Five statistical questions about the tree of life

Stochastic modeling of phylogenies raises five questions that have received varying levels of attention from quantitatively inclined biologists. 1) How large do we expect (from the model) the ratio of maximum historical diversity to current diversity to be? 2) From a correct phylogeny of the extant species of a clade, what can we deduce about past speciation and extinction rates? 3) What proportion of extant species are in fact descendants of still-extant ancestral species, and how does this compare with predictions of models? 4) When one moves from trees on species to trees on sets of species (whether traditional higher order taxa or clades within PhyloCode), does one expect trees to become more unbalanced as a purely logical consequence of tree structure, without signifying any real biological phenomenon? 5) How do we expect that fluctuation rates for counts of higher order taxa should compare with fluctuation rates for number of species? We present a mathematician's view based on an oversimplified modeling framework in which all these questions can be studied coherently.     

Introduction to ‘Origin and evolution of the nervous system’

In 1665, Robert Hooke demonstrated in Micrographia the power of the microscope and comparative observations, one of which revealed similarities between the arthropod and vertebrate eyes. Utilizing comparative observations, Saint-Hilaire in 1822 was the first to propose that the ventral nervous system of arthropods corresponds to the dorsal nervous system of vertebrates. Since then, studies on the origin and evolution of the nervous system have become inseparable from studies about Metazoan origins and the origins of organ systems. The advent of genome sequence data and, in turn, phylogenomics and phylogenetics have refined cladistics and expanded our understanding of Metazoan phylogeny. However, the origin and evolution of the nervous system is still obscure and many questions and problems remain. A recurrent problem is whether and to what extent sequence data provide reliable guidance for comparisons across phyla. Are genetic data congruent with the geological fossil records? How can we reconcile evolved character loss with phylogenomic records? And how informative are genetic data in relation to the specification of nervous system morphologies? These provide some of the background and context for a Royal Society meeting to discuss new data and concepts that might achieve insights into the origin and evolution of brains and nervous systems.     

Phylogenetic models and model selection for noncoding DNA

Awareness of the complex structure and evolutionary dynamics of noncoding DNA has improved both noncoding sequence alignment and the use of microstructural changes as characters in phylogenetic analysis. The next step is to consider improvements in the use and selection of phylogenetic models for noncoding sequence data. Models of character evolution are central to phylogeny estimation, but the use of an inadequate model can mislead topology selection and branch length estimations. This is particularly likely when sequence divergence is either limited (nearly invariable, as in population-level or species-level studies) or extreme (nearly saturated, as in deep-level studies that focus on conserved secondary structures). Noncoding data sets are often at these extremes, and they can be particularly awkward for model definition and model selection. This paper introduces the goals of model use in phylogenetics and identifies ten issues that arise from the application of models to noncoding sequence data. It is concluded that most of these issues derive from small data set sizes, very low or very high sequence variability, limitations of current phylogenetic models, and possibly character definition and nonindependence. Recommendations are made that should help to improve alignment, character quality, model selection, and phylogeny estimation based on noncoding sequence data.     

Codon usage patterns in cytochrome oxidase I across multiple insect orders

Synonymous codon usage bias is determined by a combination of mutational biases, selection at the level of translation, and genetic drift. In a study of mtDNA in insects, we analyzed patterns of codon usage across a phylogeny of 88 insect species spanning 12 orders. We employed a likelihood-based method for estimating levels of codon bias and determining major codon preference that removes the possible effects of genome nucleotide composition bias. Three questions are addressed: (1) How variable are codon bias levels across the phylogeny? (2) How variable are major codon preferences? and (3) Are there phylogenetic constraints on codon bias or preference? There is high variation in the level of codon bias values among the 88 taxa, but few readily apparent phylogenetic patterns. Bias level shifts within the lepidopteran genus Papilio are most likely a result of population size effects. Shifts in major codon preference occur across the tree in all of the amino acids in which there was bias of some level. The vast majority of changes involves double-preference models, however, and shifts between single preferred codons within orders occur only 11 times. These shifts among codons in double-preference models are phylogenetically conservative.     

