Trying out a million genes to find the perfect pair with RTIST.

MOTIVATION: Consensus methods can be used for reconstructing a species tree from several gene trees, which exhibit incompatible topologies due to incomplete lineage sorting. Motivated by the fact that there are no anomalous rooted gene trees with three taxa and no anomalous unrooted gene trees with four taxa in the multispecies coalescent model, several contemporary methods form the gene tree consensus by finding the median tree with respect to the triplet or quartet distance-i.e. estimate the species tree as the tree which minimizes the sum of triplet or quartet distances to the input gene trees. These methods reformulate the solution to the consensus problem as the solution to a recursively solved dynamic programming (DP) problem. We present an iterative, easily parallelizable approach to finding the exact median triplet tree and implement it as an open source software package that can also find suboptimal consensus trees within a specified triplet distance to the gene trees. The most time-consuming step for methods of this type is the creation of a weights array for all possible subtree bipartitions. By grouping the relevant calculations and array update operations of different bipartitions of the same subtree together, this implementation finds the exact median tree of many gene trees faster than comparable methods, has better scaling properties with respect to the number of gene trees and has a smaller memory footprint. RESULTS: RTIST (Rooted Triple Inference of Species Trees) finds the exact median triplet tree of a set of gene trees. Its runtime and memory footprints scale better than existing algorithms. RTIST can resolve all the non-unique median trees, as well as sub-optimal consensus trees within a user-specified triplet distance to the median. Although it is limited in the number of taxa (≤20), its runtime changes little when the number of gene trees is changed by several orders of magnitude. AVAILABILITY AND IMPLEMENTATION: RTIST is written in C and Python. It is freely available at https://github.com/glebzhelezov/rtist.

Probabilities of Unranked and Ranked Anomaly Zones under Birth-Death Models.

A labeled gene tree topology that is more probable than the labeled gene tree topology matching a species tree is called "anomalous." Species trees that can generate such anomalous gene trees are said to be in the "anomaly zone." Here, probabilities of "unranked" and "ranked" gene tree topologies under the multispecies coalescent are considered. A ranked tree depicts not only the topological relationship among gene lineages, as an unranked tree does, but also the sequence in which the lineages coalesce. In this article, we study how the parameters of a species tree simulated under a constant-rate birth-death process can affect the probability that the species tree lies in the anomaly zone. We find that with more than five taxa, it is possible for species trees to have both anomalous unranked and ranked gene trees. The probability of being in either type of anomaly zone increases with more taxa. The probability of anomalous gene trees also increases with higher speciation rates. We observe that the probabilities of unranked anomaly zones are higher and grow much faster than those of ranked anomaly zones as the speciation rate increases. Our simulation shows that the most probable ranked gene tree is likely to have the same unranked topology as the species tree. We design the software PRANC, which computes probabilities of ranked gene tree topologies given a species tree under the coalescent model.

PRANC: ML species tree estimation from the ranked gene trees under coalescence.

SUMMARY: PRANC computes the Probabilities of RANked gene tree topologies under the multispecies coalescent. A ranked gene tree is a gene tree accounting for the temporal ordering of internal nodes. PRANC can also estimate the maximum likelihood (ML) species tree from a sample of ranked or unranked gene tree topologies. It estimates the ML tree with estimated branch lengths in coalescent units. AVAILABILITY AND IMPLEMENTATION: PRANC is written in C++ and freely available at github.com/anastasiiakim/PRANC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Heuristics for unrooted, unranked, and ranked anomaly zones under birth-death models.

Species trees that can generate a nonmatching gene tree topology that is more probable than the topology matching the species tree are said to be in an anomaly zone. We introduce some heuristic approaches to infer whether species trees are in anomaly zones when it is difficult or impossible to compute the entire distribution of gene tree topologies. Here, probabilities of unrooted, unranked, and ranked gene tree topologies under the multispecies coalescent are used. A ranked tree can be viewed as an unranked tree with a temporal ordering of its internal nodes. Overall, considering probabilities of unrooted or unranked gene tree topologies within one nearest neighbor interchange from the species tree topology is a reasonable heuristic to infer the existence of anomalous unrooted or unranked gene trees, respectively. We investigated a test proposed by Linkem et al. (2016) which classifies a species tree as being in an unranked anomaly zone if there is a subset of four taxa in an unranked anomaly zone. We find this test to have high true positive rates, but it can also have high false positive rates. For ranked trees, because at least one of the most probable ranked gene tree topologies must have the same unranked topology as the species tree, we propose to use only those ranked gene trees that have topologies that match the unranked species tree topology. We find that the probability that the species tree is in unrooted and unranked anomaly zones tends to increase with the speciation rate, and the probability of all three types of anomaly zones increases rapidly with the number of taxa. We find that probabilities that species trees are in an anomaly zone can be quite high for moderately high speciation rates.

