Confidence intervals in molecular dating by maximum likelihood.

Molecular dating has been widely used to infer the times of past evolutionary events using molecular sequences. This paper describes three bootstrap methods to infer confidence intervals under a penalized likelihood framework. The basic idea is to use data pseudoreplicates to infer uncertainty in the branch lengths of a phylogeny reconstructed with molecular sequences. The three specific bootstrap methods are nonparametric (direct tree bootstrapping), semiparametric (rate smoothing), and parametric (Poisson simulation). Our extensive simulation study showed that the three methods perform generally well under a simple strict clock model of molecular evolution; however, the results were less positive with data simulated using an uncorrelated or a correlated relaxed clock model. Several factors impacted, possibly in interaction, the performance of the confidence intervals. Increasing the number of calibration points had a positive effect, as well as increasing the sequence length or the number of sequences although both latter effects depended on the model of evolution. A case study is presented with a molecular phylogeny of the Felidae (Mammalia: Carnivora). A comparison was made with a Bayesian analysis: the results were very close in terms of confidence intervals and there was no marked tendency for an approach to produce younger or older bounds compared to the other.

ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R.

Summary: After more than fifteen years of existence, the R package ape has continuously grown its contents, and has been used by a growing community of users. The release of version 5.0 has marked a leap towards a modern software for evolutionary analyses. Efforts have been put to improve efficiency, flexibility, support for 'big data' (R's long vectors), ease of use and quality check before a new release. These changes will hopefully make ape a useful software for the study of biodiversity and evolution in a context of increasing data quantity. Availability and implementation: ape is distributed through the Comprehensive R Archive Network: http://cran.r-project.org/package=ape. Further information may be found at http://ape-package.ird.fr/.

Putative Origins of Cell-Free DNA in Humans: A Review of Active and Passive Nucleic Acid Release Mechanisms.

Through various pathways of cell death, degradation, and regulated extrusion, partial or complete genomes of various origins (e.g., host cells, fetal cells, and infiltrating viruses and microbes) are continuously shed into human body fluids in the form of segmented cell-free DNA (cfDNA) molecules. While the genetic complexity of total cfDNA is vast, the development of progressively efficient extraction, high-throughput sequencing, characterization via bioinformatics procedures, and detection have resulted in increasingly accurate partitioning and profiling of cfDNA subtypes. Not surprisingly, cfDNA analysis is emerging as a powerful clinical tool in many branches of medicine. In addition, the low invasiveness of longitudinal cfDNA sampling provides unprecedented access to study temporal genomic changes in a variety of contexts. However, the genetic diversity of cfDNA is also a great source of ambiguity and poses significant experimental and analytical challenges. For example, the cfDNA population in the bloodstream is heterogeneous and also fluctuates dynamically, differs between individuals, and exhibits numerous overlapping features despite often originating from different sources and processes. Therefore, a deeper understanding of the determining variables that impact the properties of cfDNA is crucial, however, thus far, is largely lacking. In this work we review recent and historical research on active vs. passive release mechanisms and estimate the significance and extent of their contribution to the composition of cfDNA.

A comprehensive framework for detecting copy number variants from single nucleotide polymorphism data: 'rCNV', a versatile r package for paralogue and CNV detection.

Recent studies have highlighted the significant role of copy number variants (CNVs) in phenotypic diversity, environmental adaptation and species divergence across eukaryotes. The presence of CNVs also has the potential to introduce genotyping biases, which can pose challenges to accurate population and quantitative genetic analyses. However, detecting CNVs in genomes, particularly in non-model organisms, presents a formidable challenge. To address this issue, we have developed a statistical framework and an accompanying r software package that leverage allelic-read depth from single nucleotide polymorphism (SNP) data for accurate CNV detection. Our framework capitalises on two key principles. First, it exploits the distribution of allelic-read depth ratios in heterozygotes for individual SNPs by comparing it against an expected distribution based on binomial sampling. Second, it identifies SNPs exhibiting an apparent excess of heterozygotes under Hardy-Weinberg equilibrium. By employing multiple statistical tests, our method not only enhances sensitivity to sampling effects but also effectively addresses reference biases, resulting in optimised SNP classification. Our framework is compatible with various NGS technologies (e.g. RADseq, Exome-capture). This versatility enables CNV calling from genomes of diverse complexities. To streamline the analysis process, we have implemented our framework in the user-friendly r package 'rCNV', which automates the entire workflow seamlessly. We trained our models using simulated data and validated their performance on four datasets derived from different sequencing technologies, including RADseq (Chinook salmon-Oncorhynchus tshawytscha), Rapture (American lobster-Homarus americanus), Exome-capture (Norway spruce-Picea abies) and WGS (Malaria mosquito-Anopheles gambiae).

