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At least 19 recordsLinked to original sources
PubMed1977

Complexity of branching dendritic trees: dependence on number of trees per cell and effects of branch loss during sectioning.

We have investigated whether the complexity of dendritic trees is correlated with the number of primary dendrites per neuron (trees per cell). In estimating the average number of branches of centrifugal orders 1-5 per tree we used statistical methods to compensate for loss of parts of trees during sectioning. Limitations of these methods are discussed. Neurons from four populations, stained by the Golgi-Cox method, were examined: stellate cells from layer IV, area 17 of visual cortex, in normal and dark-reared cats; the pyramidal cells from layer V, somatosensory cortex, in two strains of rats. In all four groups of neurons the average number of branches of higher orders (3, 4, 5) per tree tended to be smaller in neurons bearing more trees. Thus all trees from a population of neurons should not be assumed to be equivalent. The decreasin high-order branches per tree tended to offset the increase in number of trees per cell. In three of the four groups these opposed tendencies maintained the average number of high-order branches per neuron nearly independent of the number of trees per cell. Natural selection may have favoured near-constancy in the number of high-order branches to reduce dispersion among neurons of one type in functional input-output rleations.

Animals↗
PubMed2026

Population history rather than tree age contributes to the evolutionary importance of ancient trees in an endangered conifer.

Ancient trees are in global decline and face increasing conservation challenges. Their exceptional longevity has fostered the view that they are genetic reservoirs, yet whether old age is synonymous with unique genetic variation remains unclear. Here we assembled a ~8-Gb chromosome-level reference genome for the critically endangered conifer Glyptostrobus pensilis, now largely restricted to southern China with scattered populations in Vietnam and Laos, and resequenced 147 individuals, including 64 ancient (>100 years old and persisting in human-dominated landscapes), 33 wild and 50 recently cultivated individuals. Ancient individuals comprised both likely natural relics and historically introduced individuals and formed two deeply divergent lineages and one ancestral-admixed group, each with distinct demographic histories of prolonged contraction and genomic erosion. Lineage identity explained more variation in genome-wide diversity, inbreeding and genetic load than the three conservation types, despite broad differences in age structure. Rare-allele analyses revealed pronounced heterogeneity among ancient trees: only relic and ancestral-origin individuals from high-diversity lineages contributed substantial unique variation, much of which is poorly represented in wild and cultivated populations. Together, our findings suggest that ancient trees are not uniformly genetically irreplaceable and that, at least in this conifer, evolutionary importance is shaped more strongly by population history than by age alone.

Endangered Species↗
PubMed2026

The impact of non-native trees on galling and herbivory in New York City across space and time.

Cities and suburbs frequently plant native and non-native trees as foundation species, with non-natives cultivated in these areas for centuries while remaining non-invasive. Although previous research has found that native trees often host more arthropods, studies have not simultaneously looked across space and time to determine the consistency of tree origin on urban arthropods. We combined varied methods across spatial and temporal scales in New York City to test if native tree leaves consistently have more insect and mite interactions than long-established non-native trees, predicting stronger effect sizes for specialists (galling arthropods) than generalists (herbivory). We examined (1) congeneric species pairs, controlled for growing conditions and stoichiometry in an arboretum, (2) diverse oaks at a botanical garden, (3) community science records across Brooklyn, and (4) herbarium specimens from 1883 through present across the city. Across spatiotemporal scales, we found consistent results. Specialist interactions were striking: contemporary native trees supported numerous galling species, while only one congeneric non-native species hosted any galls. For generalists, contemporary native trees had equivalent to slightly greater herbivory. Over the last century, herbarium records showed that herbivory increased on non-native trees to nearly the level of natives, whereas native trees increased in gall abundance while non-native trees remained rarely galled. Our results demonstrate the impact of tree origin on tree-arthropod interactions in a real-world urban setting, with far fewer galls even when non-native tree species have been cultivated locally for centuries. Our findings will help city planners and property owners confidently choose native trees to promote arthropod biodiversity.

