Recent developments in genetic data analysis: what can they tell us about human demographic history?

Ignoring population structure in hominin evolutionary models can lead to the inference of spurious admixture events

Genomic and ancient DNA data have revolutionized palaeoanthropology and our vision of human evolution, with indisputable landmarks like the sequencing of Neanderthal and Denisovan genomes. Yet, using genetic data to identify, date and quantify evolutionary events-such as ancient bottlenecks or admixture-is not straightforward, as inferences may depend on model assumptions. In the last two decades, the idea that Neanderthals and members of the Homo sapiens lineage interbred has gained momentum. From the status of unlikely theory, it has reached consensus among human evolutionary biologists. This theory is mainly supported by statistical approaches that depend on demographic models minimizing or ignoring population structure, despite its widespread occurrence and the fact that, when ignored, population structure can lead to the inference of spurious demographic events. We simulated genomic data under a structured and admixture-free model of human evolution, and found that all the tested admixture approaches identified long Neanderthal fragments in our simulated genomes and an admixture event that never took place. We also observed that several published admixture models failed to predict important empirical diversity or admixture statistics, and that we could identify several scenarios from our structured model that better predicted these statistics jointly. Using a simulated time series of ancient DNA, the structured scenarios could also predict the trajectory of the empirical D statistics. Our results suggest that models accounting for population structure are fundamental to improve our understanding of human evolution, and that admixture between Neanderthals and H. sapiens needs to be re-evaluated in the light of structured models. Beyond the Neanderthal case, we argue that ancient hybridization events, which are increasingly documented in many species, including with other hominins, may also benefit from such re-evaluation.

Species-Specific Traits Shape Genetic Diversity During an Expansion-Contraction Cycle and Bias Demographic History Reconstruction

Species ranges are dynamic, experiencing expansions, contractions or shifts in response to habitat changes driven by extrinsic factors such as climate change or human activities. While existing research examines the genetic consequences of spatial processes, few studies integrate species-specific traits to analyse how habitat changes affect co-existing species. In this study, we address this gap by investigating how genetic diversity patterns vary among species with different traits (such as generation length, population density and dispersal) experiencing similar habitat changes. Using spatial simulations and a simpler panmictic population model, we investigate the temporal genetic diversity in refugium populations undergoing range expansion of their habitat, followed by stationary and contraction periods. By varying habitat contraction speed and species traits, we identified three distinct temporal dynamics of genetic diversity during contraction: (i) a decrease in genetic diversity, (ii) an initial increase followed by a decrease and (iii) a continuous increase throughout the contraction period. We show that genetic diversity trajectories during population decline can be predicted by comparing sampled population diversity to equilibrium values expected under expanded and contracted habitat ranges. Our study also challenges the belief that high genetic diversity in a refugium population is due to a recent and rapid habitat loss. Instead, we found contrasting effects of contraction speed on genetic diversity depending on the interaction between species-specific traits and the dynamics of habitat change. Finally, using simulated genetic data, we found that demographic histories inferred from effective population size estimates may vary across species, even when they experience similar habitat changes.

Genetic differentiation and phylogeography of Erythroneurini (Hemiptera, Cicadellidae, Typhlocybinae) in the southwestern karst area of China

Erythroneurini is the largest tribe of the microleafhopper subfamily Typhlocybinae. Most prior research on this tribe has focused on traditional classification, phylogeny, and control of agricultural pests, and the phylogeography of the group remains poorly understood. In this study, the mitochondrial genomes of 10 erythroneurine species were sequenced, and sequences of four genes were obtained for 12 geographical populations of Seriana bacilla. The new sequence data were combined with previously available mitochondrial DNA sequence data and analyzed using Bayesian and Maximum-Likelihood-based phylogenetic methods to elucidate relationships among genera and species and estimate divergence times. Seriana was shown to be derived from within Empoascanara. Phylogeographic and population genetic analysis of the endemic Chinese species Seriana bacilla suggest that the species diverged about 54.85 Mya (95% HPD: 20.76-66.23 million years) in the Paleogene period and that population divergence occurred within the last 14 million years. Ancestral area reconstruction indicates that Seriana bacilla may have originated in the central region of Guizhou, and geographical barriers are the main factors affecting gene flow among populations. Ecological niche modeling using the MaxEnt model suggests that the distribution of the species was more restricted in the past but is likely to expand in the future years 2050 and 2070.

The importance of well protected forests for the conservation genetics of West African colobine monkeys

In tropical forests, anthropogenic activities are major drivers of the destruction and degradation of natural habitats, causing severe biodiversity loss. African colobine monkeys (Colobinae) are mainly folivore and strictly arboreal primates that require large forests to subsist, being among the most vulnerable of all nonhuman primates. The Western red colobus Piliocolobus badius and the King colobus Colobus polykomos inhabit highly fragmented West African forests, including the Cantanhez Forests National Park (CFNP) in Guinea-Bissau. Both species are also found in the largest and best-preserved West African forest-the Taï National Park (TNP) in Ivory Coast. Colobine monkeys are hunted for bushmeat in both protected areas, but these exhibit contrasting levels of forest fragmentation, thus offering an excellent opportunity to investigate the importance of well-preserved forests for the maintenance of evolutionary potential in these arboreal primates. We estimated genetic diversity, population structure, and demographic history by using microsatellite loci and mitochondrial DNA. We then compared the genetic patterns of the colobines from TNP with the ones previously obtained for CFNP and found contrasting genetic patterns. Contrary to the colobines from CFNP that showed very low genetic diversity and a strong population decline, the populations in TNP still maintain high levels of genetic diversity and we found no clear signal of population decrease in Western red colobus and a limited decrease in King colobus. These results suggest larger and historically more stable populations in TNP compared to CFNP. We cannot exclude the possibility that the demographic effects resulting from the recent increase of bushmeat hunting are not yet detectable in TNP using genetic data. Nevertheless, the fact that the TNP colobus populations are highly genetically diverse and maintain large effective population sizes suggests that well-preserved forests are crucial for the maintenance of populations, species, and probably for the evolutionary potential in colobines.

