Coalescent Theory Research Articles

Using a coalescent approach to assess gene flow and effective population size of Acrocomia aculeata (Jacq.) Lodd. Ex Mart. in the Brazilian Atlantic Forest

Acrocomia aculeata is a tropical palm tree native to Central and South America that has significant economic, social, and environmental potential. However, land encroachment due to the expansion of agribusiness, and other factors such as urban sprawl, have resulted in the fragmentation and destruction of its habitat, leading to the loss of genes and genotypes in A. aculeata populations. In this context, the objective of this study was to characterize the genetic variability of A. aculeata populations by estimating gene flow and effective population size using an approach based on coalescent theory. Four populations located in the municipalities of Teodoro Sampaio (TSI and TSII), Rosana (RA), and Amparo (AP) in Sao Paulo State, Brazil, were genotyped with nine microsatellite markers. Gene flow and effective population size were estimated using a coalescent-based Bayesian inference implemented in the MIGRATE-N software. The effective population size (Ne) was obtained considering an assumed mutation rate of 5 × 10−5. Gene flow (Nm) for pairwise populations ranged from 0.28 to 1.17, with higher levels of migration between the three geographically proximal locations (TSI, TSII, and RA). The estimates of effective population size (Ne) were 444, 835, 838, and 874 for AP, TSII, RA, and TSI, respectively, showing that the effects caused by genetic drift may be more pronounced when Ne is smaller. The coalescent-based results add to our understanding of A. aculeata population genetics and suggest that some traditional assessment methods may be ineffective in characterizing historical evolutionary processes.

Developments in coalescent theory from single loci to chromosomes

Developments in coalescent theory from single loci to chromosomes

Extensive cryptic diversity of giant clams (Cardiidae: Tridacninae) revealed by DNA-sequence-based species delimitation approaches with new data from Hainan Island, South China Sea

AbstractAccurate species delimitation is important, especially for endangered species. As one of the most conspicuous bivalve taxa, giant clams are threatened throughout their geographic range. Many phylogeographic studies have revealed strong population structure among giant clams in the Indo-Pacific, suggesting cryptic diversity within these species. However, less attention has been paid to their identification and delimitation. In this study, we assembled a comprehensive dataset of mitochondrial cytochrome c oxidase subunit I (COI) sequences for Tridacna species, focusing on new sequences from Hainan Island in the South China Sea and previously published ones from Japan, Taiwan, Singapore, the Philippines, Indonesia, Australia, the Solomon Islands and the Red Sea. Three nominal species, Tridacna crocea, T. squamosa and T. noae, were recognized at Hainan Island on the basis of distance-based DNA barcoding, with mean interspecific K2P distances of 10.6–24.7% for seven Tridacna species (T. crocea, T. squamosa, T. noae, T. maxima, T. mbalavuana, T. derasa and T. gigas). The most abundant species, T. noae, represents the first record of this species from Hainan Island. Using a combination of phylogenetic and DNA-based species delimitation analyses (automatic barcode gap discovery, generalized mixed Yule coalescent and Bayesian Poisson tree processes), we found strong support for a total of 13 operational taxonomic units (OTUs) for the seven nominal Tridacna species. These results, coupled with the fact that each OTU occupies different regions in the Indo-Pacific, strongly suggest multiple cryptic species of giant clams. Our findings point to the need for taxonomic revisionary work on giant clams throughout the Indo-Pacific; such work will have important conservation implications.

Colonization history of the Canary Islands endemic Lavatera acerifolia, (Malvaceae) unveiled with genotyping‐by‐sequencing data and niche modelling

