Repetitive genomic regions and the inference of demographic history

Inference of demographic histories using whole-genome datasets has provided insights into diversification, adaptation, hybridization, and plant–pathogen interactions, and stimulated debate on the impact of anthropogenic interventions and past climate on species demography. However, the impact of repetitive genomic regions on these inferences has mostly been ignored by masking of repeats. We use the Populus trichocarpa genome (Pop_tri_v3) to show that masking of repeat regions leads to lower estimates of effective population size (N_e) in the distant past in contrast to an increase in N_e estimates in recent times. However, in human datasets, masking of repeats resulted in lower estimates of N_e at all time points. We demonstrate that repeats affect demographic inferences using diverse methods like PSMC, MSMC, SMC++, and the Stairway plot. Our genomic analysis revealed that the biases in N_e estimates were dependent on the repeat class type and its abundance in each atomic interval. Notably, we observed a weak, yet consistently significant negative correlation between the repeat abundance of an atomic interval and the N_e estimates for that interval, which potentially reflects the recombination rate variation within the genome. The rationale for the masking of repeats has been that variants identified within these regions are erroneous. We find that polymorphisms in some repeat classes occur in callable regions and reflect reliable coalescence histories (e.g., LTR Gypsy, LTR Copia). The current demography inference methods do not handle repeats explicitly, and hence the effect of individual repeat classes needs careful consideration in comparative analysis. Deciphering the repeat demographic histories might provide a clear understanding of the processes involved in repeat accumulation.Subject terms: Genetic variation, Genome evolution     

Joint inference of microsatellite mutation models, population history and genealogies using transdimensional Markov Chain Monte Carlo

We provide a framework for Bayesian coalescent inference from microsatellite data that enables inference of population history parameters averaged over microsatellite mutation models. To achieve this we first implemented a rich family of microsatellite mutation models and related components in the software package BEAST. BEAST is a powerful tool that performs Bayesian MCMC analysis on molecular data to make coalescent and evolutionary inferences. Our implementation permits the application of existing nonparametric methods to microsatellite data. The implemented microsatellite models are based on the replication slippage mechanism and focus on three properties of microsatellite mutation: length dependency of mutation rate, mutational bias toward expansion or contraction, and number of repeat units changed in a single mutation event. We develop a new model that facilitates microsatellite model averaging and Bayesian model selection by transdimensional MCMC. With Bayesian model averaging, the posterior distributions of population history parameters are integrated across a set of microsatellite models and thus account for model uncertainty. Simulated data are used to evaluate our method in terms of accuracy and precision of estimation and also identification of the true mutation model. Finally we apply our method to a red colobus monkey data set as an example.     

Global population structure and demographic history of the grey seal

Although the grey seal Halichoerus grypus is one of the most familiar and intensively studied of all pinniped species, its global population structure remains to be elucidated. Little is also known about how the species as a whole may have historically responded to climate‐driven changes in habitat availability and anthropogenic exploitation. We therefore analysed samples from over 1500 individuals collected from 22 colonies spanning the Western and Eastern Atlantic and the Baltic Sea regions, represented by 350 bp of the mitochondrial hypervariable region and up to nine microsatellites. Strong population structure was observed at both types of marker, and highly asymmetrical patterns of gene flow were also inferred, with the Orkney Islands being identified as a source of emigrants to other areas in the Eastern Atlantic. The Baltic and Eastern Atlantic regions were estimated to have diverged a little over 10 000 years ago, consistent with the last proposed isolation of the Baltic Sea. Approximate Bayesian computation also identified genetic signals consistent with postglacial population expansion across much of the species range, suggesting that grey seals are highly responsive to changes in habitat availability.     

