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Results for “plant biology”

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At least 19 recordsLinked to original sources

bioRxiv2026

VizR: An Interactive Web Platform for End-to-End RNA-Seq Analysis and Visualization in Plant Biology

RNA sequencing (RNA-seq) is widely used to investigate transcriptional programs in plant biology, yet the need to combine multiple specialized tools and bioinformatics expertise to convert raw sequencing reads into biologically interpretable results remains a major technical barrier for many plant biologists. Here, we present VizR (VIsualiZation of Rna seq), a web- based platform that integrates end-to-end RNA-seq analysis and visualization within a single integrated environment. VizR automates upstream processing, including quality control, adapter trimming, genome alignment, and transcript quantification, and connects the resulting expression data to downstream exploratory analyses. Its interface is designed to make expression patterns immediately searchable and interpretable: users can query genes through an equalizer-style expression-pattern interface, inspect expression profiles using inline heatmaps embedded in gene tables, and perform context-integrated gene ontology analysis throughout the workflow. VizR also supports comparative analysis through interactive Venn diagram module, allowing users to transfer gene sets directly from result tables. As a Docker- based application, VizR can be deployed locally and accessed through a standard web browser. By unifying automated RNA-seq processing, interactive visualization, and functional interpretation, VizR lowers the technical barrier to transcriptome analysis and provides a practical platform for plant biology research.

bioinformatics↗

bioRxiv2024

Implementation of pupylation-based proximity labelling in plant biology reveals regulatory factors in cellulose biosynthesis

Knowledge about how and where proteins interact provides a pillar for cell biology. Biotin-related proximity labelling approaches are efficiently monitoring protein interactions but may have labelling-related drawbacks. Here, we introduce pupylation-based proximity labelling (PUP-IT) as a tool for protein interaction detection in plant biology. We show that PUP-IT readily confirmed and extended protein interactions for several known protein complexes, across different types of plant systems. To further demonstrate the power of PUP-IT, we used the system to identify protein interactions of the protein complex that underpin cellulose synthesis in plants. Apart from known complex components, we identified the ARF-GEF BEN1 (BFA-VISUALIZED ENDOCYTIC TRAFFICKING DEFECTIVE1). We show that BEN1 contributes to cellulose synthesis by regulating the trafficking of the cellulose synthesis protein complex between the trans-Golgi network and the plasma membrane. Our results, therefore, introduce PUP-IT as a new and powerful proximity labelling system to identify protein interactions in plant cells.

plant biology↗

bioRxiv2021

Structural studies on cell wall biogenesis-I: A method to produce high-quality protoplasts from alga Micrasterias denticulata, an emerging model in plant biology

Micrasterias denticulate is a freshwater unicellular green alga emerging as a model system in plant cell biology. This is an algae that has been examined in the context of cell wall research from early 1970s. Protoplast production from such a model system is important for many downstream physiological and cell biological studies. The algae produce intact protoplast in a straight two-step protocol involving 5% mannitol, 2% cellulysin, 4mM calcium chloride under a temperature ramping strategy. The process of protoplast induction and behavior of protoplast was examined by light microscopy and reported in this study.

plant biology↗

bioRxiv2025

Enhancing CRISPR Education: A Plug-And-Play Framework for Teaching Gene Editing in Plant Biology

Modern molecular biology tools and technologies such as CRISPR have sped up scientific discovery. From an educational perspective, these advancements are both exciting and overwhelming. Educators shaping these future scientists face the ongoing challenge of staying compliant with the latest developments in molecular biology while finding effective ways to teach these discoveries. As the use of CRISPR gene editing technology continues to expand globally, there is an increasing need for a workforce that is both knowledgeable about its theoretical foundations and trained in its practical use. While advanced, technology-driven STEM courses have the potential to improve student retention, they are often lecture-heavy and lack intentional engagement strategies that support deeper learning. Moreover, agriculture is the second most impacted sector by this technology, yet there is a significant lack of teaching materials focused on CRISPR in plant biology. To address these gaps, we developed a framework for teaching gene editing that incorporates multiple engagement strategies beyond traditional lecture-based instruction. This framework was implemented over two semesters in an Introduction to Gene Editing course at Tennessee State University, offered to both undergraduate and graduate students enrolled in a degree in Agricultural Sciences. This manuscript outlines the various strategies used in the course including active learning, multimodal instructional approaches and experiential learning strategies that can be adopted in other classrooms to effectively teach gene editing. Survey-based results from the course indicate a measurable increase in student comfort with designing and executing CRISPR-Cas based experiments. Societal Impact StatementPlant biology lacks accessible teaching materials for CRISPR, a powerful gene-editing technology widely used to improve agriculture. We developed an engaging framework to teach CRISPR concepts to advanced undergraduates and graduate students in plant sciences, which can be readily adopted by other instructors. The approach increased self-reported confidence in students and comfort in explaining CRISPR. Since instructors often have limited time to design interactive lessons, this framework offers a ready-to-use, effective strategy that makes CRISPR more widely available in classrooms, ultimately strengthening CRISPR literacy in the future agricultural workforce.