An initiative to implement immediate postpartum long-acting reversible contraception in rural New Mexico.

BACKGROUND: Over the past decade, many states have developed approaches to reimburse for immediate postpartum long-acting reversible contraception. Despite expanded coverage, few hospitals offer immediate postpartum long-acting reversible contraception. OBJECTIVES: Immediate postpartum long-acting reversible contraception implementation is complex and requires a committed multidisciplinary team. After New Mexico Medicaid approved reimbursement for this service, the New Mexico Perinatal Collaborative developed and initiated an evidence-based implementation program containing several components. We sought to evaluate timing of the implementation process and facilitators and barriers to immediate postpartum long-acting reversible contraception in several New Mexico rural hospitals. The primary study outcome was time from New Mexico Perinatal Collaborative program component introduction in each hospital to the hospital's completion of the corresponding implementation step. Secondary outcomes included barriers and facilitators to immediate postpartum contraception implementation. STUDY DESIGN: In this mixed-methods study, conducted from April 2017 to May 2018, we completed semistructured questionnaires and interviews with 20 key personnel from 7 New Mexico hospitals that planned to implement immediate postpartum long-acting reversible contraception. The New Mexico Perinatal Collaborative introduced program components to hospitals in a stepped-wedge design. Participants contributed baseline and follow-up data at 4 time periods detailing the steps taken towards program implementation and the timing of step completion at their hospital. Qualitative data were analyzed using directed qualitative content analysis principles based on the Consolidated Framework for Implementation Research. RESULTS: Investigators conducted 43 interviews during the 14-month study period. Median time to complete steps toward implementation-patient education, clinician training, nursing education, charge capture, available supplies, and protocols or guidelines-ranged from 7 days for clinician training to 357 days to develop patient education materials. Facilitators of immediate postpartum contraception readiness were local hospital clinical champions and institutional administrative and financial stability. Of the 7 hospitals, 4 completed all Perinatal Collaborative implementation program components and 3 of those piloted immediate postpartum long-acting reversible contraception services. Two publicly funded hospitals currently offer immediate postpartum long-acting reversible contraception without verification of payment for the device or insertion. The third hospital piloted the program with 8 contraceptive devices, did not receive reimbursement due to identified flaws in Medicaid billing guidance and does not currently offer the service. The remaining 3 of the 7 hospitals declined to complete the NMPC program; the hospital that completed the program but did not pilot immediate postpartum long-acting reversible contraception did so because Medicaid billing mechanisms were incompatible with their automated billing systems. Participants consistently reported that lack of reimbursement was the major barrier to immediate postpartum long-acting reversible contraception implementation. CONCLUSION: Despite the New Mexico Perinatal Collaborative's robust implementation process and hospital engagement, most hospitals did not offer immediate postpartum long-acting reversible contraception over the study period. Reimbursement obstacles prevented full service implementation. Interventions to improve immediate postpartum long-acting reversible contraception access must begin with implementation of seamless billing and reimbursement mechanisms to ensure adequate hospital payments.

Modeling Hybridization Under the Network Multispecies Coalescent.

Simultaneously modeling hybridization and the multispecies coalescent is becoming increasingly common, and inference of species networks in this context is now implemented in several software packages. This article addresses some of the conceptual issues and decisions to be made in this modeling, including whether or not to use branch lengths and issues with model identifiability. This article is based on a talk given at a Spotlight Session at Evolution 2017 meeting in Portland, Oregon. This session included several talks about modeling hybridization and gene flow in the presence of incomplete lineage sorting. Other talks given at this meeting are also included in this special issue of Systematic Biology.