AbstractAimDifferentiation of island lineages from mainland relatives and radiation after initial colonization are two important processes generating island diversity. Both of these processes are influenced by colonization dynamics and contemporary connections between island species and their source populations. The classic island progression rule model, that is dispersal from mainland to older islands and subsequently to younger islands, can be considered a null hypothesis, particularly for islands that are geographically aligned perpendicular to the mainland coast with ages inversely proportional to distance from the mainland. Alterations to this pattern have been reported, particularly in archipelagos that are geographically closely adjacent to mainland source populations. Here we aim to integrate genomic and environmental niche data to infer the colonization history of a Canary endemic species and to understand its current diversity patterns.LocationCanary Islands.TaxonLavatera acerifolia (Malvaceae).MethodsWe used high‐throughput genotyping‐by‐sequencing (GBS) combined with species distribution modelling (SDM) projected onto past conditions. Genetic structure (clustering methods), relatedness (coalescent and ML trees), nucleotide diversity and differentiation (population genetics) were assessed based on SNPs obtained from three alternative bioinformatics pipelines. The influence of environmental variables over time was assessed with a generalized linear model in which the response variable was amount of heterozygous sites per individual.ResultsFour genetic groups were identified arranged along a longitudinal gradient, and the earliest diverging coincides with the older, and easternmost, islands (Lanzarote and Fuerteventura). Genetic diversity is reduced in the westernmost islands, which are more distant from the mainland, host few populations and yet apparently offer more suitable habitats.Main conclusionsThe inferred colonization scenario generally fits the progression rule model, but suggests a more complex pattern for the central islands. For the westernmost islands, the contrast between high availability of suitable habitats and reduced genetic diversity and number of populations suggests a colonization front moving at a slow pace, rather than local extinctions, as an explanation for the scarcity of populations in those islands. Historical projections of SDM lend support to this interpretation.

Ancient DNA helps trace the peopling of the world

Many of us are fascinated by narratives regarding the origin and evolution of our species. Who are we? How did we people the world? Answers to these simple questions remain elusive even though researchers have been quite successful in describing past human morphology and culture using evidence from anthropology, archaeology, history, sociology and linguistics. However, when they address human migrations, archaeologists are somewhat restricted to surviving artifactual evidence and limited to descriptions of culture expansions, which may have occurred by the movement of either ideas or people. The advent of genomics, by which one can sequence whole or part of an individual's DNA, provided a powerful means to dig into past human demographic history. Notably, the coalescent theory posits that individuals in a population share genetic variants that originated from a common ancestor. This powerful theory is the basis for a number of bioanalytical innovations that utilize genetic data to reconstruct human movements around the world.

Ancestral Population Genomics with Jocx, a Coalescent Hidden Markov Model.

Coalescence theory lets us probe the past demographics of present-day genetic samples and much information about the past can be gleaned from variation in rates of coalescence event as we trace genetic lineages back in time. Fewer and fewer lineages will remain, however, so there is a limit to how far back we can explore. Without recombination, we would not be able to explore ancient speciation events because of this-any meaningful species concept would require that individuals of one species are closer related than they are to individuals of another species, once speciation is complete. Recombination, however, opens a window to the deeper past. By scanning along a genomic alignment, we get a sequential variant of the coalescence process as it looked at the time of the speciation. This pattern of coalescence times is fixed at speciation time and does not erode with time; although accumulated mutations and genomic rearrangements will eventually hide the signal, it enables us to glance at events in the past that would not be observable without recombination. So-called coalescence hidden Markov models allow us to exploit this, and in this chapter, we present the tool Jocx that uses a framework of these models to infer demographic parameters in ancient speciation events.

Sequential Monte Carlo with transformations

This paper examines methodology for performing Bayesian inference sequentially on a sequence of posteriors on spaces of different dimensions. For this, we use sequential Monte Carlo samplers, introducing the innovation of using deterministic transformations to move particles effectively between target distributions with different dimensions. This approach, combined with adaptive methods, yields an extremely flexible and general algorithm for Bayesian model comparison that is suitable for use in applications where the acceptance rate in reversible jump Markov chain Monte Carlo is low. We use this approach on model comparison for mixture models, and for inferring coalescent trees sequentially, as data arrives.

The effect of alignment uncertainty, substitution models and priors in building and dating the mammal tree of life

