine bird, the tree sparrow (Passer montanus).

METHODOLOGY

We assessed genetic differences among tree sparrows (Passer montanus) sampled at 19 sites within Beijing Municipality, China, using 7 DNA microsatellites as genetic markers.

RESULTS

AMOVA showed that genetic variation between sites, between urban and rural populations, and between opposite sides of the same highway, were very weak. Mantel tests on all samples, and on urban samples only, indicated that the age and number of highways, and the number of ordinary roads, were uncorrelated with genetic differences (F ST) among tree sparrows from different urban sites. Birds sampled at urban sites had similar levels of genetic diversity to those at rural sites. There was, however, evidence of some weak genetic structure between urban sites. Firstly, there were significant genetic differences (F ST) between birds from opposite sides of the same highway, but no significant F ST values between those from sites that were not separated by highways. Secondly, birds from eleven urban sites had loci that significantly deviated from the Hardy-Weinberg equilibrium but no such deviation was found in birds from rural sites.

CONCLUSION

We cannot, therefore, conclusively reject the hypothesis that highways have no effect on the gene flow of tree sparrow populations. Furthermore, since the significance of these results may increase with time, we suggested that research on the influence of highways on gene flow in urban bird populations needs to be conducted over several decades.

Estimation of effective population size in continuously distributed populations: there goes the neighborhood

Use of genetic methods to estimate effective population size (Ne) is rapidly increasing, but all approaches make simplifying assumptions unlikely to be met in real populations. In particular, all assume a single, unstructured population, and none has been evaluated for use with continuously distributed species. We simulated continuous populations with local mating structure, as envisioned by Wright's concept of neighborhood size (NS), and evaluated performance of a single-sample estimator based on linkage disequilibrium (LD), which provides an estimate of the effective number of parents that produced the sample (Nb). Results illustrate the interacting effects of two phenomena, drift and mixture, that contribute to LD. Samples from areas equal to or smaller than a breeding window produced estimates close to the NS. As the sampling window increased in size to encompass multiple genetic neighborhoods, mixture LD from a two-locus Wahlund effect overwhelmed the reduction in drift LD from incorporating offspring from more parents. As a consequence, never approached the global Ne, even when the geographic scale of sampling was large. Results indicate that caution is needed in applying standard methods for estimating effective size to continuously distributed populations.

Inference in two dimensions: allele frequencies versus lengths of shared sequence blocks

We outline two approaches to inference of neighbourhood size, N, and dispersal rate, σ(2), based on either allele frequencies or on the lengths of sequence blocks that are shared between genomes. Over intermediate timescales (10-100 generations, say), populations that live in two dimensions approach a quasi-equilibrium that is independent of both their local structure and their deeper history. Over such scales, the standardised covariance of allele frequencies (i.e. pairwise FST) falls with the logarithm of distance, and depends only on neighbourhood size, N, and a 'local scale', κ; the rate of gene flow, σ(2), cannot be inferred. We show how spatial correlations can be accounted for, assuming a Gaussian distribution of allele frequencies, giving maximum likelihood estimates of N and κ. Alternatively, inferences can be based on the distribution of the lengths of sequence that are identical between blocks of genomes: long blocks (>0.1 cM, say) tell us about intermediate timescales, over which we assume a quasi-equilibrium. For large neighbourhood size, the distribution of long blocks is given directly by the classical Wright-Malécot formula; this relationship can be used to infer both N and σ(2). With small neighbourhood size, there is an appreciable chance that recombinant lineages will coalesce back before escaping into the distant past. For this case, we show that if genomes are sampled from some distance apart, then the distribution of lengths of blocks that are identical in state is geometric, with a mean that depends on N and σ(2).

