Demographic expansion of parasitic nematodes of livestock based on mitochondrial DNA regions that conflict with the infinite-sites model

Mitochondrial ND4 sequences of populations of four species of parasitic nematodes of livestock were subjected to demographic analyses. Deviation from selective neutrality was detectable using the frequency spectrum of segregating sites and highly negative neutrality statistics. However, the mitochondrial data sets do not comply with the infinite-sites model that underlies these tests, and as a consequence, it was not established whether these features are solely a result of population expansion, or whether aspects of the molecular evolution of these mitochondrial regions are also involved. Coalescent analyses based on Fu's Fs neutrality test, which incorporated estimates of rate heterogeneity, the transition-transversion ratio and nucleotide bias, as well as analyses that are fairly robust to deviations from the infinite-sites model supported population expansion. Also analyses that do not depend on the infinite-sites model suggested historical population expansion of these nematodes. The very similar time since expansion, the absence of signatures of positive selection in ND4 and the logical association with human demography imply that selective sweeps of mitochondrial variants are less probable, and that expansion is the most likely scenario for the parasitic nematodes of livestock. The methods used to characterize the expansion have different assumptions and emphasize different aspects of expansions. The resulting restrictions on the interpretation of expansions are outlined.     

The impact of population expansion and mutation rate heterogeneity on DNA sequence polymorphism

In order to study the effect of mutation rate heterogeneity on patterns of DNA polymorphism, we simulated samples of DNA sequences with gamma- distributed nucleotide substitution rates in stationary and expanding populations. We find that recent population expansions and mutation rate heterogeneity have similar effects on several polymorphism indicators, like the shape and the mean of the observed pairwise difference distribution, or the number of segregating sites. The inferred size of population expansion thus appears overestimated if nucleotides have dissimilar substitution rates. Interestingly, population expansion and uneven mutation rates have contrasting effects on Tajima's D statistic when acting separately, and the consequence on the associated test of selective neutrality is investigated. The patterns of polymorphism of several human populations analyzed for the mitochondrial control region are examined, mainly showing the difficulty in quantifying the respective contribution of past demographic history and uneven mutation rates from a single sampled evolutionary process. However, substitution rates appear more heterogeneous in the second hypervariable segment of the control region than in the first segment.      

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.     

Geography best explains global patterns of genetic diversity and postglacial co‐expansion in marine turtles

For many species, climate oscillations drove cycles of population contraction during cool glacial periods followed by expansion during interglacials. Some groups, however, show evidence of uniform and synchronous expansion, while others display differences in the timing and extent of demographic change. We compared demographic histories inferred from genetic data across marine turtle species to identify responses to postglacial warming shared across taxa and to examine drivers of past demographic change at the global scale. Using coalescent simulations and approximate Bayesian computation (ABC), we estimated demographic parameters, including the likelihood of past population expansion, from a mitochondrial data set encompassing 23 previously identified lineages from all seven marine turtle species. For lineages with a high posterior probability of expansion, we conducted a hierarchical ABC analysis to estimate the proportion of lineages expanding synchronously and the timing of synchronous expansion. We used Bayesian model averaging to identify variables associated with expansion and genetic diversity. Approximately 60% of extant marine turtle lineages showed evidence of expansion, with the rest mainly exhibiting patterns of genetic diversity most consistent with population stability. For lineages showing expansion, there was a strong signal of synchronous expansion after the Last Glacial Maximum. Expansion and genetic diversity were best explained by ocean basin and the degree of endemism for a given lineage. Geographic differences in sensitivity to climate change have implications for prioritizing conservation actions in marine turtles as well as for identifying areas of past demographic stability and potential resilience to future climate change for broadly distributed taxa.     

