Philosophical Transactions of the Royal Society B: Biological Sciences最新文献

The effect of traits on diversification rates is a major topic of study in the fields of evolutionary biology and palaeontology. Many researchers investigating these macroevolutionary questions currently make use of the extensive suite of state-dependent speciation and extinction (SSE) models. These models were developed for, and are almost exclusively used with, phylogenetic trees of extant species. However, analyses considering only extant taxa are limited in their power to estimate extinction rates. Furthermore, SSE models can erroneously detect associations between neutral traits and diversification rates when the true associated trait is not observed. In this study, we examined the impact of including fossil data on the accuracy of parameter estimates under the binary-state speciation and extinction (BiSSE) model. This was achieved by combining SSE models with the fossilized birth-death process. We show that the inclusion of fossils improves the accuracy of extinction-rate estimates for analyses applying the BiSSE model in a Bayesian inference framework, with no negative impact on speciation-rate and state transition-rate estimates when compared with estimates from trees of only extant taxa. However, even with the addition of fossil data, analyses under the BiSSE model continued to incorrectly identify correlations between diversification rates and neutral traits.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Variation in a sample of molecular sequence data informs about the past evolutionary history of the sample's population. Traditionally, Bayesian modelling coupled with the standard coalescent is used to infer the sample's bifurcating genealogy and demographic and evolutionary parameters such as effective population size and mutation rates. However, there are many situations where binary coalescent models do not accurately reflect the true underlying ancestral processes. Here, we propose a Bayesian non-parametric method for inferring effective population size trajectories from a multifurcating genealogy under the [Formula: see text]-coalescent. In particular, we jointly estimate the effective population size and the model parameter for the Beta-coalescent model, a special type of [Formula: see text]-coalescent. Finally, we test our methods on simulations and apply them to study various viral dynamics as well as Japanese sardine population size changes over time. The code and vignettes can be found in the phylodyn package.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