Trees↗
PubMed1979

A general approach to proving the minimality of phylogenetic trees illustrated by an example with a set of 23 vertebrates.

We have recently described a method of building phylogenetic trees and have outlined an approach for proving whether a particular tree is optimal for the data used. In this paper we describe in detail the method of establishing lower bounds on the length of a minimal tree by partitioning the data set into subsets. All characters that could be involved in duplications in the data are paired with all other such characters. A matching algorithm is then used to obtain the pairing of characters that reveals the most duplications in the data. This matching may still not account for all nucleotide substitutions on the tree. The structure of the tree is then used to help select subsets of three or more characters until the lower bound found by partitioning is equal to the length of the tree. The tree must then be a minimal tree since no tree can exist with a length less than that of the lower bound. The method is demonstrated using a set of 23 vertebrate cytochrome c sequences with the criterion of minimizing the total number of nucleotide substitutions. There are 131130 7045768798 96033440625 topologically distinct trees that can be constructed from this data set. The method described in this paper does identify 144 minimal tree variants. The method is general in the sense that it can be used for other data and other criteria of length. It need not however always be possible to prove a treee minimal but the method will give an upper and lower bound on the length of minimal trees.

Amino Acid Sequence↗
PubMed2026

Treemble: a graphical tool to generate Newick strings from phylogenetic tree images.

SUMMARY: Phylogenetic trees are ubiquitous and central to biology, but most published trees are available only as visual diagrams and not in the machine-readable Newick format. There are, thus, thousands of published trees in the scientific literature that are unavailable for follow-up analyses, comparisons, and supertree construction. Experts can easily read such diagrams, but the manual construction of a Newick string from a diagram is laborious, error-prone, and time-consuming. Previous attempts to semi-automate the reading of tree images relied on image processing techniques. These often encounter difficulties as typical published tree diagrams contain various graphical elements and annotations that overlap the branches, such as error bars on internal nodes. Here we introduce Treemble, a user-friendly desktop application for generating Newick strings from tree images. The user simply clicks to mark node locations, assisted by a deep learning-based node detection tool, and Treemble algorithmically assembles the tree from the node coordinates alone. Treemble also facilitates the automatic reading of tip name labels and can be used for both rectangular and circular trees. AVAILABILITY AND IMPLEMENTATION: Treemble is a native desktop application for macOS and Windows and is freely available, with documentation, at treemble.org. Source code is available at github.com/John-Allard/Treemble. The trained node detection model is available at huggingface.co/John-Allard/treemble-1.

Phylogeny↗
PubMed2026

LAML-Pro: joint maximum likelihood inference of cell genotypes and cell lineage trees.

MOTIVATION: Recent dynamic lineage tracing technologies use genome editing to induce heritable mutations, or edits, that accumulate across successive cell divisions. These edits are measured using single-cell sequencing or imaging, providing data to reconstruct cell lineages at single-cell resolution. Current computational approaches to infer cell lineage trees, or phylogenies, from these data perform two separate steps: (i) Identify each cell's edits (genotype) from the raw sequencing or imaging data; (ii) Infer a cell lineage tree from the cell genotypes. However, genotyping cells is an inexact process and genotype errors can yield an inaccurate lineage tree. For example, using fluorescence based-imaging to measure edits results in a high fraction (≈25%-50%) of uncertain or erroneous genotypes. RESULTS: We introduce Lineage Analysis via Maximum Likelihood with PRobabilistic Observations (LAML-Pro), an algorithm that jointly infers cell genotypes and a cell lineage tree. LAML-Pro is based on the Probabilistic Mixed-type Missing Observation (PMMO) model, which we derive to describe both the genome editing and genotype observation processes. LAML-Pro constructs lineage trees from thousands of cells in under an hour by leveraging the sparsity of transitions under the PMMO model. On simulated data, we demonstrate that LAML-Pro corrects genotype errors and infers substantially more accurate trees than existing methods which are vulnerable to genotype errors. Applied to data from two recent imaging-based lineage tracing systems, LAML-Pro reduces genotype errors by 5-fold and produces more spatially coherent lineage trees compared to existing methods. AVAILABILITY AND IMPLEMENTATION: LAML-Pro is implemented in C++ and is available as both a command-line interface and as a Python library at: github.com/raphael-group/LAML-Pro.

