Using phylochronology to reveal cryptic population histories: review and synthesis of 29 ancient DNA studies

The evolutionary history of a population involves changes in size, movements and selection pressures through time. Reconstruction of population history based on modern genetic data tends to be averaged over time or to be biased by generally reflecting only recent or extreme events, leaving many population historic processes undetected. Temporal genetic data present opportunities to reveal more complex population histories and provide important insights into what processes have influenced modern genetic diversity. Here we provide a synopsis of methods available for the analysis of ancient genetic data. We review 29 ancient DNA studies, summarizing the analytical methods and general conclusions for each study. Using the serial coalescent and a model-testing approach, we then re-analyse data from two species represented by these data sets in a common interpretive framework. Our analyses show that phylochronologic data can reveal more about population history than modern data alone, thus revealing 'cryptic' population processes, and enable us to determine whether simple or complex models best explain the data. Our re-analyses point to the need for novel methods that consider gene flow, multiple populations and population size in reconstruction of population history. We conclude that population genetic samples over large temporal and geographical scales, when analysed using more complex models and the serial coalescent, are critical to understand past population dynamics and provide important tools for reconstructing the evolutionary process.     

Bayesian estimation of the timing and severity of a population bottleneck from ancient DNA

In this first application of the approximate Bayesian computation approach using the serial coalescent, we demonstrated the estimation of historical demographic parameters from ancient DNA. We estimated the timing and severity of a population bottleneck in an endemic subterranean rodent, Ctenomys sociabilis, over the last 10,000 y from two cave sites in northern Patagonia, Argentina. Understanding population bottlenecks is important in both conservation and evolutionary biology. Conservation implications include the maintenance of genetic variation, inbreeding, fixation of mildly deleterious alleles, and loss of adaptive potential. Evolutionary processes are impacted because of the influence of small populations in founder effects and speciation. We found a decrease from a female effective population size of 95,231 to less than 300 females at 2,890 y before present: a 99.7% decline. Our study demonstrates the persistence of a species depauperate in genetic diversity for at least 2,000 y and has implications for modes of speciation in the incredibly diverse rodent genus Ctenomys. Our approach shows promise for determining demographic parameters for other species with ancient and historic samples and demonstrates the power of such an approach using ancient DNA.     

Sex-biased genetic component distribution among populations: additive genetic and maternal contributions to phenotypic differences among populations of Chinook salmon

An approach frequently used to demonstrate a genetic basis for population-level phenotypic differences is to employ common garden rearing designs, where observed differences are assumed to be attributable to primarily additive genetic effects. Here, in two common garden experiments, we employed factorial breeding designs between wild and domestic, and among wild populations of Chinook salmon (Oncorhynchus tshawytscha). We measured the contribution of additive (V(A)) and maternal (V(M)) effects to the observed population differences for 17 life history and fitness-related traits. Our results show that, in general, maternal effects contribute more to phenotypic differences among populations than additive genetic effects. These results suggest that maternal effects are important in population phenotypic differentiation and also signify that the inclusion of the maternal source of variation is critical when employing models to test population differences in salmon, such as in local adaptation studies.     

Temporal change in genetic integrity suggests loss of local adaptation in a wild Atlantic salmon (Salmo salar) population following introgression by farmed escapees

In some wild Atlantic salmon populations, rapid declines in numbers of wild returning adults has been associated with an increase in the prevalence of farmed salmon. Studies of phenotypic variation have shown that interbreeding between farmed and wild salmon may lead to loss of local adaptation. Yet, few studies have attempted to assess the impact of interbreeding at the genome level, especially among North American populations. Here, we document temporal changes in the genetic makeup of the severely threatened Magaguadavic River salmon population (Bay of Fundy, Canada), a population that might have been impacted by interbreeding with farmed salmon for nearly 20 years. Wild and farmed individuals caught entering the river from 1980 to 2005 were genotyped at 112 single-nucleotide polymorphisms (SNPs), and/or eight microsatellite loci, to scan for potential shifts in adaptive genetic variation. No significant temporal change in microsatellite-based estimates of allele richness or gene diversity was detected in the wild population, despite its precipitous decline in numbers over the last two decades. This might reflect the effect of introgression from farmed salmon, which was corroborated by temporal change in linkage-disequilibrium. Moreover, SNP genome scans identified a temporal decrease in candidate loci potentially under directional selection. Of particular interest was a SNP previously shown to be strongly associated with an important quantitative trait locus for parr mark number, which retained its genetic distinctiveness between farmed and wild fish longer than other outliers. Overall, these results indicate that farmed escapees have introgressed with wild Magaguadavic salmon resulting in significant alteration of the genetic integrity of the native population, including possible loss of adaptation to wild conditions.     

