Phylogenetic Models Research Articles

Temporal changes in spatial scale and autocorrelation structure of forest openings based on taxonomic, phylogenetic, and functional turnover

ContextDuring European settlement, Illinois grasslands were converted for agricultural purposes. Remaining natural areas in southern Illinois include natural xeric forest openings, with communities representative of remnant grasslands and adjacent hardwood forests. Previous research in these openings shows plant communities are driven by edaphic conditions. ObjectivesThe first objective aimed to characterize spatial scale and autocorrelation structure of these openings based on climatic, environmental, and diversity variables. The second objective was to predict taxonomic, phylogenetic, and functional turnover between 1988 and 2019, using climatic and environmental variables. MethodsSurveys were conducted to calculate taxonomic, phylogenetics and functional trait metrics and analyses of these dimensions of diversity. Randomization tests were used to assess phylogenetic and functional clustering and over-dispersion at each site. Spatially-explicit climatic and environmental variables were included from earlier surveys and data repositories. Global Moran's I and spatial autocorrelograms were used to assess spatial structure of climatic, environmental, and diversity variables and generalized dissimilarity modeling was used to characterize taxonomic, phylogenetic, and functional turnover based on environmental variables. ResultsSoil depth was the only environmental variable which exhibited significant global spatial autocorrelation. Overall, sandstone sites were phylogenetically over-dispersed while loess sites were phylogenetically clustered. Climate variables and diversity metrics exhibited significant spatial structure during surveys. Generalized dissimilarity models showed that geographic distance between openings was the most influential driver of turnover across surveys. ConclusionsPrevious glacial events explained the spatial structure of soil depth across sites, due to Quaternary loess deposition in loess sites. High diversity values were clustered in the southeastern portions of the study area. Functional generalized dissimilarity models best predicted turnover in these openings compared to taxonomic and phylogenetic models.

Quantification of microbial community assembly processes during degradation on diverse plastispheres based on physicochemical characters and phylogenetic bin-based null model analysis

To understand the differences in degradation processes depending on the chemical properties of polymers, it is necessary to both quantify the microbiome composition and evaluate the process of microbial turnover (i.e., community assembly processes) in a variety of polymer materials. In this study, using a phylogenetic bin-based null model analysis (i.e., iCAMP), we evaluated community assembly processes from original estuary water to 37 types of polymers, which provide overwhelmingly diverse niches for microbes, in 14-day incubation experiments. First, we evaluated the polymer properties related to degradation rates. Polymers with higher adipic acid (AdA) monomer exhibited higher motility, hydrophilicity, and degradation rates, whereas those with higher aromatic monomer exhibited the opposite trends. Second, microbiome composition analysis was performed, and the microbiomes were significantly changed by the AdA or aromatic content. This was consistent with the polymer properties, suggesting that polymer motility and hydrophilicity attributable to the first-order structure modify the accessibility of the enzyme to the reaction site and hence the degradation rate, resulting in differences in microbiome community composition. Finally, we determined community assembly processes from estuary water to plastics using a phylogenetic bin-based null model analysis. The importance of heterogeneous selection was higher in mobile, hydrophilic, and fast-degrading polymers, while that of homogeneous selection was lower. This suggests that the environmental difference between before and after incubation becomes significant under rapid degradation, which select microbes adapted to biofilm environments. In addition, the more stochastic turnover prevailed, the more variation in the communities (i.e., β-diversity) increased. This suggests that turnover processes not dictated by the environment lead to instability in community compositions.

Evolutionary analyses of intrinsically disordered regions reveal widespread signals of conservation.

Intrinsically disordered regions (IDRs) are segments of proteins without stable three-dimensional structures. As this flexibility allows them to interact with diverse binding partners, IDRs play key roles in cell signaling and gene expression. Despite the prevalence and importance of IDRs in eukaryotic proteomes and various biological processes, associating them with specific molecular functions remains a significant challenge due to their high rates of sequence evolution. However, by comparing the observed values of various IDR-associated properties against those generated under a simulated model of evolution, a recent study found most IDRs across the entire yeast proteome contain conserved features. Furthermore, it showed clusters of IDRs with common "evolutionary signatures," i.e. patterns of conserved features, were associated with specific biological functions. To determine if similar patterns of conservation are found in the IDRs of other systems, in this work we applied a series of phylogenetic models to over 7,500 orthologous IDRs identified in the Drosophila genome to dissect the forces driving their evolution. By comparing models of constrained and unconstrained continuous trait evolution using the Brownian motion and Ornstein-Uhlenbeck models, respectively, we identified signals of widespread constraint, indicating conservation of distributed features is mechanism of IDR evolution common to multiple biological systems. In contrast to the previous study in yeast, however, we observed limited evidence of IDR clusters with specific biological functions, which suggests a more complex relationship between evolutionary constraints and function in the IDRs of multicellular organisms.