Impact of model assumptions on demographic inferences: the case study of two sympatric mouse lemurs in northwestern Madagascar

BACKGROUND

Quaternary climate fluctuations have been acknowledged as major drivers of the geographical distribution of the extraordinary biodiversity observed in tropical biomes, including Madagascar. The main existing framework for Pleistocene Malagasy diversification assumes that forest cover was strongly shaped by warmer Interglacials (leading to forest expansion) and by cooler and arid glacials (leading to forest contraction), but predictions derived from this scenario for forest-dwelling animals have rarely been tested with genomic datasets.

RESULTS

We generated genomic data and applied three complementary demographic approaches (Stairway Plot, PSMC and IICR-simulations) to infer population size and connectivity changes for two forest-dependent primate species (Microcebus murinus and M. ravelobensis) in northwestern Madagascar. The analyses suggested major demographic changes in both species that could be interpreted in two ways, depending on underlying model assumptions (i.e., panmixia or population structure). Under panmixia, the two species exhibited larger population sizes across the Last Glacial Maximum (LGM) and towards the African Humid Period (AHP). This peak was followed by a population decline in M. ravelobensis until the present, while M. murinus may have experienced a second population expansion that was followed by a sharp decline starting 3000 years ago. In contrast, simulations under population structure suggested decreasing population connectivity between the Last Interglacial and the LGM for both species, but increased connectivity during the AHP exclusively for M. murinus.

CONCLUSION

Our study shows that closely related species may differ in their responses to climatic events. Assuming that Pleistocene climatic conditions in the lowlands were similar to those in the Malagasy highlands, some demographic dynamics would be better explained by changes in population connectivity than in population size. However, changes in connectivity alone cannot be easily reconciled with a founder effect that was shown for M. murinus during its colonization of the northwestern Madagascar in the late Pleistocene. To decide between the two alternative models, more knowledge about historic forest dynamics in lowland habitats is necessary. Altogether, our study stresses that demographic inferences strongly depend on the underlying model assumptions. Final conclusions should therefore be based on a comparative evaluation of multiple approaches.

On the use of genome-wide data to model and date the time of anthropogenic hybridisation: An example from the Scottish wildcat

While hybridisation has long been recognised as an important natural phenomenon in evolution, the conservation of taxa subject to introgressive hybridisation from domesticated forms is a subject of intense debate. Hybridisation of Scottish wildcats and domestic cats is a good example in this regard. Here, we developed a modelling framework to determine the timescale of introgression using approximate Bayesian computation (ABC). Applying the model to ddRAD-seq data from 129 individuals, genotyped at 6546 loci, we show that a population of wildcats genetically distant from domestic cats is still present in Scotland. These individuals were found almost exclusively within the captive breeding programme. Most wild-living cats sampled were introgressed to some extent. The demographic model predicts high levels of gene-flow between domestic cats and Scottish wildcats (13% migrants per generation) over a short timeframe, the posterior mean for the onset of hybridisation (T₁ ) was 3.3 generations (~10 years) before present. Although the model had limited power to detect signals of ancient admixture, we found evidence that significant recent hybridisation may have occurred subsequent to the founding of the captive breeding population (T₂ ). The model consistently predicts T₁ after T₂ , estimated here to be 19.3 generations (~60 years) ago, highlighting the importance of this population as a resource for conservation management. Additionally, we evaluate the effectiveness of current methods to classify hybrids. We show that an optimised 35 SNP panel is a better predictor of the ddRAD-based hybrid score in comparison with a morphological method.

Inferring number of populations and changes in connectivity under the n-island model

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

Cryptic Patterns of Speciation in Cryptic Primates: Microendemic Mouse Lemurs and the Multispecies Coalescent

Mouse lemurs (Microcebus) are a radiation of morphologically cryptic primates distributed throughout Madagascar for which the number of recognized species has exploded in the past two decades. This taxonomic revision has prompted understandable concern that there has been substantial oversplitting in the mouse lemur clade. Here, we investigate mouse lemur diversity in a region in northeastern Madagascar with high levels of microendemism and predicted habitat loss. We analyzed RADseq data with multispecies coalescent (MSC) species delimitation methods for two pairs of sister lineages that include three named species and an undescribed lineage previously identified to have divergent mtDNA. Marked differences in effective population sizes, levels of gene flow, patterns of isolation-by-distance, and species delimitation results were found among the two pairs of lineages. Whereas all tests support the recognition of the presently undescribed lineage as a separate species, the species-level distinction of two previously described species, M. mittermeieri and M. lehilahytsara is not supported-a result that is particularly striking when using the genealogical discordance index (gdi). Nonsister lineages occur sympatrically in two of the localities sampled for this study, despite an estimated divergence time of less than 1 Ma. This suggests rapid evolution of reproductive isolation in the focal lineages and in the mouse lemur clade generally. The divergence time estimates reported here are based on the MSC calibrated with pedigree-based mutation rates and are considerably more recent than previously published fossil-calibrated relaxed-clock estimates. We discuss the possible explanations for this discrepancy, noting that there are theoretical justifications for preferring the MSC estimates in this case. [Cryptic species; effective population size; microendemism; multispecies coalescent; speciation; species delimitation.].