Estimating divergence times from DNA sequences

The patterns of genetic variation within and among individuals and populations can be used to make inferences about the evolutionary forces that generated those patterns. Numerous population genetic approaches have been developed in order to infer evolutionary history. Here, we present the “Two-Two (TT)” and the “Two-Two-outgroup (TTo)” methods; two closely related approaches for estimating divergence time based in coalescent theory. They rely on sequence data from two haploid genomes (or a single diploid individual) from each of two populations. Under a simple population-divergence model, we derive the probabilities of the possible sample configurations. These probabilities form a set of equations that can be solved to obtain estimates of the model parameters, including population split times, directly from the sequence data. This transparent and computationally efficient approach to infer population divergence time makes it possible to estimate time scaled in generations (assuming a mutation rate), and not as a compound parameter of genetic drift. Using simulations under a range of demographic scenarios, we show that the method is relatively robust to migration and that the TTo method can alleviate biases that can appear from drastic ancestral population size changes. We illustrate the utility of the approaches with some examples, including estimating split times for pairs of human populations as well as providing further evidence for the complex relationship among Neandertals and Denisovans and their ancestors.     

微卫星标记对黑龙江流域大麻哈鱼遗传多样性的研究

采用 12个微卫星标记 ,对中国 3个大麻哈鱼洄游群体 (乌苏里江、黑龙江和绥芬河 )的遗传多样性进行了检测。计算出各个种群的基因杂合度、遗传多样性和各个座位的多态信息含量。结果表明 ,3个大麻哈鱼洄游种群的平均基因杂合度分别为 :0 .6 732、0 5 995、0 .6 917,种群遗传多样性分别为 0 .70 82、0 .6 5 11、0 .76 16。这些结果表明大麻哈鱼遗传多样性还比较丰富 ,其资源的恢复具有良好的前景 ,说明当前中国大麻哈鱼资源数量下降并非由遗传因素引起 ,主要原因可能是由于过度捕捞和水域环境污染等人为因素造成。人工增殖放流为恢复中国大麻哈鱼资源起到了重要作用 ,但目前大麻哈鱼的小种群极易产生遗传瓶颈的现状也应引起人们高度重视     

The distribution of <Emphasis Type="Italic">F</Emphasis><Subscript><Emphasis Type="Italic">st</Emphasis></Subscript> and other genetic statistics for a class of population structure models

We examine genetic statistics used in the study of structured populations. In a 1999 paper, Wakeley observed that the coalescent process associated with the finite island model can be decomposed into a scattering phase and a collecting phase. This decomposition becomes exact in the large population limit with the coalescent at the end of the scattering phase converging to the Ewens sampling formula and the coalescent during the collecting phase converging to the Kingman coalescent. In this paper we introduce a class of limiting models, which we refer to as G/KC models, that generalize Wakeley’s decomposition. G in G/KC represents a completely general limit for the scattering phase, while KC represents a Kingman coalescent limit for the collecting phase. We show that both the island and two-dimensional stepping stone models converge to G/KC models in the large population limit. We then derive the distribution of the statistic F _st for all G/KC models under a large sample limit for the cases of strong or weak mutation, thereby deriving the large population, large sample limiting distribution of F _st for the island and two-dimensional stepping stone models as a special case of a general formula. Our methods allow us to take the large population and large sample limits simultaneously. In the context of large population, large sample limits, we show that the variance of F _st in the presence of weak mutation collapses as O(\frac1logd){O(\frac{1}{\log d})} where d is the number of demes sampled. Further, we show that this O(\frac1logd){O(\frac{1}{\log d})} is caused by a heavy tail in the distribution of F _st . Our analysis of F _st can be extended to an entire class of genetic statistics, and we use our approach to examine homozygosity measures. Our analysis uses coalescent based methods.     