Cell Lineage↗
PubMed2026

LAML-Pro: Joint Maximum Likelihood Inference of Cell Genotypes and Cell Lineage Trees.

MOTIVATION: Recent dynamic lineage tracing technologies use genome editing to induce heritable mutations, or edits, that accumulate across successive cell divisions. These edits are measured using single-cell sequencing or imaging, providing data to reconstruct cell lineages at single-cell resolution. Current computational approaches to infer cell lineage trees, or phylogenies, from these data perform two separate steps: (1) Identify each cell's edits (genotype) from the raw sequencing or imaging data; (2) Infer a cell lineage tree from the cell genotypes. However, genotyping cells is an inexact process and genotype errors can yield an inaccurate lineage tree. For example, using fluorescence based-imaging to measure edits results in a high fraction (≈ 25-50%) of uncertain or erroneous genotypes. RESULTS: We introduce Lineage Analysis via Maximum Likelihood with PRobabilistic Observations (LAML-Pro), an algorithm that jointly infers cell genotypes and a cell lineage tree. LAML-Pro is based on the Probabilistic Mixed-type Missing Observation (PMMO) model, which we derive to describe both the genome editing and genotype observation processes. LAML-Pro constructs lineage trees from thousands of cells in under an hour by leveraging the sparsity of transitions under the PMMO model. On simulated data, we demonstrate that LAML-Pro corrects genotype errors and infers substantially more accurate trees than existing methods which are vulnerable to genotype errors. Applied to data from two recent imaging-based lineage tracing systems, LAML-Pro reduces genotype errors by 5-fold and produces more spatially coherent lineage trees compared to existing methods. AVAILABILITY AND IMPLEMENTATION: LAML-Pro is freely available at: github.com/raphael-group/LAML-Pro.

Journal Article↗
PubMed2026

Bit-reproducible parallel phylogenetic tree inference.

MOTIVATION: Phylogenetic trees describe the evolutionary history among biological species based on their genomic data. Maximum likelihood (ML) based phylogenetic inference tools search for the tree and evolutionary model that best explain the observed genomic data. Given the independence of likelihood score calculations between different genomic sites, parallel computation is commonly deployed. This is followed by a parallel summation over the per-site scores to obtain the overall likelihood score of the tree. However, basic arithmetic operations on IEEE 754 floating-point numbers, such as addition and multiplication, inherently introduce rounding errors. Consequently, the order by which floating-point operations are executed affects the exact resulting likelihood value since these operations are not associative. Moreover, parallel reduction algorithms in numerical codes re-associate operations as a function of the core count and cluster network topology, inducing different round-off errors. These low-level deviations can cause heuristic searches to diverge and induce high-level result discrepancies (e.g. yield topologically distinct phylogenies). This effect has also been observed in multiple scientific fields beyond phylogenetics. RESULTS: We observe that varying the degree of parallelism results in diverging phylogenetic tree searches (high-level results) for over 31% out of 10&#xa0;179 empirical datasets. More importantly, 8% of these diverging datasets yield trees that are statistically significantly worse than the best-known ML tree for the dataset (AU-test, P&#x2009;<&#x2009;.05). To alleviate this, we develop a variant of the widely used phylogenetic inference tool RAxML-NG, which does yield bit-reproducible results under varying core-counts, with a slowdown of only 0%-12.7% (median 0.8%) on up to 768 cores. For this, we introduce the ReproRed reduction algorithm, which yields bit-identical results under varying core-counts, by maintaining a fixed operation order that is independent of the communication pattern. ReproRed is thus applicable to all associative reduction operations-in contrast to competitors, which are confined to summation. Our ReproRed reduction algorithm only exchanges the theoretical minimum number of messages, overlaps communication with computation, and utilizes fast base-cases for local reductions. ReproRed is able to all-reduce (via a subsequent broadcast) 4.1&#xd7;106 operands across 48-768 cores in 19.7-48.61&#x2009;&#x3bc;s, thereby exhibiting a slowdown of 13%-93% over a non-reproducible all-reduce algorithm. ReproRed outperforms the state-of-the-art reproducible all-reduction algorithm ReproBLAS (offers summation only) beyond 10&#xa0;000 elements per core. In summary, we re-assess non-reproducibility in parallel phylogenetic inference, present the first bit-reproducible parallel phylogenetic inference tool, as well as introduce a general algorithm and open-source code for conducting reproducible associative parallel reduction operations. AVAILABILITY AND IMPLEMENTATION: ReproRed: https://doi.org/10.5281/zenodo.15004918 (LGPL)-Reproducible RAxML-NG version https://doi.org/10.5281/zenodo.15017407 (GPL).

