Dating Microbial Evolution with MCMCtree.

This protocol explains how to use the program MCMCtree to estimate divergence times in microbial phylogenies. The main advantage of MCMCtree is the implementation of an approximation to the molecular data likelihood that dramatically speeds up computation during Bayesian MCMC sampling of divergence times and evolutionary rates. The approximation allows the analysis of large phylogenies with hundreds of taxa and molecular alignments with thousands or millions of sites. Two examples are used to illustrate Bayesian clock dating with MCMCtree. The first is a phylogeny of (mostly) microbial eukaryotes and prokaryotes encompassing the major groups of life on Earth, and for which fossil information, to calibrate the nodes of the phylogeny, is available. The second is a phylogeny of influenza viruses with known sampling times. An overview of Bayesian MCMC sampling is given as well as practical advice on issues such as construction of the time and rate prior and assessment of convergence of MCMC chains. Strategies for estimating times in microbial phylogenies for which neither fossil information nor sampling times are known are discussed.

Receptor deorphanization in an echinoderm reveals kisspeptin evolution and relationship with SALMFamide neuropeptides.

BACKGROUND: Kisspeptins are neuropeptides that regulate reproductive maturation in mammals via G-protein-coupled receptor-mediated stimulation of gonadotropin-releasing hormone secretion from the hypothalamus. Phylogenetic analysis of kisspeptin-type receptors indicates that this neuropeptide signaling system originated in a common ancestor of the Bilateria, but little is known about kisspeptin signaling in invertebrates. RESULTS: Contrasting with the occurrence of a single kisspeptin receptor in mammalian species, here, we report the discovery of an expanded family of eleven kisspeptin-type receptors in a deuterostome invertebrate - the starfish Asterias rubens (phylum Echinodermata). Furthermore, neuropeptides derived from four precursor proteins were identified as ligands for six of these receptors. One or more kisspeptin-like neuropeptides derived from two precursor proteins (ArKPP1, ArKPP2) act as ligands for four A. rubens kisspeptin-type receptors (ArKPR1,3,8,9). Furthermore, a family of neuropeptides that act as muscle relaxants in echinoderms (SALMFamides) are ligands for two A. rubens kisspeptin-type receptors (ArKPR6,7). The SALMFamide neuropeptide S1 (or ArS1.4) and a 'cocktail' of the seven neuropeptides derived from the S1 precursor protein (ArS1.1-ArS1.7) act as ligands for ArKPR7. The SALMFamide neuropeptide S2 (or ArS2.3) and a 'cocktail' of the eight neuropeptides derived from the S2 precursor protein (ArS2.1-ArS2.8) act as ligands for ArKPR6. CONCLUSIONS: Our findings reveal a remarkable diversity of neuropeptides that act as ligands for kisspeptin-type receptors in starfish and provide important new insights into the evolution of kisspeptin signaling. Furthermore, the discovery of the hitherto unknown relationship of kisspeptins with SALMFamides, neuropeptides that were discovered in starfish prior to the identification of kisspeptins in mammals, presents a radical change in perspective for research on kisspeptin signaling.

A species-level timeline of mammal evolution integrating phylogenomic data.

High-throughput sequencing projects generate genome-scale sequence data for species-level phylogenies1-3. However, state-of-the-art Bayesian methods for inferring timetrees are computationally limited to small datasets and cannot exploit the growing number of available genomes4. In the case of mammals, molecular-clock analyses of limited datasets have produced conflicting estimates of clade ages with large uncertainties5,6, and thus the timescale of placental mammal evolution remains contentious7-10. Here we develop a Bayesian molecular-clock dating approach to estimate a timetree of 4,705 mammal species integrating information from 72 mammal genomes. We show that increasingly larger phylogenomic datasets produce diversification time estimates with progressively smaller uncertainties, facilitating precise tests of macroevolutionary hypotheses. For example, we confidently reject an explosive model of placental mammal origination in the Palaeogene8 and show that crown Placentalia originated in the Late Cretaceous with unambiguous ordinal diversification in the Palaeocene/Eocene. Our Bayesian methodology facilitates analysis of complete genomes and thousands of species within an integrated framework, making it possible to address hitherto intractable research questions on species diversifications. This approach can be used to address other contentious cases of animal and plant diversifications that require analysis of species-level phylogenomic datasets.

