An instantaneous coalescent method insensitive to population structure

A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDL are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

Phylogeographic analyses are a key interface between ecological and evolu- tionary ways of knowing because such analyses integrate the cumulative effects of demographic (ecological) processes over geological (evolutionary) time scales. Newly developed coalescent methods allow evolutionary ecologists to overcome some limitations associated with inferring population history from classic methods such as Wright's FST. Here we briefly contrast classic and coalescent methods for looking backward in time through a population genetic lens, focusing on the key advantages of the isolation-with- migration (IM) class of coalescent methods for distinguishing ancient connectedness from actual recurrent contemporary gene flow as causes of genetic similarity or differentiation among populations. Making this critical distinction can lead to the discovery of otherwise obscured histories underlying conventional patterns of spatial variation. We illustrate the importance of these insights using analyses of Pacific fishes, snails, and sea stars in which population sizes and divergence times are more important than rates of contemporary gene flow as determinants of population genetic differentiation. We then extend the IM method to genetic data from two model metapopulation species (California abalone, Australian damselfish). The analyses show the potential use of non-equilibrium IM methods for differentiating among metapopulation models that make different predictions about pop- ulation parameters and have different implications for the design of marine protected areas and other conservation goals. At face value, the results largely rule out classic metapop- ulation dynamics (dominated by extinction and colonization rather than connectivity via ongoing recurrent gene flow) but, at the same time, do not strongly support a modern marine metapopulation dynamic (ecologically significant connectivity between demes). However, the results also highlight the need for much more data (i.e., loci) sampled on different spatial scales in order to determine whether metapopulation dynamics might exist

The gene tree delusion

The molecular era has fundamentally reshaped our knowledge of the evolution and diversification of angiosperms. One outstanding question is the phylogenetic placement of Amborella trichopoda Baill., commonly thought to represent the first lineage of extant angiosperms. Here, we leverage publicly available data and provide a broad coalescent-based species tree estimation of 45 seed plants. By incorporating 310 nuclear genes, our coalescent analyses strongly support a clade containing Amborella plus water lilies (i.e., Nymphaeales) that is sister to all other angiosperms across different nucleotide rate partitions. Our results also show that commonly applied concatenation methods produce strongly supported, but incongruent placements of Amborella: slow-evolving nucleotide sites corroborate results from coalescent analyses, whereas fast-evolving sites place Amborella alone as the first lineage of extant angiosperms. We further explored the performance of coalescent versus concatenation methods using nucleotide sequences simulated on (i) the two alternate placements of Amborella with branch lengths and substitution model parameters estimated from each of the 310 nuclear genes and (ii) three hypothetical species trees that are topologically identical except with respect to the degree of deep coalescence and branch lengths. Our results collectively suggest that the Amborella alone placement inferred using concatenation methods is likely misled by fast-evolving sites. This appears to be exacerbated by the combination of long branches in stem group angiosperms, Amborella, and Nymphaeales with the short internal branch separating Amborella and Nymphaeales. In contrast, coalescent methods appear to be more robust to elevated substitution rates.

Coalescence vs. concatenation: Sophisticated analyses vs. first principles applied to rooting the angiosperms

The Early Diagnosis of Cerebral Palsy

Recent research indicates that anthropometrics can be used to study microevolutionary forces acting on humans. We examine the use of morphological traits in reconstructing the population history of Aleuts and Eskimos of the Bering Sea. From 1979 to 1981, W. S. Laughlin measured a sample of St. Lawrence Island Eskimos and Pribilof Island Aleuts. These samples included adult participants from St. George and St. Paul in the Pribilof Islands and from Gambell and Savoonga on St. Lawrence Island. The Relethford-Blangero method was used to examine the phylogenetic relationship between Aleuts and Eskimos. Anthropometric measurements for Native North Americans (measured by Boas and a team of trained anthropometrists in 1890-1904) and Native Mesoamericans (compiled from the literature for 1898-1952) were used for comparison. A principal components analysis of means for measurements and a neighbor-joining tree were constructed using Euclidean distances. All these tests revealed the same strong relationship among the focus populations. The R matrix from the Relethford-Blangero method clusters Aleuts and Eskimos separately and accounts for 97.3% of the variation in the data. Phenotypic variation within the population is minimal and therefore minimum F(ST) values are low. Genetic distances were compared to a Euclidean distance matrix of anthropometric measurements using a Mantel test and gave a high but not significant correlation. Our results provide evidence of a close phylogenetic relationship between Aleut and Eskimo populations in the Bering Sea. However, it is apparent that history has affected the relationship among the populations. Despite previous findings of higher European admixture in Gambell (based on blood group markers) than in Savoonga, Savoonga has greater within-group variation in anthropometric measurements. Anthropometrics reveal a close relationship between Gambell and St. Paul as a result of European admixture. The St. George population was the most divergent of the populations, indicating that it diverged from the Eskimos and St. Paul because of the compounding effects of genetic drift and limited European gene flow. These findings are in agreement with previous anthropometric and genetic studies of the Aleut and Eskimo populations and support the utility of anthropometrics in inferring population history and structure.

