Estimation of primate speciation dates using local molecular clocks

shinyTempSignal: an R shiny application for exploring temporal and other phylogenetic signals

The molecular clock model is fundamental for inferring species divergence times from molecular sequences. However, its direct application may introduce significant biases due to sequencing errors, recombination events, and inaccurately labeled sampling times. Improving accuracy necessitates rigorous quality control measures to identify and remove potentially erroneous sequences. Furthermore, while not all branches of a phylogenetic tree may exhibit a clear temporal signal, specific branches may still adhere to the assumptions, with varying evolutionary rates. Supporting a relaxed molecular clock model better aligns with the complexities of evolution. The root-to-tip regression method has been widely used to analyze the temporal signal in phylogenetic studies and can be generalized for detecting other phylogenetic signals. Despite its utility, there remains a lack of corresponding software implementations for broader applications. To address this gap, we present shinyTempSignal, an interactive web application implemented with the shiny framework, available as an R package and publicly accessible at https://github.com/YuLab-SMU/shinyTempSignal. This tool facilitates the analysis of temporal and other phylogenetic signals under both strict and relaxed models. By extending the root-to-tip regression method to diverse signals, shinyTempSignal helps in the detection of evolving features or traits, thereby laying the foundation for deeper insights and subsequent analyses.

Shrinkage-based Random Local Clocks with Scalable Inference

Molecular clock models undergird modern methods of divergence-time estimation. Local clock models propose that the rate of molecular evolution is constant within phylogenetic subtrees. Current local clock inference procedures exhibit one or more weaknesses, namely they achieve limited scalability to trees with large numbers of taxa, impose model misspecification, or require a priori knowledge of the existence and location of clocks. To overcome these challenges, we present an autocorrelated, Bayesian model of heritable clock rate evolution that leverages heavy-tailed priors with mean zero to shrink increments of change between branch-specific clocks. We further develop an efficient Hamiltonian Monte Carlo sampler that exploits closed form gradient computations to scale our model to large trees. Inference under our shrinkage clock exhibits a speed-up compared to the popular random local clock when estimating branch-specific clock rates on a variety of simulated datasets. This speed-up increases with the size of the problem. We further show our shrinkage clock recovers known local clocks within a rodent and mammalian phylogeny. Finally, in a problem that once appeared computationally impractical, we investigate the heritable clock structure of various surface glycoproteins of influenza A virus in the absence of prior knowledge about clock placement. We implement our shrinkage clock and make it publicly available in the BEAST software package.

Deciphering the mandibular shape variation in a group of Malagasy primates using Fourier outline analysis

OBJECTIVES

Among living Malagasy primates, the family Lemuridae has previously been recognized as presenting a higher mandibular morphological variation than other families. We conducted a quantitative analysis of mandibular size and shape within the five genera (Lemur, Eulemur, Hapalemur, Prolemur, and Varecia) associated with a set of covariables that could explain this variation.

MATERIALS AND METHODS

We used Fourier outline analysis on the left hemimandible of 182 specimens covering the Lemuridae family. The influence of the phylogeny but also seven covariables (genus, diet, sex, sexual behavior, mating system, ecoregion, and forest type) on mandibular variation was examined using multivariate statistics and model selection.

RESULTS

Our results indicate that the high level of morphological variation within the family, associated with a phylogenetic effect and differences in diet, is due to a strong distinction between the genera Prolemur and Hapalemur and the other genera of the family. A second analysis, correcting this strong effect, indicates that mandibular shape variation is influenced not only by the phylogeny and the diet but by a combination of all the covariables.

DISCUSSION

The analysis of morphological variation is a powerful tool with major applications, both for the estimation of biological diversity and for the understanding of the fundamental parameters of species' ecology. Our work indicates that, if mandibular shape variation is mainly driven by dietary adaptation, other variables describing ecology and habitat should be considered and taken into account for an integrative understanding of species resources and the establishment of conservation measures.

Detecting Episodic Evolution through Bayesian Inference of Molecular Clock Models

Molecular evolutionary rate variation is a key aspect of the evolution of many organisms that can be modeled using molecular clock models. For example, fixed local clocks revealed the role of episodic evolution in the emergence of SARS-CoV-2 variants of concern. Like all statistical models, however, the reliability of such inferences is contingent on an assessment of statistical evidence. We present a novel Bayesian phylogenetic approach for detecting episodic evolution. It consists of computing Bayes factors, as the ratio of posterior and prior odds of evolutionary rate increases, effectively quantifying support for the effect size. We conducted an extensive simulation study to illustrate the power of this method and benchmarked it to formal model comparison of a range of molecular clock models using (log) marginal likelihood estimation, and to inference under a random local clock model. Quantifying support for the effect size has higher sensitivity than formal model testing and is straight-forward to compute, because it only needs samples from the posterior and prior distribution. However, formal model testing has the advantage of accommodating a wide range molecular clock models. We also assessed the ability of an automated approach, known as the random local clock, where branches under episodic evolution may be detected without their a priori definition. In an empirical analysis of a data set of SARS-CoV-2 genomes, we find "very strong" evidence for episodic evolution. Our results provide guidelines and practical methods for Bayesian detection of episodic evolution, as well as avenues for further research into this phenomenon.

A timescale for placental mammal diversification based on Bayesian modeling of the fossil record

The timing of the placental mammal radiation has been the focus of debate over the efficacy of competing methods for establishing evolutionary timescales. Molecular clock analyses estimate that placental mammals originated before the Cretaceous-Paleogene (K-Pg) mass extinction, anywhere from the Late Cretaceous to the Jurassic. However, the absence of definitive fossils of placentals before the K-Pg boundary is compatible with a post-Cretaceous origin. Nevertheless, lineage divergence must occur before it can be manifest phenotypically in descendent lineages. This, combined with the non-uniformity of the rock and fossil records, requires the fossil record to be interpreted rather than read literally. To achieve this, we introduce an extended Bayesian Brownian bridge model that estimates the age of origination and, where applicable, extinction through a probabilistic interpretation of the fossil record. The model estimates the origination of placentals in the Late Cretaceous, with ordinal crown groups originating at or after the K-Pg boundary. The results reduce the plausible interval for placental mammal origination to the younger range of molecular clock estimates. Our findings support both the Long Fuse and Soft Explosive models of placental mammal diversification, indicating that the placentals originated shortly prior to the K-Pg mass extinction. The origination of many modern mammal lineages overlapped with and followed the K-Pg mass extinction.

