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Bouckaert, R.

Publications and source records attributed to Bouckaert, R..

At least 19 recordsLinked to original sources

DensiTree 3: Making Sense of Pairs of Sets of Trees

Motivation: Tree sets appear naturally when performing model based phylogenetic analyses. When tracking host-parasite co-evolution, testing sensitivity of different model assumptions, or even just checking convergence of individual runs of the same analysis, the question arises: are a given pair of tree sets the same? And if they are not the same, how do they differ? Results: We provide DensiTree 3, an interactive tool for inspecting pairs of sets of trees that allow visualising both tree sets using a single panel. Incorporation of CCDs provide better summary trees, taxon orderings and extra functionality like rogue detection, making it easier to interpret tree samples. Furthermore, a clade comparison graph allows inspection of differences in clade support and clade heights linked to the double-DensiTree panel. Together, these visualisations of tree sets make it easy to identify potential differences in the tree sets and interactively inspect these differences. Furthermore, recent advances in conditional clade distributions (CCDs) to represent tree distributions have been incorporated in DensiTree 3, and the most visible part of the user interface has been updated for a more modern look. Availability: DensiTree 3 is freely available from https://cs.auckland.ac.nz/~remco/DensiTree/. The program is licensed under GPL and source code is available via the link above.

bioinformatics↗

A first order approximation of a joint Potts and phylogenetic model

This study introduces a novel model that integrates the capacity of Potts models to capture structural dependencies with the computational efficiency afforded by Felsenstein's algorithm in phylogenetics. While the present work focuses on protein models, the PhyloPotts framework is equally applicable to alignments of discrete states, including RNA, DNA, and 3DI characters. Our findings indicate that, although phylogenetic estimates do not consistently exhibit reduced bias relative to standard models, the approach substantially enhances the accuracy of ancestral sequence reconstruction. The method is freely available via an open source implementation in the PhyloPotts package for BEAST 2 from https://github.com/rbouckaert/potts.

bioinformatics↗

A hierarchical clock-mixture model for Bayesian phylogenetic dating

Conditioning the inference of a Bayesian phylogenetic time tree on a single molecular clock model treats clock choice as fixed, even when support among plausible clock families is uncertain. When that assumption is wrong, estimated timescales and their uncertainty can be distorted. Existing practice usually addresses this by fitting strict, uncorrelated lognormal relaxed (UCLN), and autocorrelated clocks separately and comparing their marginal likelihoods, but this requires multiple computationally expensive model selection analyses. Here we introduce a hierarchical clock-mixture framework, implemented as the open-source RelaxClockAveraging package for BEAST 2, that separates two questions that are often conflated in clock comparison: whether branch-specific rate variation is needed at all, and, if it is, whether that variation is better described as uncorrelated or autocorrelated. The method averages analytically between strict and relaxed clocks at the top level and then compares UCLN and autocorrelated models within the relaxed class on a shared branch-rate vector, returning posterior probabilities for all three clock families together with model-averaged summaries for parameters shared across them. In stratified simulations, the generating clock family was retained in the 95% posterior model set in all replicates, while model-averaged estimates of the overall substitution rate, root age, and tree length remained accurate. On a DENV-4 benchmark, the mixture reproduced the higher-effort nested-sampling ranking of clock families while avoiding the extreme run-to-run variability of independent marginal-likelihood estimates. On empirical benchmarks, the method recovered strong support for the autocorrelated clock on the classical 31-taxon chloroplast rbcL data set. On an RSV-A G-gene data set it concentrated virtually all posterior support on UCLN while preserving the established RSV-A timescale. On a 245-taxon structured-coalescent H3N2 dataset it assigned most posterior mass to the relaxed-clock class, with support within that class concentrated on the autocorrelated family, and the inferred timescale remained consistent with the published estimate. These results show that clock-model support and downstream timescale sensitivity are related but not identical. Single-clock dating analyses can still be adequate, but fixing a clock model should be justified by posterior support rather than treated as a default assumption.

