An adjacent-swap Markov chain on coalescent trees

The standard coalescent is widely used in evolutionary biology and population genetics to model the ancestral history of a sample of molecular sequences as a rooted and ranked binary tree. In this paper we present a representation of the space of ranked trees as a space of constrained ordered matched pairs. We use this representation to define ergodic Markov chains on labeled and unlabeled ranked tree shapes analogously to transposition chains on the space of permutations. We show that an adjacent-swap chain on labeled and unlabeled ranked tree shapes has a mixing time at least of order $n^3$ , and at most of order $n^{4}$ . Bayesian inference methods rely on Markov chain Monte Carlo methods on the space of trees. Thus it is important to define good Markov chains which are easy to simulate and for which rates of convergence can be studied.

Phylogeny-based conservation priorities for Australian freshwater fishes

Conservation scientists are increasingly interested in the question of how extinction prunes the tree of life. This question is particularly important for Australian freshwater fishes because there is a broad mix of ∼300 old and young species, many of which are severely threatened. We used a complete species-level phylogeny of Australian freshwater fishes to examine phylogenetic nonrandomness of extinction risk. We computed the potential loss of phylogenetic diversity by simulating extinction across the tree under a pattern weighted based on International Union for Conservation of Nature extinction risk category and compared this loss to projected diversity loss under a random null model of extinction. Finally, we calculated EDGE (evolutionary distinctiveness, global endangerment) scores for 251 freshwater and 60 brackish species and compiled a list of high-priority species for conservation actions based on their extinction risk and evolutionary uniqueness. Extinction risk was not random and was clustered in both diversity cradles (recently diversifying, species-rich clades, such as Galaxiidae and Percichthyidae) and museums (older, species-poor groups, such as freshwater chondrichthyans). Clustered extinction made little difference to the average expected loss of phylogenetic diversity. However, the upper bound of loss was higher under a selective model of extinction, particularly when the counts of species lost were low. Thus, the loss of highly threatened species would diminish the tree of life more than a null model of randomly distributed extinction.  High priority species included both widely recognized and charismatic ones, such as the Queensland lungfish (Neoceratodus forsteri), river sharks, and freshwater sawfishes, and lesser-known species that receive less public attention, including the salamanderfish (Lepidogalaxias salamandroides), cave gudgeons, and many galaxiids, rainbowfishes, and pygmy perches.

Relative Importance of Ecological, Evolutionary and Anthropogenic Pressures on Extinction Risk in Chinese Angiosperm Genera

China has many threatened plant species, which are exposed to environmental degradation and other anthropogenic pressures. We assessed support for potential extinction pathways in Chinese angiosperm genera and quantified possible threats to phylogenetic diversity. We compiled a database and phylogeny for 27,409 Chinese angiosperm species in 2,453 genera. For each genus, we used the International Union for Conservation of Nature (IUCN) Red List classifications to quantify extinction risk and calculated predictors corresponding to their ecological, evolutionary characteristics and exposure to human pressures. We first tested for phylogenetic clustering in extinction risk among genera and then tested support for direct and indirect causal pathways involving our predictors using piecewise structural equation models. Finally, we quantified the potential loss of phylogenetic diversity under different extinction scenarios. We found that extinction risk is non-randomly distributed among Chinese angiosperm genera, with the proportion of threatened species higher in range-limited and species-rich taxa. Habitat loss had a significant positive effect on threatened species richness. Phylogenetic diversity loss under scenarios: the decreasing habitat loss and relative extinction rate were high. Thus, genera would suffer from high extinction risk, if species in these genera occupy similar niches and overlapping ranges. While diversification or speciation via niche divergence might increase range-limited species vulnerable to stochastic extinction, this could reduce extinction risk of the whole clade by expanding its range and climatic niche tolerance. Endemic genera with higher extinction rates, less climatic niche divergence, and lower range segregation are especially vulnerable to anthropogenic disturbances.

SEQUENTIAL IMPORTANCE SAMPLING FOR MULTIRESOLUTION KINGMAN-TAJIMA COALESCENT COUNTING

Statistical inference of evolutionary parameters from molecular sequence data relies on coalescent models to account for the shared genealogical ancestry of the samples. However, inferential algorithms do not scale to available data sets. A strategy to improve computational efficiency is to rely on simpler coalescent and mutation models, resulting in smaller hidden state spaces. An estimate of the cardinality of the state-space of genealogical trees at different resolutions is essential to decide the best modeling strategy for a given dataset. To our knowledge, there is neither an exact nor approximate method to determine these cardinalities. We propose a sequential importance sampling algorithm to estimate the cardinality of the sample space of genealogical trees under different coalescent resolutions. Our sampling scheme proceeds sequentially across the set of combinatorial constraints imposed by the data, which in this work are completely linked sequences of DNA at a non recombining segment. We analyze the cardinality of different genealogical tree spaces on simulations to study the settings that favor coarser resolutions. We apply our method to estimate the cardinality of genealogical tree spaces from mtDNA data from the 1000 genomes and a sample from a Melanesian population at the β-globin locus.