Molecular timetrees using relaxed clocks and uncertain phylogenies

A common practice in molecular systematics is to infer phylogeny and then scale it to time by using a relaxed clock method and calibrations. This sequential analysis practice ignores the effect of phylogenetic uncertainty on divergence time estimates and their confidence/credibility intervals. An alternative is to infer phylogeny and times jointly to incorporate phylogenetic errors into molecular dating. We compared the performance of these two alternatives in reconstructing evolutionary timetrees using computer-simulated and empirical datasets. We found sequential and joint analyses to produce similar divergence times and phylogenetic relationships, except for some nodes in particular cases. The joint inference performed better when the phylogeny was not well resolved, situations in which the joint inference should be preferred. However, joint inference can be infeasible for large datasets because available Bayesian methods are computationally burdensome. We present an alternative approach for joint inference that combines the bag of little bootstraps, maximum likelihood, and RelTime approaches for simultaneously inferring evolutionary relationships, divergence times, and confidence intervals, incorporating phylogeny uncertainty. The new method alleviates the high computational burden imposed by Bayesian methods while achieving a similar result.

A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India

BACKGROUND

Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data.

METHODS

A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5).

RESULTS

The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM.

CONCLUSIONS

The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.

The dawn of relaxed phylogenetics

Tracing the history of evolution across time is a primary goal of evolutionary biology. The 2006 publication of a landmark study on relaxed phylogenetics in PLOS Biology enabled biologists to shed light on evolution's tempo and shaped the future of evolutionary studies.

Consideration of genetic variation and evolutionary history in future conservation of Indian one-horned rhinoceros (Rhinoceros unicornis)

Background

The extant members of the Asian rhinos have experienced severe population and range declines since Pleistocene through a combination of natural and anthropogenic factors. The one-horned rhino is the only Asian species recovered from such conditions but most of the extant populations are reaching carrying capacity. India currently harbours ~ 83% of the global wild one-horned rhino populations distributed across seven protected areas. Recent assessments recommend reintroduction-based conservation approaches for the species, and implementation of such efforts would greatly benefit from detailed genetic assessments and evolutionary history of these populations. Using mitochondrial data, we investigated the phylogeography, divergence and demographic history of one-horned rhinos across its Indian range.

Results

We report the first complete mitogenome from all the extant Indian wild one-horned rhino populations (n = 16 individuals). Further, we identified all polymorphic sites and assessed rhino phylogeography (2531 bp mtDNA, n = 111 individuals) across India. Results showed 30 haplotypes distributed as three distinct genetic clades (F_st value 0.68–1) corresponding to the states of Assam (n = 28 haplotypes), West Bengal and Uttar Pradesh (both monomorphic). The reintroduced population of Uttar Pradesh showed maternal signatures of Chitwan National Park, Nepal. Mitochondrial phylogenomics suggests one-horned rhino diverged from its recent common ancestors ~ 950 Kya and different populations (Assam, West Bengal and Uttar Pradesh/Nepal) coalesce at ~ 190–50 Kya, corroborating with the paleobiogeography history of the Indian subcontinent. Further, the demography analyses indicated historical decline in female effective population size ~ 300–200 Kya followed by increasing trends during ~ 110–60 Kya.

Conclusion

The phylogeography and phylogenomic outcomes suggest recognition of three ‘Evolutionary Significant Units (ESUs)’ in Indian rhino. With ongoing genetic isolation of the current populations, future management efforts should focus on identifying genetically variable founder animals and consider periodic supplementation events while planning future rhino reintroduction programs in India. Such well-informed, multidisciplinary approach will be the only way to ensure evolutionary, ecological and demographic stability of the species across its range.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-022-02045-2.

The evolution of primate malaria parasites: A study on the origin and diversification of Plasmodium in lemurs

Among the primate malaria parasites, those found in lemurs have been neglected. Here, six Plasmodium lineages were detected in 169 lemurs. Nearly complete mitochondrial genomes (mtDNA, ≈6Kb) and apicoplast loci (≈6Kb) were obtained from these parasites and other Haemosporida species. Plasmodium spp. in lemurs are a diverse clade that shares a common ancestor with other primate parasites from continental Africa. Time-trees for the mtDNA were estimated under different scenarios, and the origin of the lemur clade coincides with the proposed time of their host species' most recent common ancestor (Lemuridae-Indriidae). A time tree with fewer taxa was estimated with mtDNA + Apicoplast loci. Those time estimates overlapped but were younger and had narrower credibility intervals than those from mtDNA alone. Importantly, the mtDNA + Apicoplast estimates that the clade including the most lethal malaria parasite in humans, Plasmodium falciparum, may have originated with Homininae (African apes). Finally, the phylogenetic congruence of the lemurs and their parasites was explored. A statistically significant scenario identified four cospeciation, two duplications, four transfer (host-switches), and zero loss events. Thus, the parasite species sampled in lemurs seem to be radiating with their hosts.

Investigating the reliability of molecular estimates of evolutionary time when substitution rates and speciation rates vary

Background

An accurate timescale of evolutionary history is essential to testing hypotheses about the influence of historical events and processes, and the timescale for evolution is increasingly derived from analysis of DNA sequences. But variation in the rate of molecular evolution complicates the inference of time from DNA. Evidence is growing for numerous factors, such as life history and habitat, that are linked both to the molecular processes of mutation and fixation and to rates of macroevolutionary diversification. However, the most widely used methods rely on idealised models of rate variation, such as the uncorrelated and autocorrelated clocks, and molecular dating methods are rarely tested against complex models of rate change. One relationship that is not accounted for in molecular dating is the potential for interaction between molecular substitution rates and speciation, a relationship that has been supported by empirical studies in a growing number of taxa. If these relationships are as widespread as current evidence suggests, they may have a significant influence on molecular dates.

Results

We simulate phylogenies and molecular sequences under three different realistic rate variation models—one in which speciation rates and substitution rates both vary but are unlinked, one in which they covary continuously and one punctuated model in which molecular change is concentrated in speciation events, using empirical case studies to parameterise realistic simulations. We test three commonly used “relaxed clock” molecular dating methods against these realistic simulations to explore the degree of error in molecular dates under each model. We find average divergence time inference errors ranging from 12% of node age for the unlinked model when reconstructed under an uncorrelated rate prior using BEAST 2, to up to 91% when sequences evolved under the punctuated model are reconstructed under an autocorrelated prior using PAML.

Conclusions

We demonstrate the potential for substantial errors in molecular dates when both speciation rates and substitution rates vary between lineages. This study highlights the need for tests of molecular dating methods against realistic models of rate variation generated from empirical parameters and known relationships.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-022-02015-8.