The Effects of Variable Mutation Rates across Sites on the Phylogenetic Estimation of Effective Population Size or Mutation Rate of DNA Sequences

Multiple hits at some sites of human mitochondrial DNA sequences suggest that the commonly assumed infinite-sites model can be violated. Under the neutral Wright-Fisher model without recombination and population subdivision, we investigated, by computer simulations, the effect of multiple hits on the estimation of the essential parameter θ = 4N(e)μ by FU's UPBLUE procedure. We found that with moderate mutation rate heterogeneity, UPBLUE performs very well in terms of unbiasness and efficiency. Under extreme mutation rate heterogeneity, if sample size is reasonably large (e.g., >60), UPBLUE is still very satisfactory; otherwise we developed a new correction equation. Given knowledge of the degree of mutation rate heterogeneity, the performance of UPBLUE with the new correction equation was tested to be fairly satisfactory: there is almost no bias and the sampling variance is only slightly higher than the theoretical minimum variance. Thus, with an appropriate correction, UPBLUE is relatively robust to the multiple hits. In genealogies reconstructed by UPGMA, we found that the total length of branches directly linked to the tips is underestimated, and those far away tend to be overestimated, while the total length of all branches is not biased.     

Quaternary range and demographic expansion of Liolaemus darwinii (Squamata: Liolaemidae) in the Monte Desert of Central Argentina using Bayesian phylogeography and ecological niche modelling

Until recently, most phylogeographic approaches have been unable to distinguish between demographic and range expansion processes, making it difficult to test for the possibility of range expansion without population growth and vice versa. In this study, we applied a Bayesian phylogeographic approach to reconstruct both demographic and range expansion in the lizard Liolaemus darwinii of the Monte Desert in Central Argentina, during the Late Quaternary. Based on analysis of 14 anonymous nuclear loci and the cytochrome b mitochondrial DNA gene, we detected signals of demographic expansion starting at ~55 ka based on Bayesian Skyline and Skyride Plots. In contrast, Bayesian relaxed models of spatial diffusion suggested that range expansion occurred only between ~95 and 55 ka, and more recently, diffusion rates were very low during demographic expansion. The possibility of population growth without substantial range expansion could account for the shared patterns of demographic expansion during the Last Glacial Maxima (OIS 2 and 4) in fish, small mammals and other lizards of the Monte Desert. We found substantial variation in diffusion rates over time, and very high rates during the range expansion phase, consistent with a rapidly advancing expansion front towards the southeast shown by palaeo‐distribution models. Furthermore, the estimated diffusion rates are congruent with observed dispersal rates of lizards in field conditions and therefore provide additional confidence to the temporal scale of inferred phylogeographic patterns. Our study highlights how the integration of phylogeography with palaeo‐distribution models can shed light on both demographic and range expansion processes and their potential causes.     

The number of segregating sites in expanding human populations, with implications for estimates of demographic parameters

The frequency distribution of pairwise differences between sequences of mtDNA has recently been used to estimate the size of human populations before and after a hypothetical episode of rapid population growth and the time at which the population grew. To test the internal consistency of this method, we used three different sets of human mtDNA data and the corresponding demographic parameters estimated from the distribution of pairwise differences to determine by simulation the expected number of segregating sites, S, and its empirical distribution. The results indicate that the observed values of S are significantly lower than expected in two of three cases under the assumption of the infinite-sites model. Further simulations in which mutations were allowed to occur more than once at the same site and in which there was variation in mutation rate among sites show that the expected number of segregating sites can be much lower than under the infinite-site assumption. Nevertheless, the observed value of S is still significantly different from the value expected under the expansion hypothesis in two of three cases.      

Genetic traces of east-to-west human expansion waves in Eurasia

In this study, we describe the landscape of human demographic expansions in Eurasia using a large continental Y chromosome and mitochondrial DNA dataset. Variation at these two uniparentally-inherited genetic systems retraces expansions that occurred in the past 60 ky, and shows a clear decrease of expansion ages from east to west Eurasia. To investigate the demographic events at the origin of this westward decrease of expansion ages, the estimated divergence ages between Eurasian populations are compared with the estimated expansion ages within each population. Both markers suggest that the demographic expansion diffused from east to west in Eurasia in a demic way, i.e., through migrations of individuals (and not just through diffusion of new technologies), highlighting the prominent role of eastern regions within Eurasia during Palaeolithic times.     