Genetic Divergence and Polyphyly in the Octocoral Genus Swiftia [Cnidaria: Octocorallia], Including a Species Impacted by the DWH Oil Spill

Mesophotic coral ecosystems (MCEs) are recognized around the world as diverse and ecologically important habitats. In the northern Gulf of Mexico (GoMx), MCEs are rocky reefs with abundant black corals and octocorals, including the species Swiftia exserta. Surveys following the Deepwater Horizon (DWH) oil spill in 2010 revealed significant injury to these and other species, the restoration of which requires an in-depth understanding of the biology, ecology, and genetic diversity of each species. To support a larger population connectivity study of impacted octocorals in the GoMx, this study combined sequences of mtMutS and nuclear 28S rDNA to confirm the identity of Swiftia sea fans in the GoMx, compare these markers for different polyp colors in the GoMx and Atlantic, and examine the phylogeny of the genus. Two mtMutS haplotypes were identified, one seemingly endemic to the northern GoMx. Compared to other North Atlantic Swiftia, S. exserta, the type of the genus was found to be extremely divergent and distinct from the two other Swiftia at both loci, with strong evidence of polyphyly in the genus. This information refines our understanding of the geographical distribution of injured coral and highlights how little is known about MCEs. Substantial taxonomic revisions may be needed for several taxa injured by the DWH oil spill.

Evolutionary Sample Size and Consilience in Phylogenetic Comparative Analysis

Phylogenetic comparative methods (PCMs) are commonly used to study evolution and adaptation. However, frequently used PCMs for discrete traits mishandle single evolutionary transitions. They erroneously detect correlated evolution in these situations. For example, hair and mammary glands cannot be said to have evolved in a correlated fashion because each evolved only once in mammals, but a commonly used model (Pagel's Discrete) statistically supports correlated (dependent) evolution. Using simulations, we find that rate parameter estimation, which is central for model selection, is poor in these scenarios due to small effective (evolutionary) sample sizes of independent character state change. Pagel's Discrete model also tends to favor dependent evolution in these scenarios, in part, because it forces evolution through state combinations unobserved in the tip data. This model prohibits simultaneous dual transitions along branches. Models with underlying continuous data distributions (e.g., Threshold and GLMM) are less prone to favor correlated evolution, but are still susceptible when evolutionary sample sizes are small. We provide three general recommendations for researchers who encounter these common situations: 1) Create study designs that evaluate a priori hypotheses and maximize evolutionary sample sizes; 2) assess the suitability of evolutionary models-for discrete traits, we introduce the phylogenetic imbalance ratio; and 3) evaluate evolutionary hypotheses with a consilience of evidence from disparate fields, like biogeography and developmental biology. Consilience plays a central role in hypothesis testing within the historical sciences where experiments are difficult or impossible to conduct, such as many hypotheses about correlated evolution. These recommendations are useful for investigations that employ any type of PCM.

Inferring the number and position of changes in selective regime in a non-equilibrium mutation-selection framework

BACKGROUND

Recovering the historical patterns of selection acting on a protein coding sequence is a major goal of evolutionary biology. Mutation-selection models address this problem by explicitly modelling fixation rates as a function of site-specific amino acid fitness values.However, they are restricted in their utility for investigating directional evolution because they require prior knowledge of the locations of fitness changes in the lineages of a phylogeny.

RESULTS

We apply a modified mutation-selection methodology that relaxes assumptions of equlibrium and time-reversibility. Our implementation allows us to identify branches where adaptive or compensatory shifts in the fitness landscape have taken place, signalled by a change in amino acid fitness profiles. Through simulation and analysis of an empirical data set of [Formula: see text]-lactamase genes, we test our ability to recover the position of adaptive events within the tree and successfully reconstruct initial codon frequencies and fitness profile parameters generated under the non-stationary model.

CONCLUSION

We demonstrate successful detection of selective shifts and identification of the affected branch on partitions of 300 codons or more. We successfully reconstruct fitness parameters and initial codon frequencies in simulated data and demonstrate that failing to account for non-equilibrium evolution can increase the error in fitness profile estimation. We also demonstrate reconstruction of plausible shifts in amino acid fitnesses in the bacterial [Formula: see text]-lactamase family and discuss some caveats for interpretation.

Distance metrics for ranked evolutionary trees

Genealogical tree modeling is essential for estimating evolutionary parameters in population genetics and phylogenetics. Recent mathematical results concerning ranked genealogies without leaf labels unlock opportunities in the analysis of evolutionary trees. In particular, comparisons between ranked genealogies facilitate the study of evolutionary processes of different organisms sampled at multiple time periods. We propose metrics on ranked tree shapes and ranked genealogies for lineages isochronously and heterochronously sampled. Our proposed tree metrics make it possible to conduct statistical analyses of ranked tree shapes and timed ranked tree shapes or ranked genealogies. Such analyses allow us to assess differences in tree distributions, quantify estimation uncertainty, and summarize tree distributions. We show the utility of our metrics via simulations and an application in infectious diseases.