Displayed Trees Do Not Determine Distinguishability Under the Network Multispecies Coalescent.

Recent work in estimating species relationships from gene trees has included inferring networks assuming that past hybridization has occurred between species. Probabilistic models using the multispecies coalescent can be used in this framework for likelihood-based inference of both network topologies and parameters, including branch lengths and hybridization parameters. A difficulty for such methods is that it is not always clear whether, or to what extent, networks are identifiable-that is whether there could be two distinct networks that lead to the same distribution of gene trees. For cases in which incomplete lineage sorting occurs in addition to hybridization, we demonstrate a new representation of the species network likelihood that expresses the probability distribution of the gene tree topologies as a linear combination of gene tree distributions given a set of species trees. This representation makes it clear that in some cases in which two distinct networks give the same distribution of gene trees when sampling one allele per species, the two networks can be distinguished theoretically when multiple individuals are sampled per species. This result means that network identifiability is not only a function of the trees displayed by the networks but also depends on allele sampling within species. We additionally give an example in which two networks that display exactly the same trees can be distinguished from their gene trees even when there is only one lineage sampled per species. [gene tree, hybridization, identifiability, maximum likelihood, species tree, phylogeny.].

Split Probabilities and Species Tree Inference Under the Multispecies Coalescent Model.

Using topological summaries of gene trees as a basis for species tree inference is a promising approach to obtain acceptable speed on genomic-scale datasets, and to avoid some undesirable modeling assumptions. Here we study the probabilities of splits on gene trees under the multispecies coalescent model, and how their features might inform species tree inference. After investigating the behavior of split consensus methods, we investigate split invariants-that is, polynomial relationships between split probabilities. These invariants are then used to show that, even though a split is an unrooted notion, split probabilities retain enough information to identify the rooted species tree topology for trees of 5 or more taxa, with one possible 6-taxon exception.

Inferring rooted species trees from unrooted gene trees using approximate Bayesian computation.

Methods for inferring species trees from gene trees motivated by incomplete lineage sorting typically use either rooted gene trees to infer a rooted species tree, or use unrooted gene trees to infer an unrooted species tree, which is then typically rooted using one or more outgroups. Theoretically, however, it has been known since 2011 that it is possible to consistently infer the root of the species tree directly from unrooted gene trees without assuming an outgroup. Here, we use approximate Bayesian computation to infer the root of the species tree from unrooted gene trees assuming the multispecies coalescent model. It is hoped that this approach will be useful in cases where an appropriate outgroup is difficult to find and gene trees do not follow a molecular clock. We use approximate Bayesian computation to infer the root of the species tree from unrooted gene trees. This approach could also be useful when there is prior information that makes a small number of root locations plausible in an unrooted species tree.

Does Gene Tree Discordance Explain the Mismatch between Macroevolutionary Models and Empirical Patterns of Tree Shape and Branching Times?

Classic null models for speciation and extinction give rise to phylogenies that differ in distribution from empirical phylogenies. In particular, empirical phylogenies are less balanced and have branching times closer to the root compared to phylogenies predicted by common null models. This difference might be due to null models of the speciation and extinction process being too simplistic, or due to the empirical datasets not being representative of random phylogenies. A third possibility arises because phylogenetic reconstruction methods often infer gene trees rather than species trees, producing an incongruity between models that predict species tree patterns and empirical analyses that consider gene trees. We investigate the extent to which the difference between gene trees and species trees under a combined birth-death and multispecies coalescent model can explain the difference in empirical trees and birth-death species trees. We simulate gene trees embedded in simulated species trees and investigate their difference with respect to tree balance and branching times. We observe that the gene trees are less balanced and typically have branching times closer to the root than the species trees. Empirical trees from TreeBase are also less balanced than our simulated species trees, and model gene trees can explain an imbalance increase of up to 8% compared to species trees. However, we see a much larger imbalance increase in empirical trees, about 100%, meaning that additional features must also be causing imbalance in empirical trees. This simulation study highlights the necessity of revisiting the assumptions made in phylogenetic analyses, as these assumptions, such as equating the gene tree with the species tree, might lead to a biased conclusion.

Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees.

