Biology subjects

Guo, X.

Publications and source records attributed to Guo, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

mMap: a comprehensive and continuously updated species distribution database facilitating the understanding of mosquito diversity and distribution patterns

Mosquitoes, as vectors of deadly diseases like malaria and dengue, exhibit complex and dynamic global distribution patterns influenced by climate change and human activity. However, gaps in species-level data and biases in existing databases hinder accurate risk assessments. Here, we present mMap (v1.01), a comprehensive and curated mosquito distribution database integrating multi-source records from literature (36,242 entries across 1,809 studies), museum collections, and field reports in 6 languages. Systematic data harmonization and validation workflows address taxonomic and spatial uncertainties, enabling family-level analyses previously constrained by fragmented data. Our results reveal significant range expansions for 28 invasive species (e.g., Aedes albopictus in Europe) and corrections to historical distributions (e.g., Ae. vexans in 22 new countries). The interactive mMap platform (accessible at https://mos-map.vercel.app/) provides open-access tools for visualizing spatial-temporal trends, automated SDM forecasting, and expert-curated species profiles. By unifying dispersed data into a scalable framework, mMap advances research on mosquito biodiversity, invasion ecology, and disease risk mapping, offering a critical resource for global health strategies in an era of rapid environmental change.

ecology↗

bioRxiv2025

DOMINO: diffusion-optimised graph learning identifies domain structures with enhanced accuracy and scalability

Spatial transcriptomics enables in situ molecular profiling, allowing to measure the cellular transcriptional output within the tissue. As the tissue architecture is conserved, spatial domains with specific transcriptional patterns can be identified, facilitating the discovery and understanding of functional tissue compartments. Thus, several methods to uncover and identify these spatial domains have been developed. However, most of these existing methods do not scale to rapidly increasing data sizes and focus only on local structure while missing the global view of the tissue. Here, we present DOMINO, a diffusion-optimised contrastive learning framework for spatial domain detection. DOMINO utilises graph diffusion convolution to propagate information beyond immediate neighbours and jointly optimises local and, importantly, global graph structure via contrastive learning. This novel framework yields biologically interpretable domains with clearer boundaries and scales to large datasets, outperforming state-of-the-art methods across healthy and malignant benchmark datasets. We apply DOMINO to a newly generated spatial transcriptomic dataset of endometriosis-associated ovarian cancers, which could not be processed by existing domain detection methods owing to its size. We uncovered conserved proliferative and non-proliferative tumour states that recurred across these tumours and were independently validated in an external clear cell ovarian cancer spatial transcriptomic dataset. Proliferative domains were characterised by elevated expression of EIF4A1 and HSPA8, increased cell cycle activity, reduced mast cell abundance, and coordinated stromal remodelling, including altered fibroblast states and spatial organisation. In parallel, integrative analysis across tumours revealed subtype-specific multicellular ecosystems associated with either endometrioid or clear cell ovarian carcinomas, together with a tumour-excluded stromal domain that could only be resolved through the integration of spatial and transcriptional information. These findings demonstrate how well DOMINO scales up and that it uncovers biologically meaningful spatial programs spanning tumour intrinsic states, tumour microenvironment interactions, and subtype-specific tissue architecture that are not recovered by conventional expression-based clustering approaches.

bioinformatics↗

bioRxiv2025

Substrates Coupling and Inhibition of the human Na+- dependent Cl-/HCO3-exchanger

Maintaining pH homeostasis is essential for neuronal excitability and for regulating cerebrospinal fluid (CSF). The Na+-dependent Cl-/HCO3- exchanger, NCBE (SLC4A10), abundant in the choroid plexus, contributes to CSF pH control by mediating bicarbonate flux, yet its molecular mechanism has remained unclear. Here we report cryo-EM structures of human NCBE in multiple functional states, revealing conserved binding sites for Na+, Cl-, and HCO3-, as well as an unexpected K+ site indicating relaxed cation selectivity. The inhibitor DIDS binds above the substrate cavity, locking NCBE in an outward-facing conformation and defining a subfamily-selective inhibitory mechanism. Functional assays and molecular dynamics simulations validate ion coordination and inhibitor effects. Comparison of cryo-EM structures with an AlphaFold3 inward-facing model supports an elevator-like mechanism and completes the conformational cycle of Na+-coupled HCO3- transporters. Together, these findings define the structural basis of NCBE and provide a framework for understanding ion coupling and pharmacological modulation within the SLC4 family.