Using protein structural information in evolutionary inference: transmembrane proteins

We present a model of amino acid sequence evolution based on a hidden Markov model that extends to transmembrane proteins previous methods that incorporate protein structural information into phylogenetics. Our model aims to give a better understanding of processes of molecular evolution and to extract structural information from multiple alignments of transmembrane sequences and use such information to improve phylogenetic analyses. This should be of value in phylogenetic studies of transmembrane proteins: for example, mitochondrial proteins have acquired a special importance in phylogenetics and are mostly transmembrane proteins. The improvement in fit to example data sets of our new model relative to less complex models of amino acid sequence evolution is statistically tested. To further illustrate the potential utility of our method, phylogeny estimation is performed on primate CCR5 receptor sequences, sequences of l and m subunits of the light reaction center in purple bacteria, guinea pig sequences with respect to lagomorph and rodent sequences of calcitonin receptor and K-substance receptor, and cetacean sequences of cytochrome b.     

Genome‐wide survey of nuclear protein‐coding markers for beetle phylogenetics and their application in resolving both deep and shallow‐level divergences

Beetles (Coleoptera) are the most diverse and species‐rich insect group, representing an impressive explosive radiation in the evolutionary history of insects, and their evolutionary relationships are often difficult to resolve. The amount of ‘traditional markers’ (e.g. mitochondrial genes and nuclear rDNAs) for beetle phylogenetics is small, and these markers often lack sufficient signals in resolving relationships for such a rapidly radiating lineage. Here, based on the available genome data of beetles and other related insect species, we performed a genome‐wide survey to search nuclear protein‐coding (NPC) genes suitable for research on beetle phylogenetics. As a result, we identified 1470 candidate loci, which provided a valuable data resource to the beetle evolutionary research community for NPC marker development. We randomly chose 180 candidate loci from the database to design primers and successfully developed 95 NPC markers which can be PCR amplified from standard genomic DNA extracts. These new nuclear markers are universally applicable across Coleoptera, with an average amplification success rate of 90%. To test the phylogenetic utility, we used them to investigate the backbone phylogeny of Coleoptera (18 families sampled) and the family Coccinellidae (39 species sampled). Both phylogenies are well resolved (average bootstrap support >95%), showing that our markers can be used to address phylogenetic questions of various evolutionary depth (from species level to family level). In general, the newly developed nuclear markers are much easier to use and more phylogenetically informative than the ‘traditional markers’, and show great potential to expedite resolution of many parts in the Beetle Tree of Life.     

Fifteen compelling open questions in plant cell biology

As scientists, we are at least as excited about the open questions—the things we do not know—as the discoveries. Here, we asked 15 experts to describe the most compelling open questions in plant cell biology. These are their questions: How are organelle identity, domains, and boundaries maintained under the continuous flux of vesicle trafficking and membrane remodeling? Is the plant cortical microtubule cytoskeleton a mechanosensory apparatus? How are the cellular pathways of cell wall synthesis, assembly, modification, and integrity sensing linked in plants? Why do plasmodesmata open and close? Is there retrograde signaling from vacuoles to the nucleus? How do root cells accommodate fungal endosymbionts? What is the role of cell edges in plant morphogenesis? How is the cell division site determined? What are the emergent effects of polyploidy on the biology of the cell, and how are any such “rules” conditioned by cell type? Can mechanical forces trigger new cell fates in plants? How does a single differentiated somatic cell reprogram and gain pluripotency? How does polarity develop de-novo in isolated plant cells? What is the spectrum of cellular functions for membraneless organelles and intrinsically disordered proteins? How do plants deal with internal noise? How does order emerge in cells and propagate to organs and organisms from complex dynamical processes? We hope you find the discussions of these questions thought provoking and inspiring.

We asked 15 experts to address what they consider to be the most compelling open questions in plant cell biology and these are their questions.     

Community Phylogenetics: Assessing Tree Reconstruction Methods and the Utility of DNA Barcodes

Studies examining phylogenetic community structure have become increasingly prevalent, yet little attention has been given to the influence of the input phylogeny on metrics that describe phylogenetic patterns of co-occurrence. Here, we examine the influence of branch length, tree reconstruction method, and amount of sequence data on measures of phylogenetic community structure, as well as the phylogenetic signal (Pagel’s λ) in morphological traits, using Trichoptera larval communities from Churchill, Manitoba, Canada. We find that model-based tree reconstruction methods and the use of a backbone family-level phylogeny improve estimations of phylogenetic community structure. In addition, trees built using the barcode region of cytochrome c oxidase subunit I (COI) alone accurately predict metrics of phylogenetic community structure obtained from a multi-gene phylogeny. Input tree did not alter overall conclusions drawn for phylogenetic signal, as significant phylogenetic structure was detected in two body size traits across input trees. As the discipline of community phylogenetics continues to expand, it is important to investigate the best approaches to accurately estimate patterns. Our results suggest that emerging large datasets of DNA barcode sequences provide a vast resource for studying the structure of biological communities.     

