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We present the fifth edition of the TimeTree of Life resource (TToL5), a product of the timetree of life project that aims to synthesize published molecular timetrees and make evolutionary knowledge easily accessible to all. Using the TToL5 web portal, users can retrieve published studies and divergence times between species, the timeline of a species' evolution beginning with the origin of life, and the timetree for a given evolutionary group at the desired taxonomic rank. TToL5 contains divergence time information on 137,306 species, 41% more than the previous edition. The TToL5 web interface is now ADA-compliant and mobile-friendly, a result of comprehensive source code refactoring. TToL5 also offers programmatic access to species divergence times and timelines through an application programming interface, which is accessible at timetree.temple.edu/api. TToL5 is publicly available at timetree.org.
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Felsenstein's bootstrap approach is widely used to assess confidence in species relationships inferred from multiple sequence alignments. It resamples sites randomly with replacement to build alignment replicates of the same size as the original alignment and infers a phylogeny from each replicate dataset. The proportion of phylogenies recovering the same grouping of species is its bootstrap confidence limit. But, standard bootstrap imposes a high computational burden in applications involving long sequence alignments. Here, we introduce the bag of little bootstraps approach to phylogenetics, bootstrapping only a few little samples, each containing a small subset of sites. We report that the median bagging of bootstrap confidence limits from little samples produces confidence in inferred species relationships similar to standard bootstrap but in a fraction of computational time and memory. Therefore, the little bootstraps approach can potentially enhance the rigor, efficiency, and parallelization of big data phylogenomic analyses.
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Simultaneous molecular dating of population and species divergences is essential in many biological investigations, including phylogeography, phylodynamics and species delimitation studies. In these investigations, multiple sequence alignments consist of both intra- and interspecies samples (mixed samples). As a result, the phylogenetic trees contain interspecies, interpopulation and within-population divergences. Bayesian relaxed clock methods are often employed in these analyses, but they assume the same tree prior for both inter- and intraspecies branching processes and require specification of a clock model for branch rates (independent vs. autocorrelated rates models). We evaluated the impact of a single tree prior on Bayesian divergence time estimates by analysing computer-simulated data sets. We also examined the effect of the assumption of independence of evolutionary rate variation among branches when the branch rates are autocorrelated. Bayesian approach with coalescent tree priors generally produced excellent molecular dates and highest posterior densities with high coverage probabilities. We also evaluated the performance of a non-Bayesian method, RelTime, which does not require the specification of a tree prior or a clock model. RelTime's performance was similar to that of the Bayesian approach, suggesting that it is also suitable to analyse data sets containing both populations and species variation when its computational efficiency is needed.
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Evolução Molecular , Mamíferos , Modelos Genéticos , Filogenia , Animais , Teorema de Bayes , Simulação por Computador , Reprodutibilidade dos TestesRESUMO
We report the likely most recent common ancestor of SARS-CoV-2 - the coronavirus that causes COVID-19. This progenitor SARS-CoV-2 genome was recovered through a novel application and advancement of computational methods initially developed to reconstruct the mutational history of tumor cells in a patient. The progenitor differs from the earliest coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the USA harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide as soon as weeks after the first reported cases of COVID-19. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains, which have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic. There have been multiple replacements of predominant coronavirus strains in Europe and Asia and the continued presence of multiple high-frequency strains in Asia and North America. We provide a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).
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From the first day of 2021, all manuscripts published in the journal Molecular Biology and Evolution (MBE) will be freely accessible online without a subscription. This exciting change will make all the MBE content available to all readers immediately upon publication.
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BACKGROUND: Prostate cancer (PC) risk increases with African ancestry and a history of sexually transmitted infections (STIs). Also, single-nucleotide polymorphisms (SNPs) in toll-like receptor (TLR) genes influence PC risk. This pilot study explores interactions between STIs and TLR-related SNPs in relation to PC risk among Jamaican men. METHODS: This case-control study evaluates two TLR related SNPs in 356 Jamaican men (194 controls and 162 cases) with or without history of STIs using stepwise penalized logistic regression in multivariable analyses. RESULTS: Age (odds ratio [OR] = 1.08; 95% confidence interval [CI]: 1.04-1>.12; p < .001) and IRF3_rs2304206 GG genotype (OR = 0.47; 95% CI: 0.29-0<.78; p = .003) modulated PC risk in people with history of STIs. In the population with no history of STIs, resulting interactions between risk factors did not survive correction for multiple hypothesis testing. CONCLUSION: Overall, an interaction between the IFR3_rs2304206 variant and a history of exposure to STIs leads to greater decrease of PC risk than the presence of polymorphic genotype alone. These findings are suggestive and require further validation. Identification of gene variants along with detection of lifestyle behaviors may contribute to identification of men at a greater risk of PC development in the population.
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Predisposição Genética para Doença , Genótipo , Polimorfismo de Nucleotídeo Único , Neoplasias da Próstata/etiologia , Infecções Sexualmente Transmissíveis/complicações , Receptores Toll-Like/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Casos e Controles , Humanos , Jamaica , Masculino , Pessoa de Meia-Idade , Projetos Piloto , Neoplasias da Próstata/genética , Neoplasias da Próstata/patologia , Medição de Risco , Fatores de RiscoRESUMO
The conventional wisdom in molecular evolution is to apply parameter-rich models of nucleotide and amino acid substitutions for estimating divergence times. However, the actual extent of the difference between time estimates produced by highly complex models compared with those from simple models is yet to be quantified for contemporary data sets that frequently contain sequences from many species and genes. In a reanalysis of many large multispecies alignments from diverse groups of taxa, we found that the use of the simplest models can produce divergence time estimates and credibility intervals similar to those obtained from the complex models applied in the original studies. This result is surprising because the use of simple models underestimates sequence divergence for all the data sets analyzed. We found three fundamental reasons for the observed robustness of time estimates to model complexity in many practical data sets. First, the estimates of branch lengths and node-to-tip distances under the simplest model show an approximately linear relationship with those produced by using the most complex models applied on data sets with many sequences. Second, relaxed clock methods automatically adjust rates on branches that experience considerable underestimation of sequence divergences, resulting in time estimates that are similar to those from complex models. And, third, the inclusion of even a few good calibrations in an analysis can reduce the difference in time estimates from simple and complex models. The robustness of time estimates to model complexity in these empirical data analyses is encouraging, because all phylogenomics studies use statistical models that are oversimplified descriptions of actual evolutionary substitution processes.
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Evolução Molecular , Genômica/métodos , Modelos Genéticos , Filogenia , Plantas/genéticaRESUMO
The Molecular Evolutionary Genetics Analysis (MEGA) software enables comparative analysis of molecular sequences in phylogenetics and evolutionary medicine. Here, we introduce the macOS version of the MEGA software. This new version eliminates the need for virtualization and emulation programs previously required to use MEGA on Apple computers. MEGA for macOS utilizes memory and computing resources efficiently for conducting evolutionary analyses on macOS. It has a native Cocoa graphical user interface that is programmed to provide a consistent user experience across macOS, Windows, and Linux. MEGA for macOS is available from www.megasoftware.net free of charge.