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bioRxiv2024

The Early Dodder Gets the Host: Decoding the Coiling Patterns of Cuscuta campestris with Automated Image Processing

Cuscuta spp., commonly known as dodders, are rootless and leafless stem parasitic plants. Upon germination, Cuscuta starts rotating immediately in a counterclockwise direction (circumnutation) to locate a host plant, creating a seamless vascular connection to steal water and nutrients from its host. In this study, our aim was to elucidate the dynamics of the coiling patterns of Cuscuta, which is an essential step for successful parasitism. Using time-lapse photography, we recorded the circumnutation and coiling movements of C. campestris at different inoculation times on non- living hosts. Subsequent image analyses were facilitated through an in-house Python-based image processing pipeline to detect coiling locations, angles, initiation and completion times, and duration of coiling stages in between. The study revealed that the coiling efficacy of C. campestris varied with the inoculation time of day, showing higher success and fastinitiation in morning than in evening. These observations suggest that Cuscuta, despite lacking leaves and a developed chloroplast, can discern photoperiod changes, significantly determining its parasitic efficiency. The automated image analysis results confirmed the reliability of our Python pipeline by aligning closely with manual annotations. This study provides significant insights into the parasitic strategies of C. campestris and demonstrates the potential of integrating computational image analysis in plant biology for exploring complex plant behaviors. Furthermore, this method provides an efficient tool for investigating plant movement dynamics, laying the foundation for future studies on mitigating the economic impacts of parasitic plants.

plant biology↗

bioRxiv2025

PlantScience.ai: An LLM-Powered Virtual Scientist for Plant Science

The accelerating growth of plant science literature presents a major challenge for researchers seeking to extract accurate, up-to-date knowledge from an increasingly fragmented and domain-specific corpus. General-purpose large language models (LLMs), while powerful, often misinterpret plant science terminology and lack mechanisms for source traceability. We created PlantScience.ai, a virtual plant biology scientist powered by our automated scientific knowledge graph construction pipeline (AutoSKG). PlantScience.ai exhibits expert-level reasoning in plant biology and maintains scholarly rigour in its citations. Through continuous learning, it integrates the latest research, ensuring that its knowledge base remains current and scientifically robust. Apart from providing the answers to the scientific questions, PlantScience.ai can interact with human scientists, follow instructions, and retrieve information with citation awareness, grounding each response in primary sources to ensure accuracy and verifiability. PlantScience.ai marks a pivotal advance toward a collaborative scientific paradigm in which virtual and human plant scientists work synergistically to accelerate discovery while preserving the unique value of human insight. PlantScience.ai is available at https://plantscience.ai.

plant biology↗

bioRxiv2024

A novel toolbox of GATEWAY-compatible vectors for rapid functional gene analysis in soybean composite plants

The generation of transgenic plants is essential for plant biology research to investigate plant physiology, pathogen interactions and gene function. However, producing stable transgenic plants for plants such as soybean is a laborious and time-consuming process, which can impede research progress. Composite plants consisting of wild-type shoots and transgenic roots are an alternative method for generating transgenic plant tissues that can facilitate functional analysis of genes-of-interest involved in root development or root-microbe interactions. In this report, we introduce a novel set of GATEWAY-compatible vectors that enable a wide range of molecular biology uses in roots of soybean composite plants. These vectors incorporate in-frame epitope fusions of green fluorescent protein, 3x-HA, or miniTurbo-ID, which can be easily fused to a gene-of-interest using the GATEWAY cloning system. Moreover, these vectors allow for the identification of transgenic roots using either mCherry fluorescence or the RUBY marker. We demonstrate the functionality of these vectors by expressing subcellular markers in soybean, providing evidence of their effectiveness in generating protein fusions in composite soybean plants. Furthermore, we show how these vectors can be used for gene function analysis by expressing the bacterial effector, AvrPphB in composite roots, enabling the identification of soybean targets via immunoprecipitation followed by mass spectrometry. Additionally, we demonstrate the successful expression of stable miniTurbo-ID fusion proteins in composite roots. Overall, this new set of vectors is a powerful tool that can be used to assess subcellular localization and perform gene function analyses in soybean roots without the need to generate stable transgenic plants. Key MessageWe developed a set of GATEWAY vectors to accelerate gene function analysis in soybean composite plants to rapidly screen transgenic roots and investigate subcellular localization, protein-protein interactions, and root-pathogen interactions.