biophysics↗

bioRxiv2025

scCotag: Diagonal integration of single-cell multi-omics data via prior-informed co-optimal transport and regularized barycentric mapping

Recent advances in high-throughput single-cell technologies have enabled characterization of cellular states across distinct omics layers, yielding complementary insights into the organization of biological systems. To jointly leverage these disparate modalities, computational methods have been developed to align non-overlapping cell populations profiled in different omics layers, a task known as diagonal integration, thereby facilitating more fine-grained biological interpretations. However, existing integration approaches unrealistically assume that all cells are alignable and treat prior-knowledge-derived feature correspondences as fully reliable, retaining them unrefined throughout the alignment process. In this work, we introduce scCotag, a co-optimal transport (COOT)-based deep learning frame-work for diagonal integration of single-cell multi-omics data, to address these limitations. scCotag first infers cell alignment and feature correspondence with prior-informed COOT in an iterative manner, and then leverages the resulting transport plans to jointly learn cell and feature embeddings via regularized barycentric mapping and graph reweighting. Systematic benchmarking on human brain, bone marrow, and blood single-cell RNA-seq and ATAC-seq datasets demonstrates the overall superior performance of scCotag over state-of-the-art methods in both cell alignment accuracy and embedding accuracy. In particular, scCotag excels in simulated imbalance scenarios where not all cells are alignable. Applying scCotag to data in postmortem brains of Alzheimers disease (AD) and non-AD (NoAD) patients further yields more fine-grained biological interpretation of regulatory mechanisms. Together, these results demonstrate that scCotag provides a robust framework for single-cell diagonal integration and regulatory inference.

bioinformatics↗

bioRxiv2025

A global atlas of deep-sea cold seep viruses uncovers extensive genomic novelty, pervasive viral dark matter, and biotechnological potential

Cold seeps are globally distributed deep-sea ecosystems harboring diverse chemosynthetic microbial communities, yet their viral components remain poorly understood. Here, we establish the Global Cold Seep Virome, a comprehensive catalog of 191,937 species-level viral operational taxonomic units (vOTUs) and 2.44 million viral protein clusters reconstructed from 314 metagenomes spanning 18 cold seep sites worldwide. Most vOTUs are distinct from those in existing environmental viromes, suggesting that cold seeps harbor a largely unexplored viral reservoir. Host prediction suggests diverse viral associations with key prokaryotes, including anaerobic methanotrophic archaea. Protein annotation reveals that these viruses encode widespread uncharacterized proteins and viral hallmark proteins with divergent physicochemical properties, potentially contributing to their ecological adaptability. We also identify putative auxiliary metabolic genes, anti-defense genes, and lysins, and experimentally validate representative anti-defense proteins and lysins with strong activities. This resource expands current knowledge of deep-sea viral diversity and provides a foundation for studying virus-host interactions, testing biogeochemical hypotheses, and exploring biotechnological potential in cold seep ecosystems.

microbiology↗

bioRxiv2025

Cross-task, explainable, and real-time decoding of human emotion states by integrating grey and white matter intracranial neural activity

Decoding human emotion states from intracranial neural activity is key in developing brain-computer interfaces and new therapies for affective disorders. However, real-world application of decoding requires high performance that integrates neural activity from both grey and white matter, stable generalization across different contexts, sufficient neural encoding explainability, and robust real-time implementation, all of which remain elusive. Here, we simultaneously recorded intracranial electroencephalogram (iEEG) and abundant self-rated valence and arousal scores across two emotion-eliciting tasks in eighteen subjects, forming the largest intracranial neural dataset for emotion decoding. We then developed personalized decoding models within a hybrid deep learning framework involving both self-supervised and supervised components. The models achieved high-performance decoding of continuous valence/arousal states, doubling the R-squared performance of prior EEG/iEEG decoding. Critically, the models significantly improved performance by integrating grey and white matter signals and demonstrated cross-task generalization. The models further revealed shared and preferred mesolimbic-thalamo-cortical subnetworks encoding valence and arousal, showing neurophysiological explainability. Finally, the models realized robust real-time decoding in four new subjects. Our results have implications for advancing emotion decoding neurotechnology toward deployable affective brain-computer interfaces and closed-loop therapeutic systems for affective disorders.