The IICR (inverse instantaneous coalescence rate) as a summary of genomic diversity: insights into demographic inference and model choice

Several inferential methods using genomic data have been proposed to quantify and date population size changes in the history of species. At the same time an increasing number of studies have shown that population structure can generate spurious signals of population size change. Recently, Mazet et al. (2016) introduced, for a sample size of two, a time-dependent parameter, which they called the IICR (inverse instantaneous coalescence rate). The IICR is equivalent to a population size in panmictic models, but not necessarily in structured models. It is characterised by a temporal trajectory that suggests population size changes, as a function of the sampling scheme, even when the total population size was constant. Here, we extend the work of Mazet et al. (2016) by (i) showing how the IICR can be computed for any demographic model of interest, under the coalescent, (ii) applying this approach to models of population structure (1D and 2D stepping stone, split models, two- and three-island asymmetric gene flow, continent-island models), (iii) stressing the importance of the sampling strategy in generating different histories, (iv) arguing that IICR plots can be seen as summaries of genomic information that can thus be used for model choice or model exclusion (v) applying this approach to the question of admixture between humans and Neanderthals. Altogether these results are potentially important given that the widely used PSMC (pairwise sequentially Markovian coalescent) method of Li and Durbin (2011) estimates the IICR of the sample, not necessarily the history of the populations.

Inference of sex-specific expansion patterns in human populations from Y-chromosome polymorphism

Studying the current distribution of genetic diversity in humans has important implications for our understanding of the history of our species. We analyzed a set of linked STR and SNP loci from the paternally inherited Y chromosome to infer the past demography of 55 African and Eurasian populations, using both the parametric and nonparametric coalescent-based methods implemented in the BEAST application. We inferred expansion events in most sedentary farmer populations, while we found constant effective population sizes for both nomadic hunter-gatherers and seminomadic herders. Our results differed, on several aspects, from previous results on mtDNA and autosomal markers. First, we found more recent expansion patterns in Eurasia than in Africa. This discrepancy, substantially stronger than the ones found with the other kind of markers, may result from a lower effective population size for men, which might have made male-transmitted markers more sensitive to the out-of-Africa bottleneck. Second, we found expansion signals only for sedentary farmers but not for nomadic herders in Central Asia, while these signals were found for both kind of populations in this area when using mtDNA or autosomal markers. Expansion signals in this area may result from spatial expansion processes and may have been erased for the Y chromosome among the herders because of restricted male gene flow.

Robust demographic inference from genomic and SNP data

We introduce a flexible and robust simulation-based framework to infer demographic parameters from the site frequency spectrum (SFS) computed on large genomic datasets. We show that our composite-likelihood approach allows one to study evolutionary models of arbitrary complexity, which cannot be tackled by other current likelihood-based methods. For simple scenarios, our approach compares favorably in terms of accuracy and speed with ∂a∂i, the current reference in the field, while showing better convergence properties for complex models. We first apply our methodology to non-coding genomic SNP data from four human populations. To infer their demographic history, we compare neutral evolutionary models of increasing complexity, including unsampled populations. We further show the versatility of our framework by extending it to the inference of demographic parameters from SNP chips with known ascertainment, such as that recently released by Affymetrix to study human origins. Whereas previous ways of handling ascertained SNPs were either restricted to a single population or only allowed the inference of divergence time between a pair of populations, our framework can correctly infer parameters of more complex models including the divergence of several populations, bottlenecks and migration. We apply this approach to the reconstruction of African demography using two distinct ascertained human SNP panels studied under two evolutionary models. The two SNP panels lead to globally very similar estimates and confidence intervals, and suggest an ancient divergence (>110 Ky) between Yoruba and San populations. Our methodology appears well suited to the study of complex scenarios from large genomic data sets.

Human genetic data reveal contrasting demographic patterns between sedentary and nomadic populations that predate the emergence of farming

Demographic changes are known to leave footprints on genetic polymorphism. Together with the increased availability of large polymorphism data sets, coalescent-based methods allow inferring the past demography of populations from their present-day patterns of genetic diversity. Here, we analyzed both nuclear (20 noncoding regions) and mitochondrial (HVS-I) resequencing data to infer the demographic history of 66 African and Eurasian human populations presenting contrasting lifestyles (nomadic hunter-gatherers, nomadic herders, and sedentary farmers). This allowed us to investigate the relationship between lifestyle and demography and to address the long-standing debate about the chronology of demographic expansions and the Neolithic transition. In Africa, we inferred expansion events for farmers, but constant population sizes or contraction events for hunter-gatherers. In Eurasia, we inferred higher expansion rates for farmers than herders with HVS-I data, except in Central Asia and Korea. Although isolation and admixture processes could have impacted our demographic inferences, these processes alone seem unlikely to explain the contrasted demographic histories inferred in populations with different lifestyles. The small expansion rates or constant population sizes inferred for herders and hunter-gatherers may thus result from constraints linked to nomadism. However, autosomal data revealed contraction events for two sedentary populations in Eurasia, which may be caused by founder effects. Finally, the inferred expansions likely predated the emergence of agriculture and herding. This suggests that human populations could have started to expand in Paleolithic times, and that strong Paleolithic expansions in some populations may have ultimately favored their shift toward agriculture during the Neolithic.