BackgroundThe flood of genomic data to help build and date the tree of life requires automation at several critical junctures, most importantly during sequence assembly and alignment. It is widely appreciated that automated alignment protocols can yield inaccuracies, but the relative impact of various sources error on phylogenomic analysis is not yet known. This study employs an updated mammal data set of 5162 coding loci sampled from 90 species to evaluate the effects of alignment uncertainty, substitution models, and fossil priors on gene tree, species tree, and divergence time estimation. Additionally, a novel coalescent likelihood ratio test is introduced for comparing competing species trees against a given set of gene trees.ResultsThe aligned DNA sequences of 5162 loci from 90 species were trimmed and filtered using trimAL and two filtering protocols. The final dataset contains 4 sets of alignments - before trimming, after trimming, filtered by a recently proposed pipeline, and further filtered by comparing ML gene trees for each locus with the concatenation tree. Our analyses suggest that the average discordance among the coalescent trees is significantly smaller than that among the concatenation trees estimated from the 4 sets of alignments or with different substitution models. There is no significant difference among the divergence times estimated with different substitution models. However, the divergence dates estimated from the alignments after trimming are more recent than those estimated from the alignments before trimming.ConclusionsOur results highlight that alignment uncertainty of the updated mammal data set and the choice of substitution models have little impact on tree topologies yielded by coalescent methods for species tree estimation, whereas they are more influential on the trees made by concatenation. Given the choice of calibration scheme and clock models, divergence time estimates are robust to the choice of substitution models, but removing alignments deemed problematic by trimming algorithms can lead to more recent dates. Although the fossil prior is important in divergence time estimation, Bayesian estimates of divergence times in this data set are driven primarily by the sequence data.

Population Genetic Inference With MIGRATE.

Many evolutionary biologists collect genetic data from natural populations and then need to investigate the relationship among these populations to compare different biogeographic hypotheses. MIGRATE, a useful tool for exploring relationships between populations and comparing hypotheses, has existed since 1998. Throughout the years, it has steadily improved in both the quality of algorithms used and in the efficiency of carrying out those calculations, thus allowing for a larger number of loci to be evaluated. This efficiency has been enhanced, as MIGRATE has been developed to perform many of its calculations concurrently when running on a computer cluster. The program is based on the coalescence theory and uses Bayesian inference to estimate posterior probability densities of all the parameters of a user‐specified population model. Complex models, which include migration and colonization parameters, can be specified. These models can be evaluated using marginal likelihoods, thus allowing a user to compare the merits of different hypotheses. The three presented protocols will help novice users to develop sophisticated analysis techniques useful for their research projects. © 2019 The Authors. Basic Protocol 1: First steps with MIGRATE Basic Protocol 2: Population model specification Basic Protocol 3: Prior distribution specification Basic Protocol 4: Model selection Support Protocol 1: Installing the program MIGRATE Support Protocol 2: Installation of parallel MIGRATE

Chance, Variation and Shared Ancestry: Population Genetics After the Synthesis.

Chance has been a focus of attention ever since the beginning of population genetics, but neutrality has not, as natural selection once appeared to be the only worthwhile issue. Neutral change became a major source of interest during the neutralist-selectionist debate, 1970-1980. It retained interest beyond this period for two reasons that contributed to its becoming foundational for evolutionary reasoning. On the one hand, neutral evolution was the first mathematical prediction to emerge from Mendelian inheritance: until then evolution by natural selection was considered the alternative to the fixity of species; now it appears to be the alternative to continuous change. Second, neutral change generated a set of clear predictions on standing variation. These could be used as a reference for detecting more elusive alternative mechanisms of evolution including natural selection. In the wake of the transition from Mendelism to genomics, the combination of coalescent theory, DNA sequence variation, and numerical analysis made it possible to integrate contingent aspects of the history of species into a new null model, thus opening a new dimension in the concept of population that the Modern Synthesis formerly considered as a mere gene pool.

Altered lentiviral infection dynamics follow genetic rescue of the Florida panther.

Wildlife translocations are a commonly used strategy in endangered species recovery programmes. Although translocations require detailed assessment of risk, their impact on parasite distribution has not been thoroughly assessed. This is despite the observation that actions that alter host-parasite distributions can drive evolution or introduce new parasites to previously sequestered populations. Here, we use a contemporary approach to amplify viral sequences from archived biological samples to characterize a previously undocumented impact of the successful genetic rescue of the Florida panther (Puma concolor coryi). Our efforts reveal transmission of feline immunodeficiency virus (FIV) during translocation of pumas from Texas to Florida, resulting in extirpation of a historic Florida panther FIV subtype and expansion of a genetically stable subtype that is highly conserved in Texas and Florida. We used coalescent theory to estimate viral demography across time and show an exponential increase in the effective population size of FIV coincident with expansion of the panther population. Additionally, we show that FIV isolates from Texas are basal to isolates from Florida. Interestingly, FIV genomes recovered from Florida and Texas demonstrate exceptionally low interhost divergence. Low host genomic diversity and lack of additional introgressions may underlie the surprising lack of FIV evolution over 2 decades. We conclude that modern FIV in the Florida panther disseminated following genetic rescue and rapid population expansion, and that infectious disease risks should be carefully considered during conservation efforts involving translocations. Further, viral evolutionary dynamics may be significantly altered by ecological niche, host diversity and connectivity between host populations.