Glaciation effects on the phylogeographic structure of Oligoryzomys longicaudatus (Rodentia: Sigmodontinae) in the southern Andes

The long-tailed pygmy rice rat Oligoryzomys longicaudatus (Sigmodontinae), the major reservoir of Hantavirus in Chile and Patagonian Argentina, is widely distributed in the Mediterranean, Temperate and Patagonian Forests of Chile, as well as in adjacent areas in southern Argentina. We used molecular data to evaluate the effects of the last glacial event on the phylogeographic structure of this species. We examined if historical Pleistocene events had affected genetic variation and spatial distribution of this species along its distributional range. We sampled 223 individuals representing 47 localities along the species range, and sequenced the hypervariable domain I of the mtDNA control region. Aligned sequences were analyzed using haplotype network, bayesian population structure and demographic analyses. Analysis of population structure and the haplotype network inferred three genetic clusters along the distribution of O. longicaudatus that mostly agreed with the three major ecogeographic regions in Chile: Mediterranean, Temperate Forests and Patagonian Forests. Bayesian Skyline Plots showed constant population sizes through time in all three clusters followed by an increase after and during the Last Glacial Maximum (LGM; between 26,000-13,000 years ago). Neutrality tests and the "g" parameter also suggest that populations of O. longicaudatus experienced demographic expansion across the species entire range. Past climate shifts have influenced population structure and lineage variation of O. longicaudatus. This species remained in refugia areas during Pleistocene times in southern Temperate Forests (and adjacent areas in Patagonia). From these refugia, O. longicaudatus experienced demographic expansions into Patagonian Forests and central Mediterranean Chile using glacial retreats.

A new model for extinction and recolonization in two dimensions: quantifying phylogeography

Classical models of gene flow fail in three ways: they cannot explain large-scale patterns; they predict much more genetic diversity than is observed; and they assume that loosely linked genetic loci evolve independently. We propose a new model that deals with these problems. Extinction events kill some fraction of individuals in a region. These are replaced by offspring from a small number of parents, drawn from the preexisting population. This model of evolution forwards in time corresponds to a backwards model, in which ancestral lineages jump to a new location if they are hit by an event, and may coalesce with other lineages that are hit by the same event. We derive an expression for the identity in allelic state, and show that, over scales much larger than the largest event, this converges to the classical value derived by Wright and Malécot. However, rare events that cover large areas cause low genetic diversity, large-scale patterns, and correlations in ancestry between unlinked loci.

A likelihood framework for estimating phylogeographic history on a continuous landscape

Due to lack of an adequate statistical framework, biologists studying phylogeography are abandoning traditional methods of estimating phylogeographic history in favor of statistical methods designed to test a priori hypotheses. These new methods may, however, have limited descriptive utility. Here, we develop a new statistical framework that can be used to both test a priori hypotheses and estimate phylogeographic history of a gene (and the statistical confidence in that history) in the absence of such hypotheses. The statistical approach concentrates on estimation of geographic locations of the ancestors of a set of sampled organisms. Now we use (2) to derive the likelihood of the ancestral geographic coordinates and the value of the scaled dispersal parameter, given the observed geographic coordinates (assuming known topology and branch lengths). Using a maximum likelihood approach, which is implemented in the new program PhyloMapper, we apply this statistical framework to a 246-taxon mitochondrial genealogy of North American chorus frogs, focusing in detail on one of these species. We demonstrate three lines of evidence for recent northward expansion of the mitochondrion of the coastal clade of Pseudacris feriarum: higher per-generation dispersal distance in the recently colonized region, a noncentral ancestral location, and directional migration. After illustrating one method of accommodating phylogenetic uncertainty, we conclude by discussing how extensions of this framework could function to incorporate a priori ecological and geological information into phylogeographic analyses.

The scale of population structure in Arabidopsis thaliana

The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales.

Much of the modern field of population genetics is premised on particular models of what an organism's population structure is and how it behaves. The classic models generally start with the idea of a single randomly mating population that has reached an evolutionary equilibrium. Many models relax some of these assumptions, allowing for phenomena such as assortative mating, discrete sub-populations with migration, self-fertilization, and sex-ratio distortion. Virtually all models, however, have as their core premise the notion that there exist classes of exchangeable individuals each of which represents an identical, independent sample from that class' distribution. For certain organisms, such as Drosophila melanogaster, these models do an excellent job of describing how populations work. For other organisms, such as humans, these models can be reasonable approximations but require a great deal of care in assembling samples and can begin to break down as sampling becomes locally dense. For the vast majority of organisms the applicability of these models has never been investigated.