scientific communication and education↗

bioRxiv2017

The unrealized potential of herbaria in global change biology

Plant and fungal specimens in herbaria are becoming primary resources for investigating how plant phenology and geographic distributions shift with climate change, greatly expanding inferences across spatial, temporal, and phylogenetic dimensions. However, these specimens contain a wealth of additional data--including nutrients, defensive compounds, herbivore damage, disease lesions, and signatures of physiological processes--that capture ecological and evolutionary responses to the Anthropocene but which are less frequently utilized. Here, we outline the diversity of herbarium data, global change topics to which they have been applied, and new hypotheses they could inform. We find that herbarium data have been used extensively to study impacts of climate change and invasive species, but that such data are less commonly used to address other drivers of biodiversity loss, including habitat conversion, pollution, and overexploitation. In addition, we note that fungal specimens are under-explored relative to vascular plants. To facilitate broader application of plant and fungal specimens in global change research, we outline the limitations of these data and modern sampling and statistical tools that may be applied to surmount challenges they present. Using a case study of insect herbivory, we illustrate how novel herbarium data may be employed to test hypotheses for which few data exist, despite potentially large biases. With the goal of positioning herbaria as hubs for global change research, we suggest future research directions and curation priorities.

plant biology↗

bioRxiv2026

Bacteriophage P22 virus-like particles as nanoscale protein scaffolds for plant synthetic biology

Advancing the utility of plant synthetic biology requires the continued development of protein engineering tools. Self-assembling protein compartments, such as virus-like particles (VLPs), provide versatile scaffolds for synthetic biology. However, few plant-expressed VLPs have demonstrated broad amenability to protein engineering, restricting their applications to specific contexts. Here, the Salmonella typhimurium bacteriophage P22 VLP is explored as a novel protein scaffold for plant synthetic biology, demonstrating its application in a eukaryote for the first time. Through transient expression in the biofactory plant Nicotiana benthamiana, the capacity for P22 VLPs to correctly assemble and selectively encapsulate recombinant protein cargo is demonstrated. The durability of this protein scaffold is explored, through co-encapsulation of multiple cargo protein species and by encapsulation through direct fusion to the P22 coat protein. Finally, the ability to simultaneously program cargo encapsulation and external protein display on P22 VLPs in vivo is demonstrated through SpyTag/SpyCatcher-mediated protein conjugation. This work demonstrates the broad utility of P22 VLPs as nanoscale protein scaffolds for plant synthetic biology.

synthetic biology↗

bioRxiv2019

A reversible memory switch for plant synthetic biology based on the phage PhiC31 integration system

Plant synthetic biology aims to contribute to global food security by engineering plants with new or improved functionalities. In recent years, synthetic biology has rapidly advanced from the setup of basic genetic devices to the design of increasingly complex gene circuits able to provide organisms with novel functions. While many bacterial, fungal and mammalian unicellular chassis have been extensively engineered, this progress has been delayed in plants due to their complex multicellular nature and the lack of reliable DNA devices that allow an accurate design of more sophisticated biological circuits. Among these basic devices, gene switches are crucial to deploying new layers of regulation into the engineered organisms. Of special interest are bistable genetic toggle switches, which allow a living organism to exist in two alternative states and switch between them with a minimal metabolic burden. Naturally occurring toggle switches control important decision-making processes such as cell fate and developmental events. We sought to engineer whole plants with an orthogonal genetic toggle switch to be able to regulate artificial functions with minimal interference with their natural pathways. Here we report a bistable toggle memory switch for whole plants based on the phage PhiC31 serine integrase and its cognate recombination directionality factor (RDF). This genetic device was designed to control the transcription of two genes of interest by inversion of a central DNA regulatory element. Each state of the device is defined by one transcriptionally active gene of interest, while the other one remains inactive. The state of the switch can be reversibly modified by the action of the recombination actuators, which were administered externally (e.g. via agroinfiltration), or produced internally in response to an inducible chemical stimulus. We extensively characterized the kinetics, memory, and reversibility of this genetic switch in Nicotiana benthamiana through transient and stable transformation experiments using transgenic plants and hairy roots. Finally, we coupled the integrase expression to an estradiol-inducible promoter as a proof of principle of inducible activation of the switch.