Inferring ancestral sequences in taxon-rich phylogenies

Statistical consistency in phylogenetics has traditionally referred to the accuracy of estimating phylogenetic parameters for a fixed number of species as we increase the number of characters. However, it is also useful to consider a dual type of statistical consistency where we increase the number of species, rather than characters. This raises some basic questions: what can we learn about the evolutionary process as we increase the number of species? In particular, does having more species allow us to infer the ancestral state of characters accurately? This question is particularly important when sequence evolution varies in a complex way from character to character, as methods applicable for i.i.d. models may no longer be valid. In this paper, we assemble a collection of results to analyse various approaches for inferring ancestral information with increasing accuracy as the number of taxa increases.     

A likelihood framework for inferring the evolution of geographic range on phylogenetic trees

Abstract At a time when historical biogeography appears to be again expanding its scope after a period of focusing primarily on discerning area relationships using cladograms, new inference methods are needed to bring more kinds of data to bear on questions about the geographic history of lineages. Here we describe a likelihood framework for inferring the evolution of geographic range on phylogenies that models lineage dispersal and local extinction in a set of discrete areas as stochastic events in continuous time. Unlike existing methods for estimating ancestral areas, such as dispersal‐vicariance analysis, this approach incorporates information on the timing of both lineage divergences and the availability of connections between areas (dispersal routes). Monte Carlo methods are used to estimate branch‐specific transition probabilities for geographic ranges, enabling the likelihood of the data (observed species distributions) to be evaluated for a given phylogeny and parameterized paleogeographic model. We demonstrate how the method can be used to address two biogeographic questions: What were the ancestral geographic ranges on a phylogenetic tree? How were those ancestral ranges affected by speciation and inherited by the daughter lineages at cladogenesis events? For illustration we use hypothetical examples and an analysis of a Northern Hemisphere plant clade (Cercis), comparing and contrasting inferences to those obtained from dispersal‐vicariance analysis. Although the particular model we implement is somewhat simplistic, the framework itself is flexible and could readily be modified to incorporate additional sources of information and also be extended to address other aspects of historical biogeography.     

Poor taxon sampling, poor character sampling, and non-repeatable analyses of a contrived dataset do not provide a more credible estimate of insect phylogeny: a reply to Kjer

The wealth of data available for phylogenetic analysis of the insect orders, from both morphological and molecular sources, is steadily increasing. However, controversy exists among the methodologies one can use to reconstruct ordinal relationships. Recently, Kjer (2004 ) presented an analysis of insect ordinal relationships based exclusively on a single source of information: 18S rDNA sequence data. Kjer claims that his analysis resulted in a more “credible” phylogeny for the insect orders and strongly criticized our previous phylogenetic results. However, Kjer only used a subset of the data that are currently available for insect ordinal phylogeny, misrepresented our analyses, and omitted other analyses we have published on insect ordinal phylogeny. In our estimation, Kjer did a poor job of representing the current state of affairs in insect ordinal phylogenetics. Furthermore, we examine a number of analytical issues that are relevant not only for insect phylogeny, but systematics as a science, such as: repeatability and objectivity, locating alignment boundaries, secondary structure, goodness of fit measure, epistemological coherence, practicality and homology. © The Willi Hennig Society 2005.     

A user's guide to animal welfare science

Here, I provide a guide for those new to the burgeoning field of animal welfare science as to what this comprehensive, relatively young discipline is all about. Drawing on all branches of biology, including behavioural ecology and neuroscience, the science of animal welfare asks three big questions: Are animals conscious? How can we assess good and bad welfare in animals? How can we use science to improve animal welfare in practice? I also provide guidelines for an evidence-based approach to welfare issues for policy makers and other users of animal welfare research.     

