Biology subjects

Xie, D.

Publications and source records attributed to Xie, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Structural basis of RNA-guided transcription by a dCas12f-σE-RNAP complex

RNA-guided proteins have emerged as critical transcriptional regulators in both natural and engineered biological systems by modulating RNA polymerase (RNAP) and its associated factors1-3. In bacteria, di-verse clades of repurposed TnpB and CRISPR-associated proteins repress gene expression by blocking transcription initiation or elongation, enabling non-canonical modes of regulatory control and adaptive immunity1,4,5. Intriguingly, a distinct class of nuclease-dead Cas12f homologs (dCas12f) instead activates gene expression through its association with unique extracytoplasmic function sigma factors ({sigma}E)6, though the molecular basis has remained elusive. Here we reveal a novel mode of RNA-guided transcription initiation by determining cryo-electron microscopy structures of the dCas12f-{sigma}E system from Flagellimonas taeanensis. We captured multiple conformational and compositional states, including the DNA-bound dCas12f-{sigma}E-RNAP holoenzyme complex, revealing how RNA-guided DNA binding leads to {sigma}E-RNAP recruitment and nascent mRNA synthesis at a precisely defined distance downstream of the R-loop. Rather than following the classical paradigm of {sigma}E-dependent promoter recognition, these studies show that recognition of the -35 element is largely supplanted by CRISPR-Cas targeting, while the melted -10 element is stabilized through unusual stacking interactions rather than insertion into the typical recognition pocket. Collectively, this work provides high-resolution insights into an unexpected mechanism of RNA-guided transcription, expanding our understanding of bacterial gene regulation and opening new avenues for pro-grammable transcriptional control.

biochemistry↗

bioRxiv2025

Sequential Amino Acid Mutagenesis-Driven De Novo Evolution of Adenine Deaminases Enables Efficient In Vivo Base Editing in Primate

Base editing allows for the precise modification of genetic information, providing new avenues for treating diseases1. The adenine base editor ABE8e is currently the most efficient and widely used tool for adenine base editing. ABE8e was developed through multiple rounds of directed evolution of Escherichia coli tRNA adenine deaminase, including phage-assisted continuous evolution (PACE)2,3. While PACE is highly effective, it is a complex system that poses challenges for implementation4. Despite its high efficiency, ABE8e is associated with limitations such as relatively higher bystander editing effects and elevated off-target activity5, which need to be addressed to further enhance its precision and safety. Here, we developed a novel method for the de novo discovery of evolved ABE components, particularly adenine deaminases. This process involves identifying candidate proteins through AI-based structural prediction and clustering, followed by the enhancement of deaminase editing activity through screening libraries created by sequential amino acid saturation mutagenesis. This evolutionary strategy simplifies the approach by employing saturation mutagenesis libraries tailored to specific segments, thereby enabling exploration of an expanded sequence space and increasing the likelihood of discovering adenine deaminases with superior capabilities. The newly developed hpABE5.20 here demonstrates a more refined editing window, reduced DNA off-target effects that are both sgRNA-dependent and -independent, and minimized RNA off-target activity, while maintaining robust editing efficiency relative to ABE8e. Furthermore, hpABE5.20 has been successfully applied for precise and effective therapeutic adenine base editing in cellular disease models, humanized mice, and non-human primates.

bioengineering↗

bioRxiv2025

STM is required for fate establishment of productive shoot progenitor cells in Arabidopsis tissue culture

De novo shoot regeneration via the two-step tissue culture method is widely used for vegetative reproduction of plants and for gene transformation and editing. A key step in tissue culture is the fate transition from shoot progenitor cells (SPCs) to productive SPCs (prSPCs), which are capable of differentiating into a shoot. In this study, we identified the class I KNOTTED1-like homeobox (KNOX) transcription factor gene SHOOT-MERISTEMLESS (STM) as the key controller of, and marker gene for, the fate transition from SPCs into prSPCs, indicating that STM might serve as a candidate of molecular tools to improve de novo shoot regeneration in the agricultural applications.

plant biology↗

bioRxiv2025

Intratumoral Resident Microbes Directly Participate in Resistance to EGFR-TKI Targeted Drug Therapy through Metabolism in NSCLC