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

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

The influence of historical landscape change on genetic variation and population structure of a terrestrial salamander (Plethodon cinereus)

Forest loss and fragmentation is expected to shape the genetic structure of amphibian populations and reduce genetic variation. Another factor widely understood to have impacted these same parameters in North America is the range expansion that occurred following glacial retreat at the end of the Pleistocene. The Eastern Red-Backed Salamander (Plethodon cinereus) has been subjected to both processes. In this context, we investigated the historical events that are likely to have shaped genetic variation in this species using a panel of six microsatellite markers screened on individuals sampled across ten localities in northeastern Indiana, USA. We found low genetic diversity across forest patches and minimal differentiation. We expected population structure associated with forest fragmentation to result from genetic drift in isolation but instead found that a balance between gene flow and drift was ~50 times more likely. Ratios of allele number and range (M), and coalescent modeling of population demography suggested the occurrence of marked historic decline in effective population size across the region. Taken together, the data point to a loss of genetic variation which preceded deforestation over the past 200 years. This result indicates an important role for ancient demographic processes in shaping current genetic variation that may make it difficult to detect the effect of recent habitat fragmentation.     

Coalescent Times and Patterns of Genetic Diversity in Species with Facultative Sex: Effects of Gene Conversion,Population Structure,and Heterogeneity

Many diploid organisms undergo facultative sexual reproduction. However, little is currently known concerning the distribution of neutral genetic variation among facultative sexual organisms except in very simple cases. Understanding this distribution is important when making inferences about rates of sexual reproduction, effective population size, and demographic history. Here we extend coalescent theory in diploids with facultative sex to consider gene conversion, selfing, population subdivision, and temporal and spatial heterogeneity in rates of sex. In addition to analytical results for two-sample coalescent times, we outline a coalescent algorithm that accommodates the complexities arising from partial sex; this algorithm can be used to generate multisample coalescent distributions. A key result is that when sex is rare, gene conversion becomes a significant force in reducing diversity within individuals. This can reduce genomic signatures of infrequent sex (i.e., elevated within-individual allelic sequence divergence) or entirely reverse the predicted patterns. These models offer improved methods for assessing null patterns of molecular variation in facultative sexual organisms.     

Island models and the coalescent process

Using a coalescent approach, we derive several classical results and extend them to more general models. We find that the classic result for constant population size and constant migration rates holds in models with varying population size and varying migration rates with the obvious substitution of effective population size and mean migration fraction. In addition, the relationship of a 'local' F _ST to local gene flow is derived. This result may be useful for analysing gene flow in a regional subset of a large global population, using only data from the regional subset.     

Bayesian logistic regression using a perfect phylogeny

Haplotype data capture the genetic variation among individuals in a population and among populations. An understanding of this variation and the ancestral history of haplotypes is important in genetic association studies of complex disease. We introduce a method for detecting associations between disease and haplotypes in a candidate gene region or candidate block with little or no recombination. A perfect phylogeny demonstrates the evolutionary relationship between single-nucleotide polymorphisms (SNPs) in the haplotype blocks. Our approach extends the logic regression technique of Ruczinski and others (2003) to a Bayesian framework, and constrains the model space to that of a perfect phylogeny. Environmental factors, as well as their interactions with SNPs, may be incorporated into the regression framework. We demonstrate our method on simulated data from a coalescent model, as well as data from a candidate gene study of sarcoidosis.     

Demographic and genetic consequences of population subdivision in Formosa land-locked salmon <Emphasis Type="Italic">Oncorhynchus masou formosanus</Emphasis>, the southernmost subspecies of the salmonids

A few studies have evaluated demographic and genetic consequences of population subdivision by damming on the population as a whole. Formosa landlocked salmon Oncorhynchus masou formosanus have persisted as a relatively large population that has recently been subdivided into seven subpopulations by erosion-control dams and a natural waterfall. The present study simulated the demographic and genetic dynamics of this subdivided salmon population using VORTEX, an individual-based stochastic model. Although the population as a whole did not experience extinction over 200 simulation years, the loss of genetic variation was often detrimental (>10% loss). Isolated headwater subpopulations frequently reached extinction. Even when the subpopulations did persist through the 200 years, they experienced dramatic loss of genetic variation, suggesting short-term genetic threats. Due to the unidirectional dispersal of the fish, the damming puts headwater subpopulations at higher risk of extinction and loss of genetic variation, which affects persistence of the population as a whole, particularly from a genetic perspective.     