Evolutionary characteristics of the mitochondrial NADH dehydrogenase subunit 6 gene in some populations of four sympatric Mustela species (Mustelidae, Mammalia) from central Europe.

Selection on or reticulate evolution of mtDNA is documented in various mammalian taxa and could lead to misleading phylogenetic conclusions if not recognized. We sequenced the MT-ND6 gene of four sympatric Mustelid species of the genus Mustela from some central European populations. We hypothesised positive selection on MT-ND6, given its functional importance and the different body sizes and life histories of the species, even though climatic differences may be unimportant for adaptation in sympatry. MT-ND6 genes were sequenced in 187 sympatric specimens of weasels, Mustela nivalis, stoats, M. erminea, polecats, M. putorius, and steppe polecats, M. eversmannii, from eastern Austria and of fourteen allopatric polecats from eastern-central Germany. Median joining networks, neighbour joining and maximum likelihood analyses as well as Bayesian inference grouped all species according to earlier published phylogenetic models. However, polecats and steppe polecats, two very closely related species, shared the same two haplotypes. We found only negative selection within the Mustela sequences, including 131 downloaded ones covering thirteen species. Positive selection was observed on three MT-ND6 codons of other mustelid genera retrieved from GenBank. Negative selection for MT-ND6 within the genus Mustela suggests absence of both environmental and species-specific effects of cellular energy metabolism despite large species-specific differences in body size. The presently found shared polymorphism in European polecats and steppe polecats may result from ancestral polymorphism before speciation and historical or recent introgressive hybridization; it may indicate mtDNA capture of steppe polecats by M. putorius in Europe.

Binding Evolution of the Dengue Virus Envelope Against DC-SIGN: A Combined Approach of Phylogenetics and Molecular Dynamics Analyses Over 30 Years of Dengue Virus in Brazil

The Red Queen Hypothesis (RQH), derived from Lewis Carroll's “Through the Looking-Glass”, postulates that organisms must continually adapt in response to each other to maintain relative fitness. Within the context of host-pathogen interactions, the RQH implies an evolutionary arms race, wherein viruses evolve to exploit hosts and hosts evolve to resist viral invasion. This study delves into the dynamics of the RQH in the context of virus-cell interactions, specifically focusing on virus receptors and cell receptors. We observed multiple virus-host systems and noted patterns of co-evolution. As viruses evolved receptor-binding proteins to effectively engage with cell receptors, cells countered by altering their receptor genes. This ongoing mutual adaptation cycle has influenced the molecular intricacies of receptor-ligand interactions. Our data supports the RQH as a driving force behind the diversification and specialization of both viral and host cell receptors. Understanding this co-evolutionary dance offers insights into the unpredictability of emerging viral diseases and potential therapeutic interventions. Future research is crucial to dissect the nuanced molecular changes and the broader ecological consequences of this ever-evolving battle. Here, we combine phylogenetic inferences, structural modeling, and molecular dynamics analyses to describe the epidemiological characteristics of major Brazilian DENV strains that circulated from 1990 to 2022 from a combined perspective, thus providing us with a more detailed picture on the dynamics of such interactions over time.

The Evolution of Rodent Tail Morphology.