Evolutionary Shift from Purifying Selection towards Divergent Selection of SARS-CoV2 Favors its Invasion into Multiple Human Organs

SARS-CoV2 virus is believed to be originated from a closely related bat Coronavirus RaTG13 lineage and uses its key entry-point residues in S1 protein to attach with human ACE2 receptor. SARS-CoV2 could enter human from bat with its poorly developed entry-point residues much before its known appearance with slower mutation rate or recently with efficiently developed entry-point residues with higher mutation rate or through an intermediate host. Temporal analysis of SARS-CoV2 genome shows that its nucleotide substitution rate is as low as 27nt/year with an evolutionary rate of 9×10⁻⁴/site/year, which is well within the range of other RNA virus (10⁻⁴ to 10⁻⁶/site/year). TMRCA of SARS-CoV2 from bat RaTG13 lineage appears to be in between 9 and 14 years. Evolution of a critical entry-point residue Y493Q needs two substitutions with an intermediate virus carrying Y493H (Y>H>Q) but has not been identified in known twenty-nine bat CoV virus. Genetic codon analysis indicates that SARS-CoV2 evolution during propagation in human disobeys neutral evolution as nonsynonymous mutations surpass synonymous mutations with the increase of ω (d_n/d_s). Taken together, genetic data suggests that SARS-CoV2 is originated long time back before its appearance in human in 2019. Increase of ω signifies that SARs-CoV2 evolution is approaching towards diversifying selection from purifying selection predictably for its infection power to evade multiple human organs.

Purifying Selection Determines the Short-Term Time Dependency of Evolutionary Rates in SARS-CoV-2 and pH1N1 Influenza

High-throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Crucially, there are an increasing number of molecular clock analyses using external evolutionary rate priors to infer evolutionary parameters. However, it is not clear which rate prior is appropriate for a given time window of observation due to the time-dependent nature of evolutionary rate estimates. Here, we characterize the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and data set sizes affect the accuracy of parameter estimation. We further use a generalized McDonald-Kreitman test to estimate the number of segregating nonneutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by ∼50% and ∼100%, respectively, over the course of 1 year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating nonneutral sites, demonstrating the role of purifying selection in generating the time dependency of evolutionary parameters during pandemics.

The emergence of SARS-CoV-2 variants of concern is driven by acceleration of the substitution rate

The ongoing SARS-CoV-2 pandemic has seen an unprecedented amount of rapidly generated genome data. These data have revealed the emergence of lineages with mutations associated to transmissibility and antigenicity, known as variants of concern (VOCs). A striking aspect of VOCs is that many of them involve an unusually large number of defining mutations. Current phylogenetic estimates of the substitution rate of SARS-CoV-2 suggest that its genome accrues around two mutations per month. However, VOCs can have 15 or more defining mutations and it is hypothesized that they emerged over the course of a few months, implying that they must have evolved faster for a period of time. We analyzed genome sequence data from the GISAID database to assess whether the emergence of VOCs can be attributed to changes in the substitution rate of the virus and whether this pattern can be detected at a phylogenetic level using genome data. We fit a range of molecular clock models and assessed their statistical performance. Our analyses indicate that the emergence of VOCs is driven by an episodic increase in the substitution rate of around 4-fold the background phylogenetic rate estimate that may have lasted several weeks or months. These results underscore the importance of monitoring the molecular evolution of the virus as a means of understanding the circumstances under which VOCs may emerge.

Accounting for the Biological Complexity of Pathogenic Fungi in Phylogenetic Dating

In the study of pathogen evolution, temporal dating of phylogenies provides information on when species and lineages may have diverged in the past. When combined with spatial and epidemiological data in phylodynamic models, these dated phylogenies can also help infer where and when outbreaks occurred, how pathogens may have spread to new geographic locations and/or niches, and how virulence or drug resistance has developed over time. Although widely applied to viruses and, increasingly, to bacterial pathogen outbreaks, phylogenetic dating is yet to be widely used in the study of pathogenic fungi. Fungi are complex organisms with several biological processes that could present issues with appropriate inference of phylogenies, clock rates, and divergence times, including high levels of recombination and slower mutation rates although with potentially high levels of mutation rate variation. Here, we discuss some of the key methodological challenges in accurate phylogeny reconstruction for fungi in the context of the temporal analyses conducted to date and make recommendations for future dating studies to aid development of a best practices roadmap in light of the increasing threat of fungal outbreaks and antifungal drug resistance worldwide.

Comparative genetics of scyphozoan species reveals the geological history and contemporary processes of the Mediterranean Sea

Jellyfish are useful genetic indicators for aquatic ecosystems as they have limited mobility and are highly exposed to the water column. By using comparative genomics and the molecular clock (timetree) of Rhizostoma pulmo, we revealed a divergence point between the East and West Mediterranean Sea (MS) populations that occurred 4.59 million years ago (mya). It is suggested that the two distinct ecological environments we know today were formed at this time. We propose that before this divergence, the highly mixed Atlantic and Mediterranean waters led to the wide dispersal of different species including R. pulmo. At 4.59 mya, the Western and Eastern MS were formed, indicating the possibility of a dramatic environmental event. For the first time, we find that for the jellyfish we examined, the division of the MS in east and west is not at the Straits of Sicily as generally thought, but significantly to the east. Using genomics of the Aurelia species, we examined contemporary anthropogenic impacts with a focus on migration of scyphozoa across the Suez Canal (Lessepsian migration). Aurelia sp. is among the few scyphozoa we find in both the MS and the Red Sea, but our DNA analysis revealed that the Red Sea Aurelia sp. did not migrate or mix with MS species. Phyllorhiza punctata results showed that this species was only recently introduced to the MS as a result of anthropogenic transportation activity, such as ballast water discharge, and revealed a migration vector from Australia to the MS. Our findings demonstrate that jellyfish genomes can be used as a phylogeographic molecular tool to trace past events across large temporal scales and reveal invasive species introduction due to human activity.