A Darwinian Uncertainty Principle.

Reconstructing ancestral characters and traits along a phylogenetic tree is central to evolutionary biology. It is the key to understanding morphology changes among species, inferring ancestral biochemical properties of life, or recovering migration routes in phylogeography. The goal is 2-fold: to reconstruct the character state at the tree root (e.g., the region of origin of some species) and to understand the process of state changes along the tree (e.g., species flow between countries). We deal here with discrete characters, which are “unique,” as opposed to sequence characters (nucleotides or amino-acids), where we assume the same model for all the characters (or for large classes of characters with site-dependent models) and thus benefit from multiple information sources. In this framework, we use mathematics and simulations to demonstrate that although each goal can be achieved with high accuracy individually, it is generally impossible to accurately estimate both the root state and the rates of state changes along the tree branches, from the observed data at the tips of the tree. This is because the global rates of state changes along the branches that are optimal for the two estimation tasks have opposite trends, leading to a fundamental trade-off in accuracy. This inherent “Darwinian uncertainty principle” concerning the simultaneous estimation of “patterns” and “processes” governs ancestral reconstructions in biology. For certain tree shapes (typically speciation trees) the uncertainty of simultaneous estimation is reduced when more tips are present; however, for other tree shapes it does not (e.g., coalescent trees used in population genetics).

The transition distribution of a sample from a Wright-Fisher diffusion with general small mutation rates.

The transition distribution of a sample taken from a Wright-Fisher diffusion with general small mutation rates is found using a coalescent approach. The approximation is equivalent to having at most one mutation in the coalescent tree of the sample up to the most recent common ancestor with additional mutations occurring on the lineage from the most recent common ancestor to the time origin if complete coalescence occurs before the origin. The sampling distribution leads to an approximation for the transition density in the diffusion with small mutation rates. This new solution has interest because the transition density in a Wright-Fisher diffusion with general mutation rates is not known.

Genetic Diversity, Population Structure, and Migration Scenarios of the Marsupial "Monito del Monte" in South-Central Chile.

In this study, we quantified the 3 pivotal genetic processes (i.e., genetic diversity, spatial genetic structuring, and migration) necessary for a better biological understanding and management of the singular "living-fossil" and near-threatened mouse opossum marsupial Dromiciops gliroides, the "Monito del Monte," in south-central Chile. We used 11 microsatellite loci to genotype 47 individuals distributed on the mainland and northern Chiloé Island. Allelic richness, observed and expected heterozygosity, inbreeding coefficient, and levels of genetic differentiation were estimated. The genetic structure was assessed based on Bayesian clustering methods. In addition, potential migration scenarios were evaluated based on a coalescent theory framework and Bayesian approach to parameter estimations. Microsatellites revealed moderate to high levels of genetic diversity across sampled localities. Moreover, such molecular markers suggested that at least 2 consistent genetic clusters could be identified along the D. gliroides distribution ("Northern" and "Southern" cluster). However, general levels of genetic differentiation observed among localities and between the 2 genetic clusters were relatively low. Migration analyses showed that the most likely routes of migration of D. gliroides occurred 1) from the Southern cluster to the Northern cluster and 2) from the Mainland to Chiloé Island. Our results could represent critical information for future conservation programs and for a recent proposal about the taxonomic status of this unique mouse opossum marsupial.