Genetic evidence for long-term population decline in a savannah-dwelling primate: inferences from a hierarchical bayesian model

The purpose of this study was to test for evidence that savannah baboons (Papio cynocephalus) underwent a population expansion in concert with a hypothesized expansion of African human and chimpanzee populations during the late Pleistocene. The rationale is that any type of environmental event sufficient to cause simultaneous population expansions in African humans and chimpanzees would also be expected to affect other codistributed mammals. To test for genetic evidence of population expansion or contraction, we performed a coalescent analysis of multilocus microsatellite data using a hierarchical Bayesian model. Markov chain Monte Carlo (MCMC) simulations were used to estimate the posterior probability density of demographic and genealogical parameters. The model was designed to allow interlocus variation in mutational and demographic parameters, which made it possible to detect aberrant patterns of variation at individual loci that could result from heterogeneity in mutational dynamics or from the effects of selection at linked sites. Results of the MCMC simulations were consistent with zero variance in demographic parameters among loci, but there was evidence for a 10- to 20-fold difference in mutation rate between the most slowly and most rapidly evolving loci. Results of the model provided strong evidence that savannah baboons have undergone a long-term historical decline in population size. The mode of the highest posterior density for the joint distribution of current and ancestral population size indicated a roughly eightfold contraction over the past 1,000 to 250,000 years. These results indicate that savannah baboons apparently did not share a common demographic history with other codistributed primate species.     

Heterogeneity of microsatellite mutations within and between loci,and implications for human demographic histories.

Microsatellites have been widely used to reconstruct human evolution. However, the efficient use of these markers relies on information regarding the process producing the observed variation. Here, we present a novel approach to the locus-by-locus characterization of this process. By analyzing somatic mutations in cancer patients, we estimated the distributions of mutation size for each of 20 loci. The same loci were then typed in three ethnically diverse population samples. The generalized stepwise mutation model was used to test the predicted relationship between population and mutation parameters under two demographic scenarios: constant population size and rapid expansion. The agreement between the observed and expected relationship between population and mutation parameters, even when the latter are estimated in cancer patients, confirms that somatic mutations may be useful for investigating the process underlying population variation. Estimated distributions of mutation size differ substantially amongst loci, and mutations of more than one repeat unit are common. A new statistic, the normalized population variance, is introduced for multilocus estimation of demographic parameters, and for testing demographic scenarios. The observed population variation is not consistent with a constant population size. Time estimates of the putative population expansion are in agreement with those obtained by other methods.     

Effects of Mitochondrial DNA Rate Variation on Reconstruction of Pleistocene Demographic History in a Social Avian Species,Pomatostomus superciliosus

Mitochondrial sequence data is often used to reconstruct the demographic history of Pleistocene populations in an effort to understand how species have responded to past climate change events. However, departures from neutral equilibrium conditions can confound evolutionary inference in species with structured populations or those that have experienced periods of population expansion or decline. Selection can affect patterns of mitochondrial DNA variation and variable mutation rates among mitochondrial genes can compromise inferences drawn from single markers. We investigated the contribution of these factors to patterns of mitochondrial variation and estimates of time to most recent common ancestor (T_MRCA) for two clades in a co-operatively breeding avian species, the white-browed babbler Pomatostomus superciliosus. Both the protein-coding ND3 gene and hypervariable domain I control region sequences showed departures from neutral expectations within the superciliosus clade, and a two-fold difference in T_MRCA estimates. Bayesian phylogenetic analysis provided evidence of departure from a strict clock model of molecular evolution in domain I, leading to an over-estimation of T_MRCA for the superciliosus clade at this marker. Our results suggest mitochondrial studies that attempt to reconstruct Pleistocene demographic histories should rigorously evaluate data for departures from neutral equilibrium expectations, including variation in evolutionary rates across multiple markers. Failure to do so can lead to serious errors in the estimation of evolutionary parameters and subsequent demographic inferences concerning the role of climate as a driver of evolutionary change. These effects may be especially pronounced in species with complex social structures occupying heterogeneous environments. We propose that environmentally driven differences in social structure may explain observed differences in evolutionary rate of domain I sequences, resulting from longer than expected retention times for matriarchal lineages in the superciliosus clade.     