AbstractPopulation-level variation in rodent tail structures has been variously attributed to facilitating social communication, locomotion, thermoregulation, and predator avoidance. Little is known, however, about the applicability of these ecological and social correlates to explaining the tremendous interspecific diversity of this appendage. To investigate the potential drivers of rodent tail morphology at a macroevolutionary level, we first carefully reviewed the literature and constructed a list of major hypotheses regarding this variation. We then compiled a database of 11 different tail traits related to length, color, texture, and ecological characteristics for 2,101 species of rodents (order Rodentia) and examined their key evolutionary correlates. Using Bayesian phylogenetic mixed models across the entire order and additionally within the five rodent suborders, we found that tail length is correlated with both temperature (Allen's rule) and locomotory mode, that black tips are more common in brightly lit environments, that naked tails are often found in warmer climates, that fluffy-tipped tails are more common in smaller and/or arboreal species, that prehensility is predominant in arboreal species and/or species with longer tails, and that tail autotomy is more common in open environments. Most of our tested predictions, largely drawn from population-level studies, are not recapitulated across the entire order, potentially indicating a role of local ecological context in shaping tail morphology.

Global latitudinal gradients and the evolution of body size in dinosaurs and mammals

Global climate patterns fundamentally shape the distribution of species and ecosystems. For example, Bergmann’s rule predicts that homeothermic animals, including birds and mammals, inhabiting cooler climates are generally larger than close relatives from warmer climates. The modern world, however, lacks the comparative data needed to evaluate such macroecological rules rigorously. Here, we test for Bergmann’s rule in Mesozoic dinosaurs and mammaliaforms that radiated within relatively temperate global climate regimes. We develop a phylogenetic model that accounts for biases in the fossil record and allows for variable evolutionary dispersal rates. Our analysis also includes new fossil data from the extreme high-latitude Late Cretaceous Arctic Prince Creek Formation. We find no evidence for Bergmann’s rule in Mesozoic dinosaurs or mammaliaforms, the ancestors of extant homeothermic birds and mammals. When our model is applied to thousands of extant dinosaur (bird) and mammal species, we find that body size evolution remains independent of latitude. A modest temperature effect is found in extant, but not in Mesozoic, birds, suggesting that body size evolution in modern birds was influenced by Bergmann’s rule during Cenozoic climatic change. Our study provides a general approach for studying macroecological rules, highlighting the fossil record’s power to address longstanding ecological principles.

Plant functional traits couple with range size and shape in European trees

AbstractAimPlant functional traits are frequently proposed as influential factors in species distribution. However, there is a gap in assessing how plant resource‐economic traits relate to the size and shape of a species' geographical range, and to what extent these relationships are conserved over evolutionary history. Specifically, an acquisitive strategy (characterized by heightened metabolism, shorter lifespan and quicker generation turnover) may promote isotropic range formations, resulting in less elongated and larger ranges. Here, I tested this link using data from 98 native European tree species.LocationPalaearctic.Time periodPresent.Major taxa studiedTrees.MethodsI used chorological maps to quantify two independent range attributes: species' range area and elongation. I considered 28 functional traits linked to resource‐use strategy measured in above‐ and below‐ground organs. I used multi‐response phylogenetic mixed models to calculate the conservative trait correlation (CTC) and the phylogenetically independent correlation (IND) component of each functional trait with range area and elongation.ResultsRange area positively correlated with resource acquisitive strategies, while range elongation correlated with resource conservative strategies. This pattern was consistent across the examined traits but statistically significant in seven out of the 28 traits, including specific leaf area, specific root area and root mycorrhizal colonization. Traits related to leaf and root nutritional status exhibited the weakest relationships with range attributes. Significant correlations were more frequent in the IND component and often showed contrasting trends compared to CTC.Main conclusionsPlant resource‐use strategy emerges as a relevant factor to gain insights on what shapes species' geographical distribution, alongside more established drivers such as dispersal limitation and climatic tolerance. Trait‐range relationships are driven by processes leaving a weak phylogenetic signature. These processes may result from direct selection, where functional traits impact range attributes, or indirect effects, such as the co‐variation of ranges and traits with environmental niche optima.

Anthropogenic nest material use in a global sample of birds.

As humans increasingly modify the natural world, many animals have responded by changing their behaviour. Understanding and predicting the extent of these responses is a key step in conserving these species. For example, the tendency for some species of birds to incorporate anthropogenic items-particularly plastic material-into their nests is of increasing concern, as in some cases, this behaviour has harmful effects on adults, young and eggs. Studies of this phenomenon, however, have to date been largely limited in geographic and taxonomic scope. To investigate the global correlates of anthropogenic (including plastic) nest material use, we used Bayesian phylogenetic mixed models and a data set of recorded nest materials in 6147 species of birds. We find that, after controlling for research effort and proximity to human landscape modifications, anthropogenic nest material use is correlated with synanthropic (artificial) nesting locations, breeding environment and the number of different nest materials the species has been recorded to use. We also demonstrate that body mass, range size, conservation status and brain size do not explain variation in the recorded use of anthropogenic nest materials. These results indicate that anthropogenic materials are more likely to be included in nests when they are more readily available, as well as potentially by species that are more flexible in their nest material choice.