plant biology↗

bioRxiv2026

Research Process Graph: LLM-Driven Extraction and Hierarchical Organization of Research Logic

Plant biology now publishes thousands of experimental research articles each year, but their core research logic, namely what questions are being asked, with what methods, and what is being found, remains locked inside free text and invisible to systematic analysis. Here we present a structured, 20-year atlas of The Plant Cell in which every paper is converted into a typed, directed Research Process Graph (RPG) of Question (Q), Method (M) and Finding (F) nodes connected by Q[->]M and M[->]F edges. A benchmarked large language model pipeline applied to 2,633 Plant Cell research articles published 2005-2026 recovered >110,000 Q/M/F nodes and >126,000 directed Q[->]M[->]F chains with>98% precision. A second LLM pass generalises each node into a paper-independent canonical form and assigns it to one of 10 top-level (L1) and [~]90 sub-level (L2) categories for each node type, producing the first comprehensive map of plant-biology research logic at the resolution of individual research questions. The atlas reveals that Plant Cell papers fall into seven canonical paper recipes with characteristic Q[->]M[->]F sub-structures, that peripheral experimental techniques have largely turned over while a stable methodological core persisted, and that the strongest correlate of per-PI citation impact is methodological breadth, not productivity or topical breadth. We release the atlas as a public, browsable database with five complementary interfaces: paper views, an LLM-powered research assistant, expert profiles, a taxonomy browser, and a method explorer. The database, available at https://rpg.connectome.tools/, turns the literature into a queryable community resource.

plant biology↗

bioRxiv2024

Computational Transcriptomic and Comparative Genomic Analysis of dead box RNA Helicase gene AT2G45810 Expressed in Plants Arabidopsis thaliana

Arabidopsis thaliana is a short life cycle, small genome, and Brassicaceae family winter annual small flowering plants. It is popularly used as a model organism in genetics and plant biology research, and it is essential to understanding the molecular biology of many plant features, including light sensing and flower formation. It also plays a key role in the science of agronomy, and plant transcriptomics as well as genomics. When it comes to the development of multicellular creatures, transcriptional programs are crucial. The constantly active growth of different organ systems is supported by transcriptional programs. Arabidopsis embryos possess remarkable transcriptomes compared to other plant tissues comprising somatic embryo differentiation circumstances operating during plant embryogenesis. Here we show that the transcriptomic analysis of the genome dead box RNA helicase gene AT2G45810 of Arabidopsis thaliana Araport11 species which revealed the specific gene expression patterns of Arabidopsis tissue-specific information of developmental map, embryo, single cell, DNA damage, cellular interactions, pathway analysis, etc., through In Silico or computational approaches. In this particular study, we used the TAIR, Phytozome, and plant comparative genomics portal for retrieving and identification of specific genes of interest. Next, we used web-based Bar utoronto tools to visualize other data, including functional genomics. Their protein and gene expression tools facilitate the exploration of promoters, the identification of protein-protein interactions, the viewing of expression patterns as electronic fluorescent pictographs or heatmaps, and more.

developmental biology↗

bioRxiv2023

Silicon supplementation and jasmonate activation synergistically increase phenolic defences against a legume herbivore