Complete chloroplast genome of the medicinal plant Evolvulus alsinoides: comparative analysis, identification of mutational hotspots and evolutionary dynamics with species of Solanales

Evolvulus alsinoides, belonging to the family Convolvulaceae, is an important medicinal plant widely used as a nootropic in the Indian traditional medicine system. In the genus Evolvulus, no research on the chloroplast genome has been published. Hence, the present study focuses on annotation, characterization, identification of mutational hotspots, and phylogenetic analysis in the complete chloroplast genome (cp) of E. alsinoides. Genome comparison and evolutionary dynamics were performed with the species of Solanales. The cp genome has 114 genes (80 protein-coding genes, 30 transfer RNA, and 4 ribosomal RNA genes) that were unique with total genome size of 157,015 bp. The cp genome possesses 69 RNA editing sites and 44 simple sequence repeats (SSRs). Predicted SSRs were randomly selected and validated experimentally. Six divergent hotspots such as trnQ-UUG, trnF-GAA, psaI, clpP, ndhF, and ycf1 were discovered from the cp genome. These microsatellites and divergent hot spot sequences of the Taxa 'Evolvulus' could be employed as molecular markers for species identification and genetic divergence investigations. The LSC area was found to be more conserved than the SSC and IR region in genome comparison. The IR contraction and expansion studies show that nine genes rpl2, rpl23, ycf1, ycf2, ycf1, ndhF, ndhA, matK, and psbK were present in the IR-LSC and IR-SSC boundaries of the cp genome. Fifty-four protein-coding genes in the cp genome were under negative selection pressure, indicating that they were well conserved and were undergoing purifying selection. The phylogenetic analysis reveals that E. alsinoides is closely related to the genus Cressa with some divergence from the genus Ipomoea. This is the first time the chloroplast genome of the genus Evolvulus has been published. The findings of the present study and chloroplast genome data could be a valuable resource for future studies in population genetics, genetic diversity, and evolutionary relationship of the family Convolvulaceae.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01051-w.

COVID-19 in Amazonas, Brazil, was driven by the persistence of endemic lineages and P.1 emergence

The northern state of Amazonas is among the regions in Brazil most heavily affected by the COVID-19 epidemic and has experienced two exponentially growing waves, in early and late 2020. Through a genomic epidemiology study based on 250 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from different Amazonas municipalities sampled between March 2020 and January 2021, we reveal that the first exponential growth phase was driven mostly by the dissemination of lineage B.1.195, which was gradually replaced by lineage B.1.1.28 between May and June 2020. The second wave coincides with the emergence of the variant of concern (VOC) P.1, which evolved from a local B.1.1.28 clade in late November 2020 and replaced the parental lineage in <2 months. Our findings support the conclusion that successive lineage replacements in Amazonas were driven by a complex combination of variable levels of social distancing measures and the emergence of a more transmissible VOC P.1 virus. These data provide insights to understanding the mechanisms underlying the COVID-19 epidemic waves and the risk of dissemination of SARS-CoV-2 VOC P.1 in Brazil and, potentially, worldwide.

Insights from macroevolutionary modelling and ancestral state reconstruction into the radiation and historical dietary ecology of Lemuriformes (Primates, Mammalia)

Background

Lemurs once rivalled the diversity of rest of the primate order despite thier confinement to the island of Madagascar. We test the adaptive radiation model of Malagasy lemur diversity using a novel combination of phylogenetic comparative methods and geometric methods for quantifying tooth shape.

Results

We apply macroevolutionary model fitting approaches and disparity through time analysis to dental topography metrics associated with dietary adaptation, an aspect of mammalian ecology which appears to be closely related to diversification in many clades. Metrics were also reconstructed at internal nodes of the lemur tree and these reconstructions were combined to generate dietary classification probabilities at internal nodes using discriminant function analysis. We used these reconstructions to calculate rates of transition toward folivory per million-year intervals. Finally, lower second molar shape was reconstructed at internal nodes by modelling the change in shape of 3D meshes using squared change parsimony along the branches of the lemur tree. Our analyses of dental topography metrics do not recover an early burst in rates of change or a pattern of early partitioning of subclade disparity. However, rates of change in adaptations for folivory were highest during the Oligocene, an interval of possible forest expansion on the island.

Conclusions

There was no clear phylogenetic signal of bursts of morphological evolution early in lemur history. Reconstruction of the molar morphologies corresponding to the ancestral nodes of the lemur tree suggest that this may have been driven by a shift toward defended plant resources, however. This suggests a response to the ecological opportunity offered by expanding forests, but not necessarily a classic adaptive radiation initiated by dispersal to Madagascar.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01793-x.

Assessing Uncertainty in the Rooting of the SARS-CoV-2 Phylogeny

The rooting of the SARS-CoV-2 phylogeny is important for understanding the origin and early spread of the virus. Previously published phylogenies have used different rootings that do not always provide consistent results. We investigate several different strategies for rooting the SARS-CoV-2 tree and provide measures of statistical uncertainty for all methods. We show that methods based on the molecular clock tend to place the root in the B clade, whereas methods based on outgroup rooting tend to place the root in the A clade. The results from the two approaches are statistically incompatible, possibly as a consequence of deviations from a molecular clock or excess back-mutations. We also show that none of the methods provide strong statistical support for the placement of the root in any particular edge of the tree. These results suggest that phylogenetic evidence alone is unlikely to identify the origin of the SARS-CoV-2 virus and we caution against strong inferences regarding the early spread of the virus based solely on such evidence.

Functional and Adaptive Significance of Promoter Mutations That Affect Divergent Myocardial Expressions of TRIM72 in Primates

Cis-regulatory elements play important roles in tissue-specific gene expression and in the evolution of various phenotypes, and mutations in promoters and enhancers may be responsible for adaptations of species to environments. TRIM72 is a highly conserved protein that is involved in energy metabolism. Its expression in the heart varies considerably in primates, with high levels of expression in Old World monkeys and near absence in hominids. Here, we combine phylogenetic hypothesis testing and experimentation to demonstrate that mutations in promoter are responsible for the differences among primate species in the heart-specific expression of TRIM72. Maximum likelihood estimates of lineage-specific substitution rates under local-clock models show that relative to the evolutionary rate of introns, the rate of promoter was accelerated by 78% in the common ancestor of Old World monkeys, suggesting a role for positive selection in the evolution of the TRIM72 promoter, possibly driven by selective pressure due to changes in cardiac physiology after species divergence. We demonstrate that mutations in the TRIM72 promoter account for the differential myocardial TRIM72 expression of the human and the rhesus macaque. Furthermore, changes in TRIM72 expression alter the expression of genes involved in oxidative phosphorylation, which in turn affects mitochondrial respiration and cardiac energy capacity. On a broader timescale, phylogenetic regression analyses of data from 29 mammalian species show that mammals with high cardiac expression of TRIM72 have high heart rate, suggesting that the expression changes of TRIM72 may be related to differences in the heart physiology of those species.