EGFR-TKIs targeted therapy represents a cornerstone in the treatment of non-small cell lung cancer (NSCLC). Nonetheless, a subset of patients inevitably develops acquired resistance to EGFR-TKIs, posing a significant clinical challenge. An increasing number of evidence has documented the presence of microbial communities within tumor microenvironments, but the potential interplay between tumor-resident microbiota and resistance to EGFR-TKIs remains poorly understood. Here, we report that prolonged EGFR-TKIs treatment markedly alters the diversity of tumor-resident microbiota, characterized by a notable enrichment of Bacillus mycoides and Pseudomonas veronii. In vitro experiments revealed that co-culture of gefitinib with either B. mycoides or P. veronii significantly attenuated its tumor-suppressive efficacy, both in vitro and in vivo. Mechanistically, gefitinib underwent extensive biotransformation in the presence of these bacteria, yielding redox derivatives and conjugation products, which collectively diminished its antitumor activity. Specifically, B. mycoides metabolized gefitinib into B.mPM9-C33 H45 Cl F N3 O4, while P. veronii generated P.vPM2-C24 H29 Cl N4 O3, both of which were consistently detected in in vivo and in vitro models. Furthermore, heterologous expression of maltose acetyltransferase from B. mycoides in E. coli BL21 conferred the capacity to metabolize gefitinib, underscoring the enzymatic basis of this metabolic conversion. Collectively, these findings demonstrate that B. mycoides and P. veronii drive tumor resistance to EGFR-TKIs through metabolic inactivation of the drug, unveiling a previously unrecognized role of tumor-resident microbiota in modulating therapeutic responses and providing novel insights into the mechanisms underlying EGFR-TKIs resistance in NSCLC.

microbiology↗

bioRxiv2025

Bayesian model-averaging of parametric coalescent models for phylodynamic inference

Bayesian phylodynamic models have become essential for reconstructing population history from genetic data, yet their accuracy depends crucially on choosing appropriate demographic models. To address uncertainty in model choice, we introduce a Bayesian Model Averaging (BMA) framework that integrates multiple parametric coalescent models- including constant, exponential, logistic, and Gompertz growth-along with their "expansion" variants that account for non-zero ancestral populations. Implemented in a Bayesian setting with Metropolis-coupled MCMC, this approach allows the sampler to switch among candidate growth functions, thereby capturing demographic histories without having to pre-specify a single model. Simulation studies verify that the logistic and Gompertz models may require specialised sampling strategies such as adaptive multivariate proposals to achieve robust mixing. We demonstrate the performance of these models on datasets simulated under different substitution models, and show that joint inference of genealogy and population parameters is well-calibrated when properly incorporating correlated-move operators and BMA. We then apply this method to two real-world datasets. Analysis of Egyptian Hepatitis C virus (HCV) sequences indicates that models with a founder population followed by a rapid expansion are well supported, with a slight preference for Gompertz-like expansions. Our analysis of a single metastatic colorectal cancer (CRC) single-cell dataset suggests that exponentiallike growth is plausible even for an advanced stage cancer patient. We believe this highlights that tumour subclones may retain substantial proliferative capacity into the later stages of the disease. Overall, our unified BMA framework reduces the need for restrictive model selection procedures and can also provide deeper biological insights into epidemic spread and tumour evolution. By systematically integrating multiple growth hypotheses within a standard Bayesian setting, this approach naturally avoids overfitting and offers a powerful tool for inferring population histories across diverse biological domains.

evolutionary biology↗

bioRxiv2025

Somatic repetitive element insertions Define New Biomarkers in Pan-cancer genome

Repetitive elements insertions (REIs), including tandem repeat insertions (TRIs) and transposable element insertions (TEIs), constitute >90% of large-scale (>50bp) somatic insertions and are linked to diseases and cancer biomarkers. However, the genomic landscape of large-scale REIs in pan-cancer has not been well-characterized due to short-read sequencing limitations. Here, we detected somatic REIs in 325 cancer genomes across 12 cancer types using long-read whole-genome sequencing and customized algorithms. The diverse sequence patterns of somatic TRIs and the insertion mechanisms of somatic TEIs were characterized across different cancer types. We identified 152 high-frequency somatic TRIs, with 10 showing pan-cancer characteristics, including TRIs in SHROOM2, PALMD, and the enhancer of PTPRZ1. The MHC class II gene cluster exhibited the highest somatic TEI abundance, affecting [~]40% tumors. Adenocarcinomas and squamous cell carcinomas exhibited differing TEI distributions within this region. Our study highlights REIs as important but under-explored markers for personalized cancer diagnosis and immunotherapy.