A Mutation-Selection Model of Protein Evolution under Persistent Positive Selection.

We use first principles of population genetics to model the evolution of proteins under persistent positive selection (PPS). PPS may occur when organisms are subjected to persistent environmental change, during adaptive radiations, or in host-pathogen interactions. Our mutation-selection model indicates protein evolution under PPS is an irreversible Markov process, and thus proteins under PPS show a strongly asymmetrical distribution of selection coefficients among amino acid substitutions. Our model shows the criteria ω>1 (where ω is the ratio of nonsynonymous over synonymous codon substitution rates) to detect positive selection is conservative and indeed arbitrary, because in real proteins many mutations are highly deleterious and are removed by selection even at positively selected sites. We use a penalized-likelihood implementation of the PPS model to successfully detect PPS in plant RuBisCO and influenza HA proteins. By directly estimating selection coefficients at protein sites, our inference procedure bypasses the need for using ω as a surrogate measure of selection and improves our ability to detect molecular adaptation in proteins.

Nectar-feeding bats and birds show parallel molecular adaptations in sugar metabolism enzymes.

In most vertebrates, the demand for glucose as the primary substrate for cellular respiration is met by the breakdown of complex carbohydrates, or energy is obtained by protein and lipid catabolism. In contrast, a few bat and bird species have convergently evolved to subsist on nectar, a sugar-rich mixture of glucose, fructose, and sucrose.1-4 How these nectar-feeders have adapted to cope with life-long high sugar intake while avoiding the onset of metabolic syndrome and diabetes5-7 is not understood. We analyzed gene sequences obtained from 127 taxa, including 22 nectar-feeding bat and bird genera that collectively encompass four independent origins of nectarivory. We show these divergent taxa have undergone pervasive molecular adaptation in sugar catabolism pathways, including parallel selection in key glycolytic and fructolytic enzymes. We also uncover convergent amino acid substitutions in the otherwise evolutionarily conserved aldolase B (ALDOB), which catalyzes rate-limiting steps in fructolysis and glycolysis, and the mitochondrial gatekeeper pyruvate dehydrogenase (PDH), which links glycolysis and the tricarboxylic acid cycle. Metabolomic profile and enzyme functional assays are consistent with increased respiratory flux in nectar-feeding bats and help explain how these taxa can both sustain hovering flight and efficiently clear simple sugars. Taken together, our results indicate that nectar-feeding bats and birds have undergone metabolic adaptations that have enabled them to exploit a unique energy-rich dietary niche among vertebrates.

Dietary Diversification and Specialization in Neotropical Bats Facilitated by Early Molecular Evolution.

Dietary adaptation is a major feature of phenotypic and ecological diversification, yet the genetic basis of dietary shifts is poorly understood. Among mammals, Neotropical leaf-nosed bats (family Phyllostomidae) show unmatched diversity in diet; from a putative insectivorous ancestor, phyllostomids have radiated to specialize on diverse food sources including blood, nectar, and fruit. To assess whether dietary diversification in this group was accompanied by molecular adaptations for changing metabolic demands, we sequenced 89 transcriptomes across 58 species and combined these with published data to compare ∼13,000 protein coding genes across 66 species. We tested for positive selection on focal lineages, including those inferred to have undergone dietary shifts. Unexpectedly, we found a broad signature of positive selection in the ancestral phyllostomid branch, spanning genes implicated in the metabolism of all major macronutrients, yet few positively selected genes at the inferred switch to plantivory. Branches corresponding to blood- and nectar-based diets showed selection in loci underpinning nitrogenous waste excretion and glycolysis, respectively. Intriguingly, patterns of selection in metabolism genes were mirrored by those in loci implicated in craniofacial remodeling, a trait previously linked to phyllostomid dietary specialization. Finally, we show that the null model of the widely-used branch-site test is likely to be misspecified, with the implication that the test is too conservative and probably under-reports true cases of positive selection. Our findings point to a complex picture of adaptive radiation, in which the evolution of new dietary specializations has been facilitated by early adaptations combined with the generation of new genetic variation.

Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur.

Mutations are the raw material on which evolution acts, and knowledge of their frequency and genomic distribution is crucial for understanding how evolution operates at both long and short timescales. At present, the rate and spectrum of de novo mutations have been directly characterized in relatively few lineages. Our study provides the first direct mutation-rate estimate for a strepsirrhine (i.e., the lemurs and lorises), which comprises nearly half of the primate clade. Using high-coverage linked-read sequencing for a focal quartet of gray mouse lemurs (Microcebus murinus), we estimated the mutation rate to be among the highest calculated for a mammal at 1.52 × 10-8 (95% credible interval: 1.28 × 10-8-1.78 × 10-8) mutations/site/generation. Further, we found an unexpectedly low count of paternal mutations, and only a modest overrepresentation of mutations at CpG sites. Despite the surprising nature of these results, we found both the rate and spectrum to be robust to the manipulation of a wide range of computational filtering criteria. We also sequenced a technical replicate to estimate a false-negative and false-positive rate for our data and show that any point estimate of a de novo mutation rate should be considered with a large degree of uncertainty. For validation, we conducted an independent analysis of context-dependent substitution types for gray mouse lemur and five additional primate species for which de novo mutation rates have also been estimated. These comparisons revealed general consistency of the mutation spectrum between the pedigree-based and the substitution-rate analyses for all species compared.

Dire wolves were the last of an ancient New World canid lineage.

Dire wolves are considered to be one of the most common and widespread large carnivores in Pleistocene America1, yet relatively little is known about their evolution or extinction. Here, to reconstruct the evolutionary history of dire wolves, we sequenced five genomes from sub-fossil remains dating from 13,000 to more than 50,000 years ago. Our results indicate that although they were similar morphologically to the extant grey wolf, dire wolves were a highly divergent lineage that split from living canids around 5.7 million years ago. In contrast to numerous examples of hybridization across Canidae2,3, there is no evidence for gene flow between dire wolves and either North American grey wolves or coyotes. This suggests that dire wolves evolved in isolation from the Pleistocene ancestors of these species. Our results also support an early New World origin of dire wolves, while the ancestors of grey wolves, coyotes and dholes evolved in Eurasia and colonized North America only relatively recently.

Molecular Clocks without Rocks: New Solutions for Old Problems.

Molecular data have been used to date species divergences ever since they were described as documents of evolutionary history in the 1960s. Yet, an inadequate fossil record and discordance between gene trees and species trees are persistently problematic. We examine how, by accommodating gene tree discordance and by scaling branch lengths to absolute time using mutation rate and generation time, multispecies coalescent (MSC) methods can potentially overcome these challenges. We find that time estimates can differ - in some cases, substantially - depending on whether MSC methods or traditional phylogenetic methods that apply concatenation are used, and whether the tree is calibrated with pedigree-based mutation rates or with fossils. We discuss the advantages and shortcomings of both approaches and provide practical guidance for data analysis when using these methods.

Phylogenomic Resolution of the Cetacean Tree of Life Using Target Sequence Capture.