evolutionary biology↗

Regenerative base editing enables deep lineage recording

Reconstructing the lineage histories of individual cells can reveal the dynamics of developmental and disease processes. In engineered recording systems, cells stochastically edit synthetic barcode sequences as they proliferate, creating distinct, heritable edit patterns that can be used to reconstruct the lineage trees relating individual cells in a manner analogous to phylogenetic reconstruction. However, recording depth is often limited by the kinetics of the editing process: the rate of editing declines exponentially over time for an array of independently editable targets, leading to most edits occurring in early generations. Here, we introduce the hypercascade, a regenerative molecular recording system that takes advantage of the predictability of A-to-G base editing to progressively create new target sites over time. The hypercascade packs 4 editable target sites in every 20 bp of sequence, enabling high density information storage. More importantly, the hypercascades regenerative logic leads to an approximately constant rate of mutation accumulation over time. This in turn facilitates reconstruction of deep lineage relationships. We demonstrate this by reconstructing trees spanning 23 days of editing and approximately 17 generations after a single polyclonal engineering step. Finally, simulations show that the hypercascade has the potential to record chromatin state transition dynamics across multiple genomic loci in parallel. The hypercascade thus provides a flexible and broadly useful tool for molecular recording.

bioengineering↗

Improved Phylogenetic Posterior Estimation through Regularised Conditional Clade Distributions

Bayesian phylogenetic inference uses Markov chain Monte Carlo sampling to estimate the posterior distribution of phylogenetic trees. However, the complex geometry of treespace makes these distributions difficult to characterise. Traditional approaches often summarise posterior samples into a single point estimate, discarding much of the information contained in the full distribution. Conditional clade distributions (CCDs) address this by providing a tractable model of the full tree distribution, but existing parameterisations exhibit complementary strengths. We introduce a new family of models called regularised conditional clade distributions (regCCD), which apply regularisation to balance sample fidelity against overfitting, thereby combining the strengths of existing parameterisations. We show that regCCD outperforms existing models in capturing the posterior distribution and provides better point estimates than its underlying model. Furthermore, we provide an efficient procedure for selecting the optimal regularisation parameter for a given posterior tree set. Finally, we demonstrate the application of regCCD in assessing whether different phylogenetic models or data produce statistically distinguishable tree distributions.

evolutionary biology↗

Improving the Scalability of Bayesian Phylodynamic Inference through Efficient MCMC Proposals

In Bayesian phylodynamics, we jointly reconstruct the posterior distribution of timed phylogenetic trees, evolutionary and population dynamic parameters. Most approaches in the field use Markov chain Monte Carlo (MCMC) for inference. Inferring timed phylogenetic trees using MCMC relies on a set of proposal distributions - operators - to explore different phylogenetic tree topologies, node ranks, and heights. However, inefficiencies in these proposal distributions limit the speed and scale with which phylodynamic analyses can be performed. Here, we introduce two classes of operators that allow scaling of phylodynamic analyses by reducing the time needed to reach convergence. We propose an improved proposal distribution to scale trees based on the intervals between consecutive nodes in the tree, and a set of operators informed by a pseudo parsimony score to explore different tree topologies. Contrary to already existing operators that make large changes to areas of the tree with no mutations at all, our new parsimony-focused operators target areas of the tree with many mutations. We first demonstrate the correctness of these proposal distributions using a well-calibrated simulation study. We then demonstrate the improvements of using the updated proposal distributions using a number of large real-world datasets, showing a substantial increase in effective sample size per hour across viral datasets as well as a reduction in the number of samples required for the MCMC chain to reach stationarity. Finally, we apply the operators to a 10,000-sequence H3N2 dataset including phylogeography and finish the analysis within two weeks. The operators are implemented in the TargetedBeast package, which is available as an open-source package for BEAST2 and a user-friendly graphical user interface. The speed improvements in the TargetedBeast package are beneficial to any phylodynamics method implemented in BEAST2 that relies on standard phylogenetic trees, such as coalescent-skyline, birth-death skyline, and structured phylodynamic methods.