When history repeats itself: exploring the genetic architecture of host-plant adaptation in two closely related lepidopteran species

The genus Ostrinia includes two allopatric maize pests across Eurasia, namely the European corn borer (ECB, O. nubilalis) and the Asian corn borer (ACB, O. furnacalis). A third species, the Adzuki bean borer (ABB, O. scapulalis), occurs in sympatry with both the ECB and the ACB. The ABB mostly feeds on native dicots, which probably correspond to the ancestral host plant type for the genus Ostrinia. This situation offers the opportunity to characterize the two presumably independent adaptations or preadaptations to maize that occurred in the ECB and ACB. In the present study, we aimed at deciphering the genetic architecture of these two adaptations to maize, a monocot host plant recently introduced into Eurasia. To this end, we performed a genome scan analysis based on 684 AFLP markers in 12 populations of ECB, ACB and ABB. We detected 2 outlier AFLP loci when comparing French populations of the ECB and ABB, and 9 outliers when comparing Chinese populations of the ACB and ABB. These outliers were different in both countries, and we found no evidence of linkage disequilibrium between any two of them. These results suggest that adaptation or preadaptation to maize relies on a different genetic architecture in the ECB and ACB. However, this conclusion must be considered in light of the constraints inherent to genome scan approaches and of the intricate evolution of adaptation and reproductive isolation in the Ostrinia spp. complex.

Inferring demography from runs of homozygosity in whole-genome sequence, with correction for sequence errors

Whole-genome sequence is potentially the richest source of genetic data for inferring ancestral demography. However, full sequence also presents significant challenges to fully utilize such large data sets and to ensure that sequencing errors do not introduce bias into the inferred demography. Using whole-genome sequence data from two Holstein cattle, we demonstrate a new method to correct for bias caused by hidden errors and then infer stepwise changes in ancestral demography up to present. There was a strong upward bias in estimates of recent effective population size (Ne) if the correction method was not applied to the data, both for our method and the Li and Durbin (Inference of human population history from individual whole-genome sequences. Nature 475:493-496) pairwise sequentially Markovian coalescent method. To infer demography, we use an analytical predictor of multiloci linkage disequilibrium (LD) based on a simple coalescent model that allows for changes in Ne. The LD statistic summarizes the distribution of runs of homozygosity for any given demography. We infer a best fit demography as one that predicts a match with the observed distribution of runs of homozygosity in the corrected sequence data. We use multiloci LD because it potentially holds more information about ancestral demography than pairwise LD. The inferred demography indicates a strong reduction in the Ne around 170,000 years ago, possibly related to the divergence of African and European Bos taurus cattle. This is followed by a further reduction coinciding with the period of cattle domestication, with Ne of between 3,500 and 6,000. The most recent reduction of Ne to approximately 100 in the Holstein breed agrees well with estimates from pedigrees. Our approach can be applied to whole-genome sequence from any diploid species and can be scaled up to use sequence from multiple individuals.

The confounding effect of population structure on Bayesian skyline plot inferences of demographic history

Many coalescent-based methods aiming to infer the demographic history of populations assume a single, isolated and panmictic population (i.e. a Wright-Fisher model). While this assumption may be reasonable under many conditions, several recent studies have shown that the results can be misleading when it is violated. Among the most widely applied demographic inference methods are Bayesian skyline plots (BSPs), which are used across a range of biological fields. Violations of the panmixia assumption are to be expected in many biological systems, but the consequences for skyline plot inferences have so far not been addressed and quantified. We simulated DNA sequence data under a variety of scenarios involving structured populations with variable levels of gene flow and analysed them using BSPs as implemented in the software package BEAST. Results revealed that BSPs can show false signals of population decline under biologically plausible combinations of population structure and sampling strategy, suggesting that the interpretation of several previous studies may need to be re-evaluated. We found that a balanced sampling strategy whereby samples are distributed on several populations provides the best scheme for inferring demographic change over a typical time scale. Analyses of data from a structured African buffalo population demonstrate how BSP results can be strengthened by simulations. We recommend that sample selection should be carefully considered in relation to population structure previous to BSP analyses, and that alternative scenarios should be evaluated when interpreting signals of population size change.

Signature of a pre-human population decline in the critically endangered Reunion Island endemic forest bird Coracina newtoni

The exceptional biodiversity of Reunion Island is threatened by anthropogenic landscape changes that took place during the 350 years of human colonization. During this period the human population size increased dramatically from 250 to 800,000. The arrival of humans together with the development of agriculture, invasive species such as rats and cats, and deforestation has lead to the extinction of more than half of the original vertebrate species of the island. For the remaining species, significant work is being carried out to identify threats and conservation status, but little genetic work has been carried on some of the most endangered species. In the last decade theoretical studies have shown the ability of neutral genetic markers to infer the demographic history of endangered species and identify and date past population size changes (expansions or bottlenecks). In this study we provide the first genetic data on the critically endangered species the Reunion cuckoo-shrike Coracina newtoni. The Reunion cuckoo-shrike is a rare endemic forest bird surviving in a restricted 12-km(2) area of forested uplands and mountains. The total known population consists of less than one hundred individuals out of which 45 were genotyped using seventeen polymorphic microsatellite loci. We found a limited level of genetic variability and weak population structure, probably due to the limited geographic distribution. Using Bayesian methods, we identified a strong decline in population size during the Holocene, most likely caused by an ancient climatic or volcanic event around 5000 years ago. This result was surprising as it appeared in apparent contradiction with the accepted theory of recent population collapse due to deforestation and predator introduction. These results suggest that new methods allowing for more complex demographic models are necessary to reconstruct the demographic history of populations.

