Additive Uncorrelated Relaxed Clock Models for the Dating of Genomic Epidemiology Phylogenies.
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ABSTRACT:
SUBMITTER: Didelot X
PROVIDER: S-EPMC8480190 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Rapid relaxed-clock dating methods are frequently applied to analyze phylogenomic data sets containing hundreds to thousands of sequences because of their accuracy and computational efficiency. However, the relative performance of different rapid dating methods is yet to be compared on the same data sets, and, thus, the power and pitfalls of selecting among these approaches remain unclear. We compared the accuracy, bias, and coverage probabilities of RelTime, treePL, and least-squares dating time estimates by applying them to analyze computer-simulated data sets in which evolutionary rates varied extensively among branches in the phylogeny. RelTime estimates were consistently more accurate than the other two, particularly when evolutionary rates were autocorrelated or shifted convergently among lineages. The 95% confidence intervals (CIs) around RelTime dates showed appropriate coverage probabilities (95% on average), but other methods produced rather low coverage probabilities because of overly narrow CIs of time estimates. Overall, RelTime appears to be a more efficient method for estimating divergence times for large phylogenies.
| S-EPMC8633771 | biostudies-literature
Project description:We present molecular dating analyses for land plants that incorporate 33 fossil calibrations, permit rates of molecular evolution to be uncorrelated across the tree, and take into account uncertainties in phylogenetic relationships and the fossil record. We attached a prior probability to each fossil-based minimum age, and explored the effects of relying on the first appearance of tricolpate pollen grains as a lower bound for the age of eudicots. Many of our divergence-time estimates for major clades coincide well with both the known fossil record and with previous estimates. However, our estimates for the origin of crown-clade angiosperms, which center on the Late Triassic, are considerably older than the unequivocal fossil record of flowering plants or than the molecular dates presented in recent studies. Nevertheless, we argue that our older estimates should be taken into account in studying the causes and consequences of the angiosperm radiation in relation to other major events, including the diversification of holometabolous insects. Although the methods used here do help to correct for lineage-specific heterogeneity in rates of molecular evolution (associated, for example, with evolutionary shifts in life history), we remain concerned that some such effects (e.g., the early radiation of herbaceous clades within angiosperms) may still be biasing our inferences.
| S-EPMC2851901 | biostudies-other
Project description: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).
| S-EPMC7880504 | biostudies-literature
Project description:In phylogenetics, the unrooted model of phylogeny and the strict molecular clock model are two extremes of a continuum. Despite their dominance in phylogenetic inference, it is evident that both are biologically unrealistic and that the real evolutionary process lies between these two extremes. Fortunately, intermediate models employing relaxed molecular clocks have been described. These models open the gate to a new field of "relaxed phylogenetics." Here we introduce a new approach to performing relaxed phylogenetic analysis. We describe how it can be used to estimate phylogenies and divergence times in the face of uncertainty in evolutionary rates and calibration times. Our approach also provides a means for measuring the clocklikeness of datasets and comparing this measure between different genes and phylogenies. We find no significant rate autocorrelation among branches in three large datasets, suggesting that autocorrelated models are not necessarily suitable for these data. In addition, we place these datasets on the continuum of clocklikeness between a strict molecular clock and the alternative unrooted extreme. Finally, we present analyses of 102 bacterial, 106 yeast, 61 plant, 99 metazoan, and 500 primate alignments. From these we conclude that our method is phylogenetically more accurate and precise than the traditional unrooted model while adding the ability to infer a timescale to evolution.
| S-EPMC1395354 | biostudies-literature
Project description:Phylogenetic trees inferred from sequence data often have branch lengths measured in the expected number of substitutions and therefore, do not have divergence times estimated. These trees give an incomplete view of evolutionary histories since many applications of phylogenies require time trees. Many methods have been developed to convert the inferred branch lengths from substitution unit to time unit using calibration points, but none is universally accepted as they are challenged in both scalability and accuracy under complex models. Here, we introduce a new method that formulates dating as a nonconvex optimization problem where the variance of log-transformed rate multipliers is minimized across the tree. On simulated and real data, we show that our method, wLogDate, is often more accurate than alternatives and is more robust to various model assumptions.
| S-EPMC7947844 | biostudies-literature
Project description:BackgroundBecause rates of evolution and species divergence times cannot be estimated directly from molecular data, all current dating methods require that specific assumptions be made before inferring any divergence time. These assumptions typically bear either on rates of molecular evolution (molecular clock hypothesis, local clocks models) or on both rates and times (penalized likelihood, Bayesian methods). However, most of these assumptions can affect estimated dates, oftentimes because they underestimate large amounts of rate change.Principal findingsA significant modification to a recently proposed ad hoc rate-smoothing algorithm is described, in which local molecular clocks are automatically placed on a phylogeny. This modification makes use of hybrid approaches that borrow from recent theoretical developments in microarray data analysis. An ad hoc integration of phylogenetic uncertainty under these local clock models is also described. The performance and accuracy of the new methods are evaluated by reanalyzing three published data sets.ConclusionsIt is shown that the new maximum likelihood hybrid methods can perform better than penalized likelihood and almost as well as uncorrelated Bayesian models. However, the new methods still tend to underestimate the actual amount of rate change. This work demonstrates the difficulty of estimating divergence times using local molecular clocks.