synthetic biology↗

bioRxiv2025

BOTany Methods: Accessible Automation for Plant Synthetic Biology

Most members of the synthetic biology community, particularly plant scientists, lack access to liquid handling robots to scale up experiments, enhance reproducibility, and accelerate the Design, Build, Test, Learn cycle. Biofoundries enable high throughput data acquisition to train AI models and to develop new bioproducts, but they are capital-intensive to set up and not widely distributed. Entry-level, 3D-printed robots offer more affordable alternatives, but suffer from a shortage of validated protocols that can be modified without prior coding experience. To enhance access to biological automation, we developed a collection of modular BOTany Methods using Opentrons OT-2 robots to streamline the most common methods for molecular biology research and education. Our comprehensive workflow offers automation for a variety of procedures, ranging from simple but repetitive tasks (such as primer dilution and PCR setup) to more complex operations, including Plant Modular Cloning (MoClo), bacterial transformation, and plasmid extraction. Our BOTany Methods enable undergraduate students and other early career researchers to run designer experiments using table-based inputs, without editing the custom Python scripts. This pipeline enables end-to-end molecular cloning with minimal user intervention, enhancing throughput and traceability for synthetic biology applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/671538v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1b98282org.highwire.dtl.DTLVardef@2727bdorg.highwire.dtl.DTLVardef@a2157borg.highwire.dtl.DTLVardef@1305107_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Sphingolipid-driven interleaflet coupling orchestrates Rho-GTPase recruitment to nanodomains for signal activation in plants

Biological membranes are both laterally heterogeneous and asymmetrical across leaflets, yet how this asymmetry contributes to signal transduction remains unclear. Here we show that sphingolipid-driven interleaflet coupling coordinates nanodomain organization and Rho-GTPase activation in plants. Using molecular dynamics simulations, super-resolution and single-molecule imaging, quantitative genetics, and biochemistry, we find that very long acyl chain (VLCFA)-containing sphingolipids in the outer leaflet interdigitate with phosphatidylserine (PS) in the inner leaflet, forming a vertical molecular bridge that organizes PS into nanodomains. This coupling promotes recruitment and activation of the Rho-GTPase ROP6 in response to auxin, whereas disruption of VLCFA synthesis or sphingolipid composition disperses PS and ROP6 nanodomains, impairing cytoskeletal reorganization and directional growth. Our findings reveal interleaflet coupling as a fundamental organizing principle linking membrane asymmetry to signaling, providing a conceptual framework for spatial and temporal control of signal transduction across eukaryotic membranes.

plant biology↗

bioRxiv2025

A high-throughput heterologous expression platform for plant synthetic biology based on Arabidopsis suspension cells

Efficient heterologous expression platforms are essential for plant synthetic biology, particularly for engineering complex multigene pathways. Here, we establish a high-throughput system for both transient and stable transformation of Arabidopsis thaliana suspension cells using plant cell pack infiltration. This method requires no specialized equipment or consumables and is compatible with several cell lines. It enables rapid generation of 100 g of transgenic cells within two weeks and allows expression of at least 6 stacked genes from a single construct. We characterized constitutive promoters for gene expression in Arabidopsis cells and validated plastid targeting peptides. A library of NifB homologs was screened for expression and solubility and several archaeal variants suitable for plant expression were identified. We further engineered stable cell lines expressing up to six genes, encoding the NifB module components NifU, NifS, FdxN, and NifB, demonstrating that the newly developed platform integrates into an established workflow for nitrogenase engineering. The platform accelerates design-build-test cycles and facilitates the production of delicate proteins that require large amounts of transgenic biomass. It thus represents a versatile and scalable tool for advancing synthetic biology and for tackling major biotechnological challenges, such as biological nitrogen fixation. HighlightWe developed a fast and scalable expression platform in Arabidopsis suspension cells, enabling transient and stable multigene expression for applications in plant synthetic biology such as nitrogenase engineering.