Relating dispersal and range expansion of California sea otters

Linking dispersal and range expansion of invasive species has long challenged theoretical and quantitative ecologists. Subtle differences in dispersal can yield large differences in geographic spread, with speeds ranging from constant to rapidly increasing. We developed a stage-structured integrodifference equation (IDE) model of the California sea otter range expansion that occurred between 1914 and 1986. The non-spatial model, a linear matrix population model, was coupled to a suite of candidate dispersal kernels to form stage-structured IDEs. Demographic and dispersal parameters were estimated independent of range expansion data. Using a single dispersal parameter, alpha, we examined how well these stage-structured IDEs related small scale demographic and dispersal processes with geographic population expansion. The parameter alpha was estimated by fitting the kernels to dispersal data and by fitting the IDE model to range expansion data. For all kernels, the alpha estimate from range expansion data fell within the 95% confidence intervals of the alpha estimate from dispersal data. The IDE models with exponentially bounded kernels predicted invasion velocities that were captured within the 95% confidence bounds on the observed northbound invasion velocity. However, the exponentially bounded kernels yielded range expansions that were in poor qualitative agreement with range expansion data. An IDE model with fat (exponentially unbounded) tails and accelerating spatial spread yielded the best qualitative match. This model explained 94% and 97% of the variation in northbound and southbound range expansions when fit to range expansion data. These otters may have been fat-tailed accelerating invaders or they may have followed a piece-wise linear spread first over kelp forests and then over sandy habitats. Further, habitat-specific dispersal data could resolve these explanations.     

Population growth of human Y chromosomes: a study of Y chromosome microsatellites

We use variation at a set of eight human Y chromosome microsatellite loci to investigate the demographic history of the Y chromosome. Instead of assuming a population of constant size, as in most of the previous work on the Y chromosome, we consider a model which permits a period of recent population growth. We show that for most of the populations in our sample this model fits the data far better than a model with no growth. We estimate the demographic parameters of this model for each population and also the time to the most recent common ancestor. Since there is some uncertainty about the details of the microsatellite mutation process, we consider several plausible mutation schemes and estimate the variance in mutation size simultaneously with the demographic parameters of interest. Our finding of a recent common ancestor (probably in the last 120,000 years), coupled with a strong signal of demographic expansion in all populations, suggests either a recent human expansion from a small ancestral population, or natural selection acting on the Y chromosome.     

Recovering population parameters from a single gene genealogy: an unbiased estimator of the growth rate

We show that the number of lineages ancestral to a sample, as a function of time back into the past, which we call the number of lineages as a function of time (NLFT), is a nearly deterministic property of large-sample gene genealogies. We obtain analytic expressions for the NLFT for both constant-sized and exponentially growing populations. The low level of stochastic variation associated with the NLFT of a large sample suggests using the NLFT to make estimates of population parameters. Based on this, we develop a new computational method of inferring the size and growth rate of a population from a large sample of DNA sequences at a single locus. We apply our method first to a sample of 1,212 mitochondrial DNA (mtDNA) sequences from China, confirming a pattern of recent population growth previously identified using other techniques, but with much smaller confidence intervals for past population sizes due to the low variation of the NLFT. We further analyze a set of 63 mtDNA sequences from blue whales (BWs), concluding that the population grew in the past. This calls for reevaluation of previous studies that were based on the assumption that the BW population was fixed.     

Influence of spatial and temporal heterogeneities on the estimation of demographic parameters in a continuous population using individual microsatellite data

Drift and migration disequilibrium are very common in animal and plant populations. Yet their impact on methods of estimation of demographic parameters was rarely evaluated especially in complex realistic population models. The effect of such disequilibria on the estimation of demographic parameters depends on the population model, the statistics, and the genetic markers used. Here we considered the estimation of the product Dsigma2 from individual microsatellite data, where D is the density of adults and sigma2 the average squared axial parent-offspring distance in a continuous population evolving under isolation by distance. A coalescence-based simulation algorithm was used to study the effect on Dsigma2 estimation of temporal and spatial fluctuations of demographic parameters. Estimation of present-time Dsigma2 values was found to be robust to temporal changes in dispersal, to density reduction, and to spatial expansions with constant density, even for relatively recent changes (i.e., a few tens of generations ago). By contrast, density increase in the recent past gave Dsigma2 estimations biased largely toward past demographic parameters values. The method was also robust to spatial heterogeneity in density and estimated local demographic parameters when the density is homogenous around the sampling area (e.g., on a surface that equals four times the sampling area). Hence, in the limit of the situations studied in this article, and with the exception of the case of density increase, temporal and spatial fluctuations of demographic parameters appear to have a limited influence on the estimation of local and present-time demographic parameters with the method studied.     