Recent research indicates that anthropometrics can be used to study microevolutionary forces acting on humans. We examine the use of morphological traits in reconstructing the population history of Aleuts and Eskimos of the Bering Sea. From 1979 to 1981, W. S. Laughlin measured a sample of St. Lawrence Island Eskimos and Pribilof Island Aleuts. These samples included adult participants from St. George and St. Paul in the Pribilof Islands and from Gambell and Savoonga on St. Lawrence Island. The Relethford- Blangero method was used to examine the phylogenetic relationship between Aleuts and Eskimos. Anthropometric measurements for Native North Americans (measured by Boas and a team of trained anthropometrists in 1890–1904) and Native Mesoamericans (compiled from the literature for 1898–1952) were used for comparison. A principal components analysis of means for measurements and a neighbor-joining tree were constructed using Euclidean distances. All these tests revealed the same strong relationship among the focus populations. The R matrix from the Relethford-Blangero method clusters Aleuts and Eskimos separately and accounts for 97.3% of the variation in the data. Phenotypic variation within the population is minimal and therefore minimum FST values are low. Genetic distances were compared to a Euclidean distance matrix of anthropometric measurements using a Mantel test and gave a high but not significant correlation. Our results provide evidence of a close phylogenetic relationship between Aleut and Eskimo populations in the Bering Sea. However, it is apparent that history has affected the relationship among the populations. Despite previous findings of higher European admixture in Gambell (based on blood group markers) than in Savoonga, Savoonga has greater within-group variation in anthropometric measurements. Anthropometrics reveal a close relationship between Gambell and St. Paul as a result of European admixture. The St. George population was the most divergent of the populations, indicating that it diverged from the Eskimos and St. Paul because of the compounding effects of genetic drift and limited European gene flow. These findings are in agreement with previous anthropometric and genetic studies of the Aleut and Eskimo populations and support the utility of anthropometrics in inferring population history and structure.

It is well known that species with elevated substitution rates can give rise to disproportionately long branches in the species tree. This combination of long and short branches can contribute to long-branch artifacts (LBA). Despite efforts to remedy LBA via increased taxon sampling and methodological improvements in gene tree estimation, it remains unclear how long and short branches affect species tree estimation in the presence of incomplete lineage sorting (ILS). Here, we examine the combined influence of long external and short internal branches on concatenation and coalescent methods using both simulated and empirical data. Our results demonstrate that the presence of long and short branches alone does not obviously confound the consistency of concatenation and coalescent methods. However, when long external and short internal branches occur simultaneously with high ILS, concatenation methods can be misled, especially when two of these long branches are sister lineages. In contrast, coalescent methods are more robust under these circumstances. This is particularly relevant because this topological pattern also characterizes numerous ancient rapid radiations across the tree of life. Because short internal branches can increase the potential for ILS and gene tree discordance, our results collectively suggest that coalescent methods are more likely to infer the correct species tree in cases of ancient rapid radiations where long external and short internal branches are in close phylogenetic proximity.