Saturation and base composition bias explain phylogenomic conflict in Plasmodium

Despite recent genome-based advances in understanding Plasmodium molecular evolution and its relationship to disease mechanisms and potential drug development, the phylogenetics of the group is currently limited to single-gene analyses. Here we develop and analyze a set of N100 putative orthologous genes derived from genome comparisons. We aimed to minimize systematic errors that arise when reconstructing the Plasmodium phylogeny with a genome-scale data set by evaluating the congruence of different genes, optimality criteria, and models of sequence evolution with previous studies encompassing fewer characters and more species. Saturation in substitutions and bias in base frequencies at third-codon positions characterized most Plasmodium genes. Molecular evolution models that partitioned rates of change by codon position were best at accounting for these sequence characteristics, as were analyses of amino acid alignments. These methods also ameliorated, but did not entirely avoid, the impact of reduced taxon sampling on phylogeny. The use of these models and expanded taxon sampling are necessary to maximize detection of multiple substitutions, overcome compositional biases, and, ultimately, resolve with confidence the phylogeny of Plasmodium.     

Does phylogenetic distance aid in detecting environmental gradients related to species composition?

Questions: How should we evaluate the success of new distance measures combining community abundance and phylogenetic information? How do we interpret ordinations using these metrics? Methods: We generated synthetic data along a known environmental gradient with two hypothetical underlying phylogenetic structures: niche phylogenetically conserved or dispersed along a gradient. We also examined tree species composition associated with gradients in elevation and longitude in Oregon, USA. NMS ordinations of plots in species space from phylogenetic (PD) and Sørensen distance (SD) matrices allowed comparison of the use of PD in different scenarios. Results: PD caused plots to cluster based on the clades that they contained, reducing stress with the synthetic data but not with the real example. Phylogenetic distance highlighted clades related to gradients when these were associated. When phylogeny was not conserved along a gradient, that gradient was less strong. Regardless of phylogenetic conservation, NMS using SD consistently extracted the strongest gradients in species composition. Conclusions: The success of PD should be evaluated on how well it extracts gradients in species composition and allows community ecologists to determine which gradients are partially explained by phylogeny and not based on its ability to reduce ordination stress. PD ordinations can help community ecologists interpret niche conservation but may obscure gradients related to species composition when niches are not conserved along the gradient of interest at the scale of the study.     

Probabilism and Phylogenetic Inference

The maximum likelihood approach to phylogenetics rests on frequency probability theory. This stands in stark contrast to the logical probability of corroboration-based cladistic parsimony. History is particular and cannot be described in terms of universal statements about abstract generalities, the task of the historical sciences being one of explanation, not prediction. Thus, frequency probability methods of estimation are inappropriate for making historical inferences. Maximum likelihood estimation procedures are deconstructed from numerous perspectives in spite of their supposed impressive technicalities. Charges of parsimony's inconsistency are rendered mute, because its justification lies elsewhere, yet maximum likelihood is still subject to Wald's dilemma if realism is of any interest. Although all epistemologies make assumptions, the models employed by maximum likelihood are problematic and deterministic, as opposed to the unproblematic background knowledge characteristic of cladistics. Apart from issues of logical and sampling dependencies, the requirements of frequency probability theory are non-trivial and the maximum likelihood estimation of phylogeny can neither escape, nor satisfy the tenets of calculus independence (e.g. i.i.d.) inherent in the multiplicative relations of the method. If phylogeneticists are to maintain a rational foundation for their epistemology, neo-justificationist appeals to some metaphysical truth must be abandoned in favour of the realism of sophisticated falsification.     

From Haeckel’s phylogenetics and Hennig’s cladistics to the method of maximum likelihood: Advantages and limitations of modern and traditional approaches to phylogeny reconstruction

The maximum likelihood and Bayesian methods are based on parametric models of character evolution. They assume that if we know these models as well as distribution of character states in studied organisms, we can infer the probability of different phylogenetic trajectories leading from ancestors to modern forms. In fact, these methods are mathematized variants of the traditional Haeckel’s approach to phylogeny reconstruction. In contrast to classical and parsimonious cladistics, they infer phylogenies without such limitations as necessity of strictly dichotomous evolution, exclusion of plesiomorphic characters, and acceptance of only holophyletic taxa. They assume that evolution may be reticulated, any homologous characters—both apomorphic and plesiomorphic—can be used for inferring phylogenies, and interpretation of evolutionary lineages as taxa is optional. Thus, the main difference between the new and more traditional approaches to phylogeny reconstruction lies not in the characters used (molecular or morphological) but in the methodology of analysis. It must be admitted that a revolution began in phylogenetics 10–20 years ago. However, the fundamental changes in phylogenetics have been carried out so calmly and neatly by the people who started this revolution, that many systematists still do not realize their importance.     