Harvesting evolutionary signals in a forest of prokaryotic gene trees.

Phylogenomic studies produce increasingly large phylogenetic forests of trees with patchy taxonomical sampling. Typically, prokaryotic data generate thousands of gene trees of all sizes that are difficult, if not impossible, to root. Their topologies do not match the genealogy of lineages, as they are influenced not only by duplication, losses, and vertical descent but also by lateral gene transfer (LGT) and recombination. Because this complexity in part reflects the diversity of evolutionary processes, the study of phylogenetic forests is thus a great opportunity to improve our understanding of prokaryotic evolution. Here, we show how the rich evolutionary content of such novel phylogenetic objects can be exploited through the development of new approaches designed specifically for extracting the multiple evolutionary signals present in the forest of life, that is, by slicing up trees into remarkable bits and pieces: clans, slices, and clips. We harvested a forest of 6,901 unrooted gene trees comprising up to 100 prokaryotic genomes (41 archaea and 59 bacteria) to search for evolutionary events that a species tree would not account for. We identified 1) trees and partitions of trees that reflected the lifestyle of organisms rather than their taxonomy, 2) candidate lifestyle-specific genetic modules, used by distinct unrelated organisms to adapt to the same environment, 3) gene families, nonrandomly distributed in the functional space, that were frequently exchanged between archaea and bacteria, sometimes without major changes in their sequences. Finally, 4) we reconstructed polarized networks of genetic partnerships between archaea and bacteria to describe some of the rules affecting LGT between these two Domains.

Let them fall where they may: congruence analysis in massive phylogenetically messy data sets.

Interest in congruence in phylogenetic data has largely focused on issues affecting multicellular organisms, and animals in particular, in which the level of incongruence is expected to be relatively low. In addition, assessment methods developed in the past have been designed for reasonably small numbers of loci and scale poorly for larger data sets. However, there are currently over a thousand complete genome sequences available and of interest to evolutionary biologists, and these sequences are predominantly from microbial organisms, whose molecular evolution is much less frequently tree-like than that of multicellular life forms. As such, the level of incongruence in these data is expected to be high. We present a congruence method that accommodates both very large numbers of genes and high degrees of incongruence. Our method uses clustering algorithms to identify subsets of genes based on similarity of phylogenetic signal. It involves only a single phylogenetic analysis per gene, and therefore, computation time scales nearly linearly with the number of genes in the data set. We show that our method performs very well with sets of sequence alignments simulated under a wide variety of conditions. In addition, we present an analysis of core genes of prokaryotes, often assumed to have been largely vertically inherited, in which we identify two highly incongruent classes of genes. This result is consistent with the complexity hypothesis.

phangorn: phylogenetic analysis in R.

SUMMARY: phangorn is a package for phylogenetic reconstruction and analysis in the R language. Previously it was only possible to estimate phylogenetic trees with distance methods in R. phangorn, now offers the possibility of reconstructing phylogenies with distance based methods, maximum parsimony or maximum likelihood (ML) and performing Hadamard conjugation. Extending the general ML framework, this package provides the possibility of estimating mixture and partition models. Furthermore, phangorn offers several functions for comparing trees, phylogenetic models or splits, simulating character data and performing congruence analyses. AVAILABILITY: phangorn can be obtained through the CRAN homepage http://cran.r-project.org/web/packages/phangorn/index.html. phangorn is licensed under GPL 2.

Brain Allometry Across Macroevolutionary Scales in Squamates Suggests a Conserved Pattern in Snakes.

Despite historical interest in brain size evolution in vertebrates, few studies have assessed variation in brain size in squamate reptiles such as snakes and lizards. Here, we analyzed the pattern of brain allometry at macroevolutionary scale in snakes and lizards, using body mass and snout vent length as measures of body size. We also assessed potential energetic trade-offs associated with relative brain size changes in Crotalinae vipers. Body mass showed a conserved pattern of brain allometry across taxa of snakes, but not in lizards. Body length favored changes of brain allometry in both snakes and lizards, but less variability was observed in snakes. Moreover, we did not find evidence for trade-offs between brain size and the size of other organs in Crotalinae. Thus, despite the contribution of body elongation to changes in relative brain size in squamate reptiles, snakes present low variation in brain allometry across taxa. Although the mechanisms driving this conserved pattern are unknown, we hypothesize that the snake body plan plays an important role in balancing the energetic demands of brain and body size increase at macroevolutionary scales. We encourage future research on the evolution of brain and body size in snakes to test this hypothesis.