neuroscience↗

bioRxiv2025

Atypical activation and molecular glue-like dimerization mechanism of an intrinsically-biased chemokine receptor

CXCR7, also known as atypical chemokine receptor 3 (ACKR3), is a naturally-biased, {beta}-arrestin-coupled seven transmembrane receptor (7TMR) that lacks productive coupling with heterotrimeric G-proteins. Despite a critical involvement in cancer metastasis, cardiovascular pathophysiology, and inflammatory disorders, the molecular basis of non-canonical activation and functional divergence of CXCR7 remains elusive. Here, we present a complete landscape of CXCR7 activation using a series of cryo-EM structures, and discover an atypical activation mechanism that is distinct from prototypical GPCRs. CXCR7 is maintained in a basal conformation by a unique tripartite ionic-lock involving TM5-TM6, in contrast to a broadly conserved TM3-TM6 ionic-lock in GPCRs, which is disrupted upon receptor activation. Importantly, activation of CXCR7 results in a constricted pocket and distinct surface topology on the intracellular side compared to prototypical GPCRs. Serendipitously, we capture novel dimeric arrangements of CXCR7 with an inter-protomer stitching by a native phospholipid serving as a molecular glue, and identify previously unanticipated extrahelical allosteric sites on the receptor. Surprisingly, in an intermediate state structure of CXCR7, the second extracellular loop (ECL2) displays a self-blocking conformation, in stark contrast to ECL2-mediated self-activating mechanism reported recently for some orphan GPCRs. Finally, we unequivocally establish CXCR7 as an atypical opioid receptor via a large peptide library screening and structure elucidation in complex with distinct opioid peptides imparting full receptor activation. In summary, our study elucidates an atypical mechanism of CXCR7 activation, and establishes it as an alternative, non-canonical opioid receptor target with potential for novel pain therapeutics.

biochemistry↗

bioRxiv2025

Lipid peroxidation intrinsically induces mitochondrial iron overload via Bach1-HO-1 signaling to promote cardiac ferroptosis

BackgroundLipid peroxidation and iron accumulation are hallmarks of ferroptosis, a form of cell death characterized by iron-dependent oxidative damage to cellular membranes. However, the molecular link between lipid peroxidation and iron overload in the execution of ferroptosis remains elusive. Moreover, the pathophysiological implications of the interaction between lipid peroxidation and iron overload in cardiac homeostasis and remodeling are also unknown. MethodsWe assessed the role of lipid peroxidation in mediating cardiac iron overload and ferroptosis using genetic mouse models. We also performed molecular and cellular biology studies to elucidate the mechanisms by which lipid peroxidation regulates iron homeostasis and ferroptosis signaling in cardiomyocytes. ResultsCardiomyocyte-specific ablation of Gpx4 (glutathione peroxidase 4), a key suppressor of lipid peroxidation, promoted iron overload and ferroptosis in the heart, leading to dilated cardiomyopathy. Mice with heterozygous Gpx4 knockout were also predisposed to adverse cardiac remodeling and dysfunction following pressure overload. Mechanistically, elevated lipid peroxidation due to GPX4 inactivation intrinsically induced iron overload by promoting the nuclear export of Bach1 and subsequent induction of heme oxygenase-1 (HO-1). Genetic and pharmacologic inhibition of HO-1 markedly attenuated iron overload and ferroptosis in cardiomyocytes and rescued dilated cardiomyopathy associated with Gpx4 deficiency. Moreover, we identified HO-1 mitochondrial translocation as a key mechanism driving mitochondrial iron overload and ferroptosis. Targeted inhibition of mitochondrial iron overload or lipid peroxidation abrogated cardiac ferroptosis and pathological remodeling induced by Gpx4 deficiency. ConclusionsThese findings identified a mechanistic link between lipid peroxidation and iron overload via the Bach1-HO-1 signaling pathway, revealing new regulators and molecular targets for cardiac ferroptosis.

cell biology↗

bioRxiv2025

Host Phosphatase PPM1G Governs Influenza vRNP Homeostasis by Orchestrating NP Phosphorylation Dynamics and Autophagy