genomics↗

bioRxiv2025

Accurate Somatic SV detection via sequence graph model-based local pan-genome optimization

Somatic structural variations (SVs) are critical genomic alterations in cancer genomes. Long-read sequencing (LRS) is theoretically optimal for detecting somatic SVs. However, influenced by reads-to-reference alignment errors, particularly in low-complexity or highly repetitive genomic intervals, current LRS-based somatic SV callers fail to accurately detect SVs. Moreover, the lack of comprehensive ground-truth datasets hinders accurate evaluation. Here, we introduce SVscope, a novel algorithm that fundamentally addresses these challenges by leveraging full-length sequence information from span-reads and integrating local graph-genome optimization with a random forest strategy. SVscope outperforms state-of-the-art methods on six paired long-read whole-genome sequencing (WGS) benchmark cell lines, achieving a maximum F1-score improvement of 16.7%. In simulated datasets, SVscope demonstrates superior performance in both somatic SV detection and read phasing tasks. Based on the findings from SVscope, we validated 47 somatic SVs, thereby significantly expanding the existing experimentally validated ground-truth somatic SV dataset by 69.1%.

bioinformatics↗

bioRxiv2025

CD4+ Mucosal-associated Invariant T (MAIT) cells express highly diverse T cell receptors

Mucosal-associated invariant T cells are highly conserved innate-like T cells in mammals recognized for their high baseline frequency in human blood and cytotoxic effector functions during infectious diseases, autoimmunity, and cancer. While the majority of these cells express a conserved CD8{beta}+ TRAV1-2 T cell receptor recognizing microbially-derived Vitamin B2 intermediates presented by the evolutionarily conserved major histocompatibility complex I-related molecule, MR1, there is an emerging appreciation for diverse subsets that may be selected for in humans with distinct functions, including subpopulations that co-express CD4. Prior work has not examined T cell receptor (TCR) heterogeneity in CD4+ MAIT cells, largely due to bias of identifying human MAIT cells as CD8+ TRAV1-2+ cells. In this study, we adopted an unbiased single-cell TCR-sequencing approach of total MR1-5-OP-RU-tetramer-reactive T cells and discovered that CD4+ MAIT cells express highly diverse TRAV1-2 negative TCRs. To specifically characterize this TCR repertoire, we analyzed VDJ sequences of single MR1-5-OP-RU tetramer+ MAIT cells across two datasets and identified distinct TCR usage among CD4+ MAIT cells including TRAV21, TRAV8 (TRAV8-1, TRAV8-2, TRAV8-3), and TRAV12 families (TRAV12-2, TRAV12-3), as well as more variable J chain and CDR3 sequences. Non-TRAV1-2 MAIT cell TCRs were also enriched after in vitro expansion, including with Mycobacterial tuberculosis. These results indicate that mature human CD4+ MAIT cells adopt distinct TCR usage from the canonical TRAV1-2+ CD8+ subset and suggest that alternative MR1 ligands in addition to riboflavin intermediates may select them.

genomics↗

bioRxiv2025

Dual Probe Ligation In Situ Hybridization with Rolling-Circle Amplification for High-Plex Spatial Transcriptomics

New biological insights are increasingly dependent upon a deeper understanding of tissue architectures. Critical to such studies are spatial transcriptomics technologies, especially those amenable to analysis of the most widely available human tissue type, formalin-fixed and paraffin-embedded (FFPE) clinical specimens. Here we build on our previous oligonucleotide probe ligation-based approach to accurately analyze FFPE mRNA, which suffers from variable levels of degradation. Ligation In Situ Hybridization followed by rolling circle amplification (LISH-LocknRoll or LISH-LnR), provides a streamlined method to detect the spatial location of specific mRNA isoforms within FFPE tissue architectures. Iterative fluorescent probe hybridization and imaging enables highly multiplexed spatial transcriptomic studies, as demonstrated herein for fixed specimens from inclusion body myositis patients and pediatric rhabdomyosarcoma patients. We additionally demonstrate a system of molecular rheostats that can be used to fine tune the performance of the LISH-LnR assay. Combined with LISH-seq and LISH-QC, the LISH-LnR methodology provides a powerful approach to spatial transcriptomics.