This review focuses on linear birth-and-death processes (LBDPs), describing the basic properties of the population-size process and the underlying ancestral trees that record how the evolving species (or individuals or cells) are related. The first section describes the Yule, or linear birth, process setting. Analogous results for the birth-and-death process (BDP) are given. The stochastic structure of the reconstructed tree obtained by pruning branches that do not survive to the present time is detailed. In §2, the BDP with immigration is described. Immigration is a mechanism to introduce new types into a population evolving through time. For the Yule process, marked Poisson process arguments are used to illustrate properties of the sample variance of the number of families observed in two consecutive time intervals. In the final section, we describe a recent method for approximate Bayesian computation using random forests, and illustrate it with an example of inference from DNA sequence data about the split rate and mutation rate in a birth-and-death model for the evolution of a cell population.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Tree shape statistics, particularly measures of tree (im)balance, play an important role in the analysis of the shape of phylogenetic trees. With applications ranging from testing evolutionary models to studying the impact of fertility inheritance and selection, or tumour development and language evolution, the assessment of measures of tree balance is important. Currently, a multitude of at least 30 (im)balance indices can be found in the literature, alongside numerous other tree shape statistics. This diversity prompts essential questions: how can we assist researchers in choosing only a small number of indices to mitigate the challenges of multiple testing? Is there a preeminent balance index tailored to specific tasks? This research expands previous studies on the examination of index power, encompassing almost all established indices and a broader array of alternative models, such as a variety of trait-based models. Our investigation reveals distinct groups of balance indices better suited for different tree models, suggesting that decisions on balance index selection can be enhanced with prior knowledge. Furthermore, we present the R software package poweRbal which allows the inclusion of new indices and models, thus facilitating future research on the power of tree shape statistics.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Analysing single-cell lineage relationships of an organism is crucial towards understanding the fundamental cellular dynamics that drive development. Clustered regularly interspaced short palindromic repeats (CRISPR)-based dynamic lineage tracing relies on recent advances in genome editing and sequencing technologies to generate inheritable, evolving genetic barcode sequences that enable reconstruction of such cell lineage trees, also referred to as phylogenetic trees. Recent work generated custom computational strategies to produce robust tree estimates from such data. We further capitalize on these advancements and introduce GESTALT analysis using Bayesian inference (GABI), which extends the analysis of genome editing of synthetic target arrays for lineage tracing (GESTALT) data to a fully integrated Bayesian phylogenetic inference framework in software BEAST 2. This implementation allows users to represent the uncertainty in reconstructed trees and enables their scaling in absolute time. Furthermore, based on such time-scaled lineage trees, the underlying processes of growth, differentiation and apoptosis are quantified through so-called phylodynamic inference, typically relying on a birth-death or coalescent model. After validating its implementation, we demonstrate that our methodology results in robust estimates of growth dynamics characteristic of early Danio rerio development. GABI's codebase is publicly available at https://github.com/azwaans/GABI.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Viral phylodynamics focuses on using sequence data to make inferences about the population dynamics of viral diseases. These inferences commonly include estimation of growth rates, reproduction numbers and times of most recent common ancestor. With few exceptions, existing phylodynamic inference approaches assume that all observed and ancestral viral genetic variation is fitness-neutral. This assumption is commonly violated, with a large body of analyses indicating that fitness varies substantially among genotypes circulating in viral populations. Here, we focus on fitness variation arising from deleterious mutations, asking whether incomplete purifying selection of deleterious mutations has the potential to bias phylodynamic inference. We use simulations of an exponentially growing population to explore how incomplete purifying selection distorts tree shape and shifts the distribution of mutations over trees. We find that incomplete purifying selection strongly shapes the distribution of mutations while only weakly impacting tree shape. Despite incomplete purifying selection shifting the distribution of deleterious mutations, we find little discernible bias in estimates of viral growth rates and times of the most recent common ancestor. Our results reassuringly indicate that existing phylodynamic inference approaches that assume neutrality may nevertheless yield accurate epidemiological estimates in the face of incomplete purifying selection. More work is needed to assess the robustness of these findings to alternative epidemiological parametrizations.This article is part of the theme issue ''"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Yule's 1925 paper introducing the branching model that bears his name was a landmark contribution to the biodiversity sciences. In his paper, Yule developed stochastic models to explain the observed distribution of species across genera and to test hypotheses about the relationship between clade age, diversity and geographic range. Here, we discuss the intellectual context in which Yule produced this work, highlight Yule's key mathematical and conceptual contributions using both his and more modern derivations and critically examine some of the assumptions of his work through a modern lens. We then document the strange trajectory of his work through the history of macroevolutionary thought and discuss how the fundamental challenges he grappled with-such as defining higher taxa, linking microevolutionary population dynamics to macroevolutionary rates, and accounting for inconsistent taxonomic practices-remain with us a century later.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Circadian clocks are biological oscillators that evolved to coordinate rhythms in behaviour and physiology around the 24-hour day. In mammalian tissues, circadian rhythms and metabolism are highly intertwined. The clock machinery controls rhythmic levels of circulating hormones and metabolites, as well as rate-limiting enzymes catalysing biosynthesis or degradation of macromolecules in metabolic tissues, such control being exerted both at the transcriptional and post-transcriptional level. During infections, major metabolic adaptation occurs in mammalian hosts, at the level of both the single immune cell and the whole organism. Under these circumstances, the rhythmic metabolic needs of the host intersect with those of two other players: the pathogen and the microbiota. These three components cooperate or compete to meet their own metabolic demands across the 24 hours. Here, we review findings describing the circadian regulation of the host response to infection, the circadian metabolic adaptations occurring during host-microbiota-pathogen interactions and how such regulation can influence the immune response of the host and, ultimately, its own survival.This article is part of the Theo Murphy meeting issue 'Circadian rhythms in infection and immunity'.

The within-host environment changes over circadian time and influences the replication and severity of viruses. Genetic knockout of the circadian transcription factors CRYPTOCHROME 1 and CRYPTOCHROME 2 (CRY1^-/-/CRY2^-/-; CKO) leads to altered protein homeostasis and chronic activation of the integrated stress response (ISR). The adaptive ISR signalling pathways help restore cellular homeostasis by downregulating protein synthesis in response to endoplasmic reticulum overloading or viral infections. By quantitative mass spectrometry analysis, we reveal that many viral recognition proteins and type I interferon (IFN) effectors are significantly upregulated in lung fibroblast cells from CKO mice compared with wild-type (WT) mice. This basal 'antiviral state' restricts the growth of influenza A virus and is governed by the interaction between proteotoxic stress response pathways and constitutive type I IFN signalling. CKO proteome composition and type I IFN signature were partially phenocopied upon sustained depletion of CRYPTOCHROME (CRY) proteins using a small-molecule CRY degrader, with modest differential gene expression consistent with differences seen between CKO and WT cells. Our results highlight the crosstalk between circadian rhythms, cell-intrinsic antiviral defences and protein homeostasis, providing a tractable molecular model to investigate the interface of these key contributors to human health and disease.This article is part of the Theo Murphy meeting issue 'Circadian rhythms in infection and immunity'.