Phylogeny↗
PubMed2026

Comparing ARG Inference Methods Under Transmission of Reproductive Success: Tree Imbalance Matters.

Inferring coalescent trees from genomic data has become a major subject in population genetics, particularly with the recent advances in tree sequence reconstruction methods. However, it remains unclear how well these methods perform for imbalanced genealogies. Such imbalances can arise from processes such as cultural transmission of reproductive success (CTRS) or positive selection. Using simulated genomic data, we benchmarked three major software packages, SINGER, Relate, and tsinfer, by comparing the imbalance of reconstructed trees by these methods with that of the true simulated trees, for three indices that quantify this imbalance. The three methods performed well under scenarios yielding balanced trees. However, their accuracy declined as imbalance increased. Performances also varied with mutation rate, recombination rate, and sample size. This study opens possibilities for applying these methods to infer CTRS or positive selection in large-scale genomic datasets, using simulation-based inference such as approximate Bayesian computation.

Models, Genetic↗
PubMed2026

Biocontrol Potential and Mechanism of Endophytic Bacillus velezensis WSR1 Against Rubber Tree Anthracnose.

Fungal leaf anthracnose, caused by Colletotrichum species, is a major leaf disease of rubber trees, significantly reducing global natural rubber yields. To explore sustainable and safe biological control strategies, eight bacterial strains were isolated from rubber tree tissues, demonstrating antagonistic activity against Colletotrichum pathogens (C. siamense and C. australisinense). Among these, WSR1 exhibited the most pronounced antifungal effect, with inhibition rates of 87.64 and 89.03% against C. siamense and C. australisinense, respectively. Genomic analysis identified WSR1 as Bacillus velezensis. In pot experiments, WSR1 exhibited preventive efficacy of 77.24 and 73.42% for C. siamense- and C. australisinense-induced anthracnose, respectively, with therapeutic efficacy of 42.28 and 45.57%. WSR1 compromised the integrity of the cell walls and membranes of both C. siamense and C. australisinense, while inducing reactive oxygen species accumulation within the hyphae. Additionally, WSR1 enhanced rubber tree resistance to anthracnose by activating defense-related enzymes, including phenylalanine ammonia-lyase, polyphenol oxidase, and peroxidase. Plate assays and genomic analysis revealed that WSR1 secretes fungal cell wall-degrading enzymes (cellulases, pectinases, and proteases) and siderophores. Furthermore, liquid chromatography-mass spectrometry and gene cluster analysis confirmed the synthesis of antagonistic secondary metabolites, such as surfactin, macrolactin H, and fengycin. This study represents the first identification of B. velezensis as a potential biocontrol agent against rubber tree anthracnose, offering a promising candidate for the eco-friendly management of rubber tree diseases.

C. australisinense↗
PubMed2025

CRISPR RNP-Mediated Transgene-Free Genome Editing in Plants: Advances, Challenges and Future Directions for Tree Species.