Molecular cloning and biochemical characterization of indole-3-acetic acid methyltransferase from Japanese star anise (Illicium anisatum).

SABATH proteins methylate the carboxyl groups or nitrogen atoms of small plant molecules and play important roles in many developmental processes and plant defense responses. Previous studies have shown that indole-3-acetic acid (IAA) carboxyl methyltransferase (IAMT), a member of the SABATH methyltransferase family, converts IAA into its methyl ester (Me-IAA). We used RNA-seq analysis to identify a putative IAMT gene, IaIAMT, in the ancient angiosperm Illicium anisatum. Functional characterization of the recombinant IaIAMT protein expressed in Escherichia coli showed the highest level of activity with IAA, whereas indole-3-propionic acid and indole-3-butyric acid were not used as substrates. The apparent Km value of IaIAMT using IAA as a substrate was determined to be 122 µM. Phylogenetic analysis and structural modeling of IaIAMT suggested that IaIAMT evolved independently from IAMTs isolated from other plant species, whereas strict substrate specificity toward IAA was conserved in Illicium species, as observed in other plants.

Early and contemporary drivers of the HIV-1 group M pandemic.

HIV emerged silently taking time to spread and become visible only through geographically isolated clusters of life-threatening immunodeficiency, known as AIDS since the early 80s. The clusters of infection expanded, overlapping to evolve into a pandemic that is ongoing and almost as silent. Phylogenetic analysis places the emergence of HIV-1 group M, the subtype responsible for the pandemic, in the human population more than 100 years ago. Once established, the rate and direction of spread of HIV-1 from local, to national, to contemporary pandemic proportions have varied over time and place. The literature presents many theories on the emergence and drivers of the spread of the virus over the past century. Here, historical evidence and phylogenetic models are reviewed to seek clarity on the emergence, geographic spread and key world events that mark the progression of the HIV-1 pandemic. This narrative review places particular focus on: war (both its direct and indirect affects), trade and economic expansion, changes in sexual behaviors, and public health policy. Investigating the impact of major world events and policy on the emergence and spread of HIV-1 may aid better understanding of what influences the viruses transmission dynamic. By identifying multilateral targets that influence transmission, up-scaled efforts to effectively control, if not remove, HIV-1 from the human population become a possibility. Suggestions for revisions in HIV-1 global public health policy are discussed. Refocused efforts to tackle HIV-1 transmission and replace the need to manage the pathology of this terrible disease are both ethically and economically just.

Abstract 2334: Computational methods for optimizing marker selection, clonal lineage reconstruction, and longitudinal tracking of clonal dynamics via circulating tumor DNA (ctDNA)

Abstract Background: Technologies for blood-based profiling of tumor DNA (“liquid biopsy”) have offered great prospects for non-invasive early cancer diagnosis, treatment monitoring, and clinical guidance, but further advances in computational models and data analysis to optimize monitoring protocols and develop liquid biopsy as a robust quantitative assay of tumor clonal evolution. Methods: We propose new computational methods to improve our ability to characterize tumor clonal dynamics from circulating tumor DNA (ctDNA). Our methods address how to apply ctDNA assays most effectively to two distinct questions in profiling tumor clonal dynamics: 1) How to apply longitudinal ctDNA data to refine phylogenetic tree models of clonal evolution, and 2) how to most effectively characterize changes in clonal frequencies that may be indicative of treatment response or tumor progression. We pose these questions computationally in terms of a probabilistic framework for optimally identifying maximum likelihood markers for the preceding tasks and applying measured marker concentrations to their solution. We apply this framework by first evaluating the distribution of plausible clonal lineage models using bootstrap samples over pre-treatment tissue-based genetic variation data, then refining these lineage models and the clonal frequencies we can infer from them over successive longitudinal samples of selected markers. Results: We tested our method on synthetic data under various model assumptions and showed the method to be effective at refining distribution tree models and clonal frequencies over longitudinal samples so as to minimize measures of tree distance relative to the ground truth. We further apply the methods to a real ovarian cancer case and show their ability to develop and refine a clonal lineage model and assess clonal frequencies. Conclusion: Our methods show the power of ctDNA assays in conjunction with computational optimization to lead to improved marker selection, clonal lineage reconstruction, and tracking of clonal dynamics, with potential for more precise and quantitative profiling of tumor progression enabling improved clinical decision-making. Citation Format: Xuecong Fu, Yueqian Deng, Zhicheng Luo, William Laframboise, David Bartlett, Russell Schwartz. Computational methods for optimizing marker selection, clonal lineage reconstruction, and longitudinal tracking of clonal dynamics via circulating tumor DNA (ctDNA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2334.