Using Genomics to Shape the Definition of the Agglutinin-Like Sequence (ALS) Family in the Saccharomycetales.

The Candida albicans agglutinin-like sequence (ALS) family is studied because of its contribution to cell adhesion, fungal colonization, and polymicrobial biofilm formation. The goal of this work was to derive an accurate census and sequence for ALS genes in pathogenic yeasts and other closely related species, while probing the boundaries of the ALS family within the Order Saccharomycetales. Bioinformatic methods were combined with laboratory experimentation to characterize 47 novel ALS loci from 8 fungal species. AlphaFold predictions suggested the presence of a conserved N-terminal adhesive domain (NT-Als) structure in all Als proteins reported to date, as well as in S. cerevisiae alpha-agglutinin (Sag1). Lodderomyces elongisporus, Meyerozyma guilliermondii, and Scheffersomyces stipitis were notable because each species had genes with C. albicans ALS features, as well as at least one that encoded a Sag1-like protein. Detection of recombination events between the ALS family and gene families encoding other cell-surface proteins such as Iff/Hyr and Flo suggest widespread domain swapping with the potential to create cell-surface diversity among yeast species. Results from the analysis also revealed subtelomeric ALS genes, ALS pseudogenes, and the potential for yeast species to secrete their own soluble adhesion inhibitors. Information presented here supports the inclusion of SAG1 in the ALS family and yields many experimental hypotheses to pursue to further reveal the nature of the ALS family.

Phylogenetic signal and evolutionary correlates of urban tolerance in a widespread neotropical lizard clade.

Urbanization is intensifying worldwide, and while some species tolerate and even exploit urban environments, many others are excluded entirely from this new habitat. Understanding the factors that underlie tolerance of urbanization is thus of rapidly growing importance. Here, we examine urban tolerance across a diverse group of lizards: Caribbean members of the neotropical genus Anolis. Our analyses reveal that urban tolerance has strong phylogenetic signal, suggesting that closely related species tend to respond similarly to urban environments. We propose that this characteristic of urban tolerance in anoles may be used to forecast the possible responses of species to increasing urbanization. In addition, we identified several key ecological and morphological traits that tend to be associated with tolerance in Anolis. Specifically, species experiencing hot and dry conditions in their natural environment and those that maintain higher body temperatures tend to have greater tolerance of urban habitats. We also found that tolerance of urbanization is positively associated with toepad lamella number and negatively associated with ventral scale density and relative hindlimb length. The identification of factors that predispose a species to be more or less urban tolerant can provide a starting point for conservation and sustainable development in our increasingly urbanized world.

Linking morphological and molecular sources to disentangle the case of Xylodon australis.

The use of different sources of evidence has been recommended in order to conduct species delimitation analyses to solve taxonomic issues. In this study, we use a maximum likelihood framework to combine morphological and molecular traits to study the case of Xylodon australis (Hymenochaetales, Basidiomycota) using the locate.yeti function from the phytools R package. Xylodon australis has been considered a single species distributed across Australia, New Zealand and Patagonia. Multi-locus phylogenetic analyses were conducted to unmask the actual diversity under X. australis as well as the kinship relations respect their relatives. To assess the taxonomic position of each clade, locate.yeti function was used to locate in a molecular phylogeny the X. australis type material for which no molecular data was available using morphological continuous traits. Two different species were distinguished under the X. australis name, one from Australia-New Zealand and other from Patagonia. In addition, a close relationship with Xylodon lenis, a species from the South East of Asia, was confirmed for the Patagonian clade. We discuss the implications of our results for the biogeographical history of this genus and we evaluate the potential of this method to be used with historical collections for which molecular data is not available.

Publisher Correction: Host-associated microbiomes are predicted by immune system complexity and climate.

Following publication of the original paper [1], it was reported that an error in the processing of Fig. 8 occurred. In the online HTML version of the article, Fig. 8 was presented as a duplication of Fig. 7. The original article [1] has been corrected.

Host-associated microbiomes are predicted by immune system complexity and climate.