molecular biology↗

bioRxiv2025

pH adjustment increases biofuel production from inhibitory switchgrass hydrolysates

Biofuels derived from renewable and sustainable lignocellulosic biomass, such as switchgrass, offer a promising means to limit greenhouse gas emissions. However, switchgrass grown under drought conditions contains high levels of chemical compounds that inhibit microbial conversion to biofuels. Fermentation of drought switchgrass hydrolysates by engineered Saccharomyces cerevisiae and Zymomonas mobilis generates less ethanol than fermentation of hydrolyzed switchgrass from an average rainfall year. Here, we demonstrate that this inhibitory effect can be alleviated by altering the pH of drought-switchgrass hydrolysates made from two different pretreatment methods: Ammonia Fiber Expansion (AFEX) and Soaking in Aqueous Ammonia (SAA). Fermentation rates and biofuel production from AFEX- and SAA-pretreated switchgrass hydrolysates from normal and drought years were higher at pH 5.8 than at pH 5.0 for both Saccharomyces cerevisiae and Zymomonas mobilis. Additionally, SAA pretreatment of drought switchgrass enabled increased fermentation rates and titers compared to AFEX pretreatment. Using a synthetic mimic of switchgrass hydrolysate, we identified relief from pH-dependent inhibition by lignocellulose-derived inhibitors as the cause of increased biofuel production above a pH of 5.0. These results demonstrate that SAA pretreatment and pH adjustment can significantly improve fermentation and biofuel production from switchgrass hydrolysates and especially from drought-switchgrass hydrolysates by industrial microorganisms.

microbiology↗

bioRxiv2024

A Multi-Property Optimizing Generative Adversarial Network for de novo Antimicrobial Peptide Design

Antimicrobial peptides (AMPs) play a crucial role in developing novel antiinfective drugs due to their broad-spectrum antimicrobial activity and lower likelihood of causing bacterial resistance. However, laboratory synthesis of AMPs is tedious and time-consuming. Existing computational methods have limited capability in optimizing multiple desired properties simultaneously. Here, we propose a Multi-Property Optimizing Generative Adversarial Network (MPOGAN), a feedback-loop framework that iteratively learns from data with multiple desired properties. This approach enables de novo design of AMPs with potent antimicrobial activity, reduced cytotoxicity, and diversity. Through extensive computational tests, MPOGAN exhibits superior performance in optimizing multiple desired properties of generated AMPs. Ten of the most promising candidates are chemically synthesized, with nine showing potent antimicrobial activity against three bacterial strains and low cytotoxicity against eukaryotic cells. MPOGAN offers a powerful computational approach for effective multi-property optimization of AMPs, thereby advancing the field of AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

In vivo genome editing of human hematopoietic stem cells for treatment of blood disorders by mRNA delivery

Ex vivo autologous hematopoietic stem cells (HSCs) gene therapy provides promising new treatments for hematological disorders. However, current methods involve complex processes and chemotherapeutic conditioning, leading to limited accessibility for treatment and significant side effects. Here, we developed an antibody-free targeted lipid nanoparticles (LNPs) for mRNA delivery to HSCs in vivo, enabling efficient base editing of the HBG target in human HSCs to reactivate fetal hemoglobin in derived erythroid cells. Delivery of ABE8e/sgRNA mRNA with optimized structure LNPs achieves efficient in vivo base editing of HBG in transfusion-dependent {beta}-thalassemia (TDT) patients derived HSCs engrafted in immunodeficient NCG-X mice, showing restored globin chain balance in erythroid cells. Our research indicated that utilizing LNPs for delivery of genome editor achieves efficient editing of endogenous genes of human HSCs. Notably, this non-viral delivery system eliminates the need for harvesting or mobilizing HSCs, providing a potent and one-time treatment potential for blood disorders like sickle cell disease (SCD) and TDT. HighlightsO_LIAntibody-free targeted LNPs system achieves efficient mRNA delivery and base editing in human bone marrow cells including HSCs via one-time intravenous injection. C_LIO_LIDelivery of ABE8e/sgRNA mRNA with optimized LNPs achieves efficient in vivo base editing of HBG in TDT patients derived HSCs engrafted in immunodeficient NCG-X mice, showing restored globin chain balance in erythroid cells. C_LIO_LILNPs efficiently deliver gene editing system to the BM for in vivo editing of human HSCs, providing preclinical evidence for the next generation non-viral gene therapy for blood disorders. C_LI