O_LIThe accumulation of silicon (Si) is widely reported to have anti-herbivore defensive properties in grasses. There is emerging, but fragmentary, evidence that Si could play a similar role in legumes. C_LIO_LIHere, we sought to understand the effects of Si supplementation on anti-herbivore defensive properties in lucerne (Medicago sativa), especially in relation to other potential defences (i.e. phenolics) and the phytohormone that regulates anti-herbivore defences, jasmonic acid or jasmonate (JA), which is also linked to Si accumulation. C_LIO_LIWe determined how growth, root nodulation and chemistry (carbon, nitrogen and phenolic concentrations) of four genotypes of lucerne responded to Si supplementation, with and without the application of JA, and we used feeding assays to determine the subsequent effects on the feeding success of adult Sitona discoideus weevils. C_LIO_LISi supplementation increased plant mass and root nodulation of M. sativa by 61% and 227%, respectively, and reduced relative consumption (RC) and frass production by S. discoideus by 38% and 30%, respectively. Si supplementation had no effect on foliar nitrogen concentrations, most likely due to the dilution effects of increased plant growth and foliar carbon. Phenolic concentrations were negatively correlated with leaf RC; RC also decreased by 34% when JA was applied to plants. When Si was combined with JA application, phenolics were significantly enhanced, demonstrating the potential to stimulate multiple anti-herbivore properties in M. sativa. C_LIO_LISynthesis. The novel findings suggest that Si accumulation may play a more important role in legume resistance to herbivorous animals than previously thought. The ubiquity of soil Si and its emerging functional role in plant biology, including plant-animal interactions, suggest that these patterns could be common amongst legumes. C_LI

ecology↗

bioRxiv2021

Plant Metabolic Network: A multi-species resource of plant metabolic information

Plant metabolism is a pillar of our ecosystem, food security, and economy. To understand and engineer plant metabolism, we first need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we previously created the Plant Metabolic Network (PMN), an online resource of curated and computationally predicted information about the enzymes, compounds, reactions, and pathways that make up plant metabolism. Here we report PMN 15, which contains genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants, and new tools for analyzing and viewing metabolism information across species and integrating omics data in a metabolic context. We systematically evaluated the quality of the databases, which revealed that our semi-automated validation pipeline dramatically improves the quality. We then compared the metabolic content across the 126 organisms using multiple correspondence analysis and found that Brassicaceae, Poaceae, and Chlorophyta appeared as metabolically distinct groups. To demonstrate the utility of this resource, we used recently published sorghum transcriptomics data to discover previously unreported trends of metabolism underlying drought tolerance. We also used single-cell transcriptomics data from the Arabidopsis root to infer cell-type specific metabolic pathways. This work shows the continued growth and refinement of the PMN resource and demonstrates its wide-ranging utility in integrating metabolism with other areas of plant biology. One-sentence SummaryThe Plant Metabolic Network is a collection of databases containing experimentally-supported and predicted information about plant metabolism spanning many species.

plant biology↗

bioRxiv2023

In-section Click-iT detection and super-resolution CLEM: Shedding light on nucleolar ultrastructure and S-phase progression in plants.

Correlative light and electron microscopy (CLEM) is an essential tool that allows for localisation of a particular target molecule(s) and their spatial correlation with the ultrastructural map of subcellular features at the nanometer scale. Adoption of these advanced imaging methods has been limited in plant biology, due to challenges with plant tissue permeability, fluorescence labelling efficiency, indexing of features of interest throughout the complex 3D volume and their re-localization on micrographs of ultrathin cross-sections. Here, we demonstrate an imaging approach based on tissue processing and embedding into methacrylate resin followed by imaging of serial sections by both, single-molecule localization microscopy and transmission electron microscopy for correlative analysis. Importantly, we demonstrate that the use of a particular type of embedding resin is not only compatible with single-molecule localization microscopy but shows a dramatic improvement in fluorophore blinking behavior relative to the whole-mount approaches. Here we used commercially available Click-iT ethynyl-deoxyuridine cell proliferation kit to visualize the DNA replication sites of wild-type Arabidopsis thaliana seedlings, as well as FASCIATA1 and NUCLEOLIN1 mutants and applied our on-section CLEM imaging workflow for the analysis of S-phase progression and nucleolar organization in mutant plants with aberrant nucleolar phenotypes.

plant biology↗

bioRxiv2025

Causes and consequences of experimental variation in Nicotiana benthamiana transient expression