CRISPR ribonucleoprotein (RNP)-mediated genome editing offers a transgene-free platform for precise genetic modification in diverse herbaceous and tree species, including rice, wheat, apple, poplar, oil palm, rubber tree and grapevine. However, its application in woody plants faces distinct challenges, notably inefficient delivery and regeneration difficulties, particularly in species such as bamboo. While some of these issues also occur in herbaceous plants, they are often significantly more complex in woody species due to factors such as intricate cell wall architecture, widespread recalcitrant genotypes and inherent limitations of current delivery platforms. This review presents the first in-depth, critical re-evaluation of recent advancements in RNP-mediated editing in woody plants, highlighting these obstacles that warrant focused attention. Unlike plasmid-based CRISPR systems, RNP editing utilises Cas9/Cas12a protein-guide RNA complexes without integrating foreign DNA. This enables a DNA-free editing strategy that simplifies regulatory approval and minimises off-target effects due to the transient presence and rapid degradation of RNPs within plant cells. While PEG-mediated protoplast transfection and particle bombardment remain the primary reported methods for RNP delivery in trees, we evaluate promising alternative strategies such as lipofection, electroporation, cell-penetrating peptides and nanoparticle-based systems for targeted RNP delivery. Despite their promise, these advanced methods remain largely untested in woody species. Finally, we outline future research directions, including the development of tree-specific RNP delivery systems and regeneration protocols to enhance efficiency and minimise cytotoxicity. These innovations are essential for unlocking the full potential of RNP-mediated genome editing in long-lived tree species. This review provides a focused and timely roadmap for expanding the application of RNP technology across diverse woody plants.

Gene Editing↗
PubMed1977

The House-Tree-Person Test as a measure of intelligence and creativity.

The House-Tree-Person test and a verbal test of mental ability, the Basic Word Vocabulary Test, were administered to 23 male and 27 female, university undergraduates and to 27 boys and 38 girls in Grades 3 to 8. The drawings were given three separate and independent scorings by judges who computed intelligence scores according to the House-Person manual; rated them impressionistically on intelligence, using a forced-distribution method; or rated them impressionistically on creativity, using the same forced-distribution method. The three House-Tree-Person measures were highly intercorrelated for all groups of subjects. All three House-Tree-Person scores also correlated positively and significantly with vocabulary test scores for female university students, as did both Impressionistically derived House-Tree-Person scores for grade-school girls. Male students' and boys' vocabulary scores were unrelated to any of the House-Tree-Person scores. Results suggest that competence in graphic expression operates independently of verbal intelligence in males but validity as a nonverbal test of mental ability and that it can be scored efficiently and reliably by using a global, impressionistic method.

Adult↗
PubMed2025

Beyond Level-1: Identifiability of a Class of Galled Tree-Child Networks.

Inference of phylogenetic networks is of increasing interest in the genomic era. However, the extent to which phylogenetic networks are identifiable from various types of data remains poorly understood, despite its crucial role in justifying methods. This work obtains strong identifiability results for large sub-classes of galled tree-child semidirected networks. Some of the conditions our proofs require, such as the identifiability of a network's tree of blobs or the circular order of 4 taxa around a cycle in a level-1 network, are already known to hold for many data types. We show that all these conditions hold for quartet concordance factor data under various gene tree models, yielding the strongest results from 2 or more samples per taxon. Although the network classes we consider have topological restrictions, they include non-planar networks of any level and are substantially more general than level-1 networks - the only class previously known to enjoy identifiability from many data types. Our work establishes a route for proving future identifiability results for tree-child galled networks from data types other than quartet concordance factors, by checking that explicit conditions are met.

Mathematical Concepts↗
PubMed1979

Calculation of evolutionary trees from sequence data.

