Biology subjects

Lewsey, M. G.

Publications and source records attributed to Lewsey, M. G..

16 recordsLinked to original sources

bioRxiv2026

Developmental and regulatory logic of cannabis glandular trichomes resolved by single cell multiomics

Glandular trichomes of Cannabis sativa produce specialised metabolites including cannabinoids and terpenes, yet the cellular basis of trichome development and metabolic specialisation remains unresolved. Here we reconstruct the glandular trichome lineage within the C. sativa inflorescence using single-cell transcriptomics and chromatin accessibility profiling. We identify a continuous developmental trajectory from the protoderm, linking bulbous, sessile, and capitate-stalked trichomes, indicating that these morphologies represent sequential stages rather than distinct trichome types. We further identify a previously undescribed neck cell that shares a developmental origin with secretory disc cells before lineage bifurcation. Integration of chromatin accessibility with transcription factor (TF) binding reveals cell state specific regulatory programs coordinating neck cell development and specialised metabolism, redox homeostasis, and secretion in mature secretory disc cells. Methyl jasmonate elicitation induces extensive transcriptional and chromatin landscape reprogramming in mature secretory disc cells and transient repression of specialised metabolic pathways. Together, these findings provide a cell-resolved regulatory framework for glandular trichome development and function, revising prevailing models of trichome identity, maturation and defence associated metabolic regulation.

plant biology↗

bioRxiv2026

Mitochondrial Retrograde Signaling in Arabidopsis thaliana: heterogenous, spatial and polarised aspects

Organelle retrograde signaling studies have exclusively relied on bulk tissues, obscuring cell-type specificity, spatial organization, and heterogeneity within cell types. Here, we use single-nucleus and spatial RNA sequencing to define the cellular and spatial architecture of mitochondrial stress signaling in Arabidopsis thaliana. Inhibition of the mitochondrial electron transport chain by antimycin A and myxothiazol rapidly redistributed nuclei among transcriptional states within epidermal, leaf pavement, and mesophyll lineages, revealing that mitochondrial dysfunction reshapes cell identity trajectories rather than eliciting a uniform response. Stress-associated clusters were already present at low frequency in untreated samples, but the numbers of cells increased following stress treatments, indicating that stress increases the proportion of nuclei occupying pre-existing, primed transcriptional states. Gene-level analyses revealed distinct temporal dynamics and variable cell-state penetrance of the canonical mitochondrial stress markers and identified broadly responsive genes absent from earlier marker sets. Spatial transcriptomics resolved tissue-scale responses, spanning from pan-tissue induction to cell-type- and cluster-restricted activation, and uncovered pronounced adaxial-abaxial polarity in gene expression. Cell identity and spatial inferences were supported by extensive experimental validation using a custom 465-probe 10x Xenium panel and 52 promoter-GFP reporter lines. Together, these data provide a high-resolution framework for organelle-to-nucleus signaling and a resource of cell-type markers and spatial maps to dissect mitochondrial stress signaling and its integration with developmental and environmental pathways.

plant biology↗

bioRxiv2025

Marginal zone B cells are antigenically activated, infiltrate the kidneys, and exacerbate angiotensin II-dependent hypertension in mice

AimsB cells contribute to the development of hypertension, yet, the specific B cell subsets involved, the mechanism underlying their activation, and the relevance of these responses to human disease remain poorly defined. Methods and resultsWe used single-cell RNA sequencing, single-cell B cell receptor (BCR) VDJ sequencing, and high dimensional flow cytometry to characterise B cell responses in murine angiotensin II-induced hypertension. Chronic angiotensin II infusion in male and female mice increased systolic blood pressure and selectively expanded marginal zone B (MZB) cells, with evidence of antigen-dependent activation, including clonal BCR expansion, enrichment of IGHV1 B cell receptor variants, and increased expression of activation markers (CD69 and Nur77). Intercellular communication analyses revealed enhanced antigen-presentation signalling between MZB and CD8+ T cells in hypertensive mice. Activated MZB-like memory B cells also accumulated in the kidneys of hypertensive mice. Consistent with these findings, multiomic analysis of kidneys from patients with hypertensive chronic kidney disease (CKD) demonstrated an increase in memory B cells with a MZB phenotype and enrichment of antigen-presentation-linked communication with CD8+ T cells. Importantly, hypertensive responses to angiotensin II infusion were significantly blunted in mice lacking MZB cells (BAFF-R-/-). ConclusionOur findings identify MZB cells as a selectively activated, antigen-responsive B cell subset that amplified pathogenic immune responses in murine and human hypertension. By linking subset-specific BCR activation to immune cross-talk and disease causality, this study identifies MZB cells - and the (auto)antigens that activate them - as promising targets for precision immunomodulatory strategies in hypertension.