A28 Spatial spread of highly pathogenic avian influenza A (H5N8) virus in Italy, 2017–8

In winter 2016–7 the highly pathogenic avian influenza (HPAI) virus, H5N8 subtype, clade 2.3.4.4 group B, circulated extensively both in wild and domestic birds in Europe. Northern Italy was hit by three epidemic waves: the first in January–May 2017, the second in July–December 2017, and the latest in March 2018. To genetically characterize the viruses circulating in Italy we used the Illumina MiSeq platform to sequence the complete genome of representative viruses from each infected farm, for a total of 86 cases in poultry and 17 in wild birds. Maximum likelihood phylogenetic analyses performed using PhyML version 3.1 identified multiple viral introductions of distinct genotypes of HPAI H5N8 viruses in Italy at the beginning of the epidemic (January–February 2017). During the second epidemic wave a single genetic group originating from the virus A/wild duck/Poland/82A/2016 seemed to have been selected, further evolving into two different clusters, namely Italy-A and Italy-B. We identified four clusters of secondary outbreaks, the largest being the epidemic in the province of Brescia between October 2017 and March 2018, which had affected 26 farms. Evolutionary and phylogeographic analyses performed with the BEAST v1.8.4 package (applying a Bayesian Markov chain Monte Carlo approach, using a constant size coalescent tree prior and a SRD06 model of nucleotide substitution) indicated that different viral introductions had probably occurred through migratory birds from West Russia, Siberia, Central and East Europe. The discrete and continuous phylogeographic analyses showed that group Italy-A had probably emerged between February and April 2017 in the province of Mantua and had then spread eastwards, circulating in the Veneto region and eastern Lombardy; on the contrary, Italy-B had arisen between March and July 2017 in the central part of Lombardy and had spread westwards, circulating in the western part of Lombardy, Emilia Romagna, and Piedmont regions. This study was instrumental to reconstruct the virus dissemination routes and indicated that wild and domestic birds from Lombardy most likely represented the key source for the re-emergence and spread of the HPAI virus during the second and the third epidemic waves. This key spatial information will help to define appropriate disease control strategies.

The phylogenetic approach for viral infectious disease evolution and epidemiology: An updating review.

In the last decade, the phylogenetic approach is recurrent in molecular evolutionary analysis. On 12 May, 2019, about 2 296 213 papers are found, but typing "phylogeny" or "epidemiology AND phylogeny" only 199 804 and 20 133 are retrieved, respectively. Molecular epidemiology in infectious diseases is widely used to define the source of infection as so as the ancestral relationships of individuals sampled from a population. Coalescent theory and phylogeographic analysis have had scientific application in several, recent pandemic events, and nosocomial outbreaks. Hepatitis viruses and immunodeficiency virus (human immunodeficiency virus) have been largely studied. Phylogenetic analysis has been recently applied on Polyomaviruses so as in the more recent outbreaks due to different arboviruses type as Zika and chikungunya viruses discovering the source of infection and the geographic spread. Data on sequences isolated by the microorganism are essential to apply the phylogenetic tools and research in the field of infectious disease phylodinamics is growing up. There is the need to apply molecular phylogenetic and evolutionary methods in areas out of infectious diseases, as translational genomics and personalized medicine. Lastly, the application of these tools in vaccine strategy so as in antibiotic and antiviral researchers are encouraged.

Morphology and molecules reveal two new species of Porites (Scleractinia, Poritidae) from the Red Sea and the Gulf of Aden

Two new reef coral species, Porites farasani sp. nov. and Porites hadramauti sp. nov. (Scleractinia, Poritidae), are described from the Red Sea and the Gulf of Aden. Porites farasani sp. nov. only occurs in the Farasan Islands in the southern Red Sea, while P. hadramauti sp. nov. has been collected in the Yemen Hadramaut region in the Gulf of Aden. Both species presented striking in situ differences with respect to other Porites species, and were characterized by small encrusting colonies and unusual polyp colouration. In order to test the genetic distinctiveness of P. farasani sp. nov. and P. hadramauti sp. nov. between each other and with respect to other representatives in the genus Porites, we investigated their evolutionary relationships with eight other morphological species of Porites occurring in the Red Sea and in the Gulf of Aden. Two DNA loci, the mitochondrial putative control region and the nuclear ribosomal ITS region, were sequenced, and three species delimitation approaches based on barcoding threshold (Automated Barcoding Gap Discovery) and coalescence theory (Poisson-Tree process, Generalized Mixed Yule Coalescent) were applied. Phylogenetic and species delimitation analyses were overall concordant, resolving P. farasani sp. nov. and P. hadramauti sp. nov. as two divergent but closely related lineages. Of the other morphologically defined Porites species, three were genetically differentiated (P. rus, P. columnaris and P. fontanesii), but five were genetically indistinguishable. The discovery of two regional endemics confirms the importance of the Red Sea and the Gulf of Aden as regions of high biodiversity and suggests the need for an integration of genome-wide molecular data with the re-evaluation of skeletal structures in the systematics of Porites.