Adaptive dating and fast proposals: Revisiting the phylogenetic relaxed clock model

Relaxed clock models enable estimation of molecular substitution rates across lineages and are widely used in phylogenetics for dating evolutionary divergence times. Under the (uncorrelated) relaxed clock model, tree branches are associated with molecular substitution rates which are independently and identically distributed. In this article we delved into the internal complexities of the relaxed clock model in order to develop efficient MCMC operators for Bayesian phylogenetic inference. We compared three substitution rate parameterisations, introduced an adaptive operator which learns the weights of other operators during MCMC, and we explored how relaxed clock model estimation can benefit from two cutting-edge proposal kernels: the AVMVN and Bactrian kernels. This work has produced an operator scheme that is up to 65 times more efficient at exploring continuous relaxed clock parameters compared with previous setups, depending on the dataset. Finally, we explored variants of the standard narrow exchange operator which are specifically designed for the relaxed clock model. In the most extreme case, this new operator traversed tree space 40% more efficiently than narrow exchange. The methodologies introduced are adaptive and highly effective on short as well as long alignments. The results are available via the open source optimised relaxed clock (ORC) package for BEAST 2 under a GNU licence (https://github.com/jordandouglas/ORC).

Quantitative imagery analysis of spot patterns for the three-haplogroup classification of Triatoma dimidiata (Latreille, 1811) (Hemiptera: Reduviidae), an important vector of Chagas disease

Background

Spots and coloring patterns evaluated quantitatively can be used to discriminate and identify possible cryptic species. Species included in the Triatoma dimidiata (Reduviidae: Triatominae) complex are major disease vectors of Chagas disease. Phylogenetic studies have defined three haplogroups for Mexico and part of Central America. We report here our evaluation of the possibility of correctly discriminating these three T. dimidiata haplogroups using the pattern of the dorsal spots.

Methods

Digital images of the dorsal region of individuals from the three haplogroups were used. Image processing was used to extract primary and secondary variables characterizing the dorsal spot pattern. Statistical analysis of the variables included descriptive statistics, non-parametric Kruskal–Wallis tests, discriminant function analysis (DFA) and a neural classification network.

Results

A distinctive spot pattern was found for each haplogroup. The most differentiated pattern was presented by haplogroup 2, which was characterized by its notably larger central spots. Haplogroups 1 and 3 were more similar to each other, but there were consistent differences in the shape and orientation of the spots. Significant differences were found among haplogroups in almost all of the variables analyzed, with the largest differences seen for relative spot area, mean relative area of central spots, central spots Feret diameter and lateral spots Feret diameter and aspect ratio. Both the DFA and the neural network had correct discrimination values of > 90%.

Conclusions

Based on the results of this analysis, we conclude that the spot pattern can be reliably used to discriminate among the three haplogroups of T. dimidiata in Mexico, and possibly among triatomine species.

The Molecular Epidemiology and Transmission Dynamics of HIV Type 1 in a General Population Cohort in Uganda

The General Population Cohort (GPC) in south-western Uganda has a low HIV-1 incidence rate (<1%). However, new infections continue to emerge. In this research, 3796 HIV-1 pol sequences (GPC: n = 1418, non-GPC sites: n = 1223, Central Uganda: n = 1010 and Eastern Uganda: n = 145) generated between 2003–2015 were analysed using phylogenetic methods with demographic data to understand HIV-1 transmission in this cohort and inform the epidemic response. HIV-1 subtype A1 was the most prevalent strain in the GPC area (GPC and non-GPC sites) (39.8%), central (45.9%) and eastern (52.4%) Uganda. However, in the GPC alone, subtype D was the predominant subtype (39.1%). Of the 524 transmission clusters identified by Cluster Picker, all large clusters (≥5 individuals, n = 8) involved individuals from the GPC. In a multivariate analysis, clustering was strongly associated with being female (adjusted Odds Ratio, aOR = 1.28; 95% CI, 1.06–1.54), being >25 years (aOR = 1.52; 95% CI, 1.16–2.0) and being a resident in the GPC (aOR = 6.90; 95% CI, 5.22–9.21). Phylogeographic analysis showed significant viral dissemination (Bayes Factor test, BF > 3) from the GPC without significant viral introductions (BF < 3) into the GPC. The findings suggest localized HIV-1 transmission in the GPC. Intensifying geographically focused combination interventions in the GPC would contribute towards controlling HIV-1 infections.

Identification of African swine fever virus-like elements in the soft tick genome provides insights into the virus' evolution

BACKGROUND

African swine fever virus (ASFV) is a most devastating pathogen affecting swine. In 2007, ASFV was introduced into Eastern Europe where it continuously circulates and recently reached Western Europe and Asia, leading to a socio-economic crisis of global proportion. In Africa, where ASFV was first described in 1921, it is transmitted between warthogs and soft ticks of the genus Ornithodoros in a so-called sylvatic cycle. However, analyses into this virus' evolution are aggravated by the absence of any closely related viruses. Even ancient endogenous viral elements, viral sequences integrated into a host's genome many thousand years ago that have proven extremely valuable to analyse virus evolution, remain to be identified. Therefore, the evolution of ASFV, the only known DNA virus transmitted by arthropods, remains a mystery.

RESULTS

For the identification of ASFV-like sequences, we sequenced DNA from different recent Ornithodoros tick species, e.g. O. moubata and O. porcinus, O. moubata tick cells and also 100-year-old O. moubata and O. porcinus ticks using high-throughput sequencing. We used BLAST analyses for the identification of ASFV-like sequences and further analysed the data through phylogenetic reconstruction and molecular clock analyses. In addition, we performed tick infection experiments as well as additional small RNA sequencing of O. moubata and O. porcinus soft ticks.

CONCLUSION

Here, we show that soft ticks of the Ornithodoros moubata group, the natural arthropod vector of ASFV, harbour African swine fever virus-like integrated (ASFLI) elements corresponding to up to 10% (over 20 kb) of the ASFV genome. Through orthologous dating and molecular clock analyses, we provide data suggesting that integration could have occurred over 1.47 million years ago. Furthermore, we provide data showing ASFLI-element specific siRNA and piRNA in ticks and tick cells allowing for speculations on a possible role of ASFLI-elements in RNA interference-based protection against ASFV in ticks. We suggest that these elements, shaped through many years of co-evolution, could be part of an evolutionary virus-vector 'arms race', a finding that has not only high impact on our understanding of the co-evolution of viruses with their hosts but also provides a glimpse into the evolution of ASFV.