physiology↗

bioRxiv2025

High-resolution transcriptomic profiling of the aortic cellular landscape during hypertension reveals novel drivers of vascular fibrosis

BackgroundAortic stiffening is a consequence of hypertension and a major contributor to end organ damage. A key driver of aortic stiffening is fibrosis involving the excess production of extracellular matrix (ECM) proteins such as collagen, fibronectin and laminin. The present study aimed to identify the cell types and signalling mechanisms that contribute to aortic fibrosis in hypertension. Methods and ResultsMale C57BL/6 mice (10-12-week-old) were randomly assigned to a 28-day angiotensin II (0.7 mg/kg/day) or vehicle (saline) infusion via osmotic minipump (s.c.). At endpoint, scRNA-seq analysis of 26,196 cells recovered all major aortic cell populations. Among these, fibroblasts exhibited the greatest heterogeneity and shift in gene expression after angiotensin II compared to all other cell types. Gene ontology analyses revealed that after angiotensin II treatment, a particular subcluster of fibroblasts (Fibro-Cthrc1) - characterised by its high expression of Cthrc1 - was especially fibrogenic. Fibro-Cthrc1 cells were nearly undetectable in aortas from vehicle-infused mice. Transcripts relating to ECM remodelling (Thbs2, Cdh11 and Postn) and collagen production (specifically collagen type I, III and V) were more highly enriched in Fibro-Cthrc1 compared to other fibroblasts within hypertensive aortas. Moreover, GO terms corresponding to profibrotic signalling pathways (i.e., cell adhesion, extracellular matrix organisation and collagen fibril organisation) were significantly enriched in Fibro-Cthrc1. Spatial transcriptomics and immunohistochemistry confirmed the presence of Fibro-Cthrc1 in the adventitial layer of angiotensin II-infused but not vehicle-infused mice. Finally, analysis of plasma analytes in approximately 24,000 participants of the UK Biobank collection revealed CTHRC1 to be strongly associated with raised systolic blood pressure and pulse pressure, and a strong predictor of the risk of developing hypertension over a 15-year follow-up. ConclusionOur study identifies a novel fibroblast subcluster, Fibro-Cthrc1, as a potential driver of aortic fibrosis and stiffening in hypertension. This cluster is absent in normotensive aortas, suggesting that targeting Fibro-Cthrc1 therapeutically could prevent aortic fibrosis and its associated hypertensive end-organ damage. Notably, such an approach may avoid compromising physiological extracellular matrix production and vessel integrity. Translational perspectiveAortic stiffening is a hallmark of hypertension resulting from functional (vasoconstriction) and structural (extracellular matrix remodelling) alterations of the vessel wall. While several antihypertensive medications address functional changes, no therapies directly target the causes of the structural remodelling. The therapeutic challenge is to distinguish between physiological and pathological extracellular matrix remodelling. This study identifies a novel highly profibrotic fibroblast cell population (Fibro-Cthrc1) present in aortas from hypertensive, but not normotensive mice. This raises the possibility that Fibro-Cthrc1 may be a key driver of aortic stiffening and a promising future therapeutic target.

physiology↗

bioRxiv2025

Towards accurate, reference-free differential expression: A comprehensive evaluation of long-read de novo transcriptome assembly

Long-read RNA sequencing has significantly advanced transcriptomics by enabling the full length of transcripts to be assessed. However, current analysis methods often depend on a high-quality reference genome and gene annotation. Recently, de novo assembly methods have been developed to utilise long-read data in cases where a reference genome is unavailable, such as in non-model organisms. Despite the potential of these tools, there remains a lack of benchmarking and established protocols for optimal reference-free, long-read transcriptome assembly and differential expression analysis. Here, we comprehensively evaluate the current state-of-the-art long-read de novo transcriptome assembly tools, RATTLE, RNA-Bloom2 and isONform, and compare their performance to one of the leading short-read assemblers, Trinity. We assess various metrics, including assembly quality and computational efficiency, across a range of datasets, which include simulated data and spike-in sequin transcripts, where ground truth is known, and real data from human and pea (Pisum sativum) samples, using a reference-based approach to define truth. To represent contemporary analysis scenarios, the datasets cover depths from 6 million to 60 million reads, Oxford Nanopore Technologies (ONT) cDNA, ONT direct RNA and Pacific Biosciences (PacBio) 10x single-cell sequencing. Critically, we assessed the downstream impact of assembly choice on the detection of differential gene and transcript expression. Our results confirm that long reads generate longer assembled transcripts than short-reads for reference-free analysis, though limitations remain compared to reference-guided approaches, and suggest scope for improved accuracy and reduced redundancy. Of the de novo pipelines, RNA-Bloom2, coupled with Corset for transcript clustering, was the best performing in terms of both accuracy and computational efficiency. Our findings offer guidance when selecting the most effective strategy for long-read differential expression analysis, when a high-quality reference genome is unavailable.