bioinformatics↗

Reduced amino acid substitution matrices find traces of ancient coding alphabets in modern day proteins

All known living systems make proteins from the same twenty canonically-coded amino acids, but this was not always the case. Early genetic coding systems likely operated with a restricted pool of amino acid types and limited means to distinguish between them. Despite this, amino acid substitution models like LG and WAG all assume a constant coding alphabet over time. That makes them especially inappropriate for the aminoacyl-tRNA synthetases (aaRS) - the enzymes that govern translation. To address this limitation, we created a class of substitution models that accounts for evolutionary changes in the coding alphabet size by defining the transition from nineteen states in a past epoch to twenty now. We use a Bayesian phylogenetic framework to improve phylogeny estimation and testing of this two-alphabet hypothesis. The hypothesis was strongly rejected by datasets composed exclusively of "young" eukaryotic proteins. It was generally supported by "old" (aaRS and non-aaRS) proteins whose origins date from before the last universal common ancestor. Standard methods overestimate the divergence ages of proteins that originated under reduced coding alphabets in both simulated and aaRS alignments. The new model reduces this bias substantially. Our findings support the late incorporation of tryptophan into the genetic code (relative to tyrosine) and suggest that isoleucine and valine were once coded interchangeably, forming protein quasispecies. This work provides a robust, seamless framework for reconstructing phylogenies from ancient protein datasets and offers further insights into the dawn of molecular biology.

evolutionary biology↗

Evolution is coupled with branching across many granularities of life

Across many different scales of life, the rate of evolutionary change is often accelerated at the time when one lineage splits into two. The emergence of novel protein function can be facilitated by gene duplication (neofunctionalisation); rapid morphological change is often accompanied with speciation (punctuated equilibrium); and the establishment of cultural identity is frequently driven by sociopolitical division (schismogenesis). In each case, the change resists rehomogenisation; promoting assortment into distinct lineages that are susceptible to different selective pressures, leading to rapid divergence. The traditional gradualistic view of evolution struggles to detect this phenomenon. We have devised a probabilistic framework that constructs phylogenies, tests hypotheses, and improves divergence time estimation when evolutionary bursts are present. As well as assigning a clock rate of gradual evolution to each branch of a tree, this model also assigns a spike of abrupt change, and independently estimates the contributions arising from each process. We provide evidence of abrupt evolution at the time of branching for proteins (aminoacyl-tRNA synthetases), animal morphologies (cephalopods), and human languages (Indo-European). These three cases provide unique insights: for aminoacyl-tRNA synthetases, the trees are substantially different from those obtained under gradualist models; Cephalopod morphologies are found to evolve almost exclusively through abrupt shifts; and Indo-European dispersal is estimated to have started around 6000 BCE, corroborating the recently proposed hybrid explanation. This work demonstrates a robust means for detecting burstlike processes, and advances our understanding of the link between evolutionary change and branching events. Our open-source code is available under a GPL license.

evolutionary biology↗

Taking a BREATH (Bayesian Reconstruction and Evolutionary Analysis of Transmission Histories) to simultaneously infer phylogenetic and transmission trees for partially sampled outbreaks