bioengineering↗

bioRxiv2024

Involvement of 5' and 3' UTRs on SARS-CoV-2 Genome Packaging

The SARS-CoV-2 virus, responsible for the COVID-19 pandemic, packages its large single-stranded RNA genome through a precise yet enigmatic mechanism. A packaging signal (PS) within its genome was proposed to facilitate the assembly of new viral particles. Here in this study, we report the role of the 5 and 3 untranslated regions (UTRs) in PS-mediated genome packaging. Utilizing proximity ligation data, we demonstrate direct interactions between the UTRs and the PS9 element, a key packaging signal within the SARS-CoV-2 genome. Multiple evidence confirmed that the presence of UTRs enhance the packaging efficiency of infectious virus-like particles (iVLPs) and recruits more nucleocapsid (N) protein, suggesting a critical role in genome compaction and packaging. These insights into the regulatory mechanisms of SARS-CoV-2 genome packaging provide novel targets for antiviral therapeutics and contribute to the broader understanding of coronavirus assembly.

microbiology↗

bioRxiv2024

A Newborn F-box Gene Blocks Gene Flow by Selectively Degrading Phosphoglucomutase in Species Hybrids

The establishment of reproductive barriers such as postzygotic hybrid incompatibility (HI) remains the key to speciation. Gene duplication followed by differential functionalization has long been proposed as a major model underlying HI, but few supporting evidence exists. Here, we demonstrate that a new-born F-box gene, Cni-neib-1, of the nematode Caenorhabditis nigoni specifically inactivates an essential phosphoglucomutase encoded by Cbr-shls-1 in its sister species C. briggsae and their hybrids. Zygotic expression of Cni-neib-1 specifically depletes Cbr-SHLS-1, but not Cni-SHLS-1, in approximately 40 minutes starting from gastrulation, causing embryonic death. Cni-neib-1 is one of thirty-three paralogues emerging from a recent surge in F-box gene duplication events within C. nigoni, all of which are evolving under positive selection. Cni-neib-1 undergoes turnover even among C. nigoni populations. Differential expansion of F-box genes between the two species could reflect their distinctive innate immune responses. Collectively, we demonstrate how recent duplication of genes involved in protein degradation can cause unintended destruction of targets in hybrids that leads to HI, providing an invaluable insight into mechanisms of speciation. Significance statementUnderstanding how reproductive isolation forms and triggers speciation remains a central topic in evolutionary biology. In this study, the authors reveal a novel molecular mechanism that obstructs gene flow between the nematodes Caenorhabditis briggsae and C. nigoni. A recently evolved, species-specific F-box gene in C. nigoni selectively depletes an essential phosphoglucomutase enzyme in C. briggsae, leading to embryonic lethality in hybrids. This mechanism effectively prevents gene flow from C. nigoni to C. briggsae. This discovery underscores how a newborn gene, arising from recent gene duplication, can contribute to reproductive isolation by inadvertently disrupting a functionally important protein in hybrid offspring.