Model‐based demographic inference of introgression history in European whitefish species pairs'

Parallel phenotypic differentiation is generally attributed to parallel adaptive divergence as an evolutionary response to similar environmental contrasts. Such parallelism may actually originate from several evolutionary scenarios ranging from repeated parallel divergence caused by divergent selection to a unique divergence event followed by gene flow. Reconstructing the evolutionary history underlying parallel phenotypic differentiation is thus fundamental to understand the relative contribution of demography and selection on genomic divergence during speciation. In this study, we investigate the divergence history of replicate European whitefish (Coregonus lavaretus), limnetic and benthic species pairs from two lakes in Norway and two lakes in Switzerland. Demographic models accounting for semi‐permeability and linked selection were fitted to the unfolded joint allele frequency spectrum built from genome‐wide SNPs and compared to each other in each species pair. We found strong support for a model of asymmetrical post‐glacial secondary contact between glacial lineages in all four lakes. Moreover, our results suggest that heterogeneous genomic differentiation has been shaped by the joint action of linked selection accelerating lineage sorting during allopatry, and heterogeneous migration eroding divergence at different rates along the genome following secondary contact. Our analyses reveal how the interplay between demography, selection and historical contingency has influenced the levels of diversity observed in previous whitefish phylogeographic studies. This study thus provides new insights into the historical demographic and selective processes that shaped the divergence associated with ecological speciation in European whitefish.     

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.     

Effects of recent population bottlenecks on reconstructing the demographic history of prairie-chickens

Current methods of DNA sequence analysis attempt to reconstruct historical patterns of population structure and growth from contemporary samples. However, these techniques may be influenced by recent population bottlenecks, which have the potential to eliminate lineages that reveal past changes in demography. One way to examine the performance of these demographic methods is to compare samples from populations before and after recent bottlenecks. We compared estimates of demographic history from populations of greater prairie-chickens (Tympanuchus cupido) before and after recent bottlenecks using four common methods (nested clade analysis [NCA], Tajima's D, mismatch distribution, and MDIV). We found that NCA did not perform well in the presence of bottleneck events, although it did recover some genetic signals associated with increased isolation and the extinction of intermediate populations. The majority of estimates for Tajima's D, including those from bottlenecked populations, were not significantly different from zero, suggesting our data conformed to neutral expectations. In contrast, mismatch distributions including the raggedness index were more likely to identify recently bottlenecked populations with this data set. Estimates of population mutation rate (theta), population divergence time (t), and time to the most recent common ancestor (TMRCA) from MDIV were similar before and after bottlenecks; however, estimates of gene flow (M) were significantly lower in a few cases following a bottleneck. These results suggest that caution should be used when assessing demographic history from contemporary data sets, as recently fragmented and bottlenecked populations may have lost lineages that affect inferences of their demographic history.     

Integrating Pool-seq uncertainties into demographic inference

Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modelling Pool-seq sources of error. By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome) and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin) and to infer relevant demographic parameters (e.g. effective sizes and split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e. single origin) and are maintained despite gene flow. These results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.     

Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation

1. Download : Download high-res image (181KB)
2. Download : Download full-size image

     

Contrasting population structure and demographic history of cereal aphids in different environmental and agricultural landscapes

Genetic diversity of populations has important ecological and evolutionary consequences, whose understanding is fundamental to improve the sustainability of agricultural production. Studies of how differences in agricultural management and environment influence the population structure of insect pests are central to predict outbreaks and optimize control programs. Here, we have studied the population genetic diversity and evolution of Sitobion avenae and Sitobion miscanthi, which are among the most relevant aphid pests of cereals across Europe and Asia, respectively. We have used genotyping by sequencing (GBS) to identify genome‐wide single nucleotide polymorphisms (SNPs) to infer the geographic structure and migration patterns. In the present study, we show that the population structure in present‐day populations is different from that described in previous studies, which suggest that they have evolved recently possibly as a response to human‐induced changes in agriculture. This study shows that S. avenae in England is predominantly parthenogenetic and there has been a demographic and spatial expansion of a single genetic cluster, which could correspond with the insecticide resistance superclone identified in previous studies. Conversely, in China, S. miscanthi populations are mostly cyclical parthenogenetic, with one sexual stage in autumn to produce overwintering eggs, and there are six genetically differentiated subpopulations and high genetic differentiation between geographic locations, which suggests that further taxonomical research is needed. Unlike S. avenae in England, there is no evidence for insecticide resistance and there is no predominance of a single lineage in S. miscanthi in China.     