A continuous-state coalescent and the impact of weak selection on the structure of gene genealogies

Coalescent theory provides an elegant and powerful method for understanding the shape of gene genealogies and resulting patterns of genetic diversity. However, the coalescent does not naturally accommodate the effects of heritable variation in fitness. Although some methods are available for studying the effects of strong selection (Ns >> 1), few tools beyond forward simulation are available for quantifying the impact of weak selection at many sites. Here, we introduce a continuous-state coalescent capable of accurately describing the distortions to genealogies caused by moderate to weak natural selection affecting many linked sites. We calculate approximately the full distribution of pairwise coalescent times, the lengths of coalescent intervals, and the time to the most recent common ancestor of a sample. Weak selection (Ns approximately 1) is found to substantially decrease the tree depth, primarily through a shortening of the lengths of the basal coalescent intervals. Additionally, we demonstrate that only two parameters, population size and the variance of the distribution describing fitness heritability, are sufficient to describe most changes.

Colonization history of the Swiss Rhine basin by the bullhead (Cottus gobio): inference under a Bayesian spatially explicit framework

The present distribution of freshwater fish in the Alpine region has been strongly affected by colonization events occurring after the last glacial maximum (LGM), some 20,000 years ago. We use here a spatially explicit simulation framework to model and better understand their colonization dynamics in the Swiss Rhine basin. This approach is applied to the European bullhead (Cottus gobio), which is an ideal model organism to study fish past demographic processes since it has not been managed by humans. The molecular diversity of eight sampled populations is simulated and compared to observed data at six microsatellite loci under an approximate Bayesian computation framework to estimate the parameters of the colonization process. Our demographic estimates fit well with current knowledge about the biology of this species, but they suggest that the Swiss Rhine basin was colonized very recently, after the Younger Dryas some 6600 years ago. We discuss the implication of this result, as well as the strengths and limits of the spatially explicit approach coupled to the approximate Bayesian computation framework.

On the choice of genetic distance in spatial-genetic studies

We look at how to choose genetic distance so as to maximize the power of detecting spatial structure. We answer this question through analyzing two population genetic models that allow for a spatially structured population in a continuous habitat. These models, like most that incorporate spatial structure, can be characterized by a separation of timescales: the history of the sample can be split into a scattering and a collecting phase, and it is only during the scattering phase that the spatial locations of the sample affect the coalescence times. Our results suggest that the optimal choice of genetic distance is based upon splitting a DNA sequence into segments and counting the number of segments at which two sequences differ. The size of these segments depends on the length of the scattering phase for the population genetic model.

Genetics of recent habitat contraction and reduction in population size: does isolation by distance matter?

Fragmentation and loss of natural habitats are recognized as major threats to contemporary flora and fauna. Detecting past or current reductions in population size is therefore a major aim in conservation genetics. Statistical methods developed to this purpose have tended to ignore the effects of spatial population structure. However in many species, individual dispersal is restricted in space and fine-scale spatial structure such as isolation by distance (IBD) is commonly observed in continuous populations. Using a simulation-based approach, we investigated how comparative and single-point methods, traditionally used in a Wright-Fisher (WF) population context for detecting population size reduction, behave for IBD populations. We found that a complex 'quartet' of factors was acting that includes restricted dispersal, population size (i.e. habitat size), demographic history, and sampling scale. After habitat reduction, IBD populations were characterized by a stronger inertia in the loss of genetic diversity than WF populations. This inertia increases with the strength of IBD, and decreases when the sampling scale increases. Depending on the method used to detect a population size reduction, a local sampling can be more informative than a sample scaled to habitat size or vice versa. However, IBD structure led in numerous cases to incorrect inferences on population demographic history. The reanalysis of a real microsatellite data set of skink populations from fragmented and intact rainforest habitats confirmed most of our simulation results.