We introduce and apply Bayesian Reconstruction and Evolutionary Analysis of Transmission Histories (BREATH), a method to simultaneously construct phylogenetic trees and transmission trees using sequence data for a host-to-host outbreak. BREATHs transmission process that accounts for a flexible natural history of infection (including a latent period if desired) and a separate process for sampling. It allows for unsampled individuals and within-host evolution. It also accounts for the fact that an outbreak may still be ongoing at the time of analysis, using right truncation adjustment. We perform a simulation study to verify our implementation and explore sensitivity to unknown or misspecified parameters. We then apply BREATH to a previously-described 13-year outbreak of tuberculosis. We find that using a transmission process to inform the phylogenetic reconstruction results in better resolution of the phylogeny (in topology, branch length and tree height) and a more precise estimate of the time of origin of the outbreak. Considerable uncertainty remains about transmission events in the outbreak, but our reconstructed transmission network resolves two major waves of transmission consistent with the previously-described epidemiology, estimates the numbers of unsampled individuals, and describes some high-probability transmission pairs. An open source implementation of BREATH is available from https://github.com/rbouckaert/BREATH as the BREATH package to BEAST 2.

evolutionary biology↗

A tractable tree distribution parameterized by clade probabilities and its application to Bayesian phylogenetic point estimation

Bayesian phylogenetic analysis with MCMC algorithms generates an estimate of the posterior distribution of phylogenetic trees in the form of a sample of phylogenetic trees and related parameters. The high dimensionality and non-Euclidean nature of tree space complicates summarizing the central tendency and variance of the posterior distribution in tree space. Here we introduce a new tractable tree distribution and associated point estimator that can be constructed from a posterior sample of trees. Through simulation studies we show that this point estimator performs at least as well and often better than standard methods of producing Bayesian posterior summary trees. We also show that the method of summary that performs best depends on the sample size and dimensionality of the problem in non-trivial ways. Author summaryOur research introduces novel methods to analyse a set of phylogenetic tree topologies, such as those generated by Bayesian Markov Chain Monte Carlo algorithms. We define a new model for a distribution on trees that is based on observed clade frequencies. We study it together with closely related models that are based on observed clade split frequencies. These distributions are easy to work with and, as we show experimentally, provide excellent estimates of the true posterior distribution. Furthermore, we demonstrate that they enable us to find the tree with the highest posterior probability, which acts as a summary tree or point estimate of the distribution. In simulation studies, we show that the new methods performs as least as well or better than existing methods. Additionally, we highlight that choosing the best method for summarizing sets of trees remains challenging, as it depends on the sample size and complexity of the problem in non-trivial ways. This work has the potential to improve the accuracy of phylogenetic studies.

bioinformatics↗

How to validate a Bayesian evolutionary model

Biology has become a highly mathematical discipline in which probabilistic models play a central role. As a result, research in the biological sciences is now dependent on computational tools capable of carrying out complex analyses. These tools must be validated before they can be used, but what is understood as validation varies widely among methodological contributions. This may be a consequence of the still embryonic stage of the literature on statistical software validation for computational biology. Our manuscript aims to advance this literature. Here, we describe and illustrate good practices for assessing the correctness of a model implementation, with an emphasis on Bayesian methods. We also introduce a suite of functionalities for automating validation protocols. It is our hope that the guidelines presented here help sharpen the focus of discussions on (as well as elevate) expected standards of statistical software for biology.

evolutionary biology↗

Genomic database furnishes a spontaneous example of a functional Class II glycyl-tRNA synthetase urzyme

The chief barrier to studies of how genetic coding emerged is the lack of experimental models for ancestral aminoacyl-tRNA synthetases (AARS). We hypothesized that conserved core catalytic sites could represent such ancestors. That hypothesis enabled engineering functional "urzymes" from TrpRS, LeuRS, and HisRS. We describe here a fourth urzyme, GlyCA, detected in an open reading frame from the genomic record of the arctic fox, Vulpes lagopus. GlyCA is homologous to a bacterial heterotetrameric Class II GlyRS-B. Alphafold2 predicted that the N-terminal 81 amino acids would adopt a 3D structure nearly identical to the HisRS urzyme (HisCA1). We expressed and purified that N-terminal segment. Enzymatic characterization revealed a robust single-turnover burst size and a catalytic rate for ATP consumption well in excess of that previously published for HisCA1. Time-dependent aminoacylation of tRNAGly proceeds at a rate consistent with that observed for amino acid activation. In fact, GlyCA is actually 35 times more active in glycine activation by ATP than the full-length GlyRS-B -subunit dimer. ATP-dependent activation of the 20 canonical amino acids favors Class II amino acids that complement those favored by HisCA and LeuAC. These properties reinforce the notion that urzymes represent the requisite ancestral catalytic activities to implement a reduced genetic coding alphabet.