Network specificity decreases community stability and competition among avian haemosporidian parasites and their hosts

AbstractAimParasites play a fundamental role in shaping ecological communities and influencing trophic interactions. Understanding the factors that drive parasite impacts on community structure and stability (i.e. resilience to disturbances) is crucial for predicting disease dynamics and implementing effective conservation strategies. In this study, using avian malaria and malaria‐like parasites as a model system, we investigated the relationship between specificity, community stability and parasite vulnerability and their association with host diversity and climate.LocationGlobal.Time period2009–2023.Major taxa studiedAvian malaria and malaria‐like parasites.MethodsBy compiling occurrence data from a global avian haemosporidian parasite database (MalAvi), we constructed a comprehensive dataset encompassing 60 communities. We utilized a phylogenetic model approach to predict missing host–parasite interactions, enhancing the accuracy of our analyses. Network analyses based on bipartite interactions provided measures of network specificity, stability, modularity, parasite competition and vulnerability to extinction.ResultsWe found that the high network specificity reduced community stability and decreased competition among parasites. Furthermore, we found that parasite vulnerability decreased with increasing community stability, highlighting the importance of community stability in host–parasite interactions for long‐term parasite persistence. When exploring the influence of local host diversity and climate conditions on host–parasite community stability, we demonstrated that increasing host biodiversity and precipitation reduces parasite competition. Conversely, higher temperature raises competition among parasites.ConclusionThese findings provide valuable insights into the mechanisms underlying parasite impacts on communities and the interplay between specificity, community stability and environmental factors. Further, we reveal the role of climate in shaping host–parasite interactions. By unravelling the complexities of parasite‐mediated interactions, our research substantially improves the current knowledge of the importance of specificity as a modulator of interactions in bipartite networks.

AleRax: a tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss.

Genomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree. We present AleRax, a software that can infer reconciled gene trees together with a shared species tree using a simple, yet powerful, probabilistic model of gene duplication, transfer, and loss. A key feature of AleRax is its ability to account for uncertainty in the gene tree and its reconciliation by using an efficient approximation to calculate the joint phylogenetic-reconciliation likelihood and sample reconciled gene trees accordingly. Simulations and analyses of empirical data show that AleRax is one order of magnitude faster than competing gene tree inference tools while attaining the same accuracy. It is consistently more robust than species tree inference methods such as SpeciesRax and ASTRAL-Pro 2 under gene tree uncertainty. Finally, AleRax can process multiple gene families in parallel thereby allowing users to compare competing phylogenetic hypotheses and estimate model parameters, such as duplication, transfer, and loss probabilities for genome-scale datasets with hundreds of taxa. GNU GPL at https://github.com/BenoitMorel/AleRax and data are made available at https://cme.h-its.org/exelixis/material/alerax_data.tar.gz.

Extant Sequence Reconstruction: The Accuracy of Ancestral Sequence Reconstructions Evaluated by Extant Sequence Cross-Validation