History, ocean channels, and distance determine phylogeographic patterns in three widespread Philippine fruit bats (Pteropodidae)

The comparative phylogeography of widespread, codistributed species provides unique insights into regional biodiversity and diversification patterns. I used partial DNA sequences of the mitochondrial genes ND2 and cyt b to investigate phylogeographic structure in three widespread Philippine fruit bats. Ptenochirus jagori is endemic to the oceanic region of the Philippines and is most abundant in lowland primary forest. Macroglossus minimus and Cynopterus brachyotis are most common in disturbed and open habitats and are not endemic. In all three, genetic differentiation is present at multiple spatial scales and is associated to some degree with Pleistocene landbridge island groups. In P. jagori and C. brachyotis, genetic distance is correlated with geographic distance; in C. brachyotis and M. minimus, it is correlated with the sea-crossing distance between islands. P. jagori has the least overall genetic structure of these three species, whereas C. brachyotis and M. minimus have more geographic association among haplotypes, suggesting that phylogeographic patterns are linked to ecology and habitat preference. However, contrary to expectation, the two widespread, disturbed habitat species have more structure than the endemic species. Mismatch distributions suggest rapid changes in effective population size in C. brachyotis and P. jagori, whereas M. minimus appears to be demographically more stable. Geologic and geographic history are important in structuring variation, and phylogeographic patterns are the result of dynamic long-term processes rather than simply reflecting current conditions.

Sex-biased migration in humans: what should we expect from genetic data?

Different patterns of mitochondrial and Y-chromosome diversity have been cited as evidence of long-term patrilocality in human populations. However, what patterns are expected depends on the nature of the sampling scheme. Samples from a local region reveal only the recent demographic history of that region, whereas sampling over larger geographic scales accesses older demographic processes. A historical change in migration becomes evident first at local geographic scales, and alters global patterns of genetic diversity only after sufficient time has passed. Analysis of forager populations in the ethnographic record suggests that patrilocality may not have predominated among pre-agricultural humans. The higher female migration rate inferred by some genetic studies may reflect a shift to patrilocality in association with the emergence of agriculture. A recent global survey does not show the expected effects of higher female migration, possibly because the sampling scheme used for this study is accessing pre-agricultural human migration patterns. In this paper, we show how the demographic shift associated with agriculture might affect genetic diversity over different spatial scales. We also consider the prospects for studying sex-biased migration using the X-linked and autosomal markers. These multi-locus comparisons have the potential of providing more robust estimates of sex differences than Y-linked and mitochondrial data, but only if a very large number of loci are included in the analysis.

Estimating the total genetic diversity of a spatial field population from a sample and implications of its dependence on habitat area

The total genetic diversity of a species is a key factor in its persistence and conservation. Because realistic sample sizes are far smaller than the total population, it is impractical to exhaustively characterize diversity of most populations. Here, we demonstrate the possibility of calculating the genetic diversity of a spatial population from a sample using genealogical models. We trace the history of a population by simulating the locations of the ancestors of a particular sample of the population backwards in time. We use this method to estimate the genetic diversity of the global population of Pseudomonas bacteria. The same results are obtained whether using a global sample or a subsample restricted to a particular geographic region (California). The results are also validated by comparing additional predictions of the model to the data. Furthermore, we use these results to show that the level of genetic diversity in a population depends strongly on the size of its habitat, much more strongly than does biodiversity as measured by the number of species. The strong dependence of diversity on habitat area has significant implications for conservation strategies.