The evolution of cetaceans, from their early transition to an aquatic lifestyle to their subsequent diversification, has been the subject of numerous studies. However, although the higher-level relationships among cetacean families have been largely settled, several aspects of the systematics within these groups remain unresolved. Problematic clades include the oceanic dolphins (37 spp.), which have experienced a recent rapid radiation, and the beaked whales (22 spp.), which have not been investigated in detail using nuclear loci. The combined application of high-throughput sequencing with techniques that target specific genomic sequences provide a powerful means of rapidly generating large volumes of orthologous sequence data for use in phylogenomic studies. To elucidate the phylogenetic relationships within the Cetacea, we combined sequence capture with Illumina sequencing to generate data for $\sim $3200 protein-coding genes for 68 cetacean species and their close relatives including the pygmy hippopotamus. By combining data from $>$38,000 exons with existing sequences from 11 cetaceans and seven outgroup taxa, we produced the first comprehensive comparative genomic data set for cetaceans, spanning 6,527,596 aligned base pairs (bp) and 89 taxa. Phylogenetic trees reconstructed with maximum likelihood and Bayesian inference of concatenated loci, as well as with coalescence analyses of individual gene trees, produced mostly concordant and well-supported trees. Our results completely resolve the relationships among beaked whales as well as the contentious relationships among oceanic dolphins, especially the problematic subfamily Delphinidae. We carried out Bayesian estimation of species divergence times using MCMCTree and compared our complete data set to a subset of clocklike genes. Analyses using the complete data set consistently showed less variance in divergence times than the reduced data set. In addition, integration of new fossils (e.g., Mystacodon selenensis) indicates that the diversification of Crown Cetacea began before the Late Eocene and the divergence of Crown Delphinidae as early as the Middle Miocene. [Cetaceans; phylogenomics; Delphinidae; Ziphiidae; dolphins; whales.].

Phylogenomics reveals the evolutionary timing and pattern of butterflies and moths.

Butterflies and moths (Lepidoptera) are one of the major superradiations of insects, comprising nearly 160,000 described extant species. As herbivores, pollinators, and prey, Lepidoptera play a fundamental role in almost every terrestrial ecosystem. Lepidoptera are also indicators of environmental change and serve as models for research on mimicry and genetics. They have been central to the development of coevolutionary hypotheses, such as butterflies with flowering plants and moths' evolutionary arms race with echolocating bats. However, these hypotheses have not been rigorously tested, because a robust lepidopteran phylogeny and timing of evolutionary novelties are lacking. To address these issues, we inferred a comprehensive phylogeny of Lepidoptera, using the largest dataset assembled for the order (2,098 orthologous protein-coding genes from transcriptomes of 186 species, representing nearly all superfamilies), and dated it with carefully evaluated synapomorphy-based fossils. The oldest members of the Lepidoptera crown group appeared in the Late Carboniferous (∼300 Ma) and fed on nonvascular land plants. Lepidoptera evolved the tube-like proboscis in the Middle Triassic (∼241 Ma), which allowed them to acquire nectar from flowering plants. This morphological innovation, along with other traits, likely promoted the extraordinary diversification of superfamily-level lepidopteran crown groups. The ancestor of butterflies was likely nocturnal, and our results indicate that butterflies became day-flying in the Late Cretaceous (∼98 Ma). Moth hearing organs arose multiple times before the evolutionary arms race between moths and bats, perhaps initially detecting a wide range of sound frequencies before being co-opted to specifically detect bat sonar. Our study provides an essential framework for future comparative studies on butterfly and moth evolution.

Bayesian Molecular Clock Dating Using Genome-Scale Datasets.

Bayesian methods for molecular clock dating of species divergences have been greatly developed during the past decade. Advantages of the methods include the use of relaxed-clock models to describe evolutionary rate variation in the branches of a phylogenetic tree and the use of flexible fossil calibration densities to describe the uncertainty in node ages. The advent of next-generation sequencing technologies has led to a flood of genome-scale datasets for organisms belonging to all domains in the tree of life. Thus, a new era has begun where dating the tree of life using genome-scale data is now within reach. In this protocol, we explain how to use the computer program MCMCTree to perform Bayesian inference of divergence times using genome-scale datasets. We use a ten-species primate phylogeny, with a molecular alignment of over three million base pairs, as an exemplar on how to carry out the analysis. We pay particular attention to how to set up the analysis and the priors and how to diagnose the MCMC algorithm used to obtain the posterior estimates of divergence times and evolutionary rates.

Bayesian Estimation of Species Divergence Times Using Correlated Quantitative Characters.

Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modeled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population "noise") and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analyzed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times.

Rapid morphological evolution in placental mammals post-dates the origin of the crown group.