Proportioning Whole-Genome Single-Nucleotide–Polymorphism Diversity for the Identification of Geographic Population Structure and Genetic Ancestry

Recent studies have demonstrated that conflict is common among gene trees in phylogenomic studies, and that less than one percent of genes may ultimately drive species tree inference in supermatrix analyses. Herein, we examined two data sets where supermatrix and coalescent-based species trees conflict. We identified two highly influential "outlier" genes in each data set. When removed from each data set, the inferred supermatrix trees matched the topologies obtained from coalescent analyses. We also demonstrate that, while the outlier genes in the vertebrate data set have been shown in a previous study to be the result of errors in orthology detection, the outlier genes from a plant data set did not exhibit any obvious systematic error, and therefore, may be the result of some biological process yet to be determined. While topological comparisons among a small set of alternate topologies can be helpful in discovering outlier genes, they can be limited in several ways, such as assuming all genes share the same topology. Coalescent species tree methods relax this assumption but do not explicitly facilitate the examination of specific edges. Coalescent methods often also assume that conflict is the result of incomplete lineage sorting. Herein, we explored a framework that allows for quickly examining alternative edges and support for large phylogenomic data sets that does not assume a single topology for all genes. For both data sets, these analyses provided detailed results confirming the support for coalescent-based topologies. This framework suggests that we can improve our understanding of the underlying signal in phylogenomic data sets by asking more targeted edge-based questions.

Avoidable false PSMC population size peaks occur across numerous studies.

Approximate Bayesian computation (ABC) is a powerful and widely used approach in inference of population history. However, the computational effort required to discriminate among alternative historical scenarios often limits the set that is compared to those considered more likely a priori. While often justifiable, this approach will fail to consider unexpected but well-supported population histories. We used a hierarchical tournament approach, in which subsets of scenarios are compared in a first round of ABC analyses and the winners are compared in a second analysis, to reconstruct the population history of an oak gall wasp, Synergus umbraculus (Hymenoptera, Cynipidae) across the Western Palaearctic. We used 4,233bp of sequence data across seven loci to explore the relationships between four putative Pleistocene refuge populations in Iberia, Italy, the Balkans and Western Asia. We compared support for 148 alternative scenarios in eight pools, each pool comprising all possible rearrangements of four populations over a given topology of relationships, with or without founding of one population by admixture and with or without an unsampled "ghost" population. We found very little support for the directional "out of the east" scenario previously inferred for other gall wasp community members. Instead, the best-supported models identified Iberia as the first-regional population to diverge from the others in the late Pleistocene, followed by divergence between the Balkans and Western Asia, and founding of the Italian population through late Pleistocene admixture from Iberia and the Balkans. We compare these results with what is known for other members of the oak gall community, and consider the strengths and weaknesses of using a tournament approach to explore phylogeographic model space.

We introduce an approach to revealing the likelihood of different population histories that utilizes an explicit model of sequence evolution for the DNA segment under study. Based on a phylogenetic tree reconstruction method we show that a Tamura-Nei model with heterogeneous mutation rates is a fair description of the evolutionary process of the hypervariable region I of the mitochondrial DNA from humans. Assuming this complex model still allows the estimation of population history parameters, we suggest a likelihood approach to conducting statistical inference within a class of expansion models. More precisely, the likelihood of the data is based on the mean pairwise differences between DNA sequences and the number of variable sites in a sample. The use of likelihood ratios enables comparison of different hypotheses about population history, such as constant population size during the past or an increase or decrease of population size starting at some point back in time. This method was applied to show that the population of the Basques has expanded, whereas that of the Biaka pygmies is most likely decreasing. The Nuu-Chah-Nulth data are consistent with a model of constant population.

With recent advances in sequencing technology, genomic data are changing how important conservation management decisions are made. Applications such as Close-Kin Mark-Recapture demand large amounts of data to estimate population size and structure, and their full potential can only be realised through ongoing improvements in genotyping strategies. Here we introduce DArTcap, a cost-efficient method that combines DArTseq and sequence capture, and illustrate its use in a high resolution population analysis of Glyphis garricki, a rare, poorly known and threatened euryhaline shark. Clustering analyses and spatial distribution of kin pairs from four different regions across northern Australia and one in Papua New Guinea, representing its entire known range, revealed that each region hosts at least one distinct population. Further structuring is likely within Van Diemen Gulf, the region that included the most rivers sampled, suggesting additional population structuring would be found if other rivers were sampled. Coalescent analyses and spatially explicit modelling suggest that G.garricki experienced a recent range expansion during the opening of the Gulf of Carpentaria following the conclusion of the Last Glacial Maximum. The low migration rates between neighbouring populations of a species that is found only in restricted coastal and riverine habitats show the importance of managing each population separately, including careful monitoring of local and remote anthropogenic activities that may affect their environments. Overall we demonstrated how a carefully chosen SNP panel combined with DArTcap can provide highly accurate kinship inference and also support population structure and historical demography analyses, therefore maximising cost-effectiveness.