A separation-of-timescales approach to the coalescent in a continuous population

This article presents an analysis of a model of isolation by distance in a continuous, two-dimensional habitat. An approximate expression is derived for the distribution of coalescence times for a pair of sequences sampled from specific locations in a rectangular habitat. Results are qualitatively similar to previous analyses of isolation by distance, but account explicitly for the location of samples relative to the habitat boundaries. A separation-of-timescales approach takes advantage of the fact that the sampling locations affect only the recent coalescent behavior. When the population size is larger than the number of generations required for a lineage to cross the habitat range, the long-term genealogical process is reasonably well described by Kingman's coalescent with time rescaled by the effective population size. This long-term effective population size is affected by the local dispersal behavior as well as the geometry of the habitat. When the population size is smaller than the time required to cross the habitat, deep branches in the genealogy are longer than would be expected under the standard neutral coalescent, similar to the pattern expected for a panmictic population whose population size was larger in the past.

Molecular analysis reveals tighter social regulation of immigration in patrilocal populations than in matrilocal populations

Human social organization can deeply affect levels of genetic diversity. This fact implies that genetic information can be used to study social structures, which is the basis of ethnogenetics. Recently, methods have been developed to extract this information from genetic data gathered from subdivided populations that have gone through recent spatial expansions, which is typical of most human populations. Here, we perform a Bayesian analysis of mitochondrial and Y chromosome diversity in three matrilocal and three patrilocal groups from northern Thailand to infer the number of males and females arriving in these populations each generation and to estimate the age of their range expansion. We find that the number of male immigrants is 8 times smaller in patrilocal populations than in matrilocal populations, whereas women move 2.5 times more in patrilocal populations than in matrilocal populations. In addition to providing genetic quantification of sex-specific dispersal rates in human populations, we show that although men and women are exchanged at a similar rate between matrilocal populations, there are far fewer men than women moving into patrilocal populations. This finding is compatible with the hypothesis that men are strictly controlling male immigration and promoting female immigration in patrilocal populations and that immigration is much less regulated in matrilocal populations.

Estimating dispersal from short distance spatial autocorrelation

A series of theoretical studies has formed a strong connection between spatial statistics observed in populations and summary measures of the amount of dispersal. Synthesized, these developments allow dispersal to be indirectly estimated from standing spatial patterns of genetic variation under a range of conditions broad enough to be likely met in most populations of either plants or animals. The spatial correlations at the shortest distances are particularly robust to range of conditions and have disproportionately high statistical power. This review integrates theoretical results in a way that maximizes robustness and flexibility in the use of short distance autocorrelation to estimate Wright's neighborhood size, or the total variance in dispersal distances. Empirical guidelines are developed that are meant to be as practical and broad as possible. The guidelines focus on Moran's I-statistics for diploid genotypes converted to allele frequencies, but are also extended to or compared with several other approaches.

Bayesian estimation of recent migration rates after a spatial expansion

Approximate Bayesian computation (ABC) is a highly flexible technique that allows the estimation of parameters under demographic models that are too complex to be handled by full-likelihood methods. We assess the utility of this method to estimate the parameters of range expansion in a two-dimensional stepping-stone model, using samples from either a single deme or multiple demes. A minor modification to the ABC procedure is introduced, which leads to an improvement in the accuracy of estimation. The method is then used to estimate the expansion time and migration rates for five natural common vole populations in Switzerland typed for a sex-linked marker and a nuclear marker. Estimates based on both markers suggest that expansion occurred <10,000 years ago, after the most recent glaciation, and that migration rates are strongly male biased.

Mutation at high rates reduces spatial structure within populations

The question of whether or not the high rates (mu) of mutation that occur for some hypervariable markers can affect commonly used empirical measures of spatial structure of genetic variation within populations is addressed. The results show that values of these measures are approximately halved when mu is 10(-2). Finest spatial-scale correlations, measured by either Moran's I-statistics or conditional kinship, are reduced by 30%-50%. When the mutation rate is 10 times lower, much smaller reductions result, e.g. averaging 7% for the finest scale correlations. Still smaller orders of magnitude of mu cause negligible changes in spatial structure, where any effects normally would not be detectable. The reductions are caused by forward mutations, and when the reductions are measured as percentages, they are nearly independent of the amount of structure produced sans mutation, except when dispersal is nearly minimal. The percent reductions are also nearly independent of the number of alleles and of back mutations, hence of the nature of the mutation process (e.g. stepwise or not). The results demonstrate that some hypervariable loci should have reduced spatial structuring, and that marker choice may affect the values observed in experimental surveys. Moreover, if fine-scale correlations are used to indirectly estimate dispersal distances, then mutation at high rates could inflate estimates, easily up to two- to three-fold.