The influenza viral ribonucleoprotein (vRNP) serves as the machinery for viral RNA replication. It self - assembles from the RNA - dependent RNA polymerase (RdRp), viral RNA, and nucleoprotein (NP). During vRNP replication, NP proteins must rapidly switch between monomeric and polymeric states to sustain dynamic equilibrium, which relies on NP phosphorylation-dephosphorylation cycling and is crucial for viral nucleic acid replication. However, the regulatory mechanisms controlling this process remain poorly understood. In this study, we employed an RdRp/vRNP-targeted affinity mass spectrometry-based differential analysis method, discovered that the cellular protein phosphatase Mg2+/Mn2+-dependent 1G (PPM1G) is a phosphatase of NP and required for maintaining viral polymerase activity. Overexpression of PPM1G decreased viral replication. In ppm1g flox/flox-Sftpc Cre mice, lethal influenza infection led to survival and mild disease, as well as reduced lung viral loads and inflammation. These results suggest that PPM1G is a key host molecule for maintaining steady state of viral replication. PPM1G expression is upregulated upon influenza virus infection. This heightened expression occurs in response to increased viral protein production, simultaneously leading to elevated dephosphorylation of NP, which accelerates NP polymerization to promote viral replication. Meanwhile, surplus NP can be degraded through the ATG7 autophagylysosome pathway. Our research elucidates a mechanism that PPM1G maintains viral replication homeostasis by regulating NP status and fate.

microbiology↗

bioRxiv2025

A ratio-based framework using Quartet reference materials for integrating long- and short-read RNA-seq

Long-read RNA sequencing (lrRNA-seq) enables full-length transcript profiling but is confounded by technical batch effects that compromise quantification and prevent data integration across platforms, protocols, and laboratories. The lack of a transcriptome-wide biological ground truth has hindered objective benchmarking. To address these dual challenges, we leveraged certified Quartet reference materials to generate one of the largest multi-center lrRNA-seq resources to date: over one billion long reads from 144 libraries across four PacBio and Nanopore protocols in four independent laboratories. We first establish that ratio-based quantification against built-in reference samples effectively removes technical noise, revealing underlying biological signals. We then constructed the first ratio-based reference datasets for full-length transcripts-- comprising 10,218 isoforms and 6,032 alternative splicing (AS) events--and orthogonally validated them with RT-qPCR. Finally, a comprehensive benchmark using these ground truths reveals that a hybrid strategy integrating long- and short-read data (hybrid-seq) achieves the highest quantification accuracy for both isoforms and AS events. Our work provides a foundational framework and resource for evaluating lrRNA-seq technologies and accelerating the standardization of full-length transcriptomics for research and clinical applications.

genomics↗

bioRxiv2025

Whole genome sequencing reveals the phylogenetic relationship and reticulate evolution of Phrynocephalus lizards in Eurasia

Toad-headed agama (genus Phrynocephalus) is a widely distributed group of lizards across Central Eurasia, inhabiting diverse arid and semi-arid environments from the Caspian Basin to the Qinghai-Tibetan Plateau (QTP). Despite considerable research efforts over the past decades, a robust phylogenetic framework for Phrynocephalus has remained elusive. In this study, we collected 26 samples representing a substantial portion of the distribution of this genus and established a well-supported phylogeny based on whole-genome sequencing and phylogenomic approaches. We found that the Phrynocephalus lizards comprised of three major clades, including the Western Asia, Central Asia and viviparous clades. Furthermore, we provided compelling evidence for an ancient hybridization event that led to the speciation of P. mystaceus, which likely contributed to the observed phylogenetic discordance across the genome. Divergence time estimation and ancestral area reconstruction indicated that Phrynocephalus lizards originated approximately 31.57 million years ago in the Central Asia and Iranian Plateau region, followed by Miocene dispersals into the Arabian Peninsula, the Gobi Desert, and the QTP. Our results illuminate how hybridization and historical range dynamics have jointly driven the origin and diversification of Phrynocephalus, providing new insights into the formation of biodiversity in Eurasia.