evolutionary biology↗

bioRxiv2024

PSMA-specific CAR-engineered macrophages for therapy of prostate cancer

Chimeric antigen receptor (CAR)-modified macrophages (CAR-Ms) are a promising approach for the treatment of solid tumors due to its high infiltration and immune-regulation activity. Prostate cancer is a typical solid tumor associated with highly immunosuppressive microenvironment. To date, the potential application of CAR-M cell therapy in prostate cancer has been infrequently explored. The prostate-specific membrane antigen (PSMA) functions as a specific biomarker for prostate cancer. In this study, we assessed the antitumor efficacy of PSMA-targeted CAR-Ms in preclinical models. CAR-Ms were engineered to express a PSMA-specific single-chain variable fragment (scFv) and co-stimulatory domains. In vitro data demonstrated specific cytotoxicity of CAR-Ms against PSMA-expressing prostate cancer cells, which was further supported by transcriptome analysis demonstrating the pro-inflammatory phenotypes of CAR-Ms. In vivo studies using xenograft mouse models confirmed significant tumor regression after administration of PSMA-targeted CAR-Ms compared to controls. Histopathological analysis showed infiltration of CAR-Ms into tumor tissues without off-target toxicity. These results highlight the strong antitumor activity and safety of PSMA-targeted CAR-Ms, supporting their potential as a new immunotherapy for prostate cancer.

bioengineering↗

bioRxiv2024

Nuclear FAK aggravates CD8+ T cell exhaustion via the SP1-IL-6 axis in colorectal cancer

Nuclear abnormalities such as nuclear deformation are hallmarks of many diseases, including cancer. Accumulating evidence suggests that the dense and mechanically stiff tumor microenvironment promotes nuclear deformation in cancer cells. However, little is known about how nuclear deformation in neoplastic cells regulates immune exhaustion in the tumor microenvironment. Here, we found that lamin A/C-mediated nuclear stiffening in neoplastic cells promotes the nuclear translocation of phosphorylated focal adhesion kinase (pFAK), which is strongly correlated with the heterogeneity and exhaustion of CD8+ T cells within the spatial context of the tumor microenvironment in human colorectal cancer. Mechanistically, we revealed that increased nuclear tension within tumor cells promotes pFAK nuclear translocation, where nuclear pFAK was found to regulate SP1/IL-6-mediated T-cell exhaustion and the transcription of proinflammatory cytokines/chemokines. Pharmacological inhibition or disruption of pFAK nuclear translocation enhanced antitumor immune responses and synergistically potentiated PD-1 and TIM-3 immunotherapy by increasing CD8+ T-cell cytotoxicity and restoring exhaustion in preclinical models of colorectal cancer. These findings highlight the pivotal role of nuclear tension-mediated pFAK translocation into the tumor cell nucleus in regulating CD8+ T-cell exhaustion, suggesting that pFAK is a promising target for advancing cancer immunotherapy.

immunology↗

bioRxiv2024

Ferroptosis mediates the progression of hyperuricemic nephropathy by activating RAGE signaling

Hyperuricemic nephropathy (HN) represents a prevalent complication arising from hyperuricemia, typified by tubular dysfunction, inflammation, and progressive renal fibrosis, whose pathogenic mechanisms remain enigmatic. Ferroptosis, a newly elucidated iron-dependent form of regulated cell death, plays a role in various disease states. However, its involvement in HN has seldom been explored. In this study, we observed indications of ferroptosis in the renal tissues of urate oxidase knockout (UOX-/-) mice, a model of hyperuricemia, as evidenced by increased iron deposition and reduced expression of glutathione peroxidase 4 (GPX4). These findings suggest a substantial role of ferroptosis in the pathogenesis of HN. To further explore this hypothesis, UOX-/- mice were administered Ferrostatin-1, a known inhibitor ferroptosis. This treatment markedly ameliorated tubular injury, necrosis, and inflammatory cell infiltration, mitigated renal fibrosis, reinstated the expression of proteins associated with ferroptosis in renal tissues, and reduced iron overload, lipid peroxidation, and mitochondrial damage in UOX-/- mice. Additionally, we found that receptor for advanced glycation end products (RAGE) propagates ferroptosis-induced renal injury, inflammation and fibrosis, albeit without directly facilitating ferroptosis. Finally, ferroptosis and RAGE upregulation were validated in renal tissues of patients with hyperuricemia-related kidney disease. Collectively, our research elucidates the critical contribution of ferroptosis to HN pathogenesis, indicating that therapeutic strategies targeting ferroptosis and the related RAGE signaling may offer novel therapeutic approaches for managing this condition.

ecology↗

bioRxiv2024

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↗