plant biology↗

bioRxiv2025

What Large Language Models Know About Plant Molecular Biology

Large language models (LLMs) are rapidly permeating scientific research, yet their capabilities in plant molecular biology remain largely uncharacterized. Here, we present MOBIPLANT, the first comprehensive benchmark for evaluating LLMs in this domain, developed by a consortium of 112 plant scientists across 19 countries. MOBIPLANT comprises 565 expert-curated multiple-choice questions and 1,075 synthetically generated questions, spanning core topics from gene regulation to plant-environment interactions. We benchmarked seven leading chat-based LLMs using both automated scoring and human evaluation of open-ended answers. Models performed well on multiple-choice tasks (exceeding 75% accuracy), although most of them exhibited a consistent bias towards option A. In contrast, expert reviews exposed persistent limitations, including factual misalignment, hallucinations, and low self-awareness. Critically, we found that model performance strongly correlated with the citation frequency of source literature, suggesting that LLM knowledge inherits the visibility distribution of the underlying scientific corpus. Consequently, models tend to be more reliable on consolidated topics and less reliable on under-cited or recently emerging ones. We also benchmarked agents equipped with web-search and additional tools in more complex tasks involving DNA sequence analysis. These agents were outperformed by domain specific models in sequence classification and regression tasks, indicating an opportunity for joint agentic systems that combine both the reasoning power of LLMs and the dedicated processing of DNA models. This understanding is key to guiding both the development of next-generation models and the informed use of current tools in the everyday work of plant researchers. MOBIPLANT is publicly available online in this link.

plant biology↗

bioRxiv2021

Quantification of biologically and chemically bound phosphorus in activated sludge from full-scale plants with biological P-removal

Large amounts of phosphorus (P) are present in activated sludge from municipal wastewater treatment plants, where it exists in the form of metal salt precipitates or biologically bound into the biomass as nucleic acids, cell membrane components, and the extracellular polymeric substances or, in special polyphosphate-accumulating organisms (PAOs), as intracellular polyphosphate. Only recently, methods that reliably allow an absolute quantification of the different P-fractions, such as sequential extraction, Raman microspectroscopy, solid-state 31P magic angle spinning (MAS) NMR, and solution state 31P NMR have been developed. This study combines these techniques to obtain a comprehensive P mass-balance of activated sludge from four wastewater treatment plants with enhanced biological phosphate removal (EBPR). The total content of P and various cations was measured by chemical analysis (ICP-OES), and different P fractions were extracted for chemical characterization. Chemically bound P constituted 38-69% of total P, most likely in the form of Fe, Mg, or Al minerals, while organically bound P constituted 7-9%. By using Raman microspectroscopy and solution state 31P NMR and 31P MAS NMR spectroscopy before and after anaerobic P-release experiments, poly-P was quantified and constituted 22-54% of total P in the activated sludges and was found in approx. 25% of all bacterial cells. Moreover, Raman microspectroscopy in combination with fluorescence in situ hybridization (FISH) was used to quantify the species-specific intracellular poly-P of known PAO genera (Tetrasphaera, Ca. Accumulibacter, Dechloromonas) and other microorganisms known to possess high level of poly-P, such as the filamentous Ca. Microthrix. They were all abundant, as measured by quantitative-FISH and amplicon sequencing, and accumulated large amount of poly-P, depending on their cell-size, contributing substantially to the P-removal. Interestingly, in all four EBPR plants investigated, only 1-13% of total poly-P was stored by unidentified PAO, highlighting that most PAOs in the full-scale EBPR plants investigated are now known. HighlightsO_LIExhaustive P mass-balance of main organic and inorganic P-species in four EBPR plants C_LIO_LIQuantification of poly-P of FISH-defined PAO and other species with high P content C_LIO_LITotal P content was 36-50 mgP/gSS of which 31-62% was in biomass and as poly-P C_LIO_LIA high fraction of all cells (25-30%) contained a high content of poly-P C_LIO_LIKnown PAOs contained almost all poly-P in the EBPR plants investigated C_LI

microbiology↗

bioRxiv2023

A quantitative autonomous bioluminescence reporter system with a wide dynamic range for Plant Synthetic Biology

Engineered autonomous bioluminescence (EAB) offers many potential applications in Plant Synthetic Biology, notably as in vivo reporter system. Current EAB reporter configurations are limited for quantitative applications due to low dynamic range. We reconfigured the Neonothopanus nambi fungal bioluminescence (NeoLuc) pathway to serve as a high-throughput and inexpensive reporter for quantitative analysis of gene expression. We showed that by configuring the first committed step in the pathway (HispS) as the transcriptional entry point instead of the fungal luciferase, the dynamic range of the output increased dramatically, equaling that of the FLuc/RLuc reporter, and outperforming it in high throughput capacity. Furthermore, the inclusion of an enhanced GFP as normalizer allowed transient ratiometric measurements in N. benthamiana. Fast and rich datasets generated by the NeoLuc/eGFP system enabled us to undertake the optimization of new challenging synthetic gene circuits, including a complex agrochemical/optogenetic dual input switch for tight control of engineered metabolic pathways.