BACKGROUND: There has been increasing interest in coalescent models which admit multiple mergers of ancestral lineages; and to model hybridization and coalescence simultaneously. RESULTS: Hybrid-Lambda is a software package that simulates gene genealogies under multiple merger and Kingman's coalescent processes within species networks or species trees. Hybrid-Lambda allows different coalescent processes to be specified for different populations, and allows for time to be converted between generations and coalescent units, by specifying a population size for each population. In addition, Hybrid-Lambda can generate simulated datasets, assuming the infinitely many sites mutation model, and compute the F ST statistic. As an illustration, we apply Hybrid-Lambda to infer the time of subdivision of certain marine invertebrates under different coalescent processes. CONCLUSIONS: Hybrid-Lambda makes it possible to investigate biogeographic concordance among high fecundity species exhibiting skewed offspring distribution.

There are no caterpillars in a wicked forest.

Species trees represent the historical divergences of populations or species, while gene trees trace the ancestry of individual gene copies sampled within those populations. In cases involving rapid speciation, gene trees with topologies that differ from that of the species tree can be most probable under the standard multispecies coalescent model, making species tree inference more difficult. Such anomalous gene trees are not well understood except for some small cases. In this work, we establish one constraint that applies to trees of any size: gene trees with "caterpillar" topologies cannot be anomalous. The proof of this involves a new combinatorial object, called a population history, which keeps track of the number of coalescent events in each ancestral population.

Robustness to divergence time underestimation when inferring species trees from estimated gene trees.

To infer species trees from gene trees estimated from phylogenomic data sets, tractable methods are needed that can handle dozens to hundreds of loci. We examine several computationally efficient approaches-MP-EST, STAR, STEAC, STELLS, and STEM-for inferring species trees from gene trees estimated using maximum likelihood (ML) and Bayesian approaches. Among the methods examined, we found that topology-based methods often performed better using ML gene trees and methods employing coalescent times typically performed better using Bayesian gene trees, with MP-EST, STAR, STEAC, and STELLS outperforming STEM under most conditions. We examine why the STEM tree (also called GLASS or Maximum Tree) is less accurate on estimated gene trees by comparing estimated and true coalescence times, performing species tree inference using simulations, and analyzing a great ape data set keeping track of false positive and false negative rates for inferred clades. We find that although true coalescence times are more ancient than speciation times under the multispecies coalescent model, estimated coalescence times are often more recent than speciation times. This underestimation can lead to increased bias and lack of resolution with increased sampling (either alleles or loci) when gene trees are estimated with ML. The problem appears to be less severe using Bayesian gene-tree estimates.

The probability of a gene tree topology within a phylogenetic network with applications to hybridization detection.

Gene tree topologies have proven a powerful data source for various tasks, including species tree inference and species delimitation. Consequently, methods for computing probabilities of gene trees within species trees have been developed and widely used in probabilistic inference frameworks. All these methods assume an underlying multispecies coalescent model. However, when reticulate evolutionary events such as hybridization occur, these methods are inadequate, as they do not account for such events. Methods that account for both hybridization and deep coalescence in computing the probability of a gene tree topology currently exist for very limited cases. However, no such methods exist for general cases, owing primarily to the fact that it is currently unknown how to compute the probability of a gene tree topology within the branches of a phylogenetic network. Here we present a novel method for computing the probability of gene tree topologies on phylogenetic networks and demonstrate its application to the inference of hybridization in the presence of incomplete lineage sorting. We reanalyze a Saccharomyces species data set for which multiple analyses had converged on a species tree candidate. Using our method, though, we show that an evolutionary hypothesis involving hybridization in this group has better support than one of strict divergence. A similar reanalysis on a group of three Drosophila species shows that the data is consistent with hybridization. Further, using extensive simulation studies, we demonstrate the power of gene tree topologies at obtaining accurate estimates of branch lengths and hybridization probabilities of a given phylogenetic network. Finally, we discuss identifiability issues with detecting hybridization, particularly in cases that involve extinction or incomplete sampling of taxa.

Anomalous unrooted gene trees.