An integrated framework for the inference of viral population history from reconstructed genealogies

We describe a unified set of methods for the inference of demographic history using genealogies reconstructed from gene sequence data. We introduce the skyline plot, a graphical, nonparametric estimate of demographic history. We discuss both maximum-likelihood parameter estimation and demographic hypothesis testing. Simulations are carried out to investigate the statistical properties of maximum-likelihood estimates of demographic parameters. The simulations reveal that (i) the performance of exponential growth model estimates is determined by a simple function of the true parameter values and (ii) under some conditions, estimates from reconstructed trees perform as well as estimates from perfect trees. We apply our methods to HIV-1 sequence data and find strong evidence that subtypes A and B have different demographic histories. We also provide the first (albeit tentative) genetic evidence for a recent decrease in the growth rate of subtype B.     

Inferring the population structure and demographic history of the tick, Amblyomma americanum Linnaeus.

A hierarchial population genetic study was conducted on 703 individual Amblyomma americanum from nine populations in Georgia, U.S.A. Populations were sampled from the Coastal Plain, midland Piedmont region, and the upper Piedmont region. Twenty-nine distinct haplotypes were found. A minimum spanning tree was constructed that indicated these haplotypes comprised two lineages, the root of which was distinctly star-like. The majority of the variation found was among ticks within each population, indicating high amounts of gene flow and little genetic differentiation between the three regions. An overall F(ST) value of 0.006 supported the lack of genetic structuring between collection sites in Georgia. Mantel regression analysis revealed no isolation by distance. Signatures of population expansion were detected in the shapes of the mismatch distribution and tests of neutrality. The absence of genetic differentiation combined with the rejection of the null model of isolation by distance may indicate recent range expansion in Georgia or insufficient time to reach an equilibrium where genetic drift may have affected allele frequencies. Alternatively, the high degree of panmixia found within A. americanum in Georgia may be due to bird-mediated dispersal of ticks increasing the genetic similarity between geographically separated populations.     

Barcoding,population structure,and demographic history of Prodiplosis longifila associated with the Andes

Prodiplosis longifila Gagné (Diptera: Cecidomyiidae) is an insect pest that attacks various types of crops, including tomato, Solanum lycopersicum L. (Solanaceae), a vegetable with substantial economic significance worldwide. Prodiplosis longifila is a widely distributed pest in Colombia, Ecuador, and Peru, countries characterized by the presence of significant geographic barriers like the Andes Mountains. It has been reported that geographic barriers affect the dynamics and genetic differentiation of insect populations. Therefore, the aim of this study was to assess the diversity, genetic structure, and demographic history of P. longifila through the analysis of sequences within the mitochondrial region of cytochrome oxidase I (COI) and rDNA‐ITS2 in 27 populations located in Colombia and Ecuador. Analyses were performed on populations distributed in three geographic groups separated by the presence of the Andes Mountains. A total of 11 haplotypes were identified with the COI gene and only one haplotype in the rDNA‐ITS2 was found. Analyses of population structure and demographic history revealed that there is a structure associated with the Andes, which is reflected in an uneven distribution of the haplotype frequencies between regions, but even so, gene flow between populations was detected which produces low genetic differentiation. Because P. longifila has a short‐range dispersion that determines its territorial nature, it would be expected that other factors are producing the genetic exchange between populations. We suggest that the anthropogenic effect produced by farming practices, such as the use of seedlings as seed, which may carry P. longifila larvae, cause passive dispersal of pest throughout the Andes, particularly in Colombia.     

Life history evolution and demographic stochasticity

Summary Can demographic stochasticity bias the evolution of life history traits? Under a neutral version of the Cole-Charnov-Schaffer model, variance in offspring number for both annuals and perennials depends on the precise values of fitness components. Either annuals or perennials may have the larger variance (for equal ), depending on the importance of random survivalversus fixed reproduction. By extension, the variance in offspring number should generally depend on whether is mainly composed of highly variable elements or elements with limited variation. Thus, data about the variability of demographic parameters may be as important as data about their mean values.This result concerns only one source of demographic stochasticity, the probabilistic nature of demographic processes like survival. The other source of demographic stochasticity is the fact that populations are composed of whole numbers of individuals (integer arithmetic). Integer arithmetic without probabilistic demography (or environmental variation) can make it difficult for rare invaders to persist in populations even when selection would favour the invaders in a deterministic model. Integer arithmetic can also cause population coexistence when the equivalent deterministic model leads to exclusion. This effect disappears when demography is probabilistic, and probably also when there is environmental variation. Thus probabilistic demography and environmental variation may make some population patterns more, rather than less, understandable.     