bioinformatics↗

bioRxiv2025

Separately prestored proteasome components to prevent polyspermy

To ensure genome stability across generations, an egg must be fertilized by only a single sperm. However, how sperm actively contribute to preventing polyspermy has remained unknown. Here, we demonstrate that testis-specific 20S proteasome core particles (CPs) are pre-stored within the sperm heads of both mice and humans. Upon fertilization, these testis-specific 20S CPs assemble with oocyte-derived 19S regulatory particles (RPs), forming chimeric proteasomes that efficiently degrade Fetuin B, which is ubiquitinated by the E3 ligase MARCH3. The clearance of Fetuin B triggers ZP2 cleavage and subsequent zona pellucida hardening, thereby blocking additional sperm entry. The newly assembled chimeric proteasome in the zygote represents a novel strategy to prevent polyspermy during fertilization in mammals.

developmental biology↗

bioRxiv2025

Beyond the Anterior Temporal Lobe: Domain-Related Degeneration of Cortical Language Network Dynamics in Semantic Dementia

Semantic dementia (SD) is a neurodegenerative disorder marked by a progressive decline in semantic memory, mainly due to focal atrophy in the anterior temporal lobe (ATL). As the disease advances, atrophy spreads to the perisylvian regions, accompanied by non-semantic language impairments. Despite these clinical findings, the network mechanisms behind cross-domain linguistic deficits remain poorly understood. In this study, we used our recently developed meta-networking framework of cortical language network dynamics to systematically examine domain-specific network disruptions in SD. Using resting-state functional MRI (fMRI) and comprehensive neuropsychological tests across several language domains, we analyzed data from SD patients at two timepoints: baseline (n = 42) and a 2-year follow-up (n = 24). Our findings showed that the framework successfully identified domain-specific language network degeneration. Beyond the ATL, progressive atrophy disrupted the dynamic separation of language networks involved in semantic processing, phonological processing, and speech production. These disruptions were characterized by state-specific hypo- and hyper-connectivity patterns that related to distinct language impairments. At follow-up, atrophy extended to posterior temporal and prefrontal regions, worsening network function. Importantly, the patterns of language network disruption predicted individual language deficits, providing a mechanistic link between structural degeneration, functional network changes, and clinical symptoms.

neuroscience↗

bioRxiv2025

The Disruption and Normalization of Cortical Language Network Dynamics After Post-Stroke White Matter Disconnection

The human language network undergoes reorganization across different spatiotemporal scales, limited by its fixed structural neurobiological foundations. Although stroke often damages white matter, its effect on temporary language network reorganization is not fully understood. This study examined longitudinal behavioral and resting-state fMRI data from post-stroke patients with exclusive subcortical lesions at three time points: two weeks (n = 38), three months (n = 29), and one year (n = 27). Patients showed mild to moderate language impairments during the acute phase, which improved within three months. The extent of disconnection in several left-hemispheric white matter tracts was negatively associated with language deficits. Healthy controls (HC, n = 25) exhibited domain-segregation dynamics in the cortical language network, limited by the underlying white matter pathways. In patients, severe, state- and track-specific network disruptions were observed in the acute phase, characterized by hypo- and hyper-connectivity and abnormal topological features. As language recovery progressed, connectivity patterns began to return to normal, resembling those of HC, and the domain-segregation dynamics reappeared. These results deepen our understanding of structure-function coupling and indicate significant post-lesional plasticity within the cortical language network.

neuroscience↗

bioRxiv2025

Spatiotemporal WNT and BMP gradients orchestrate regional enteroendocrine cell diversity along the Drosophila midgut

Enteroendocrine cells (EEs) in metazoan are diversified into multiple subtypes that occupy specific regions along the digestive tract to fulfill their functions. How to establish this regional pattern of EE subtypes is unclear. Here, we investigated the complex distribution patterns of three major EE subtypes along the length of the pupal and adult Drosophila midgut, and found that regional EE patterning is regulated by WNT and BMP signaling in a spatiotemporally dependent manner. Furthermore, there are both Notch-dependent and -independent cell division modes of EE progenitors that contribute to the generation of regional EE diversity. Our findings suggest that intercalated WNT and BMP morphogen gradients emanating from compartment boundaries play a critical role, not only in establishing regional ISC identity and the resulting EE diversity during development, but also in maintaining regional EE diversity in adulthood--a paradigm that may be conserved in mammals.

developmental biology↗

bioRxiv2025

Optimizing effect sizes and specificity trumps machine learning when building DNA methylation reference panels for cell-type deconvolution