Infiltration of Agrobacterium tumefaciens into Nicotiana benthamiana has become a foundational technique in plant biology, enabling efficient delivery of transgenes in planta with technical ease, robust signal, and relatively high throughput. Despite transient expressions prevalence in disciplines such as synthetic biology, little work has been done to describe and address the variability inherent in this system, a concern for experiments that rely on highly quantitative readouts. In a comprehensive analysis of N. benthamiana agroinfiltration experiments, we model sources of variability that affect transient expression. Our findings emphasize the need to validate normalization methods under the specific conditions of each study, as distinct normalization schemes do not always reduce variation either within or between experiments. Using a dataset of 1,915 plants collected over three years, we develop a model of variation in N. benthamiana transient expression, using power analysis to determine the number of individual plants required for a given effect size. Drawing on our longitudinal data, these findings inform practical guidelines for minimizing variability through strategic experimental design and power analysis, providing a foundation for more robust and reproducible use of N. benthamiana in quantitative plant biology and synthetic biology applications.

plant biology↗

bioRxiv2023

PlantConnectome: knowledge networks encompassing >100,000 plant article abstracts

One of the main quests of plant biology is understanding how genes and metabolites work together to form complex networks that drive plant growth, development, and responses to environmental stimuli. However, the ever-growing volume and diversity of scientific literature make it increasingly challenging to stay current with the latest advances in gene function studies. Here, we tackle the challenge by deploying the text-mining capacities of large language models to process over 71,000 plant biology abstracts. Our approach unveiled nearly 5 million functional relationships between a wide array of biological entities--genes, metabolites, tissues, and others--with a high accuracy of over 85%. We encapsulated these findings in PlantConnectome, a user-friendly database, and demonstrated its diverse utility by providing insights into gene regulatory networks, protein-protein interactions, and stress responses. We believe this innovative use of AI in the life sciences will allow plant scientists to keep up to date with the rapidly growing corpus of scientific literature. PlantConnectome is available at https://plant.connectome.tools/.

bioinformatics↗

bioRxiv2025

Toward simple, rapid, and deep plant proteome analysis with an in-cell proteomics strategy

Although modern mass spectrometry (MS) based proteomics has been broadly employed by the plant science community, proteomics analysis of plant tissues remains highly challenging to general plant biology laboratories, mainly due to the lack of effective and easily adaptable strategies that can process plant samples for MS analysis rapidly and reliably. Existing methods often involves lengthy mechanical disruption and protein extraction, which not only require large starting materials but also can cause significant variations, compromising quantitation accuracy. Here, we present an "in-cell proteomics" strategy and benchmark its performance against conventional processing methods using several model plants, including Arabidopsis thaliana, Nicotiana benthamiana, Zea mays and Sorghum bicolor. The comprehensive datasets from this study indicate that the on-filter in-cell (OFIC) processing-based "in-cell proteomics" strategy can eliminate cell lysis of plant leaves and pollen grains, and process proteins directly, enabling the identification of 9,000 to 12,000 proteins from leaves, and 7,000 to 9,000 proteins from pollen grains using one-shot LCMS. The OFIC strategy demonstrated broadly equivalent or better performance over conventional approaches in the context of simplicity, speed, digestion effectiveness, and quantitation accuracy. Applying the strategy to investigate plant leaf infection of N. benthamiana leaves revealed interesting signature proteins that respond differentially to host-adapted Colletotrichum destructivum and nonhost-adapted Colletotrichum sublineola fungus. The single-vessel approach bypasses cell disruption, substantially simplifying plant sample preparation while reducing the required sample input and enhancing proteomic sensitivity. It offered a generalizable approach to study plant leaf infection and other significant questions in plant biology and beyond.

biochemistry↗

bioRxiv2022

BOS1 is a positive regulator of wounding induced cell death and plant susceptibility to Botrytis

Programmed cell death (PCD) is required for many aspects of plant biology, including stress responses, immunity, and plant development including root and flower development. Our understanding of PCD regulation is incomplete, especially concerning regulators involved in multiple divergent processes. The botrytis-suscetible1 (bos1) mutant is one of the genotypes most susceptible to Botrytis cinerea (Botrytis) and has revealed the role of BOS1 in cell death propagation during plant responses to wounding. The bos1-1 allele harbours a T-DNA located in the 5UTR upstream from the start codon that results in elevated BOS1 transcript levels. Here, we resequenced the bos1-1 genome and found a MAS promoter at the ends of the T-DNAs. Expression of the BOS1 gene under control of the MAS promoter conferred the characteristic bos1-1 Botrytis- sensitivity and wounding phenotypes in wildtype plants. We used Crispr-Cas9 to create new bos1 alleles that disrupt exons. These lines lacked the typical bos1-1 wounding and Botrytis phenotypes, but exhibited reduced fertility, as previously observed in other bos1 T-DNA alleles. With multiple overexpression lines of BOS1, we demonstrate that BOS1 is involved in regulation of cell death propagation in a dosage dependent manner. Our data support that bos1-1 is a gain-of-function mutant and that BOS1 acts as a positive regulator of wounding and Botrytis-induced PCD. Taken together these finding suggest that BOS1 function in both fertility and Botrytis response could be unified under cell death control.