Ancestral sequence reconstruction (ASR) is a phylogenetic method widely used to analyze the properties of ancient biomolecules and to elucidate mechanisms of molecular evolution. Despite its increasingly widespread application, the accuracy of ASR is currently unknown, as it is generally impossible to compare resurrected proteins to the true ancestors. Which evolutionary models are best for ASR? How accurate are the resulting inferences? Here we answer these questions using a cross-validation method to reconstruct each extant sequence in an alignment with ASR methodology, a method we term “extant sequence reconstruction” (ESR). We thus can evaluate the accuracy of ASR methodology by comparing ESR reconstructions to the corresponding known true sequences. We find that a common measure of the quality of a reconstructed sequence, the average probability, is indeed a good estimate of the fraction of correct amino acids when the evolutionary model is accurate or overparameterized. However, the average probability is a poor measure for comparing reconstructions from different models, because, surprisingly, a more accurate phylogenetic model often results in reconstructions with lower probability. While better (more predictive) models may produce reconstructions with lower sequence identity to the true sequences, better models nevertheless produce reconstructions that are more biophysically similar to true ancestors. In addition, we find that a large fraction of sequences sampled from the reconstruction distribution may have fewer errors than the single most probable (SMP) sequence reconstruction, despite the fact that the SMP has the lowest expected error of all possible sequences. Our results emphasize the importance of model selection for ASR and the usefulness of sampling sequence reconstructions for analyzing ancestral protein properties. ESR is a powerful method for validating the evolutionary models used for ASR and can be applied in practice to any phylogenetic analysis of real biological sequences. Most significantly, ESR uses ASR methodology to provide a general method by which the biophysical properties of resurrected proteins can be compared to the properties of the true protein.

Influence of seed mass and shape on light plasticity of germination of alpine plants on the Tibetan Plateau: The role of photoblastic taxa, dispersal ability, and life history

Responses of post-disposal germination to light play a crucial role in shaping germination niches and determining the success of seedling establishment, ultimately impacting species distribution and community composition. Seed traits are pivotal factors that influence species' germination, dispersal, and life history strategies. However, it remains unclear whether the relationship between seed traits and the light plasticity of germination is regulated by factors such as life history, photoblastic taxa, and dispersal ability.We measured the seed shape and seed mass of 114 species on the grasslands of the Tibetan Plateau. Germination experiments were conducted under two light conditions: dark and light. We also classified species based on photoblastic taxa (photostimulation vs. photoinhibition), life history (annual vs. perennial), and dispersal ability (weak vs. strong). Phylogenetic structural equation models (SEM) were used to test the complex relationship between seed traits, life history, dispersal ability, and light plasticity.We found that neither seed mass nor shape differed between the two photoblastic taxa. Species with photostimulation taxa exhibited a greater light plasticity of germination compared with photoinhibition taxa. Non-spherical seeds (elongated or flat) possessed low light plasticity of germination. The relationship between seed mass and germination light plasticity varied in different photoblastic taxa. Specifically, in photostimulation species, increased seed mass was associated with higher light plasticity of germination, whereas in photoinhibition species, an opposite relationship was evident. Moreover, dispersal ability and life history indirectly influenced the light plasticity of germination via seed shape.Our results imply that different combinations of seed traits can shape germination strategies in response to light stimulation, which in turn may influence the germination niches differentiation and species persistence in soil. Furthermore, life history and dispersal ability can indirectly affect the light plasticity of germination, which implies that the reproductive strategy of species to adapt to the environment may be regulated by multi-faceted life history strategies.

The strength of the phylogenetic signal in syntactic data

While phonological change has played a central role in assessing linguistic relatedness since the nineteenth century, the usefulness of syntactic change for this purpose has remained debated – despite recent work on the question with a variety of results. In our study, we analyze the phylogenetic signal of syntactic data using state-of-the-art Bayesian algorithms and the SSWL database (Koopman 2012–). With the phylogenetic model, we infer a minimally biased family tree. We find that, generally, the phylogenetic signal in the syntactic dataset is low. The model fails to infer larger-order subgroupings that would be found further back in time. This is in contrast to the clear-cut groupings we can obtain from running this type of model on phonological databases. This raises the question how well these syntactic properties encode phylogenetic information. As it stands, the model fails to provide evidence for strong phylogenetic signal despite the rich dataset and methods.

Novel symmetry-preserving neural network model for phylogenetic inference.