synthetic biology↗

bioRxiv2026

Genomic footprints of selfing, introduction history, and long-distance dispersal in an invasive alien plant

Biological invasions are natural experiments for studying the evolutionary and ecological processes underlying colonization success and range expansion. Using genome-wide data -- generated via genotyping-by-sequencing (GBS) from 30 populations spanning Europe and South Africa-- we investigated the colonization history and successful spread of the invasive buttonweed Cotula coronopifolia, an annual plant introduced into Europe from South Africa about 300 years ago. Our analyses identified three major lineages in Europe distributed across the continent, often co-occurring without evidence of admixture. Phylogenomic dating revealed that these lineages diverged > 2,000 years ago --well before the earliest European records-- suggesting divergence within the native range and either multiple introductions or a single introduction with multiple lineages. Mating-system inference shows that reproduction occurs primarily via self-fertilization ([~]70% on average), although outcrossing predominates in some populations, revealing a facultative mating system. This high selfing rate has led to extremely low heterozygosity in most populations and a strong genetic structure. Genetic clustering also revealed admixed individuals resulting from rare inter-lineage outcrossing; comparisons of empirical and simulated data indicate that increased diversity after sporadic admixture events decays rapidly under subsequent selfing. Both the introduction history and long-distance dispersal facilitated by waterbirds likely explain the scattered distribution of lineages across Europe. Altogether, these results provide an empirical demonstration of Bakers "ideal weed" concept, highlighting the role of a flexible mating system in providing reproductive assurance during colonization and showing how predominant selfing shapes the genomic landscape of an invasive species. SIGNIFICANCE STATEMENTUnderstanding how reproductive strategies influence colonization and spread of alien species is central to invasion biology. By combining population genomics and phylogenomic inference, this study provides key insights into the colonization history and successful invasion of the self-fertilizing plant C. coronopifolia, introduced from South Africa to Europe in the 18th century. We show that the species invasion success relies on the introduction of multiple lineages and the predominance of selfing, which has drastically reduced genetic diversity yet contributed to reproductive assurance and spread across diverse habitats. Occasional outcrossing and long-distance dispersal by waterbirds or through horticultural transport have further shaped the species genetic landscape. These findings illustrate how self-compatibility and ecological generalism can overcome genetic constraints during range expansion and provide the basis for understanding the evolutionary dynamics of selfing plant invasions.

genomics↗

bioRxiv2018

Evaluating Named-Entity Recognition approaches in plant molecular biology

Text mining research is becoming an important topic in biology with the aim to extract biological entities from scientific papers in order to extend the biological knowledge. However, few thorough studies on text mining and applications are developed for plant molecular biology data, especially rice, thus resulting a lack of datasets available to train models able to detect entities such as genes, proteins and phenotypic traits. Since there is rare benchmarks for rice, we have to face various difficulties in exploiting advanced machine learning methods for accurate analysis of rice bibliography. In this article, we developed a new training datasets (Oryzabase) as the benchmark. Then, we evaluated the performance of several current approaches to find a methodology with the best results and assigned it as the state of the art method for our own technique in the future. We applied Name Entities Recognition (NER) tagger, which is built from a Long Short Term Memory (LSTM) model, and combined with Conditional Random Fields (CRFs) to extract information of rice genes and proteins. We analyzed the performance of LSTM-CRF when applying to the Oryzabase dataset and improved the results up to 86% in F1. We found that on average, the result from LSTM-CRF is more exploitable with the new benchmark.

bioinformatics↗

bioRxiv2021

MiDAS 4: A global catalogue of full-length 16S rRNA gene sequences and taxonomy for studies of bacterial communities in wastewater treatment plants