bioinformatics↗

bioRxiv2024

Characterization of the Cannabis sativa glandular trichome epigenome

BackgroundThe relationship between epigenomics and plant specialised metabolism remains largely unexplored despite the fundamental importance of epigenomics in gene regulation and, potentially, yield of products of plant specialised metabolic pathways. The glandular trichomes of Cannabis sativa are an emerging model system that produce large quantities of cannabinoid and terpenoid specialised metabolites with known medicinal and commercial value. To address the lack of epigenomic data in plant specialised metabolism, glandular trichomes, and C. sativa, we mapped H3K4 trimethylation, H3K56 acetylation, H3K27 trimethylation post-translational modifications and the histone variant H2A.Z, using chromatin immunoprecipitation, in glandular trichomes, leaf, and stem tissues. Corresponding transcriptomic (RNA-seq) datasets were integrated, and tissue-specific analyses conducted to relate chromatin states to glandular trichome specific gene expression. ResultsCannabinoid and terpenoid biosynthetic genes, specialised metabolite transporters, and defence related genes, were co-located with distal H3K56ac chromatin, a histone mark that flanks active distal enhancers in planta, exclusively in glandular trichomes. Glandular trichome specific H3K4 trimethylated chromatin was associated with genes involved in specialised metabolism and sucrose and starch metabolism. Bi-valent chromatin loci specific to glandular trichomes, marked with H3K4 trimethylation and H3K27 trimethylation, was associated with genes of MAPK signalling pathways and plant specialised metabolism pathways, supporting recent hypotheses that implicate bi-valent chromatin in plant defence. The histone variant H2A.Z was largely found in intergenic regions and enriched in chromatin that contained genes involved in DNA homeostasis. ConclusionWe report the first genome-wide histone post-translational modification maps for C. sativa glandular trichomes, and more broadly for glandular trichomes in plants. Our findings have implications in plant adaptation and stress response and provide a basis for enhancer-mediated, targeted, gene transformation studies in plant glandular trichomes.

plant biology↗

bioRxiv2023

Transcription Factor Dynamics in Cross-Regulation of Plant Hormone Signaling Pathways

Cross-regulation between hormone signaling pathways is indispensable for plant growth and development. However, the molecular mechanisms by which multiple hormones interact and co-ordinate activity need to be understood. Here, we generated a cross-regulation network explaining how hormone signals are integrated from multiple pathways in etiolated Arabidopsis (Arabidopsis thaliana) seedlings. To do so we comprehensively characterized transcription factor activity during plant hormone responses and reconstructed dynamic transcriptional regulatory models for six hormones; abscisic acid, brassinosteroid, ethylene, jasmonic acid, salicylic acid and strigolactone/karrikin. These models incorporated target data for hundreds of transcription factors and thousands of protein-protein interactions. Each hormone recruited different combinations of transcription factors, a subset of which were shared between hormones. Hub target genes existed within hormone transcriptional networks, exhibiting transcription factor activity themselves. In addition, a group of MITOGEN-ACTIVATED PROTEIN KINASES (MPKs) were identified as potential key points of cross-regulation between multiple hormones. Accordingly, the loss of function of one of these (MPK6) disrupted the global proteome, phosphoproteome and transcriptome during hormone responses. Lastly, we determined that all hormones drive substantial alternative splicing that has distinct effects on the transcriptome compared with differential gene expression, acting in early hormone responses. These results provide a comprehensive understanding of the common features of plant transcriptional regulatory pathways and how cross-regulation between hormones acts upon gene expression.