evolutionary biology↗

Reconstructing cell histories in space with image-readable base editor recording

Knowing the ancestral states and lineage relationships of individual cells could unravel the dynamic programs underlying development. Engineering cells to actively record information within their own genomic DNA could reveal these histories, but existing recording systems have limited information capacity or disrupt spatial context. Here, we introduce baseMEMOIR, which combines base editing, sequential hybridization imaging, and Bayesian inference to allow reconstruction of high-resolution cell lineage trees and cell state dynamics while preserving spatial organization. BaseMEMOIR stochastically and irreversibly edits engineered dinucleotides to one of three alternative image-readable states. By genomically integrating arrays of editable dinucleotides, we constructed an embryonic stem cell line with 792 bits of recordable, image-readable memory, a 50-fold increase over the state of the art. Simulations showed that this memory size was sufficient for accurate reconstruction of deep lineage trees. Experimentally, baseMEMOIR allowed precise reconstruction of lineage trees 6 or more generations deep in embryonic stem cell colonies. Further, it also allowed inference of ancestral cell states and their quantitative cell state transition rates, all from endpoint images. baseMEMOIR thus provides a scalable framework for reconstructing single cell histories in spatially organized multicellular systems.

synthetic biology↗

Tertiary-interaction characters enable fast, model-based structural phylogenetics beyond the twilight zone

Protein structure is more conserved than protein sequence, and therefore may be useful for phylogenetic inference beyond the "twilight zone" where sequence similarity is highly decayed. Until recently, structural phylogenetics was constrained by the lack of solved structures for most proteins, and the reliance on phylogenetic distance methods which made it difficult to treat inference and uncertainty statistically. AlphaFold has mostly overcome the first problem by making structural predictions readily available. We address the second problem by redeploying a structural alphabet recently developed for Foldseek, a highly-efficient deep homology search program. For each residue in a structure, Foldseek identifies a tertiary interaction closest-neighbor residue in the structure, and classifies it into one of twenty "3Di" states. We test the hypothesis that 3Dis can be used as standard phylogenetic characters using a dataset of 53 structures from the ferritin-like superfamily. We performed 60 IQtree Maximum Likelihood runs to compare structure-free, PDB, and AlphaFold analyses, and default versus custom model sets that include a 3DI-specific rate matrix. Analyses that combine amino acids, 3Di characters, partitioning, and custom models produce the closest match to the structural distances tree of Malik et al. (2020), avoiding the long-branch attraction errors of structure-free analyses. Analyses include standard ultrafast bootstrapping confidence measures, and take minutes instead of weeks to run on desktop computers. These results suggest that structural phylogenetics could soon be routine practice in protein phylogenetics, allowing the re-exploration of many fundamental phylogenetic problems.

evolutionary biology↗

Variational Bayesian Phylogenies through Matrix Representation of Tree Space

In this paper, we study the distance matrix as a representation of a phylogeny by way of hierarchical clustering. By defining a multivariate normal distribution on (a subset of) the entries in a matrix, this allows us to represent a distribution over rooted time trees. Here, we demonstrate tree distributions can be represented accurately this way for a number of published tree distributions. Though such a representation does not map to unique trees, restriction to a subspace, in particular one we call a "cube", makes the representation bijective at the cost of not being able to represent all possible trees. We introduce an algorithm "cubeVB" specifically for cubes and show through well calibrated simulation study that it is possible to recover parameters of interest like tree height and length. Although a cube cannot represent all of tree space, it is a great improvement over a single summary tree, and it opens up exciting new opportunities for scaling up Bayesian phylogenetic inference. We also demonstrate how to use a matrix representation of a tree distribution to get better summary trees than commonly used maximum clade credibility trees. An open source implementation of the cubeVB algorithm is available from https://github.com/rbouckaert/cubevb as the cubevb package for BEAST 2.