Theory predicts the uneven distribution of genetic diversity within species

Global efforts to conserve species have been strongly influenced by the heterogeneous distribution of species diversity across the Earth. This is manifest in conservation efforts focused on diversity hotspots. The conservation of genetic diversity within an individual species is an important factor in its survival in the face of environmental changes and disease. Here we show that diversity within species is also distributed unevenly. Using simple genealogical models, we show that genetic distinctiveness has a scale-free power law distribution. This property implies that a disproportionate fraction of the diversity is concentrated in small sub-populations, even when the population is well-mixed. Small groups are of such importance to overall population diversity that even without extrinsic perturbations, there are large fluctuations in diversity owing to extinctions of these small groups. We also show that diversity can be geographically non-uniform--potentially including sharp boundaries between distantly related organisms--without extrinsic causes such as barriers to gene flow or past migration events. We obtained these results by studying the fundamental scaling properties of genealogical trees. Our theoretical results agree with field data from global samples of Pseudomonas bacteria. Contrary to previous studies, our results imply that diversity loss owing to severe extinction events is high, and focusing conservation efforts on highly distinctive groups can save much of the diversity.

Multilocus estimation of genetic structure within populations

Spatial structure of genetic variation within populations is well measured by statistics based on the distribution of pairs of individual genotypes, and various such statistics have been widely used in experimental studies. However, the problem of uncharacterized correlations among statistics for different alleles has limited the applications of multiallelic, multilocus summary measures, since these had unknown sampling distributions. Usually multiple alleles and/or multiple loci are required in order to precisely measure spatial structures, and to provide precise indirect estimates of the amount of dispersal in samples of reasonable size. This article examines the correlations among pair-wise statistics, including Moran I-statistics and various measures of conditional kinship, for different alleles of a locus. First the correlations are mathematically derived for random spatial distributions, which allow averages over alleles and loci to be used as more powerful yet exact test statistics for the null hypothesis. Then extensive computer simulations are conducted to examine the correlations among values for different alleles under isolation by distance processes. For loci with more than three alleles, the results show that the correlations are remarkably and perhaps surprisingly small, establishing the principle that then alleles behave as nearly independent realizations of space-time stochastic processes. The results also show that the correlations are largely robust with respect to the degree of spatial structure, and they can be used in a straightforward manner to form confidence intervals for averages. The results allow a precise connection between observations in experimental studies and levels of dispersal in theoretical models.

A highly divergent mitochondrial DNA lineage of Microtus agrestis in southern Europe

The Mediterranean peninsulas constitute important areas for endemism and intraspecific variation, and are likely places for cryptic biodiversity. We assessed the phylogeographic pattern of field voles (Microtus agrestis) in southern and central Europe by sequence analysis of a 385-bp fragment of the mitochondrial cytochrome b gene in 74 specimens from 44 localities. The majority of samples consisted of skulls collected from owl pellets. The data revealed a highly distinct cytochrome b lineage in an area ranging from Portugal to Hungary. This southern field vole phylogroup differed by a sequence divergence of 5.6-7.1% from the remaining haplotypes, a level of divergence comparable to that found between known Microtus sibling species. However, this ancient phylogeographic break that dates back many glacial cycles has not been recognised previously by either morphology or karyotype. The southern cytochrome b lineage was further divided into two well-defined sublineages that appear to have derived from different glacial refugia in the Iberian Peninsula.