Problematica old and new

Problematica are taxa that defy robust phylogenetic placement. Traditionally the term was restricted to fossil forms, but it is clear that extant taxa may be just as difficult to place, whether using morphological or molecular (nucleotide, gene or genomic) markers for phylogeny reconstruction. We discuss the kinds and causes of Problematica within the Metazoa, as well as criteria for their recognition and possible solutions. The inclusive set of Problematica changes depending upon the nature and quality of (homologous) data available, the methods of phylogeny reconstruction and the sister taxa inferred by their placement or displacement. We address Problematica in the context of pre-cladistic phylogenetics, numerical morphological cladistics and molecular phylogenetics, and focus on general biological and methodological implications of Problematica, rather than presenting a review of individual taxa. Rather than excluding Problematica from phylogeny reconstruction, as has often been preferred, we conclude that the study of Problematica is crucial for both the resolution of metazoan phylogeny and the proper inference of body plan evolution.     

The use of DNA barcodes to estimate phylogenetic diversity in forest communities of southern China

To elucidate potential ecological and evolutionary processes associated with the assembly of plant communities, there is now widespread use of estimates of phylogenetic diversity that are based on a variety of DNA barcode regions and phylogenetic construction methods. However, relatively few studies consider how estimates of phylogenetic diversity may be influenced by single DNA barcodes incorporated into a sequence matrix (conservative regions vs. hypervariable regions) and the use of a backbone family‐level phylogeny. Here, we use general linear mixed‐effects models to examine the influence of different combinations of core DNA barcodes (rbcL, matK, ITS, and ITS2) and phylogeny construction methods on a series of estimates of community phylogenetic diversity for two subtropical forest plots in Guangdong, southern China. We ask: (a) What are the relative influences of single DNA barcodes on estimates phylogenetic diversity metrics? and (b) What is the effect of using a backbone family‐level phylogeny to estimate topology‐based phylogenetic diversity metrics? The combination of more than one barcode (i.e., rbcL + matK + ITS) and the use of a backbone family‐level phylogeny provided the most parsimonious explanation of variation in estimates of phylogenetic diversity. The use of a backbone family‐level phylogeny showed a stronger effect on phylogenetic diversity metrics that are based on tree topology compared to those that are based on branch lengths. In addition, the variation in the estimates of phylogenetic diversity that was explained by the top‐rank models ranged from 0.1% to 31% and was dependent on the type of phylogenetic community structure metric. Our study underscores the importance of incorporating a multilocus DNA barcode and the use of a backbone family‐level phylogeny to infer phylogenetic diversity, where the type of DNA barcode employed and the phylogenetic construction method used can serve as a significant source of variation in estimates of phylogenetic community structure.     

Explaining forest productivity using tree functional traits and phylogenetic information: two sides of the same coin over evolutionary scale?

Given evidences that diverse ecosystems provide more services than depauperate ones, much attention has now turned toward finding meaningful and operational diversity indices. We ask two questions: (1) Does phylogenetic diversity contain additional information not explained by functional traits? And (2) What are the strength and nature of the correlation between phylogeny and functional traits according to the evolutionary scale considered? We used data from permanent forest plots of northeastern Canada for which these links have been demonstrated and important functional traits identified. We show that the nature of the relationship between traits and phylogeny varies dramatically among traits, but also according to the evolutionary distance considered. The demonstration that different characters show phylogenetic autocorrelation at different evolutionary depths suggests that phylogenetic content of traits may be too crude to determine whether phylogenies contain relevant information. However, our study provides support for the use of phylogenies to assess ecosystem functioning when key functional traits are unavailable. We also highlight a potentially important contribution of phylogenetics for conservation and the study of the impact of biodiversity loss on ecosystem functioning and the provision of services, given the accumulating evidence that mechanisms promoting diversity effects shift over time to involve different traits.     

Using landscape history to predict biodiversity patterns in fragmented landscapes

Landscape ecology plays a vital role in understanding the impacts of land‐use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape ‘terrageny’, which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over‐estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human‐modified landscapes.