The multifurcating skyline plot.

A variety of methods based on coalescent theory have been developed to infer demographic history from gene sequences sampled from natural populations. The ‘skyline plot’ and related approaches are commonly employed as flexible prior distributions for phylogenetic trees in the Bayesian analysis of pathogen gene sequences. In this work we extend the classic and generalized skyline plot methods to phylogenies that contain one or more multifurcations (i.e. hard polytomies). We use the theory of Λ-coalescents (specifically, -coalescents) to develop the ‘multifurcating skyline plot’, which estimates a piecewise constant function of effective population size through time, conditional on a time-scaled multifurcating phylogeny. We implement a smoothing procedure and extend the method to serially sampled (heterochronous) data, but we do not address here the problem of estimating trees with multifurcations from gene sequence alignments. We validate our estimator on simulated data using maximum likelihood and find that parameters of the -coalescent process can be estimated accurately. Furthermore, we apply the multifurcating skyline plot to simulated trees generated by tracking transmissions in an individual-based model of epidemic superspreading. We find that high levels of superspreading are consistent with the high-variance assumptions underlying Λ-coalescents and that the estimated parameters of the Λ-coalescent model contain information about the degree of superspreading.

Influence of the tree prior and sampling scale on Bayesian phylogenetic estimates of the origin times of language families

AbstractBayesian phylogenetic methods derived from evolutionary biology can be used to reconstruct the history of human languages using databases of cognate words. These analyses have produced exciting results regarding the origins and dispersal of linguistic and cultural groups through prehistory. Bayesian lexical dating requires the specification of priors on all model parameters. This includes the use of a prior on divergence times, often combined with a prior on tree topology and referred to as a tree prior. Violation of the underlying assumptions of the tree prior can lead to an erroneous estimate of the timescale of language evolution. To investigate these impacts, we tested the sensitivity of Bayesian dating to the tree prior in analyses of four lexical data sets. Our results show that estimates of the origin times of language families are robust to the choice of tree prior for lexical data, though less so than when Bayesian phylogenetic methods are used to analyse genetic data sets. We also used the relative fit of speciation and coalescent tree priors to determine the ability of speciation models to describe language diversification at four different taxonomic levels. We found that speciation priors were preferred over a constant-size coalescent prior regardless of taxonomic scale. However, data sets with narrower taxonomic and geographic sampling exhibited a poorer fit to ideal birth–death model expectations. Our results encourage further investigation into the nature of language diversification at different sampling scales.

Coalescent Theory of Migration Network Motifs

Natural populations display a variety of spatial arrangements, each potentially with a distinctive impact on genetic diversity and genetic differentiation among subpopulations. Although the spatial arrangement of populations can lead to intricate migration networks, theoretical developments have focused mainly on a small subset of such networks, emphasizing the island-migration and stepping-stone models. In this study, we investigate all small network motifs: the set of all possible migration networks among populations subdivided into at most four subpopulations. For each motif, we use coalescent theory to derive expectations for three quantities that describe genetic variation: nucleotide diversity, FST, and half-time to equilibrium diversity. We describe the impact of network properties on these quantities, finding that motifs with a high mean node degree have the largest nucleotide diversity and the longest time to equilibrium, whereas motifs with low density have the largest FST. In addition, we show that the motifs whose pattern of variation is most strongly influenced by loss of a connection or a subpopulation are those that can be split easily into disconnected components. We illustrate our results using two example data sets—sky island birds of genus Sholicola and Indian tigers—identifying disturbance scenarios that produce the greatest reduction in genetic diversity; for tigers, we also compare the benefits of two assisted gene flow scenarios. Our results have consequences for understanding the effect of geography on genetic diversity, and they can assist in designing strategies to alter population migration networks toward maximizing genetic variation in the context of conservation of endangered species.