The coalescent and multispecies coalescent model rooted genealogies backward through time. Often, the direction of time is unknown in trees estimated from molecular sequences due to reversible mutation models, absence of an appropriate outgroup, and the absence of the molecular clock. In this article, probabilities of unrooted gene-tree topologies under the multispecies coalescent are considered. The main result is that for any species-tree topology with seven or more taxa, there exist branch lengths such that there are unrooted gene-tree topologies that are more likely than the one that has the same unrooted topology as the species tree. Species trees with such anomalous unrooted gene trees (AUGTs) are characterized for trees with five and six taxa, and patterns of branch lengths leading to AUGTs and rooted anomalous gene trees are explored. The results could be useful for understanding gene tree discordance and designing simulations studies for inferring challenging species trees.

Genotype, haplotype and copy-number variation in worldwide human populations.

Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected--including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas--the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.

Hypernatremia in Hyperglycemia: Clinical Features and Relationship to Fractional Changes in Body Water and Monovalent Cations during Its Development.

In hyperglycemia, the serum sodium concentration ([Na]S) receives influences from (a) the fluid exit from the intracellular compartment and thirst, which cause [Na]S decreases; (b) osmotic diuresis with sums of the urinary sodium plus potassium concentration lower than the baseline euglycemic [Na]S, which results in a [Na]S increase; and (c), in some cases, gains or losses of fluid, sodium, and potassium through the gastrointestinal tract, the respiratory tract, and the skin. Hyperglycemic patients with hypernatremia have large deficits of body water and usually hypovolemia and develop severe clinical manifestations and significant mortality. To assist with the correction of both the severe dehydration and the hypovolemia, we developed formulas computing the fractional losses of the body water and monovalent cations in hyperglycemia. The formulas estimate varying losses between patients with the same serum glucose concentration ([Glu]S) and [Na]S but with different sums of monovalent cation concentrations in the lost fluids. Among subjects with the same [Glu]S and [Na]S, those with higher monovalent cation concentrations in the fluids lost have higher fractional losses of body water. The sum of the monovalent cation concentrations in the lost fluids should be considered when computing the volume and composition of the fluid replacement for hyperglycemic syndromes.

The onset of rare earth metallosis begins with renal gadolinium-rich nanoparticles from magnetic resonance imaging contrast agent exposure.

The leitmotifs of magnetic resonance imaging (MRI) contrast agent-induced complications range from acute kidney injury, symptoms associated with gadolinium exposure (SAGE)/gadolinium deposition disease, potentially fatal gadolinium encephalopathy, and irreversible systemic fibrosis. Gadolinium is the active ingredient of these contrast agents, a non-physiologic lanthanide metal. The mechanisms of MRI contrast agent-induced diseases are unknown. Mice were treated with a MRI contrast agent. Human kidney tissues from contrast-naïve and MRI contrast agent-treated patients were obtained and analyzed. Kidneys (human and mouse) were assessed with transmission electron microscopy and scanning transmission electron microscopy with X-ray energy-dispersive spectroscopy. MRI contrast agent treatment resulted in unilamellar vesicles and mitochondriopathy in renal epithelium. Electron-dense intracellular precipitates and the outer rim of lipid droplets were rich in gadolinium and phosphorus. We conclude that MRI contrast agents are not physiologically inert. The long-term safety of these synthetic metal-ligand complexes, especially with repeated use, should be studied further.

Multiple merger gene genealogies in two species: Monophyly, paraphyly, and polyphyly for two examples of Lambda coalescents.

Probabilities of monophyly, paraphyly, and polyphyly of two-species gene genealogies are computed for modest sample sizes and compared for two different Λ coalescent processes. Coalescent processes belonging to the Λ coalescent family admit asynchronous multiple mergers of active ancestral lineages. Assigning a timescale to the time of divergence becomes a central issue when different populations have different coalescent processes running on different timescales. Clade probabilities in single populations are also computed, which can be useful for testing for taxonomic distinctiveness of an observed set of monophyletic lineages. The coalescence rates of multiple merger coalescent processes are functions of coalescent parameters. The effect of coalescent parameters on the probabilities studied depends on the coalescent process, and if the population is ancestral or derived. The probability of reciprocal monophyly tends to be somewhat lower, when associated with a Λ coalescent, under the null hypothesis that two groups come from the same population. However, even for fairly recent divergence times, the probability of monophyly tends to be higher as a function of the number of generations for coalescent processes that admit multiple mergers, and is sensitive to the parameter of one of the example processes.