Distinct geographic patterns of genetic diversity are maintained in wild barley (Hordeum vulgare ssp. spontaneum) despite migration

Mutations arise in a single individual and at a single point in time and space. The geographic distribution of mutations reflects both historical population size and frequency of migration. We employ coalescence-based methods to coestimate effective population size, frequency of migration, and level of recombination compatible with observed genealogical relationships in sequence data from nine nuclear genes in wild barley (Hordeum vulgare ssp. spontaneum), a highly self-fertilizing grass species. In self-fertilizing plants, gamete dispersal is severely limited; dissemination occurs primarily through seed dispersal. Also, heterozygosity is greatly reduced, which renders recombination less effective at randomizing genetic variation and causes larger portions of the genome to trace a similar history. Despite these predicted effects of this mating system, the majority of loci show evidence of recombination. Levels of nucleotide variation and the patterns of geographic distribution of mutations in wild barley are highly heterogeneous across loci. Two of the nine sampled loci maintain highly diverged, geographic region-specific suites of mutations. Two additional loci include region-specific haplotypes with a much shallower coalescence. Despite inbreeding, sessile growth habit, and the observation of geographic structure at almost half of sampled loci, parametric estimates of migration suggest that seed dispersal is sufficient for migration across the approximately 3,500-km range of the species. Recurrent migration is also evident based on the geographic distribution of mutational variation at some loci. At one locus a single haplotype has spread rapidly enough to occur, unmodified by mutation, across the range of the species.

Coalescence in a metapopulation with recurrent local extinction and recolonization

Many species exist as metapopulations in balance between local population extinction and recolonization. The effect of these processes on average population differentiation, within-deme diversity, and species wide diversity has been considered previously. In this paper, coalescent simulations of Slatkin's propagule-pool and migrant-pool models are used to characterize the distribution of neutral genetic diversity within demes (pi(S)), diversity in the metapopulation a whole (pi(T)), the ratio F(ST) = (pi(T) - pi(S))/pi(T), Tajima's D statistic, and several ratios of gene-tree branch lengths. Using these distributions, power to detect differences in key metapopulation parameter values is determined under contrasting sampling regimes. The results indicate that it will be difficult to use sequence data from a single locus to detect a history of extinctions and recolonizations in a metapopulation because of high genealogical variance, the loss of diversity due to reductions in effective population size, and the fact that a genealogy of lineages from different demes under Slatkin's model differs from a neutral coalescent only in its time scale. Genetic indices of gene-tree shape that capture the effects of extinction/recolonization on both external branches and the length of the genealogy as a whole will provide the best indication of metapopulation dynamics if several lineages are sampled from several different demes.

Holarctic phylogeography of the root vole (Microtus oeconomus): implications for late Quaternary biogeography of high latitudes

A species-wide phylogeographical study of the root vole (Microtus oeconomus) was performed using the whole 1140 base pair mitochondrial (mt) cytochrome b gene. We examined 83 specimens from 52 localities resulting in 65 unique haplotypes. Our results demonstrate that the root vole is divided into four main mtDNA phylogenetic lineages that seem to have largely allopatric distributions. Net divergence estimates (2.0-3.5%) between phylogroups, as well as relatively high nucleotide diversity estimates within phylogroups, indicate that the distinct phylogeographical structure was initiated by historical events that predated the latest glaciation. European root voles are divided into a Northern and a Central mtDNA phylogroup. The mtDNA data in concert with fossil records imply that root voles remained north of the classical refugial areas in southern Europe during the last glacial period. The currently fragmented populations in central Europe belong to a single mtDNA phylogroup. The Central Asian and the North European lineages are separated by the Ural Mountains, a phylogeographical split also found in collared lemmings (Dicrostonyx) and the common vole (M. arvalis). The Beringian lineage occurs from eastern Russia through Alaska to northwestern Canada. This distribution is congruent with the traditional boundaries of the Beringian refugium and with phylogeographical work on other organisms. In conclusion, similarities between the phylogeographical patterns in the root vole and other rodents, such as Arctic and subarctic lemmings, as well as more temperate vole species, indicate that late Quaternary geological and climatic events played a strong role in structuring northern biotic communities.