plant biology↗

bioRxiv2023

Comparative mutant analyses reveal a novel mechanism of ARF regulation in land plants

A major challenge in plant biology is to understand how the plant hormone auxin regulates diverse transcriptional responses throughout development, in different environments, and in different species. The answer may lie in the specific complement of auxin signaling components in each cell. The balance between activators (class-A AUXIN RESPONSE FACTORS) and repressors (class-B ARFs) is particularly important. It is unclear how this balance is achieved. Through comparative analysis of novel, dominant mutants in maize and the moss Physcomitrium patens, we have discovered a [~]500-million-year-old mechanism of class-B ARF protein level regulation, important in determining cell fate decisions across land plants. Thus, our results add a key piece to the puzzle of how auxin regulates plant development.

plant biology↗

bioRxiv2025

A non-coding SNP in ELF3 alters expression of ELF3β and confers adaptation of Arabidopsis to a continental climate

Circadian clocks are biological timekeepers that influence most aspects of plant biology and allow organisms to predict and adapt to daily and seasonal environmental cycles. In particular, the important role of circadian clocks in phenology has led to numerous examples of both functional variation in circadian clock genes within natural and domesticated plant populations. To assess variation of circadian rhythms in natural Arabidopsis populations, we have phenotyped 287 accessions using a seedling transformation protocol with a circadian luciferase reporter. A genome wide association study of circadian period identified multiple single nucleotide polymorphisms (SNPs) in the core clock gene EARLY FLOWERING 3 (ELF3). We identified three ELF3 haplogroups that are associated with seasonal variability in temperature found in continental climates and found strong evidence of a selective sweep coinciding with the most recent de-glaciation period in Europe. One of the SNPs is located within intron 2 of ELF3 in the region upstream of an alternative transcription start site affecting expression of a shorter ELF3{beta} transcript. Our results indicate the important role of subtle variation in a core circadian clock gene in adaptation to changing climate.

plant biology↗

bioRxiv2025

DASH: A versatile and high-capacity gene stacking system for plant synthetic biology

DNA assembly systems based on the Golden Gate method are popular in synthetic biology but have several limitations: small insert size, incompatibility with other cloning platforms, DNA domestication requirement, generation of fusion scars, and lack of post-assembly modification. To address these obstacles, we present the DASH assembly toolset, which combines features of Golden Gate-based cloning, recombineering, and site-specific recombinase systems. We developed (1) a set of donor vectors based on the GoldenBraid platform, (2) an acceptor vector derived from the plant transformation-competent artificial chromosome (TAC) vector, pYLTAC17, and (3) a re-engineered recombineering-ready E. coli strain, CZ105, based on SW105. The initial assembly steps are carried out using the donor vectors following standard GoldenBraid assembly procedures. Importantly, existing parts and transcriptional units created using compatible Golden Gate-based systems can be transferred to the DASH donor vectors using standard single-tube restriction/ligation reactions. The cargo DNA from a DASH donor vector is then efficiently transferred in vivo in E. coli into the acceptor vector by the sequential action of a rhamnose-inducible phage-derived PhiC31 integrase and arabinose-inducible yeast-derived Flippase (FLP) recombinase using CZ105. Furthermore, recombineering-based post-assembly modification, including the removal of undesirable scars, is greatly simplified. To demonstrate the utility of the DASH system, a 116 kb DNA construct harboring a 97 kb cargo consisting of 35 transcriptional units was generated. One of the CDSs in the final assembly was replaced through recombineering, and the in planta functionality of the entire construct was tested in both transient and stable transformants.