Statistical guidelines for detecting past population shifts using ancient DNA

Populations carry a genetic signal of their demographic past, providing an opportunity for investigating the processes that shaped their evolution. Our ability to infer population histories can be enhanced by including ancient DNA data. Using serial-coalescent simulations and a range of both quantitative and temporal sampling schemes, we test the power of ancient mitochondrial sequences and nuclear single-nucleotide polymorphisms (SNPs) to detect past population bottlenecks. Within our simulated framework, mitochondrial sequences have only limited power to detect subtle bottlenecks and/or fast post-bottleneck recoveries. In contrast, nuclear SNPs can detect bottlenecks followed by rapid recovery, although bottlenecks involving reduction of less than half the population are generally detected with low power unless extensive genetic information from ancient individuals is available. Our results provide useful guidelines for scaling sampling schemes and for optimizing our ability to infer past population dynamics. In addition, our results suggest that many ancient DNA studies may face power issues in detecting moderate demographic collapses and/or highly dynamic demographic shifts when based solely on mitochondrial information.

Combining markers into haplotypes can improve population structure inference

High-throughput genotyping and sequencing technologies can generate dense sets of genetic markers for large numbers of individuals. For most species, these data will contain many markers in linkage disequilibrium (LD). To utilize such data for population structure inference, we investigate the use of haplotypes constructed by combining the alleles at single-nucleotide polymorphisms (SNPs). We introduce a statistic derived from information theory, the gain of informativeness for assignment (GIA), which quantifies the additional information for assigning individuals to populations using haplotype data compared to using individual loci separately. Using a two-loci-two-allele model, we demonstrate that combining markers in linkage equilibrium into haplotypes always leads to nonpositive GIA, suggesting that combining the two markers is not advantageous for ancestry inference. However, for loci in LD, GIA is often positive, suggesting that assignment can be improved by combining markers into haplotypes. Using GIA as a criterion for combining markers into haplotypes, we demonstrate for simulated data a significant improvement of assigning individuals to candidate populations. For the many cases that we investigate, incorrect assignment was reduced between 26% and 97% using haplotype data. For empirical data from French and German individuals, the incorrectly assigned individuals can, for example, be decreased by 73% using haplotypes. Our results can be useful for challenging population structure and assignment problems, in particular for studies where large-scale population-genomic data are available.

Inferring population decline and expansion from microsatellite data: a simulation-based evaluation of the Msvar method

Reconstructing the demographic history of populations is a central issue in evolutionary biology. Using likelihood-based methods coupled with Monte Carlo simulations, it is now possible to reconstruct past changes in population size from genetic data. Using simulated data sets under various demographic scenarios, we evaluate the statistical performance of Msvar, a full-likelihood Bayesian method that infers past demographic change from microsatellite data. Our simulation tests show that Msvar is very efficient at detecting population declines and expansions, provided the event is neither too weak nor too recent. We further show that Msvar outperforms two moment-based methods (the M-ratio test and Bottleneck) for detecting population size changes, whatever the time and the severity of the event. The same trend emerges from a compilation of empirical studies. The latest version of Msvar provides estimates of the current and the ancestral population size and the time since the population started changing in size. We show that, in the absence of prior knowledge, Msvar provides little information on the mutation rate, which results in biased estimates and/or wide credibility intervals for each of the demographic parameters. However, scaling the population size parameters with the mutation rate and scaling the time with current population size, as coalescent theory requires, significantly improves the quality of the estimates for contraction but not for expansion scenarios. Finally, our results suggest that Msvar is robust to moderate departures from a strict stepwise mutation model.

The confounding effects of population structure, genetic diversity and the sampling scheme on the detection and quantification of population size changes

The idea that molecular data should contain information on the recent evolutionary history of populations is rather old. However, much of the work carried out today owes to the work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality or stationarity. During the last 20 years the detection of population size changes has usually been carried out under the assumption that samples were obtained from populations that can be approximated by a Wright-Fisher model (i.e., assuming panmixia, demographic stationarity, etc.). However, natural populations are usually part of spatial networks and are interconnected through gene flow. Here we simulated genetic data at mutation and migration-drift equilibrium under an n-island and a stepping-stone model. The simulated populations were thus stationary and not subject to any population size change. We varied the level of gene flow between populations and the scaled mutation rate. We also used several sampling schemes. We then analyzed the simulated samples using the Bayesian method implemented in MSVAR, the Markov Chain Monte Carlo simulation program, to detect and quantify putative population size changes using microsatellite data. Our results show that all three factors (genetic differentiation/gene flow, genetic diversity, and the sampling scheme) play a role in generating false bottleneck signals. We also suggest an ad hoc method to counter this effect. The confounding effect of population structure and of the sampling scheme has practical implications for many conservation studies. Indeed, if population structure is creating "spurious" bottleneck signals, the interpretation of bottleneck signals from genetic data might be less straightforward than it would seem, and several studies may have overestimated or incorrectly detected bottlenecks in endangered species.

Formulating a historical and demographic model of recent human evolution based on resequencing data from noncoding regions

BACKGROUND

Estimating the historical and demographic parameters that characterize modern human populations is a fundamental part of reconstructing the recent history of our species. In addition, the development of a model of human evolution that can best explain neutral genetic diversity is required to identify confidently regions of the human genome that have been targeted by natural selection.