Resolving the timing and pattern of early placental mammal evolution has been confounded by conflict among divergence date estimates from interpretation of the fossil record and from molecular-clock dating studies. Despite both fossil occurrences and molecular sequences favouring a Cretaceous origin for Placentalia, no unambiguous Cretaceous placental mammal has been discovered. Investigating the differing patterns of evolution in morphological and molecular data reveals a possible explanation for this conflict. Here, we quantified the relationship between morphological and molecular rates of evolution. We show that, independent of divergence dates, morphological rates of evolution were slow relative to molecular evolution during the initial divergence of Placentalia, but substantially increased during the origination of the extant orders. The rapid radiation of placentals into a highly morphologically disparate Cenozoic fauna is thus not associated with the origin of Placentalia, but post-dates superordinal origins. These findings predict that early members of major placental groups may not be easily distinguishable from one another or from stem eutherians on the basis of skeleto-dental morphology. This result supports a Late Cretaceous origin of crown placentals with an ordinal-level adaptive radiation in the early Paleocene, with the high relative rate permitting rapid anatomical change without requiring unreasonably fast molecular evolutionary rates. The lack of definitive Cretaceous placental mammals may be a result of morphological similarity among stem and early crown eutherians, providing an avenue for reconciling the fossil record with molecular divergence estimates for Placentalia.

Constraining uncertainty in the timescale of angiosperm evolution and the veracity of a Cretaceous Terrestrial Revolution.

Through the lens of the fossil record, angiosperm diversification precipitated a Cretaceous Terrestrial Revolution (KTR) in which pollinators, herbivores and predators underwent explosive co-diversification. Molecular dating studies imply that early angiosperm evolution is not documented in the fossil record. This mismatch remains controversial. We used a Bayesian molecular dating method to analyse a dataset of 83 genes from 644 taxa and 52 fossil calibrations to explore the effect of different interpretations of the fossil record, molecular clock models, data partitioning, among other factors, on angiosperm divergence time estimation. Controlling for different sources of uncertainty indicates that the timescale of angiosperm diversification is much less certain than previous molecular dating studies have suggested. Discord between molecular clock and purely fossil-based interpretations of angiosperm diversification may be a consequence of false precision on both sides. We reject a post-Jurassic origin of angiosperms, supporting the notion of a cryptic early history of angiosperms, but this history may be as much as 121 Myr, or as little as 23 Myr. These conclusions remain compatible with palaeobotanical evidence and a more general KTR in which major groups of angiosperms diverged later within the Cretaceous, alongside the diversification of pollinators, herbivores and their predators.

An Evaluation of Different Partitioning Strategies for Bayesian Estimation of Species Divergence Times.

The explosive growth of molecular sequence data has made it possible to estimate species divergence times under relaxed-clock models using genome-scale data sets with many gene loci. In order to improve both model realism and to best extract information about relative divergence times in the sequence data, it is important to account for the heterogeneity in the evolutionary process across genes or genomic regions. Partitioning is a commonly used approach to achieve those goals. We group sites that have similar evolutionary characteristics into the same partition and those with different characteristics into different partitions, and then use different models or different values of model parameters for different partitions to account for the among-partition heterogeneity. However, how to partition data in practical phylogenetic analysis, and in particular in relaxed-clock dating analysis, is more art than science. Here, we use computer simulation and real data analysis to study the impact of the partition scheme on divergence time estimation. The partition schemes had relatively minor effects on the accuracy of posterior time estimates when the prior assumptions were correct and the clock was not seriously violated, but showed large differences when the clock was seriously violated, when the fossil calibrations were in conflict or incorrect, or when the rate prior was mis-specified. Concatenation produced the widest posterior intervals with the least precision. Use of many partitions increased the precision, as predicted by the infinite-sites theory, but the posterior intervals might fail to include the true ages because of the conflicting fossil calibrations or mis-specified rate priors. We analyzed a data set of 78 plastid genes from 15 plant species with serious clock violation and showed that time estimates differed significantly among partition schemes, irrespective of the rate drift model used. Multiple and precise fossil calibrations reduced the differences among partition schemes and were important to improving the precision of divergence time estimates. While the use of many partitions is an important approach to reducing the uncertainty in posterior time estimates, we do not recommend its general use for the present, given the limitations of current models of rate drift for partitioned data and the challenges of interpreting the fossil evidence to construct accurate and informative calibrations.