Gradients Do Grow on Trees: A Linear-Time O(N)-Dimensional Gradient for Statistical Phylogenetics

Calculation of the log-likelihood stands as the computational bottleneck for many statistical phylogenetic algorithms. Even worse is its gradient evaluation, often used to target regions of high probability. Order O(N)-dimensional gradient calculations based on the standard pruning algorithm require O(N2) operations, where N is the number of sampled molecular sequences. With the advent of high-throughput sequencing, recent phylogenetic studies have analyzed hundreds to thousands of sequences, with an apparent trend toward even larger data sets as a result of advancing technology. Such large-scale analyses challenge phylogenetic reconstruction by requiring inference on larger sets of process parameters to model the increasing data heterogeneity. To make these analyses tractable, we present a linear-time algorithm for O(N)-dimensional gradient evaluation and apply it to general continuous-time Markov processes of sequence substitution on a phylogenetic tree without a need to assume either stationarity or reversibility. We apply this approach to learn the branch-specific evolutionary rates of three pathogenic viruses: West Nile virus, Dengue virus, and Lassa virus. Our proposed algorithm significantly improves inference efficiency with a 126- to 234-fold increase in maximum-likelihood optimization and a 16- to 33-fold computational performance increase in a Bayesian framework.

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.

Measles virus and rinderpest virus divergence dated to the sixth century BCE

Many infectious diseases are thought to have emerged in humans after the Neolithic revolution. Although it is broadly accepted that this also applies to measles, the exact date of emergence for this disease is controversial. We sequenced the genome of a 1912 measles virus and used selection-aware molecular clock modeling to determine the divergence date of measles virus and rinderpest virus. This divergence date represents the earliest possible date for the establishment of measles in human populations. Our analyses show that the measles virus potentially arose as early as the sixth century BCE, possibly coinciding with the rise of large cities.

Optimizing taxon addition order and branch lengths in the construction of phylogenetic trees using maximum likelihood

Taxon addition order and branch lengths are optimized by genetic algorithms (GAS) within the fastDNAml algorithm for constructing phylogenetic trees of high likelihood. Results suggest that optimizing the order in which taxa are added improves the likelihood of the resulting trees.

Bayesian Inference of Evolutionary Histories under Time-Dependent Substitution Rates

Many factors complicate the estimation of time scales for phylogenetic histories, requiring increasingly complex evolutionary models and inference procedures. The widespread application of molecular clock dating has led to the insight that evolutionary rate estimates may vary with the time frame of measurement. This is particularly well established for rapidly evolving viruses that can accumulate sequence divergence over years or even months. However, this rapid evolution stands at odds with a relatively high degree of conservation of viruses or endogenous virus elements over much longer time scales. Building on recent insights into time-dependent evolutionary rates, we develop a formal and flexible Bayesian statistical inference approach that accommodates rate variation through time. We evaluate the novel molecular clock model on a foamy virus cospeciation history and a lentivirus evolutionary history and compare the performance to other molecular clock models. For both virus examples, we estimate a similarly strong time-dependent effect that implies rates varying over four orders of magnitude. The application of an analogous codon substitution model does not implicate long-term purifying selection as the cause of this effect. However, selection does appear to affect divergence time estimates for the less deep evolutionary history of the Ebolavirus genus. Finally, we explore the application of our approach on woolly mammoth ancient DNA data, which shows a much weaker, but still important, time-dependent rate effect that has a noticeable impact on node age estimates. Future developments aimed at incorporating more complex evolutionary processes will further add to the broad applicability of our approach.

Analysis of substitution rates showed that TLR5 is evolving at different rates among mammalian groups

Background

Toll-like receptors (TLRs) are the most widely studied innate immunity receptors responsible for recognition of invading pathogens. Among the TLR family, TLR5 is the only that senses and recognizes flagellin, the major protein of bacterial flagella. TLR5 has been reported to be under overall purifying selection in mammals, with a small proportion of codons under positive selection. However, the variation of substitution rates among major mammalian groups has been neglected. Here, we studied the evolution of TLR5 in mammals, comparing the substitution rates among groups.

Results

In this study we analysed the TLR5 substitution rates in Euungulata, Carnivora, Chiroptera, Primata, Rodentia and Lagomorpha, groups. For that, Tajima’s relative rate test, Bayesian inference of evolutionary rates and genetic distances were estimated with CODEML’s branch model and RELAX. The combined results showed that in the Lagomorpha, Rodentia, Carnivora and Chiroptera lineages TLR5 is evolving at a higher substitution rate. The RELAX analysis further suggested a significant relaxation of selective pressures for the Lagomorpha (K = 0.22, p < 0.01), Rodentia (K = 0.58, p < 0.01) and Chiroptera (K = 0.65, p < 0.01) lineages and for the Carnivora ancestral branches (K = 0.13, p < 0.01).

Conclusions

Our results show that the TLR5 substitution rate is not uniform among mammals. In fact, among the different mammal groups studied, the Lagomorpha, Rodentia, Carnivora and Chiroptera are evolving faster. This evolutionary pattern could be explained by 1) the acquisition of new functions of TLR5 in the groups with higher substitution rate, i.e. TLR5 neofunctionalization, 2) by the beginning of a TLR5 pseudogenization in these groups due to some redundancy between the TLRs genes, or 3) an arms race between TLR5 and species-specific parasites.

Inference of Ancient Whole-Genome Duplications and the Evolution of Gene Duplication and Loss Rates

Gene tree-species tree reconciliation methods have been employed for studying ancient whole-genome duplication (WGD) events across the eukaryotic tree of life. Most approaches have relied on using maximum likelihood trees and the maximum parsimony reconciliation thereof to count duplication events on specific branches of interest in a reference species tree. Such approaches do not account for uncertainty in the gene tree and reconciliation, or do so only heuristically. The effects of these simplifications on the inference of ancient WGDs are unclear. In particular, the effects of variation in gene duplication and loss rates across the species tree have not been considered. Here, we developed a full probabilistic approach for phylogenomic reconciliation-based WGD inference, accounting for both gene tree and reconciliation uncertainty using a method based on the principle of amalgamated likelihood estimation. The model and methods are implemented in a maximum likelihood and Bayesian setting and account for variation of duplication and loss rates across the species tree, using methods inspired by phylogenetic divergence time estimation. We applied our newly developed framework to ancient WGDs in land plants and investigated the effects of duplication and loss rate variation on reconciliation and gene count based assessment of these earlier proposed WGDs.