| S-EPMC1964517 | biostudies-literature
Project description:Over recent years, several alternative relaxed clock models have been proposed in the context of Bayesian dating. These models fall in two distinct categories: uncorrelated and autocorrelated across branches. The choice between these two classes of relaxed clocks is still an open question. More fundamentally, the true process of rate variation may have both long-term trends and short-term fluctuations, suggesting that more sophisticated clock models unfolding over multiple time scales should ultimately be developed. Here, a mixed relaxed clock model is introduced, which can be mechanistically interpreted as a rate variation process undergoing short-term fluctuations on the top of Brownian long-term trends. Statistically, this mixed clock represents an alternative solution to the problem of choosing between autocorrelated and uncorrelated relaxed clocks, by proposing instead to combine their respective merits. Fitting this model on a dataset of 105 placental mammals, using both node-dating and tip-dating approaches, suggests that the two pure clocks, Brownian and white noise, are rejected in favour of a mixed model with approximately equal contributions for its uncorrelated and autocorrelated components. The tip-dating analysis is particularly sensitive to the choice of the relaxed clock model. In this context, the classical pure Brownian relaxed clock appears to be overly rigid, leading to biases in divergence time estimation. By contrast, the use of a mixed clock leads to more recent and more reasonable estimates for the crown ages of placental orders and superorders. Altogether, the mixed clock introduced here represents a first step towards empirically more adequate models of the patterns of rate variation across phylogenetic trees.This article is part of the themed issue 'Dating species divergences using rocks and clocks'.
| S-EPMC4920333 | biostudies-literature
Project description:Evolutionary timescales can be inferred from molecular sequence data using a Bayesian phylogenetic approach. In these methods, the molecular clock is often calibrated using fossil data. The uncertainty in these fossil calibrations is important because it determines the limiting posterior distribution for divergence-time estimates as the sequence length tends to infinity. Here, we investigate how the accuracy and precision of Bayesian divergence-time estimates improve with the increased clock-partitioning of genome-scale data into clock-subsets. We focus on a data set comprising plastome-scale sequences of 52 angiosperm taxa. There was little difference among the Bayesian date estimates whether we chose clock-subsets based on patterns of among-lineage rate heterogeneity or relative rates across genes, or by random assignment. Increasing the degree of clock-partitioning usually led to an improvement in the precision of divergence-time estimates, but this increase was asymptotic to a limit presumably imposed by fossil calibrations. Our clock-partitioning approaches yielded highly precise age estimates for several key nodes in the angiosperm phylogeny. For example, when partitioning the data into 20 clock-subsets based on patterns of among-lineage rate heterogeneity, we inferred crown angiosperms to have arisen 198-178?Ma. This demonstrates that judicious clock-partitioning can improve the precision of molecular dating based on phylogenomic data, but the meaning of this increased precision should be considered critically.
| S-EPMC5647803 | biostudies-other
Project description:Shiga toxin-producing Escherichia coli (STEC) are a leading cause of foodborne outbreaks of human disease, but they reside harmlessly as an asymptomatic commensal in the ruminant gut. STEC serogroup O145 are difficult to isolate as routine diagnostic methods are unable to distinguish non-O157 serogroups due to their heterogeneous metabolic characteristics, resulting in under-reporting which is likely to conceal their true prevalence. In light of these deficiencies, the purpose of this study was a twofold approach to investigate enhanced STEC O145 diagnostic culture-based methods: firstly, to use a genomic epidemiology approach to understand the genetic diversity and population structure of serogroup O145 at both a local (New Zealand) (n = 47) and global scale (n = 75) and, secondly, to identify metabolic characteristics that will help the development of a differential media for this serogroup. Analysis of a subset of E. coli serogroup O145 strains demonstrated considerable diversity in carbon utilisation, which varied in association with eae subtype and sequence type. Several carbon substrates, such as D-serine and D-malic acid, were utilised by the majority of serogroup O145 strains, which, when coupled with current molecular and culture-based methods, could aid in the identification of presumptive E. coli serogroup O145 isolates. These carbon substrates warrant subsequent testing with additional serogroup O145 strains and non-O145 strains. Serogroup O145 strains displayed extensive genetic heterogeneity that was correlated with sequence type and eae subtype, suggesting these genetic markers are good indicators for distinct E. coli phylogenetic lineages. Pangenome analysis identified a core of 3,036 genes and an open pangenome of >14,000 genes, which is consistent with the identification of distinct phylogenetic lineages. Overall, this study highlighted the phenotypic and genotypic heterogeneity within E. coli serogroup O145, suggesting that the development of a differential media targeting this serogroup will be challenging.
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Project description:The additive genomic variance in linear models with random marker effects can be defined as a random variable that is in accordance with classical quantitative genetics theory. Common approaches to estimate the genomic variance in random-effects linear models based on genomic marker data can be regarded as estimating the unconditional (or prior) expectation of this random additive genomic variance, and result in a negligence of the contribution of linkage disequilibrium (LD). We introduce a novel best prediction (BP) approach for the additive genomic variance in both the current and the base population in the framework of genomic prediction using the genomic best linear unbiased prediction (gBLUP) method. The resulting best predictor is the conditional (or posterior) expectation of the additive genomic variance when using the additional information given by the phenotypic data, and is structurally in accordance with the genomic equivalent of the classical additive genetic variance in random-effects models. In particular, the best predictor includes the contribution of (marker) LD to the additive genomic variance and possibly fully eliminates the missing contribution of LD that is caused by the assumptions of statistical frameworks such as the random-effects model. We derive an empirical best predictor (eBP) and compare its performance with common approaches to estimate the additive genomic variance in random-effects models on commonly used genomic datasets.
| S-EPMC6781909 | biostudies-other