METHODOLOGY/PRINCIPAL FINDINGS

We have resequenced 20 independent noncoding autosomal regions dispersed throughout the genome in 213 individuals from different continental populations, corresponding to a total of approximately 6 Mb of diploid resequencing data. We used these data to explore and co-estimate an extensive range of historical and demographic parameters with a statistical framework that combines the evaluation of multiple models of human evolution via a best-fit approach, followed by an Approximate Bayesian Computation (ABC) analysis. From a methodological standpoint, evaluating the accuracy of the parameter co-estimation allowed us to identify the most accurate set of statistics to be used for the estimation of each of the different historical and demographic parameters characterizing recent human evolution.

CONCLUSIONS/SIGNIFICANCE

Our results support a model in which modern humans left Africa through a single major dispersal event occurring approximately 60,000 years ago, corresponding to a drastic reduction of approximately 5 times the effective population size of the ancestral African population of approximately 13,800 individuals. Subsequently, the ancestors of modern Europeans and East Asians diverged much later, approximately 22,500 years ago, from the population of ancestral migrants. This late diversification of Eurasians after the African exodus points to the occurrence of a long maturation phase in which the ancestral Eurasian population was not yet diversified.

Heterozygosity and mutation rate: evidence for an interaction and its implications: the potential for meiotic gene conversions to influence both mutation rate and distribution

If natural selection chose where new mutations occur it might well favour placing them near existing polymorphisms, thereby avoiding disruption of areas that work while adding novelty to regions where variation is tolerated or even beneficial. Such a system could operate if heterozygous sites are recognised and 'repaired' during the initial stages of crossing over. Such repairs involve an extra round of DNA replication, providing an opportunity for further mutations, thereby raising the local mutation rate. If so, the changes in heterozygosity that occur when populations grow or shrink could feed back to modulate both the rate and the distribution of mutations. Here, I review evidence from isozymes, microsatellites and single nucleotide polymorphisms that this potential is realised in real populations. I then consider the likely implications, focusing particularly on how these processes might affect microsatellites, concluding that heterozygosity does impact on the rate and distribution of mutations.

Long-term survival despite low genetic diversity in the critically endangered Madagascar fish-eagle

The critically endangered Madagascar fish-eagle (Haliaeetus vociferoides) is considered to be one of the rarest birds of prey globally and at significant risk of extinction. In the most recent census, only 222 adult individuals were recorded with an estimated total breeding population of no more than 100-120 pairs. Here, levels of Madagascar fish-eagle population genetic diversity based on 47 microsatellite loci were compared with its sister species, the African fish-eagle (Haliaeetus vocifer), and 16 of these loci were also characterized in the white-tailed eagle (Haliaeetus albicilla) and the bald eagle (Haliaeetus leucocephalus). Overall, extremely low genetic diversity was observed in the Madagascar fish-eagle compared to other surveyed Haliaeetus species. Determining whether this low diversity is the result of a recent bottleneck or a more historic event has important implications for their conservation. Using a Bayesian coalescent-based method, we show that Madagascar fish-eagles have maintained a small effective population size for hundreds to thousands of years and that its low level of neutral genetic diversity is not the result of a recent bottleneck. Therefore, efforts made to prevent Madagascar fish-eagle extinction should place high priority on maintenance of habitat requirements and reducing direct and indirect human persecution. Given the current rate of deforestation in Madagascar, we further recommend that the population be expanded to occupy a larger geographical distribution. This will help the population persist when exposed to stochastic factors (e.g. climate and disease) that may threaten a species consisting of only 200 adult individuals while inhabiting a rapidly changing landscape.

Characterization of demographic expansions from pairwise comparisons of linked microsatellite haplotypes

This work extends the methods of demographic inference based on the distribution of pairwise genetic differences between individuals (mismatch distribution) to the case of linked microsatellite data. Population genetics theory describes the distribution of mutations among a sample of genes under different demographic scenarios. However, the actual number of mutations can rarely be deduced from DNA polymorphisms. The inclusion of mutation models in theoretical predictions can improve the performance of statistical methods. We have developed a maximum-pseudolikelihood estimator for the parameters that characterize a demographic expansion for a series of linked loci evolving under a stepwise mutation model. Those loci would correspond to DNA polymorphisms of linked microsatellites (such as those found on the Y chromosome or the chloroplast genome). The proposed method was evaluated with simulated data sets and with a data set of chloroplast microsatellites that showed signal for demographic expansion in a previous study. The results show that inclusion of a mutational model in the analysis improves the estimates of the age of expansion in the case of older expansions.

Twenty years of phylogeography: the state of the field and the challenges for the Southern Hemisphere

Phylogeography is a young, vigorous and integrative field of study that uses genetic data to understand the history of populations. This field has recently expanded into many areas of biology and also into several historical disciplines of Earth sciences. In this review, I present a numerical synthesis of the phylogeography literature based on an examination of over 3000 articles published during the first 20 years of the field (i.e. from 1987 to 2006). Information from several topics needed to evaluate the progress, tendencies and deficiencies of the field is summarized for 10 major groups of organisms and at a global scale. The topics include the geography of phylogeographic surveys, comparative nature of studies, temporal scales and major environments investigated, and genetic markers used. I also identify disparities in research productivity between the developing and the developed world, and propose ways to reduce some of the challenges faced by phylogeographers from less affluent countries. Phylogeography has experienced explosive growth in recent years fuelled by developments in DNA technology, theory and statistical analysis. I argue that the intellectual maturation of the field will eventually depend not only on these recent developments, but also on syntheses of comparative information across different regions of the globe. For this to become a reality, many empirical phylogeographic surveys in regions of the Southern Hemisphere (and in developing countries of the Northern Hemisphere) are needed. I expect the information and views presented here will assist in promoting international collaborative work in phylogeography and in guiding research efforts at both regional and global levels.