Biological wastewater treatment and an increased focus on resource recovery is fundamental for environmental protection, human health, and sustainable development. Microbial communities are responsible for these processes, but our knowledge of their diversity and function is still poor, partly due to the lack of good reference databases and comprehensive global studies. Here, we sequenced more than 5 million high-quality, full-length 16S rRNA gene sequences from 740 wastewater treatment plants (WWTPs) across the world and used the sequences to construct MiDAS 4, a full-length amplicon sequence variant resolved 16S rRNA gene reference database with a comprehensive taxonomy from the domain to species-level for all references. Using a study-independent amplicon dataset from the Global Water Microbiome Consortium project (269 WWTPs), we showed that the MiDAS 4 database provides much better coverage for bacteria in WWTPs worldwide compared to commonly applied universal references databases, and greatly improved the rate of genus and species-level classification. Hence, MiDAS 4 provides a unifying taxonomy for the majority of prokaryotic diversity in WWTPs globally, which can be used for linking microbial identities with their functions across studies. Taking advantage of MiDAS 4, we carried out an amplicon-based, global-scale microbial community profiling of activated sludge plants using two common sets of primers targeting the V1-V3 and V4 region of the 16S rRNA gene. We found that the V1-V3 primers were generally best suited for this ecosystem, and revealed how environmental conditions and biogeography shape the activated sludge microbiota. We also identified process-critical taxa (core and conditionally rare or abundant taxa), encompassing 966 genera and 1530 species. These represented approximately 80% and 50% of the accumulated read abundance, respectively, and represent targets for further investigations. Finally, we showed that for well-studied functional guilds, such as nitrifiers or polyphosphate accumulating organisms, the same genera were prevalent worldwide, with only a few abundant species in each genus.

microbiology↗

bioRxiv2026

A CURE for synthetic regulation of gene expression: Rapid screening of guide RNA efficacy as a framework for enabling undergraduate research in plant synthetic biology

Course-based Undergraduate Research Experiences (CUREs) have emerged as a transformative approach to science education, expanding access to authentic research opportunities beyond the traditional undergraduate research assistant (URA) training. By embedding research into a curriculum, CUREs engage a broad and diverse population of students in a classroom environment that emphasizes experimental design, data analysis, and scientific communication. However, this has been difficult to develop for fields such as plant synthetic biology due to the long timescales of plant transformation. One avenue around this problem is to utilize a recent innovation that enables high throughput and rapid screening of gRNA efficacy by leveraging viral-based delivery of guide RNAs (gRNAs). In this work, we develop and validate a CURE with undergraduate students at Colorado State University (CSU). Students worked in teams to design and test efficacy of gRNAs targeting a Cas9-based transcriptional repressor to different regions of the promoters of the three GIBBERELLIN INSENSITIVE 1 genes (GID1a, GID1b, and GID1c) in Arabidopsis thaliana. Over the semester, students generated and analyzed gene expression data to understand the efficiency of twelve new gRNAs. We further validated CURE student-identified gRNAs with an undergraduate research assistant (URA) that assessed target gene expression and phenotypic outcomes in stable transgenic lines expressing SynTF constructs with the strongest gRNAs from the class. We further describe the curriculum structure to facilitate adoption at other institutions and present student-generated datasets demonstrating the utility of ViN-based screening for identifying effective SynTF gRNAs for plant functional genomics and engineering.

synthetic biology↗

bioRxiv2016

Araport11: a complete reannotation of the Arabidopsis thaliana reference genome

The flowering plant Arabidopsis thaliana is a dicot model organism for research in many aspects of plant biology. A comprehensive annotation of its genome paves the way for understanding the functions and activities of all types of transcripts, including mRNA, noncoding RNA, and small RNA. The most recent annotation update (TAIR10) released more than five years ago had a profound impact on Arabidopsis research. Maintaining the accuracy of the annotation continues to be a prerequisite for future progress. Using an integrative annotation pipeline, we assembled tissue-specific RNA-seq libraries from 113 datasets and constructed 48,359 transcript models of protein-coding genes in eleven tissues. In addition, we annotated various classes of noncoding RNA including small RNA, long intergenic RNA, small nucleolar RNA, natural antisense transcript, small nuclear RNA, and microRNA using published datasets and in-house analytic results. Altogether, we identified 738 novel protein-coding genes, 508 novel transcribed regions, 5051 non-coding genes, and 35846 small-RNA loci that formerly eluded annotation. Analysis on the splicing events and RNA-seq based expression profile revealed the landscapes of gene structures, untranslated regions, and splicing activities to be more intricate than previously appreciated. Furthermore, we present 692 uniformly expressed housekeeping genes, 43% of whose human orthologs are also housekeeping genes. This updated Arabidopsis genome annotation with a substantially increased resolution of gene models will not only further our understanding of the biological processes of this plant model but also of other species.

Plant Biology↗