Genetic Variability Under the Seedbank Coalescent

We analyze patterns of genetic variability of populations in the presence of a large seedbank with the help of a new coalescent structure called the seedbank coalescent. This ancestral process appears naturally as a scaling limit of the genealogy of large populations that sustain seedbanks, if the seedbank size and individual dormancy times are of the same order as those of the active population. Mutations appear as Poisson processes on the active lineages and potentially at reduced rate also on the dormant lineages. The presence of “dormant” lineages leads to qualitatively altered times to the most recent common ancestor and nonclassical patterns of genetic diversity. To illustrate this we provide a Wright–Fisher model with a seedbank component and mutation, motivated from recent models of microbial dormancy, whose genealogy can be described by the seedbank coalescent. Based on our coalescent model, we derive recursions for the expectation and variance of the time to most recent common ancestor, number of segregating sites, pairwise differences, and singletons. Estimates (obtained by simulations) of the distributions of commonly employed distance statistics, in the presence and absence of a seedbank, are compared. The effect of a seedbank on the expected site-frequency spectrum is also investigated using simulations. Our results indicate that the presence of a large seedbank considerably alters the distribution of some distance statistics, as well as the site-frequency spectrum. Thus, one should be able to detect from genetic data the presence of a large seedbank in natural populations.     

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis

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

Understanding the adaptive consequences of hatchery-wild interactions in Alaska salmon

About 31% of salmon harvested in Alaska comes from the hatchery production of hundreds of millions of pink and chum salmon and smaller numbers of sockeye, Chinook, and coho salmon. The numbers of hatchery-reared juveniles released in some areas are greater than the numbers of juveniles from wild populations. However, virtually nothing is known about the effects of hatchery fish on wild populations in Alaska. Possible effects of these interactions can be inferred from studies of salmonids in other areas, from studies of other animals, and from theory. Numerous studies show a complex relationship between the genetic architecture of a population and its environment. Adaptive responses to nature and anthropogenic selection can be influenced by variation at a single gene, or more often, by the additive effects of several genes. Studies of salmonids in other areas show that hatchery practices can lead to the loss of genetic diversity, to shifts in adult run timing and earlier maturity, to increases in parasite load, to increases in straying, to altered levels of boldness and dominance, to shifts in juvenile out-migration timing, and to changes in growth. Controlled experiments across generations show, and theory predicts, that the loss of adaptive fitness in hatchery salmon, relative to fitness in wild salmon, can occur on a remarkably short time scale. All of these changes can influence survival and impose selective regimes that influence genetically based adaptive traits. The preservation of adaptive potential in wild populations is an important buffer against diseases and climate variability and, hence, should be considered in planning hatchery production levels and release locations. The protection of wild populations is the foundation for achieving sustained harvests of salmon in Alaska.     

Analysis of a stochastic predator–prey model with applications to intrahost HIV genetic diversity

During an infection, HIV experiences strong selection by immune system T cells. Recent experimental work has shown that MHC escape mutations form an important pathway for HIV to avoid such selection. In this paper, we study a model of MHC escape mutation. The model is a predator–prey model with two prey, composed of two HIV variants, and one predator, the immune system CD8 cells. We assume that one HIV variant is visible to CD8 cells and one is not. The model takes the form of a system of stochastic differential equations. Motivated by well-known results concerning the short life-cycle of HIV intrahost, we assume that HIV population dynamics occur on a faster time scale then CD8 population dynamics. This separation of time scales allows us to analyze our model using an asymptotic approach. Using this model we study the impact of an MHC escape mutation on the population dynamics and genetic evolution of the intrahost HIV population. From the perspective of population dynamics, we show that the competition between the visible and invisible HIV variants can reach steady states in which either a single variant exists or in which coexistence occurs depending on the parameter regime. We show that in some parameter regimes the end state of the system is stochastic. From a genetics perspective, we study the impact of the population dynamics on the lineages of an HIV sample taken after an escape mutation occurs. We show that the lineages go through severe bottlenecks and that in certain parameter regimes the lineage distribution can be characterized by a Kingman coalescent. Our results depend on methods from diffusion theory and coalescent theory.     

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

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

Population Graphs: the graph theoretic shape of genetic structure

Patterns of intraspecific genetic variation result from interactions among both historical and contemporary evolutionary processes. Traditionally, population geneticists have used methods such as F-statistics, pairwise isolation by distance models, spatial autocorrelation and coalescent models to analyse this variation and to gain insight about causal evolutionary processes. Here we introduce a novel approach (Population Graphs) that focuses on the analysis of marker-based population genetic data within a graph theoretic framework. This method can be used to estimate traditional population genetic summary statistics, but its primary focus is on characterizing the complex topology resulting from historical and contemporary genetic interactions among populations. We introduce the application of Population Graphs by examining the range-wide population genetic structure of a Sonoran Desert cactus (Lophocereus schottii). With this data set, we evaluate hypotheses regarding historical vicariance, isolation by distance, population-level assignment and the importance of specific populations to species-wide genetic connectivity. We close by discussing the applicability of Population Graphs for addressing a wide range of population genetic and phylogeographical problems.