Generation time and effective population size in Polar Eskimos

North Greenland Polar Eskimos are the only hunter-gatherer population, to our knowledge, who can offer precise genealogical records spanning several generations. This is the first report from Eskimos on two key parameters in population genetics, namely, generation time (T) and effective population size (Ne). The average mother-daughter and father-son intervals were 27 and 32 years, respectively, roughly similar to the previously published generation times obtained from recent agricultural societies across the world. To gain an insight for the generation time in our distant ancestors, we calculated maternal generation time for two wild chimpanzee populations. We also provide the first comparison among three distinct approaches (genealogy, variance and life table methods) for calculating Ne, which resulted in slightly differing values for the Eskimos. The ratio of the effective to the census population size is estimated as 0.6-0.7 for autosomal and X-chromosomal DNA, 0.7-0.9 for mitochondrial DNA and 0.5 for Y-chromosomal DNA. A simulation of alleles along the genealogy suggested that Y-chromosomal DNA may drift a little faster than mitochondrial DNA in this population, in contrast to agricultural Icelanders. Our values will be useful not only in prehistoric population inference but also in understanding the shaping of our genome today.

A Markov chain Monte Carlo method for estimating population mixing using Y-chromosome markers: mixing of the Han people in China

We present a new approach for estimating mixing between populations based on non-recombining markers, specifically Y-chromosome microsatellites. A Markov chain Monte Carlo (MCMC) Bayesian statistical approach is used to calculate the posterior probability distribution of population parameters of interest, including the effective population size and the time to most recent common ancestor (MRCA). To test whether two populations are homogeneously mixed we introduce a "mixing" statistic defined for each coalescent event that weights the contribution of that ancestor's descendants to the two subpopulations, and an associated population "purity" statistic. Using simulated data with low levels of migration between two populations, we demonstrate that our method is more sensitive than other commonly used distance-based methods such as R(ST) and D(SW). To illustrate our method, we analysed mixing between 11 pre-defined Chinese ethnic/regional populations, using 5 microsatellite markers from the non-recombining region of the Y-chromosome (NRY), demonstrating a significant clustering of a subset of subpopulations with a high mutual relative degree of mixing (homogeneous mixing with support >0.99). Our analysis suggests that there is a strong correlation between effective population size and mixing with other subpopulations. Thus, despite considerable mixing between these groups, the purity statistic still identifies significant heterogeneity, suggesting that periods of historical isolation continue to leave a recoverable signal despite modern introgression.

Extreme patterns of variance in small populations: placing limits on human Y-chromosome diversity through time in the Vanuatu Archipelago

Small populations are dominated by unique patterns of variance, largely characterized by rapid drift of allele frequencies. Although the variance components of genetic datasets have long been recognized, most population genetic studies still treat all sampling locations equally despite differences in sampling and effective population sizes. Because excluding the effects of variance can lead to significant biases in historical reconstruction, variance components should be incorporated explicitly into population genetic analyses. The possible magnitude of variance effects in small populations is illustrated here via a case study of Y-chromosome haplogroup diversity in the Vanuatu Archipelago. Deme-based modelling is used to simulate allele frequencies through time, and conservative confidence bounds are placed on the accumulation of stochastic variance effects, including diachronic genetic drift and contemporary sampling error. When the information content of the dataset has been ascertained, demographic models with parameters falling outside the confidence bounds of the variance components can then be accepted with some statistical confidence. Here I emphasize how aspects of the demographic history of a population can be disentangled from stochastic variance effects, and I illustrate the extreme roles of genetic drift and sampling error for many small human population datasets.

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.

Bayesian identification of admixture events using multilocus molecular markers

Bayesian statistical methods for the estimation of hidden genetic structure of populations have gained considerable popularity in the recent years. Utilizing molecular marker data, Bayesian mixture models attempt to identify a hidden population structure by clustering individuals into genetically divergent groups, whereas admixture models target at separating the ancestral sources of the alleles observed in different individuals. We discuss the difficulties involved in the simultaneous estimation of the number of ancestral populations and the levels of admixture in studied individuals' genomes. To resolve this issue, we introduce a computationally efficient method for the identification of admixture events in the population history. Our approach is illustrated by analyses of several challenging real and simulated data sets. The software (baps), implementing the methods introduced here, is freely available at http://www.rni.helsinki.fi/~jic/bapspage.html.

Reconstructing human origins in the genomic era

Analyses of recently acquired genomic sequence data are leading to important insights into the early evolution of anatomically modern humans, as well as into the more recent demographic processes that accompanied the global radiation of Homo sapiens. Some of the new results contradict early, but still influential, conclusions that were based on analyses of gene trees from mitochondrial DNA and Y-chromosome sequences. In this review, we discuss the different genetic and statistical methods that are available for studying human population history, and identify the most plausible models of human evolution that can accommodate the contrasting patterns observed at different loci throughout the genome.