bioinformatics↗

Automated convergence diagnostic for phylogenetic MCMC analyses

Assessing convergence of Markov chain Monte Carlo (MCMC) based analyses is crucial but challenging, especially so in high dimensional and complex spaces such as the space of phylogenetic trees (treespace). In practice, it is assumed that the target distribution is the unique stationary distribution of the MCMC and convergence is achieved when samples appear to be stationary. Here we leverage recent advances in computational geometry of the treespace and introduce a method that combines classical statistical techniques and algorithms with geometric properties of the treespace to automatically evaluate and assess practical convergence of phylogenetic MCMC analyses. Our method monitors convergence across multiple MCMC chains and achieves high accuracy in detecting both practical convergence and convergence issues within treespace. Furthermore, our approach is developed to allow for real-time evaluation during the MCMC algorithm run, eliminating any of the chain post-processing steps that are currently required. Our tool therefore improves reliability and efficiency of MCMC based phylogenetic inference methods and makes analyses easier to reproduce and compare. We demonstrate the efficacy of our diagnostic via a well-calibrated simulation study and provide examples of its performance on real data sets. Although our method performs well in practice, a significant part of the underlying treespace probability theory is still missing, which creates an excellent opportunity for future mathematical research in this area. The open source package for the phylogenetic inference framework BEAST2, called ASM, that implements these methods, making them accessible through a user-friendly GUI, is available from https://github.com/rbouckaert/asm/. The open source Python package, called tetres, that provides an interface for these methods enabling their applications beyond BEAST2 can be accessed at https://github.com/bioDS/tetres/.

bioinformatics↗

Triangulation reduces the polygon of error for the history of Transeurasian

In a recent study we used an interdisciplinary approach combining linguistics, archaeology and genetics to analyse the Transeurasian languages1. Our analysis concluded that the early dispersals of these languages were driven by agriculture. A preprint published on this server presents objections to the Transeurasian hypothesis and its association with farming dispersals2. However, close inspection of that text reveals numerous misinterpretations and inconsistencies. In the interest of furthering scientific debate over Transeurasian language and population history, we address the critiques, revising datasets and fine-tuning approaches. The linguistic critique questions the quantity and quality of our datasets. Here we show that the number of surviving cognate sets for Transeurasian is in line with that for well-established language families. In addition, we find that Tian et al.s failure to reject a core of regularly corresponding cognates in the basic vocabulary creates ground for a consensus about the genealogical relatability of the Transeurasian languages. The archaeological critique attempts a re-analysis of one Bayesian test using re-scored data only for northern China. Over half of the suggested re-scorings contain inconsistencies and it is not explained why the re-analysis retains the original data for sites outside northern China, comprising almost 60% of the total. More importantly, the sweeping claim that there is no evidence supporting the prehistoric migrations analysed in our study is not backed by any discussion of the archaeological record. With respect to genetics, the preprint claims a re-analysis showing that the data do not conclusively support the farming-driven dispersal of Turkic, Mongolian, and Tungusic, nor the two-wave spread of farming to Korea. In fact, the only genetic re-analysis presented is limited to samples from Korea and Japan and does not contradict our original conservative modelling of Neolithic individuals with Hongshan and our Bronze Age ones with Upper Xiajiadian. In sum, in bringing multiple lines of evidence together through triangulation, we gained a more balanced and richer understanding of Transeurasian dispersals than each discipline could provide individually. Our research doubtless leaves room for improvement but we remain confident that triangulation did not fail, but rather brought us a step closer to understanding the history of the Transeurasian languages.

evolutionary biology↗