Evolutionary trees are usually calculated from comparisons of protein or nucleic acid sequences from present-day organisms by use of algorithms that use only the difference matrix, where the difference matrix is constructed from the sequence differences between pairs of sequences from the organisms. The difference matrix alone cannot define uniquely the correct position of the ancestor of the present-day organisms (root of the tree). Furthermore, methods using the difference matrix alone often fail to give the correct pattern of tree branching (topology) when the different sequences evolve at different rates. Only for equal rates of evolution can the difference matrix (when used with the so-called matrix method) yield exactly the correct topology and root. In this paper we present a method for calculating evolutionary trees from sequence data that uses, along with the difference matrix, the rate of evolution of the various sequences from their common ancestor. It is proven analytically that this method uniquely determines both the correct topology and root in theory for unequal rates of sequence evolution. How one would estimate an ancestral sequence to be used in the method is discussed in particular for the 5S RNA sequences from prokaryotes and eukaryotes and for ferredoxin sequences.

Amino Acid Sequence↗
PubMed2025

Bayesian inference of fitness landscapes via tree-structured branching processes.

MOTIVATION: The complex dynamics of cancer evolution, driven by mutation and selection, underlies the molecular heterogeneity observed in tumors. The evolutionary histories of tumors of different patients can be encoded as mutation trees and reconstructed in high resolution from single-cell sequencing data, offering crucial insights for studying fitness effects of and epistasis among mutations. Existing models, however, either fail to separate mutation and selection or neglect the evolutionary histories encoded by the tumor phylogenetic trees. RESULTS: We introduce FiTree, a tree-structured multi-type branching process model with epistatic fitness parameterization and a Bayesian inference scheme to learn fitness landscapes from single-cell tumor mutation trees. Through simulations, we demonstrate that FiTree outperforms state-of-the-art methods in inferring the fitness landscape underlying tumor evolution. Applying FiTree to a single-cell acute myeloid leukemia dataset, we identify epistatic fitness effects consistent with known biological findings and quantify uncertainty in predicting future mutational events. The new model unifies probabilistic graphical models of cancer progression with population genetics, offering a principled framework for understanding tumor evolution and informing therapeutic strategies. AVAILABILITY AND IMPLEMENTATION: The Python package FiTree and the analysis workflows are available at https://github.com/cbg-ethz/FiTree.

Bayes Theorem↗
PubMed1976

Induction of liver tumors by aflatoxin B1 in the tree shrew (Tupaia glis), a nonhuman primate.

The epidemiological studies suggest that aflatoxins, the toxic metabolites of the ubiquitous mold Aspergillus flavus, may play a significant role in the evolution of hepatocellular carcinoma in man in certain geographic areas of the world. To ascertain their carcinogenicity in nonhuman primates, we have administered highly purified aflatoxin B1, intermittently in the diet at 2 ppm, to 10 female and 8 male tree shrews. The tree shrew (Tupaia glis) is a nonhuman primate occurring throughout Southeast Asia which can be reared easily in captivity. Of 12 animals that survived, 6 of 6 female (100%) and 3 of 6 male (50%) tree shrews developed hepatocellular carcinomas between 74 and 172 weeks after the beginning of the experiment. None of the 8 control animals developed liver cancers. The estimated total amount of aflatoxin B1 consumed by these animals ranged from 24 to 66 mg. The development of liver tumors did not follow a specific pattern; considerable variation in hepatocellular responses to aflatoxin B1 was noted in these animals. In 2 tree shrews, the liver tumors were associated with severe post necrotic scarring; in the other 7 tumor-bearing livers, only mild to moderate portal fibrosis was encountered. This individual variation in hepatocellular response and in the amount of aflatoxin B1 required to induce hepatocellular carcinomas is attributed to inherent differences in the susceptibility within a given species of outbred animals and suggests extreme caution in proposing the "permissible" or "safe" levels of contamination of carcinogens in the food-stuffs.

Aflatoxins↗
PubMed1976

The lead, copper and zinc content of tree rings and bark. A measurement of local metallic pollution.

Analysis of samples of wood taken from different tree rings for lead by atomic absorption spectrometry showed that there was little correlation between the sample site or ring age and air borne lead concentrations. However, the concentration of lead in tree bark at several sites was particularly sensitive to traffic flow at that site. The concentration of lead, zinc and copper in the tree bark decreased with increased distance from the road and with height above the ground. The method offers a simple technique for effectively tracing atmospheric metal concentrations.

Air Pollutants↗