synthetic biology↗

bioRxiv2020

Direct data-independent acquisition (direct DIA) enables substantially improved label-free quantitative proteomics in Arabidopsis

The last decade has seen significant advances in the application of quantitative mass spectrometry-based proteomics technologies to tackle important questions in plant biology. The current standard for quantitative proteomics in plants is the use of data-dependent acquisition (DDA) analysis with or without the use of chemical labels. However, the DDA approach preferentially measures higher abundant proteins, and often requires data imputation due to quantification inconsistency between samples. In this study we systematically benchmarked a recently developed library-free data-independent acquisition (directDIA) method against a state-of-the-art DDA label-free quantitative proteomics workflow for plants. We next developed a novel acquisition approach combining MS1-level BoxCar acquisition with MS2-level directDIA analysis that we call BoxCarDIA. DirectDIA achieves a 33% increase in protein quantification over traditional DDA, and BoxCarDIA a further 8%, without any changes in instrumentation, offline fractionation, or increases in mass-spectrometer acquisition time. BoxCarDIA, especially, offers wholly reproducible quantification of proteins between replicate injections, thereby addressing the long-standing missing-value problem in label-free quantitative proteomics. Further, we find that the gains in dynamic range sampling by directDIA and BoxCarDIA translate to deeper quantification of key, low abundant, functional protein classes (e.g., protein kinases and transcription factors) that are underrepresented in data acquired using DDA. We applied these methods to perform a quantitative proteomic comparison of dark and light grown Arabidopsis cell cultures, providing a critical resource for future plant interactome studies. Our results establish BoxCarDIA as the new method of choice in quantitative proteomics using Orbitrap-type mass-spectrometers, particularly for proteomes with large dynamic range such as that of plants.

plant biology↗

bioRxiv2024

Expression of a mammalian RNA demethylase increases flower number and floral stem branching in Arabidopsis thaliana

RNA methylation plays a central regulatory role in plant biology and is a relatively new target for plant improvement efforts. In nearly all cases, perturbation of the RNA methylation machinery results in deleterious phenotypes. However, a recent landmark paper reported that transcriptome-wide use of the human RNA demethylase FTO substantially increased the yield of rice and potatoes. Here, we have performed the first independent replication of those results and broader transferability of the trait, demonstrating increased flower and fruit count in the model species Arabidopsis thaliana. We also performed RNA-seq of our FTO-transgenic plants, which we analyzed in conjunction with previously-published datasets to detect several previously-recognized patterns in the functional and structural classification of the upregulated and downregulated genes. From these, we present mechanistic hypotheses to explain these surprising results with the goal of spurring more widespread interest in this promising new approach to plant engineering.

plant biology↗

bioRxiv2019

Simultaneous and precise generation of Zebra3 and Wsl5 mutations in rice using CRISPR/Cas9-mediated adenine base editors

The CRISPR/Cas9-mediated base editing technology can efficiently generate point mutations in the genome without introducing double-strand break (DSB) or supplying a DNA donor template for homology-dependent repair (HDR). In this study, adenine base editors (ABEs) were used for rapid generation of precise point mutations in two distinct genes, OsWsl5, and OsZebra3 (Z3), in rice protoplasts and regenerated plants. The precisely engineered point mutations were stably inherited to subsequent generations. These single nucleotide alterations resulted in single amino acid changes and associated wsl5 and z3 phenotypes as evidenced by white stripe leaf and light green/dark green leaf pattern, respectively. Through selfing and segregation, transgene-free, base edited wsl5 and z3 mutants were readily obtained in a short period of time. We noticed a novel mutation (V540A) in Z3 locus could mimic the phenotype of Z3 mutation (S542P). Furthermore, we observed unexpected non-A/G or T/C mutations in the ABE editing window in a few of the edited plants. The ABE vectors and the method from in this study could be used to simultaneously generate point mutations in multiple genes in a single transformation and serve as a useful base editing tool for crop improvement as well as basic studies in plant biology.\n\nHighlightsAdenine base editors were adapted for plant base editing that can generate precise and heritable point mutations in rice genome without indel formation. The base editing approach allows rapid generation of transgene-free rice mutants with expected phenotypic changes.

plant biology↗