Accurate cell-type deconvolution is critical for correct interpretation of Epigenome-Wide Association Studies. Such cell-type deconvolution involves estimating underlying cell-type fractions in a sample, which is accomplished using a DNA methylation reference panel built from sorted or single-cell DNAm data. Two competing approaches have emerged to build such reference panels, one which uses machine-learning, and another based on optimizing effect size and cell-type specificity. Here we demonstrate that the latter approach is preferable, because, owing to the relatively small number of sorted samples used in building panels, standard machine learning does not optimize effect size and cell-type specificity, causing the model to overfit and underperform when tested in independent data. Furthermore, adult blood panels built from cell-type specific hypomethylated markers improves inference when compared to panels built from hypermethylated ones. These insights provide important guidelines for optimizing the construction of future DNAm reference panels. To aid this task, we have added a function for building an optimized DNAm reference panel to our EpiDISH R-package.

bioinformatics↗

bioRxiv2025

Renalase activates mitochondrial leak metabolism in response to cellular stress and to repair damage after injury

A variety of mechanisms enhance cell stress response and repair; however, the role of mitochondria in this activity is unclear. Here we show that exogenous renalase (RNLS), an intracellular flavin-dependent NADH oxidase, activates intramitochondrial RNLS activity to promote cell survival. RNLS interacts with the ATP synthase alpha and beta subunits (ATP5 and ATP5{beta}) and opens the ATP synthase c-subunit leak channel to increase complex I and II activities and protein synthesis rate. RNLS causes a selective, sustained, time-dependent increase in cellular protein synthesis without affecting cell proliferation, whereas RNLS deletion or direct inhibition of the mitochondrial leak blocks RNLS-mediated protein synthesis. Functional analysis of newly and differentially synthesized proteins over 24 hours reveals rapid changes in one-carbon metabolism and ribosomal biogenesis pathways as early as one hour after RNLS exposure. Mitochondrial injury is more severe in the RNLS KO kidney after acute stress, related to decreased protein synthesis rate and increased mitophagy. RNLS KO mice exposed to the stress of chronic cardiac pressure overload fail to develop cardiac hypertrophy, the physiological response, and die of heart failure and cardiac rupture. These data highlight the critical role RNLS has in activating mitochondrial leak metabolism to induce selective protein synthesis and protect against acute and chronic stress. HIGHLIGHTSO_LIRenalase interacts with the ATP synthase alpha and beta subunits C_LIO_LIRenalase activates mitochondrial leak metabolism C_LIO_LIRenalase and leak metabolism increase complex I and II activities C_LIO_LILeak metabolism increases protein synthesis rate C_LIO_LIRenalase protects against cell stress and organ injury C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/671117v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@96ea7eorg.highwire.dtl.DTLVardef@1fcffbaorg.highwire.dtl.DTLVardef@f946cdorg.highwire.dtl.DTLVardef@197498a_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

cell biology↗

bioRxiv2025

Tracking the Evolutionary Patterns of RNA Modifications from Bryophyte to Flowering Plants by Mass Spectrometry

RNA modifications are critical for the regulation of gene expression. Comprehensive profiling of RNA modifications is a prerequisite for unravelling their identities and functions. The plant hormone auxin plays pivotal roles in regulating plant growth, development, and environmental responses. In contrast to the extensive studies in animals, there is a paucity of knowledge regarding the existence and functions of RNA modifications in plants. This is due to the low abundance of modified ribonucleosides and the lack of accurate analytical methods. This study employs a state-of-the-art hydrophilic interaction liquid chromatography-tandem-mass spectrometry (HILIC-MS/MS) platform to achieve the sensitive detection of 12 nucleosides at the pM to nM level. Utilizing this platform, we were able to identify N4,2-O-dimethylcytidine (m4Cm) in plants by LC-MS/MS for the first time, which provided direct evidence for the widespread of this modification in plants. Moreover, a comprehensive investigation was undertaken to examine the 12 types of RNA modifications and their response patterns to auxin in a range of prototype plants, spanning from bryophyte (Marchantia polymorpha) to flowering plants (Arabidopsis thaliana, Oryza sativa, and Zea mays). The evolutionary patterns of the 12 RNA modifications were depicted from bryophyte to flowering plants, and their potential functions in plant growth, development, and auxin responses were revealed.

biochemistry↗