Drivers of megaherbivore demographic fluctuations: inference from elephants

Environmentally induced variation in survival and fecundity generates demographic fluctuations that affect population growth rate. However, a general pattern of the comparative influence of variation in fecundity and juvenile survival on elephant population dynamics has not been investigated at a broad scale. We evaluated the relative importance of conception, gestation, first year survival and subsequent survivorship for controlling demographic variation by exploring the relationship between past environmental conditions determined by integrated normalized difference vegetation index (INDVI) and the shape of age distributions at 17 sites across Africa. We showed that, generally, INDVI during gestation best explained anomalies in age structure. However, in areas with low mean annual rainfall, INDVI during the first year of life was critical. The results challenge Eberhardt's paradigm for population analysis that suggests that populations respond to limited resource availability through a sequential decrease in juvenile survival, reproductive rate and adult survival. Contrastingly, elephants appear to respond first through a reduction in reproductive rate. We conclude that this discrepancy is likely due to the evolutionary significance of extremely large body size – an adaptation that increases survival rate but decreases reproductive potential. Other megaherbivores may respond similarly to resource limitation due to similarities in population dynamics. Knowing how vital rates vary with changing environmental conditions will permit better forecasts of the trajectories of megaherbivore populations.     

Germ banks affect the inference of past demographic events

Continuous progress in empirical population genetics based on the whole‐genome polymorphism data requires the theoretical analysis of refined models in order to interpret the evolutionary history of populations with adequate accuracy. Recent studies focus prevalently on the aspects of demography and adaptation, whereas age structure (for example, in plants via the maintenance of seed banks) has attracted less attention. Germ banking, that is, seed or egg dormancy, is a prevalent and important life‐history trait in plants and invertebrates, which buffers against environmental variability and modulates species extinction in fragmented habitats. Within this study, we investigate the combined effect of germ banking and time‐varying population size on the neutral coalescent and particularly derive the allele frequency spectrum under some simplifying assumptions. We then perform an ABC analysis using two simple demographic scenarios—a population expansion and an instantaneous decline. We demonstrate the appreciable influence of seed banks on the estimation of demographic parameters depending on the germination rate with biases scaled by the square of the germination rate. In the more complex case of a population bottleneck, which comprises an instantaneous decline and an expansion phase, ignoring information on the germination rate denies reliable estimates of the bottleneck parameters via the allelic spectrum. In particular, when seeds remain in the bank over several generations, recent expansions may remain invisible in the frequency spectrum, whereas ancient declines leave signatures much longer than in the absence of seed bank.     

REJECTOR: software for population history inference from genetic data via a rejection algorithm

We introduce REJECTOR, software for parameter estimation and comparison of alternate models of population history from genetic data via a rejection algorithm. Through coalescent simulation, REJECTOR generates numerous gene genealogies, and hence simulated data, under a model of population history specified by the user. Summary statistics derived from such simulated data are compared with observed statistics, leading to acceptance or rejection of a given set of parameter values. We performed tests of the software using known parameter values in order to assess the inferential power provided by each summary statistic. The tests demonstrate the precision and accuracy of estimation made possible using this approach. AVAILABILITY: http://www.rejector.org     

Genome-scale analysis of demographic history and adaptive selection

One of the main topics in population genetics is identification of adaptive selection among populations. For this purpose, population history should be correctly inferred to evaluate the effect of random drift and exclude it in selection identification. With the rapid progress in genomics in the past decade, vast genomescale variations are available for population genetic analysis, which however requires more sophisticated models to infer species’ demographic history and robust methods to detect local adaptation. Here we aim to review what have been achieved in the fields of demographic modeling and selection detection. We summarize their rationales, implementations, and some classical applications. We also propose that some widely-used methods can be improved in both theoretical and practical aspects in near future.