BACKGROUND: Host-associated microbiomes, the microorganisms occurring inside and on host surfaces, influence evolutionary, immunological, and ecological processes. Interactions between host and microbiome affect metabolism and contribute to host adaptation to changing environments. Meta-analyses of host-associated bacterial communities have the potential to elucidate global-scale patterns of microbial community structure and function. It is possible that host surface-associated (external) microbiomes respond more strongly to variations in environmental factors, whereas internal microbiomes are more tightly linked to host factors. RESULTS: Here, we use the dataset from the Earth Microbiome Project and accumulate data from 50 additional studies totaling 654 host species and over 15,000 samples to examine global-scale patterns of bacterial diversity and function. We analyze microbiomes from non-captive hosts sampled from natural habitats and find patterns with bioclimate and geophysical factors, as well as land use, host phylogeny, and trophic level/diet. Specifically, external microbiomes are best explained by variations in mean daily temperature range and precipitation seasonality. In contrast, internal microbiomes are best explained by host factors such as phylogeny/immune complexity and trophic level/diet, plus climate. CONCLUSIONS: Internal microbiomes are predominantly associated with top-down effects, while climatic factors are stronger determinants of microbiomes on host external surfaces. Host immunity may act on microbiome diversity through top-down regulation analogous to predators in non-microbial ecosystems. Noting gaps in geographic and host sampling, this combined dataset represents a global baseline available for interrogation by future microbial ecology studies.

Linking genomics and population genetics with R.

Population genetics and genomics have developed and been treated as independent fields of study despite having common roots. The continuous progress of sequencing technologies is contributing to (re-)connect these two disciplines. We review the challenges faced by data analysts and software developers when handling very big genetic data sets collected on many individuals. We then expose how r, as a computing language and development environment, proposes some solutions to meet these challenges. We focus on some specific issues that are often encountered in practice: handling and analysing single-nucleotide polymorphism data, handling and reading variant call format files, analysing haplotypes and linkage disequilibrium and performing multivariate analyses. We illustrate these implementations with some analyses of three recently published data sets that contain between 60 000 and 1 000 000 loci. We conclude with some perspectives on future developments of r software for population genomics.

apex: phylogenetics with multiple genes.

Genetic sequences of multiple genes are becoming increasingly common for a wide range of organisms including viruses, bacteria and eukaryotes. While such data may sometimes be treated as a single locus, in practice, a number of biological and statistical phenomena can lead to phylogenetic incongruence. In such cases, different loci should, at least as a preliminary step, be examined and analysed separately. The r software has become a popular platform for phylogenetics, with several packages implementing distance-based, parsimony and likelihood-based phylogenetic reconstruction, and an even greater number of packages implementing phylogenetic comparative methods. Unfortunately, basic data structures and tools for analysing multiple genes have so far been lacking, thereby limiting potential for investigating phylogenetic incongruence. In this study, we introduce the new r package apex to fill this gap. apex implements new object classes, which extend existing standards for storing DNA and amino acid sequences, and provides a number of convenient tools for handling, visualizing and analysing these data. In this study, we introduce the main features of the package and illustrate its functionalities through the analysis of a simple data set.

Comparison of the Serum Tumor Markers S100 and Melanoma-inhibitory Activity (MIA) in the Monitoring of Patients with Metastatic Melanoma Receiving Vaccination Immunotherapy with Dendritic Cells.

BACKGROUND: In patients with melanoma, early dissemination via lymphatic and hematogenous routes is frequently seen. Thus, besides clinical follow-up examination and imaging, reliable melanoma-specific serological tumor markers are needed. PATIENTS AND METHODS: We retrospectively compared two serum markers for melanoma, S100 and melanoma-inhibitory activity (MIA), for monitoring of patients with metastatic melanoma under either adjuvant or therapeutic vaccination immunotherapy with dendritic cells (DC). Serum was obtained from a total of 100 patients (28 patients in stage III and 72 patients in stage IV, according to the American Joint Committee on Cancer 2002) at regular intervals during therapy, accompanied by follow-up imaging. RESULTS: When relapse was detected, both markers often remained within normal range. In contrast, in patients with metastatic measurable disease receiving therapeutic and not adjuvant DC vaccination, an increase of both markers was a strong indicator for disease progression. When comparing both markers in the whole study population, MIA showed a superior sensitivity to detect disease progression. CONCLUSION: S100 and MIA are highly sensitive tumor markers for monitoring of patients with melanoma with current metastases, but less sensitive for monitoring of tumor-free patients. In the current study, MIA had a slightly superior sensitivity to detect progressive disease compared to S100 and seems to be more useful in monitoring of patients with metastatic melanoma receiving immunotherapy.

Life history linked to immune investment in developing amphibians.