Divergence dating using mixed effects clock modelling: An application to HIV-1

The need to estimate divergence times in evolutionary histories in the presence of various sources of substitution rate variation has stimulated a rich development of relaxed molecular clock models. Viral evolutionary studies frequently adopt an uncorrelated clock model as a generic relaxed molecular clock process, but this may impose considerable estimation bias if discrete rate variation exists among clades or lineages. For HIV-1 group M, rate variation among subtypes has been shown to result in inconsistencies in time to the most recent common ancestor estimation. Although this calls into question the adequacy of available molecular dating methods, no solution to this problem has been offered so far. Here, we investigate the use of mixed effects molecular clock models, which combine both fixed and random effects in the evolutionary rate, to estimate divergence times. Using simulation, we demonstrate that this model outperforms existing molecular clock models in a Bayesian framework for estimating time-measured phylogenies in the presence of mixed sources of rate variation, while also maintaining good performance in simpler scenarios. By analysing a comprehensive HIV-1 group M complete genome data set we confirm considerable rate variation among subtypes that is not adequately modelled by uncorrelated relaxed clock models. The mixed effects clock model can accommodate this rate variation and results in a time to the most recent common ancestor of HIV-1 group M of 1920 (1915-25), which is only slightly earlier than the uncorrelated relaxed clock estimate for the same data set. The use of complete genome data appears to have a more profound impact than the molecular clock model because it reduces the credible intervals by 50 per cent relative to similar estimates based on short envelope gene sequences.

Reptile enamel matrix proteins: Selection, divergence, and functional constraint

The three major enamel matrix proteins (EMPs): amelogenin (AMEL), ameloblastin (AMBN), and enamelin (ENAM), are intrinsically linked to tooth development in tetrapods. However, reptiles and mammals exhibit significant differences in dental patterning and development, potentially affecting how EMPs evolve in each group. In most reptiles, teeth are replaced continuously throughout life, while mammals have reduced replacement to only one or two generations. Reptiles also form structurally simple, aprismatic enamel while mammalian enamel is composed of highly organized hydroxyapatite prisms. These differences, combined with reported low sequence homology in reptiles, led us to predict that reptiles may experience lower selection pressure on their EMPs as compared with mammals. However, we found that like mammals, reptile EMPs are under moderate purifying selection, with some differences evident between AMEL, AMBN, and ENAM. We also demonstrate that sequence homology in reptile EMPs is closely associated with divergence times, with more recently diverged lineages exhibiting high homology, along with strong phylogenetic signal. Lastly, despite sequence divergence, none of the reptile species in our study exhibited mutations consistent with diseases that cause degeneration of enamel (e.g. amelogenesis imperfecta). Despite short tooth retention time and simplicity in enamel structure, reptile EMPs still exhibit purifying selection required to form durable enamel.

A Not-So-Long Introduction to Computational Molecular Evolution

In this chapter, we give a not-so-long and self-contained introduction to computational molecular evolution. In particular, we present the emergence of the use of likelihood-based methods, review the standard DNA substitution models, and introduce how model choice operates. We also present recent developments in inferring absolute divergence times and rates on a phylogeny, before showing how state-of-the-art models take inspiration from diffusion theory to link population genetics, which traditionally focuses at a taxonomic level below that of the species, and molecular evolution. Although this is not a cookbook chapter, we try and point to popular programs and implementations along the way.

Global Rate Variation in Bony Vertebrates

This study investigated long-term substitution rate differences using three calibration points, divergences between lobe-finned vertebrates and ray-finned fish, between mammals and sauropsids, and between holosteans (gar and bowfin) and teleost fish with amino acid sequence data of 625 genes for 25 bony vertebrates. The result showed that the substitution rate was two to three times higher in the stem branches of lobe-finned vertebrates before the mammal-sauropsid divergence than in amniotes. The rate in the stem branch of ray-finned fish before the holostean-teleost fish divergence was also a few times higher than the holostean rate, whereas it was similar to or somewhat slower than the teleost fish rate. The phylogenetic relationship of coelacanth and lungfish with tetrapod was difficult to determine because of the short interval of the divergences. Considering the high rate in the stem branches, the divergences of coelacanth and lungfish from the stem branch were estimated as 408–427 Ma and 399–414 Ma, respectively, with the interval of 9–13 Myr. With the external calibration of the mammal-sauropsid split, the estimated times for ordinal divergences within eutherian mammals tend to be smaller than those in previous studies that used the calibration points within the lineage, with deeper divergences before the Cretaceous–Paleogene boundary and shallower ones after the boundary. In contrast the estimated times within birds were larger than those of previous studies, with the divergence between Galliformes and Anseriformes ∼80 Ma and that between Galloanserae and Neoaves 110 Ma.

The molecular clock and evolutionary timescales

The molecular clock provides a valuable means of estimating evolutionary timescales from genetic and biochemical data. Proposed in the early 1960s, it was first applied to amino acid sequences and immunological measures of genetic distances between species. The molecular clock has undergone considerable development over the years, and it retains profound relevance in the genomic era. In this mini-review, we describe the history of the molecular clock, its impact on evolutionary theory, the challenges brought by evidence of evolutionary rate variation among species, and the statistical models that have been developed to account for these heterogeneous rates of genetic change. We explain how the molecular clock can be used to infer rates and timescales of evolution, and we list some of the key findings that have been obtained when molecular clocks have been applied to genomic data. Despite the numerous challenges that it has faced over the decades, the molecular clock continues to offer the most effective method of resolving the details of the evolutionary timescale of the Tree of Life.

Bioinformatics and Translation Elongation

Codon usage depends on mutation bias, tRNA-mediated selection, and the need for high efficiency and accuracy in translation. One codon in a synonymous codon family is often strongly over-used, especially in highly expressed genes, which often leads to a high dN/dS ratio because dS is very small. Many different codon usage indices have been proposed to measure codon usage and codon adaptation. Sense codon could be misread by release factors and stop codons misread by tRNAs, which also contribute to codon usage in rare cases. This chapter outlines the conceptual framework on codon evolution, illustrates codon-specific and gene-specific codon usage indices, and presents their applications. A new index for codon adaptation that accounts for background mutation bias (Index of Translation Elongation) is presented and contrasted with codon adaptation index (CAI) which does not consider background mutation bias. They are used to re-analyze data from a recent paper claiming that translation elongation efficiency matters little in protein production. The reanalysis disproves the claim.

Local and relaxed clocks: the best of both worlds

Time-resolved phylogenetic methods use information about the time of sample collection to estimate the rate of evolution. Originally, the models used to estimate evolutionary rates were quite simple, assuming that all lineages evolve at the same rate, an assumption commonly known as the molecular clock. Richer and more complex models have since been introduced to capture the phenomenon of substitution rate variation among lineages. Two well known model extensions are the local clock, wherein all lineages in a clade share a common substitution rate, and the uncorrelated relaxed clock, wherein the substitution rate on each lineage is independent from other lineages while being constrained to fit some parametric distribution. We introduce a further model extension, called the flexible local clock (FLC), which provides a flexible framework to combine relaxed clock models with local clock models. We evaluate the flexible local clock on simulated and real datasets and show that it provides substantially improved fit to an influenza dataset. An implementation of the model is available for download from https://www.github.com/4ment/flc.