Scientists world-wide are putting together massive efforts to understand how the biodiversity that we see on Earth evolved from single-cell organisms at the origin of life and this diversification process is represented through the Tree of Life. Low sampling rates and high heterogeneity in the rate of evolution across sites and lineages produce a phenomenon denoted "long branch attraction" (LBA) in which long nonsister lineages are estimated to be sisters regardless of their true evolutionary relationship. LBA has been a pervasive problem in phylogenetic inference affecting different types of methodologies from distance-based to likelihood-based. Here, we present a novel neural network model that outperforms standard phylogenetic methods and other neural network implementations under LBA settings. Furthermore, unlike existing neural network models in phylogenetics, our model naturally accounts for the tree isomorphisms via permutation invariant functions which ultimately result in lower memory and allows the seamless extension to larger trees. We implement our novel theory on an open-source publicly available GitHub repository: https://github.com/crsl4/nn-phylogenetics.

Scalable phylogenetic Gaussian process models improve the detectability of environmental signals on local extinctions for many Red List species

Abstract Conservation biologists have a daunting task of understanding the causes of species decline associated with anthropogenic factors and predicting the extinction risk of a growing number of endangered species. By reducing variances of estimates with information on closely related species, phylogenetic information among species can bridge gaps in information on species with small range sizes when modelling large numbers of endangered species. However, modelling many species with the Gaussian process (GP), which underlies the evolutionary process of phylogenetic random effects, remains a challenge owing to the computational burden in estimating the large variance–covariance matrix. Here, we applied a phylogenetic generalised mixed model with random slopes and random intercepts to 1010 endangered vascular plant taxa in Japan following phylogenetic GPs implemented by nearest neighbour GP (NNGP) approximation. NNGP enables flexibility in changing the proximity on the phylogenetic tree of species from which information is borrowed to reduce the variances of estimates with a realistic computational burden. We evaluated the effectiveness of phylogenetic models by comparing the predictive performance and descriptive power of phylogenetic and non‐phylogenetic models and identified the anthropogenic factors contributing to the decline of each of the studied endangered species. We found that the model with phylogenetic information had better prediction performance than the model without phylogenetic information. The results showed that across all explanatory variables, the phylogenetic model could detect interspecific differences in response to environmental factors in a number of species more clearly. Combined with the phylogenetic signal results, we could also detect a phylogenetic bias in the species that could benefit from the positive effects of protected areas but reduce the local extinctions of 95% of all studied taxa. In conclusion, our model, considering phylogenetic information with NNGP, allows the elucidation of factors causing the decline of many endangered species. In future analyses, the estimation of extinction probability linked to environmental change might be applied to future climate–land use scenarios, advancing the comprehensive assessment of biodiversity degradation and threats to species at multiple scales.

Genomic and Phylogenetic Characterisation of SARS-CoV-2 Genomes Isolated in Patients from Lambayeque Region, Peru.

this study aims to identify and characterise genomic and phylogenetically isolated SARS-CoV-2 viral isolates in patients from Lambayeque, Peru. Nasopharyngeal swabs were taken from patients from the Almanzor Aguinaga Asenjo Hospital, Chiclayo, Lambayeque, Peru, which had been considered mild, moderate, and severe cases of COVID-19. Patients had to have tested positive for COVID-19, using a positive RT-PCR for SARS-CoV-2. Subsequently, the SARS-CoV-2 complete viral genome sequencing was carried out using Illumina MiSeq®. The sequences obtained from the sequence were analysed in Nextclade V1.10.0 to assign the corresponding clades, identify mutations in the SARS-CoV-2 genes and perform quality control of the sequences obtained. All sequences were aligned using MAFFT v7.471. The SARS-CoV-2 isolate Wuhan NC 045512.2 was used as a reference sequence to analyse mutations at the amino acid level. The construction of the phylogenetic tree model was achieved with IQ-TREE v1.6.12. It was determined that during the period from December 2020 to January 2021, the lineages s C.14, C.33, B.1.1.485, B.1.1, B.1.1.1, and B.1.111 circulated, with lineage C.14 being the most predominant at 76.7% (n = 23/30). These lineages were classified in clade 20D mainly and also within clades 20B and 20A. On the contrary, the variants found in the second batch of samples of the period from September to October 2021 were Delta (72.7%), Gamma (13.6%), Mu (4.6%), and Lambda (9.1%), distributed between clades 20J, 21G, 21H, 21J, and 21I. This study reveals updated information on the viral genomics of SARS-CoV-2 in the Lambayeque region, Peru, which is crucial to understanding the origins and dispersion of the virus and provides information on viral pathogenicity, transmission and epidemiology.