The broad diversity of amphibian developmental strategies has been shaped, in part, by pathogen pressure, yet trade-offs between the rate of larval development and immune investment remain poorly understood. The expression of antimicrobial peptides (AMPs) in skin secretions is a crucial defense against emerging amphibian pathogens and can also indirectly affect host defense by influencing the composition of skin microbiota. We examined the constitutive or induced expression of AMPs in 17 species at multiple life-history stages. We found that AMP defenses in tadpoles of species with short larval periods (fast pace of life) were reduced in comparison with species that overwinter as tadpoles and grow to a large size. A complete set of defensive peptides emerged soon after metamorphosis. These findings support the hypothesis that species with a slow pace of life invest energy in AMP production to resist potential pathogens encountered during the long larval period, whereas species with a fast pace of life trade this investment in defense for more rapid growth and development.

Of woods and webs: possible alternatives to the tree of life for studying genomic fluidity in E. coli.

BACKGROUND: We introduce several forest-based and network-based methods for exploring microbial evolution, and apply them to the study of thousands of genes from 30 strains of E. coli. This case study illustrates how additional analyses could offer fast heuristic alternatives to standard tree of life (TOL) approaches. RESULTS: We use gene networks to identify genes with atypical modes of evolution, and genome networks to characterize the evolution of genetic partnerships between E. coli and mobile genetic elements. We develop a novel polychromatic quartet method to capture patterns of recombination within E. coli, to update the clanistic toolkit, and to search for the impact of lateral gene transfer and of pathogenicity on gene evolution in two large forests of trees bearing E. coli. We unravel high rates of lateral gene transfer involving E. coli (about 40% of the trees under study), and show that both core genes and shell genes of E. coli are affected by non-tree-like evolutionary processes. We show that pathogenic lifestyle impacted the structure of 30% of the gene trees, and that pathogenic strains are more likely to transfer genes with one another than with non-pathogenic strains. In addition, we propose five groups of genes as candidate mobile modules of pathogenicity. We also present strong evidence for recent lateral gene transfer between E. coli and mobile genetic elements. CONCLUSIONS: Depending on which evolutionary questions biologists want to address (i.e. the identification of modules, genetic partnerships, recombination, lateral gene transfer, or genes with atypical evolutionary modes, etc.), forest-based and network-based methods are preferable to the reconstruction of a single tree, because they provide insights and produce hypotheses about the dynamics of genome evolution, rather than the relative branching order of species and lineages. Such a methodological pluralism - the use of woods and webs - is to be encouraged to analyse the evolutionary processes at play in microbial evolution.This manuscript was reviewed by: Ford Doolittle, Tal Pupko, Richard Burian, James McInerney, Didier Raoult, and Yan Boucher.

Local mobile gene pools rapidly cross species boundaries to create endemicity within global Vibrio cholerae populations.

Vibrio cholerae represents both an environmental pathogen and a widely distributed microbial species comprised of closely related strains occurring in the tropical to temperate coastal ocean across the globe (Colwell RR, Science 274:2025-2031, 1996; Griffith DC, Kelly-Hope LA, Miller MA, Am. J. Trop. Med. Hyg. 75:973-977, 2006; Reidl J, Klose KE, FEMS Microbiol. Rev. 26:125-139, 2002). However, although this implies dispersal and growth across diverse environmental conditions, how locally successful populations assemble from a possibly global gene pool, relatively unhindered by geographic boundaries, remains poorly understood. Here, we show that environmental Vibrio cholerae possesses two, largely distinct gene pools: one is vertically inherited and globally well mixed, and the other is local and rapidly transferred across species boundaries to generate an endemic population structure. While phylogeographic analysis of isolates collected from Bangladesh and the U.S. east coast suggested strong panmixis for protein-coding genes, there was geographic structure in integrons, which are the only genomic islands present in all strains of V. cholerae (Chun J, et al., Proc. Natl. Acad. Sci. U. S. A. 106:15442-15447, 2009) and are capable of acquiring and expressing mobile gene cassettes. Geographic differentiation in integrons arises from high gene turnover, with acquisition from a locally co-occurring sister species being up to twice as likely as exchange with conspecific but geographically distant V. cholerae populations. IMPORTANCE Functional predictions of integron genes show the predominance of secondary metabolism and cell surface modification, which is consistent with a role in competition and predation defense. We suggest that the integron gene pool's distinctness and tempo of sharing are adaptive in allowing rapid conversion of genomes to reflect local ecological constraints. Because the integron is frequently the main element differentiating clinical strains (Chun J, et al., Proc. Natl. Acad. Sci. U. S. A. 106:15442-15447, 2009) and its recombinogenic activity is directly stimulated by environmental stresses (Guerin E, et al., Science 324:1034, 2009), these observations are relevant for local emergence and subsequent dispersal.