Using a multi-gene approach to infer the complicated phylogeny and evolutionary history of lorises (Order Primates: Family Lorisidae)

Extensive phylogenetic studies have found robust phylogenies are modeled by using a multi-gene approach and sampling from the majority of the taxa of interest. Yet, molecular studies focused on the lorises, a cryptic primate family, have often relied on one gene, or just mitochondrial DNA, and many were unable to include all four genera in the analyses, resulting in inconclusive phylogenies. Past phylogenetic loris studies resulted in lorises being monophyletic, paraphyletic, or an unresolvable trichotomy with the closely related galagos. The purpose of our study is to improve our understanding of loris phylogeny and evolutionary history by using a multi-gene approach. We used the mitochondrial genes cytochrome b, and cytochrome c oxidase subunit 1, along with a nuclear intron (recombination activating gene 2) and nuclear exon (the melanocortin 1 receptor). Maximum Likelihood and Bayesian phylogenetic analyses were conducted based on data from each locus, as well as on the concatenated sequences. The robust, concatenated results found lorises to be a monophyletic family (Lorisidae) (PP ≥ 0.99) with two distinct subfamilies: the African Perodictinae (PP ≥ 0.99) and the Asian Lorisinae (PP ≥ 0.99). Additionally, from these analyses all four genera were all recovered as monophyletic (PP ≥ 0.99). Some of our single-gene analyses recovered monophyly, but many had discordances, with some showing paraphyly or a deep-trichotomy. Bayesian partitioned analyses inferred the most recent common ancestors of lorises emerged ∼42 ± 6 million years ago (mya), the Asian Lorisinae separated ∼30 ± 9 mya, and Perodictinae arose ∼26 ± 10 mya. These times fit well with known historical tectonic shifts of the area, as well as with the sparse loris fossil record. Additionally, our results agree with previous multi-gene studies on Lorisidae which found lorises to be monophyletic and arising ∼40 mya (Perelman et al., 2011; Pozzi et al., 2014). By taking a multi-gene approach, we were able to recover a well-supported, monophyletic loris phylogeny and inferred the evolutionary history of this cryptic family.

TreeTime: Maximum-likelihood phylodynamic analysis

Mutations that accumulate in the genome of cells or viruses can be used to infer their evolutionary history. In the case of rapidly evolving organisms, genomes can reveal their detailed spatiotemporal spread. Such phylodynamic analyses are particularly useful to understand the epidemiology of rapidly evolving viral pathogens. As the number of genome sequences available for different pathogens has increased dramatically over the last years, phylodynamic analysis with traditional methods becomes challenging as these methods scale poorly with growing datasets. Here, we present TreeTime, a Python-based framework for phylodynamic analysis using an approximate Maximum Likelihood approach. TreeTime can estimate ancestral states, infer evolution models, reroot trees to maximize temporal signals, estimate molecular clock phylogenies and population size histories. The runtime of TreeTime scales linearly with dataset size.

Heterogeneous molecular processes among the causes of how sequence similarity scores can fail to recapitulate phylogeny

Sequence similarity tools like Basic Local Alignment Search Tool (BLAST) are essential components of many functional genetic, genomic, phylogenetic and bioinformatic studies. Many modern analysis pipelines use significant sequence similarity scores (p- or E-values) and the ranked order of BLAST matches to test a wide range of hypotheses concerning homology, orthology, the timing of de novo gene birth/death and gene family expansion/contraction. Despite significant contrary findings, many of these tests still implicitly assume that stronger or higher-ranked E-value scores imply closer phylogenetic relationships between sequences. Here, we demonstrate that even though a general relationship does exist between the phylogenetic distance of two sequences and their E-value, significant and misleading errors occur in both the completeness and the order of results under realistic evolutionary scenarios. These results provide additional details to past evidence showing that studies should avoid drawing direct inferences of evolutionary relatedness from measures of sequence similarity alone, and should instead, where possible, use more rigorous phylogeny-based methods.

Defining HIV-1 transmission clusters based on sequence data

Understanding HIV-1 transmission dynamics is relevant to both screening and intervention strategies of HIV-1 infection. Commonly, HIV-1 transmission chains are determined based on sequence similarity assessed either directly from a sequence alignment or by inferring a phylogenetic tree. This review is aimed at both nonexperts interested in understanding and interpreting studies of HIV-1 transmission, and experts interested in finding the most appropriate cluster definition for a specific dataset and research question. We start by introducing the concepts and methodologies of how HIV-1 transmission clusters usually have been defined. We then present the results of a systematic review of 105 HIV-1 molecular epidemiology studies summarizing the most common methods and definitions in the literature. Finally, we offer our perspectives on how HIV-1 transmission clusters can be defined and provide some guidance based on examples from real life datasets.

Implications of hepatitis C virus subtype 1a migration patterns for virus genetic sequencing policies in Italy

Background

In-depth phylogeographic analysis can reveal migration patterns relevant for public health planning. Here, as a model, we focused on the provenance, in the current Italian HCV subtype 1a epidemic, of the NS3 resistance-associated variant (RAV) Q80K, known to interfere with the action of NS3/4A protease inhibitor simeprevir. HCV1a migration patterns were analysed using Bayesian phylodynamic tools, capitalising on newly generated and publicly available time and geo-referenced NS3 encoding virus genetic sequence data.

Results

Our results showed that both immigration and local circulation fuel the current Italian HCV1a epidemic. The United States and European continental lineages dominate import into Italy, with the latter taking the lead from the 1970s onwards. Since similar migration patterns were found for Q80K and other lineages, no clear differentiation of the risk for failing simeprevir can be made between patients based on their migration and travel history. Importantly, since HCV only occasionally recombines, these results are readily transferable to the genetic sequencing policy concerning NS5A RAVs.

Conclusions

The patient migration and travel history cannot be used to target only part of the HCV1a infected population for drug resistance testing before start of antiviral therapy. Consequently, it may be cost-effective to expand genotyping efforts to all HCV1a infected patients eligible for simeprevir-based therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0913-3) contains supplementary material, which is available to authorized users.

Emerging Concepts of Data Integration in Pathogen Phylodynamics

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.