Comparison of different strategies for using fossil calibrations to generate the time prior in Bayesian molecular clock dating.

Fossil calibrations are the utmost source of information for resolving the distances between molecular sequences into estimates of absolute times and absolute rates in molecular clock dating analysis. The quality of calibrations is thus expected to have a major impact on divergence time estimates even if a huge amount of molecular data is available. In Bayesian molecular clock dating, fossil calibration information is incorporated in the analysis through the prior on divergence times (the time prior). Here, we evaluate three strategies for converting fossil calibrations (in the form of minimum- and maximum-age bounds) into the prior on times, which differ according to whether they borrow information from the maximum age of ancestral nodes and minimum age of descendent nodes to form constraints for any given node on the phylogeny. We study a simple example that is analytically tractable, and analyze two real datasets (one of 10 primate species and another of 48 seed plant species) using three Bayesian dating programs: MCMCTree, MrBayes and BEAST2. We examine how different calibration strategies, the birth-death process, and automatic truncation (to enforce the constraint that ancestral nodes are older than descendent nodes) interact to determine the time prior. In general, truncation has a great impact on calibrations so that the effective priors on the calibration node ages after the truncation can be very different from the user-specified calibration densities. The different strategies for generating the effective prior also had considerable impact, leading to very different marginal effective priors. Arbitrary parameters used to implement minimum-bound calibrations were found to have a strong impact upon the prior and posterior of the divergence times. Our results highlight the importance of inspecting the joint time prior used by the dating program before any Bayesian dating analysis.

RelTime Rates Collapse to a Strict Clock When Estimating the Timeline of Animal Diversification.

Establishing an accurate timescale for the history of life is crucial to understand evolutionary processes. For this purpose, relaxed molecular clock models implemented in a Bayesian MCMC framework are generally used. However, these methods are time consuming. RelTime, a non-Bayesian method implementing a fast, ad hoc, algorithm for relative dating, was developed to overcome the computational inefficiencies of Bayesian software. RelTime was recently used to investigate the timing of origin of animals, yielding results consistent with early strict clock studies from the 1980s and 1990s, estimating metazoans to have a Mesoproterozoic origin-over a billion years ago. RelTime results are unexpected and disagree with the largest majority of modern, relaxed, Bayesian molecular clock analyses, which suggest animals originated in the Tonian-Cryogenian (less that 850 million years ago). Here, we demonstrate that RelTime-inferred divergence times for the origin of animals are spurious, a consequence of the inability of RelTime to relax the clock along the internal branches of the animal phylogeny. RelTime-inferred divergence times are comparable to strict-clock estimates because they are essentially inferred under a strict clock. Our results warn us of the danger of using ad hoc algorithms making implicit assumptions about rate changes along a tree. Our study roundly rejects a Mesoproterozoic origin of animals; metazoans emerged in the Tonian-Cryogenian, and diversified in the Ediacaran, in the immediate prelude to the routine fossilization of animals in the Cambrian associated with the emergence of readily preserved skeletons.

Finding Direction in the Search for Selection.

Tests for positive selection have mostly been developed to look for diversifying selection where change away from the current amino acid is often favorable. However, in many cases we are interested in directional selection where there is a shift toward specific amino acids, resulting in increased fitness in the species. Recently, a few methods have been developed to detect and characterize directional selection on a molecular level. Using the results of evolutionary simulations as well as HIV drug resistance data as models of directional selection, we compare two such methods with each other, as well as against a standard method for detecting diversifying selection. We find that the method to detect diversifying selection also detects directional selection under certain conditions. One method developed for detecting directional selection is powerful and accurate for a wide range of conditions, while the other can generate an excessive number of false positives.