Genetic diversity, population structure, effective population size and demographic history of the Finnish wolf population

The Finnish wolf population (Canis lupus) was sampled during three different periods (1996-1998, 1999-2001 and 2002-2004), and 118 individuals were genotyped with 10 microsatellite markers. Large genetic variation was found in the population despite a recent demographic bottleneck. No spatial population subdivision was found even though a significant negative relationship between genetic relatedness and geographic distance suggested isolation by distance. Very few individuals did not belong to the local wolf population as determined by assignment analyses, suggesting a low level of immigration in the population. We used the temporal approach and several statistical methods to estimate the variance effective size of the population. All methods gave similar estimates of effective population size, approximately 40 wolves. These estimates were slightly larger than the estimated census size of breeding individuals. A Bayesian model based on Markov chain Monte Carlo simulations indicated strong evidence for a long-term population decline. These results suggest that the contemporary wolf population size is roughly 8% of its historical size, and that the population decline dates back to late 19th century or early 20th century. Despite an increase of over 50% in the census size of the population during the whole study period, there was only weak evidence that the effective population size during the last period was higher than during the first. This may be caused by increased inbreeding, diminished dispersal within the population, and decreased immigration to the population during the last study period.

Bayesian inference of evolutionary history from chloroplast microsatellites in the cosmopolitan weed Capsella bursa-pastoris (Brassicaceae)

Besides showing an extraordinary degree of phenotypic variability, Capsella bursa-pastoris (Brassicaceae) is also one of the world's most common plant species and a serious weed in many countries. We have employed a coalescent-based Bayesian analysis of chloroplast microsatellite data to infer demographic and evolutionary parameters of this species. Two different demographic models applied to data from seven chloroplast microsatellite loci among 59 accessions show that the effective population size of C. bursa-pastoris is very small indicating a rapid expansion of the species, a result that is in accordance with fossil and historical data. Against this background, analysis of flowering time variation among accessions suggests that ecotypic differentiation in flowering time has occurred recently in the species' history. Finally, our results also indicate that mononucleotide repeat loci in the chloroplast genome can deteriorate in relatively short periods of evolutionary time.

Comparative phylogeographic summary statistics for testing simultaneous vicariance

Testing for simultaneous vicariance across comparative phylogeographic data sets is a notoriously difficult problem hindered by mutational variance, the coalescent variance, and variability across pairs of sister taxa in parameters that affect genetic divergence. We simulate vicariance to characterize the behaviour of several commonly used summary statistics across a range of divergence times, and to characterize this behaviour in comparative phylogeographic datasets having multiple taxon-pairs. We found Tajima's D to be relatively uncorrelated with other summary statistics across divergence times, and using simple hypothesis testing of simultaneous vicariance given variable population sizes, we counter-intuitively found that the variance across taxon pairs in Nei and Li's net nucleotide divergence (pi(net)), a common measure of population divergence, is often inferior to using the variance in Tajima's D across taxon pairs as a test statistic to distinguish ancient simultaneous vicariance from variable vicariance histories. The opposite and more intuitive pattern is found for testing more recent simultaneous vicariance, and overall we found that depending on the timing of vicariance, one of these two test statistics can achieve high statistical power for rejecting simultaneous vicariance, given a reasonable number of intron loci (> 5 loci, 400 bp) and a range of conditions. These results suggest that components of these two composite summary statistics should be used in future simulation-based methods which can simultaneously use a pool of summary statistics to test comparative the phylogeographic hypotheses we consider here.

Likelihoods from summary statistics: recent divergence between species

We describe an importance-sampling method for approximating likelihoods of population parameters based on multiple summary statistics. In this first application, we address the demographic history of closely related members of the Drosophila pseudoobscura group. We base the maximum-likelihood estimation of the time since speciation and the effective population sizes of the extant and ancestral populations on the pattern of nucleotide variation at DPS2002, a noncoding region tightly linked to a paracentric inversion that strongly contributes to reproductive isolation. Consideration of summary statistics rather than entire nucleotide sequences permits a compact description of the genealogy of the sample. We use importance sampling first to propose a genealogical and mutational history consistent with the observed array of summary statistics and then to correct the likelihood with the exact probability of the history determined from a system of recursions. Analysis of a subset of the data, for which recursive computation of the exact likelihood was feasible, indicated close agreement between the approximate and exact likelihoods. Our results for the complete data set also compare well with those obtained through Metropolis-Hastings sampling of fully resolved genealogies of entire nucleotide sequences.

A structured ancestral population for the evolution of modern humans

The view that modern humans evolved through a bottleneck from a single founding group of archaic Homo is being challenged by new analyses of contemporary genetic variation. A wide range of middle to late Pleistocene ages for gene genealogies and evidence for early population structures point to a diverse and scattered ancestry associated with a metapopulation history of local extinctions, re-colonization and admixture. A different balance of the same processes has shaped chimpanzee diversity.

Demographic estimates from Y chromosome microsatellite polymorphisms: analysis of a worldwide sample

Polymorphisms in microsatellites on the human Y chromosome have been used to estimate important demographic parameters of human history. We compare two coalescent-based statistical methods that give estimates for a number of demographic parameters using the seven Y chromosome polymorphisms in the HGDP-CEPH Cell Line Panel, a collection of samples from 52 worldwide populations. The estimates for the time to the most recent common ancestor vary according to the method used and the assumptions about the prior distributions of model parameters, but are generally consistent with other global Y chromosome studies. We explore the sensitivity of these results to assumptions about the prior distributions and the evolutionary models themselves.

The structure of biodiversity - insights from molecular phylogeography

DNA techniques, analytical methods and palaeoclimatic studies are greatly advancing our knowledge of the global distribution of genetic diversity, and how it evolved. Such phylogeographic studies are reviewed from Arctic, Temperate and Tropical regions, seeking commonalities of cause in the resulting genetic patterns. The genetic diversity is differently patterned within and among regions and biomes, and is related to their histories of climatic changes. This has major implications for conservation science.