Generating samples under a Wright-Fisher neutral model of genetic variation

A Monte Carlo computer program is available to generate samples drawn from a population evolving according to a Wright-Fisher neutral model. The program assumes an infinite-sites model of mutation, and allows recombination, gene conversion, symmetric migration among subpopulations, and a variety of demographic histories. The samples produced can be used to investigate the sampling properties of any sample statistic under these neutral models.     

Statistical properties of the variation at linked microsatellite loci: implications for the history of human Y chromosomes [published erratum appears in Mol Biol Evol 1997 Mar;14(3):354]

It has recently been suggested that observed levels of variation at microsatellite loci can be used to infer patterns of selection in genomes and to assess demographic history. In order to evaluate the feasibility of these suggestions it is necessary to know something about how levels of variation at microsatellite loci are expected to fluctuate due simply to stochasticity in the processes of mutation and inheritance (genetic sampling). Here we use recently derived properties of the stepwise mutation model to place confidence intervals around the variance in repeat score that is expected at mutation-drift equilibrium and outline a statistical test for whether an observed value differs significantly from expectation. We also develop confidence intervals for the time course of the buildup of variation following a complete elimination of variation, such as might be caused by a selective sweep or an extreme population bottleneck. We apply these methods to the variation observed at human Y-specific microsatellites. Although a number of authors have suggested the possibility of a very recent sweep, our analyses suggest that a sweep or extreme bottleneck is unlikely to have occurred anytime during the last approximately 74,000 years. To generate this result we use a recently estimated mutation rate for microsatellite loci of 5.6 x 10(-4) along with the variation observed at autosomal microsatellite loci to estimate the human effective population size. This estimate is 18,000, implying an effective number of 4,500 Y chromosomes. One important general conclusion to emerge from this study is that in order to reject mutation-drift equilibrium at a set of linked microsatellite loci it is necessary to have an unreasonably large number of loci unless the observed variance is far below that expected at mutation-drift equilibrium.      

A coalescent-based method for detecting and estimating recombination from gene sequences

Determining the amount of recombination in the genealogical history of a sample of genes is important to both evolutionary biology and medical population genetics. However, recurrent mutation can produce patterns of genetic diversity similar to those generated by recombination and can bias estimates of the population recombination rate. Hudson 2001 has suggested an approximate-likelihood method based on coalescent theory to estimate the population recombination rate, 4N(e)r, under an infinite-sites model of sequence evolution. Here we extend the method to the estimation of the recombination rate in genomes, such as those of many viruses and bacteria, where the rate of recurrent mutation is high. In addition, we develop a powerful permutation-based method for detecting recombination that is both more powerful than other permutation-based methods and robust to misspecification of the model of sequence evolution. We apply the method to sequence data from viruses, bacteria, and human mitochondrial DNA. The extremely high level of recombination detected in both HIV1 and HIV2 sequences demonstrates that recombination cannot be ignored in the analysis of viral population genetic data.     

Simulating the mitochondrial DNA inheritance

Summary Analysing the current mitochondrial DNA patterns biologists have concluded that we all descend from the same mitochondrial Eve, who is postulated to have lived around 200.000 years ago. Such a result is in agreement with the coalescence theory. Here we represent the mitochondrial DNAs as bitstrings that are maternally transmitted with mutations, and that may also participate in the selection process for survival together with the nuclear DNAs. We end up with the same common ancestor, whose mitochondrial DNA can be traced back from the current population, despite the mitochondrial mutations considered. For a given mutation rate, the degree of confidence of this tracing-back process increases even further when the selection mechanism is included.