plant biology↗

bioRxiv2023

Spatially Resolved Transcriptomic Analysis of the Germinating Barley Grain

Seeds, which provide a major source of calories for humans, are a unique stage of a flowering plant s lifecycle. During seed germination the embryo reactivates rapidly and goes through major developmental transitions to become a seedling. This requires extensive and complex spatiotemporal coordination of cell and tissue activity. Existing gene expression profiling methods, such as laser capture microdissection followed by RNA-seq and single-cell RNA-seq, suffer from either low throughput or the loss of spatial information about the cells analysed. Spatial transcriptomics methods couple high throughput analysis of gene expression simultaneously with the ability to record the spatial location of each individual region analysed. We developed a spatial transcriptomics workflow for germinating barley grain to better understand the spatiotemporal control of gene expression within individual seed cell types. More than 14,000 genes were differentially regulated across 0, 1, 3, 6 and 24 hours after imbibition. This approach enabled us to observe that many functional categories displayed specific spatial expression patterns that could be resolved at a sub-tissue level. Individual aquaporin gene family members, important for water and ion transport, had specific spatial expression patterns over time, as well as genes related to cell wall modification, membrane transport and transcription factors. Using spatial autocorrelation algorithms, we were able to identify auxin transport genes that had increasingly focused expression within subdomains of the embryo over germination time, suggestive of a role in establishment of the embryo axis. Together, our data provides an unprecedented spatially resolved cellular map for barley grain germination and specific genes to target for functional genomics to define cellular restricted processes in tissues during germination. The data can be viewed at https://spatial.latrobe.edu.au/.

plant biology↗

bioRxiv2023

Establishment of cell transcriptional identity during seed germination

Germination involves highly dynamic transcriptional programs as the cells of seeds reactivate and express the functions necessary to establish in the environment. Individual cell types have distinct roles within the embryo, so must therefore have cell-type specific gene expression and gene regulatory networks. We can better understand how the functions of different cell types are established and contribute to the embryo by determining how cell-type specific transcription begins and changes through germination. Here we describe a temporal analysis of the germinating Arabidopsis embryo at single-cell resolution. We define the highly dynamic cell-type specific patterns of gene expression and how these relate to changing cellular function as germination progresses. Underlying these are unique gene regulatory networks and transcription factor activity. We unexpectedly discover that most embryo cells transition through the same initial transcriptional state early in germination, after which cell-type specific gene expression is established. Furthermore, our analyses support previous findings that the earliest events leading to the induction of embryo growth take place in the vasculature. Overall, our study constitutes a general framework to characterise Arabidopsis cell states through embryo growth, allowing investigation of different genotypes and other plant species whose seed strategies may differ.

plant biology↗

bioRxiv2022

An environmentally-responsive transcriptional state modulates cell identities during root development

Roots are fundamental organs for plant development and response to their environment: they anchor the plant to its growth substrate, uptake nutrients and water vital to plant growth, and can sense and respond to a variety of biotic and abiotic stresses. The architecture of root systems and their growth are known to be strongly affected by the environmental conditions found in the soil. However, the acquisition of cell identities at the root meristem is still mainly viewed as ontogenetically driven, where a small number of stem cells generate all the cell types through stereotyped divisions followed by differentiation, along a simple developmental trajectory. The extent to which environmental cues precisely shape and affect these developmental trajectories remains an open question. We used single-cell RNA-seq, combined with spatial mapping, to deeply explore the trajectories of cell states at the tip of Arabidopsis roots, known to contain multiple developing lineages. Surprisingly, we found that most lineage trajectories exhibit a stereotyped bifid topology with two developmental trajectories rather than one. The formation of one of the trajectories is driven by a strong and specific activation of genes involved in the responses to various environmental stimuli, that affects only of a subset of the cells in multiple cell types simultaneously, revealing another layer of patterning of cell identities in the root that is independent of cell ontogeny. We demonstrate the robustness of this environmentally responsive transcriptional state by showing that it is present in a mutant where cell type identities are greatly perturbed, as well as in different Arabidopsis ecotypes. We also show that the root can adapt the proportion of cells that acquire this particular state in response to environmental signals such as nutrient availability. The discovery of this cell state reveals new layers of cell identity that may underpin the adaptive potential of plant development.

plant biology↗

bioRxiv2022

ColorBayes: Improved color correction of high-throughput plant phenotyping images to account for local illumination differences

BackgroundColor distortion is an inherent problem in image-based phenotyping systems that are illuminated by artificial light. This distortion is problematic when examining plants because it can cause data to be incorrectly interpreted. One of the leading causes of color distortion is the non-uniform spectral and spatial distribution of artificial light. However, color correction algorithms currently used in plant phenotyping assume that a single and uniform illuminant causes color distortion. These algorithms are consequently inadequate to correct the local color distortion caused by multiple illuminants common in plant phenotyping systems, such as fluorescent tubes and LED light arrays. We describe here a color constancy algorithm, ColorBayes, based on Bayesian inference that corrects local color distortions. The algorithm estimates the local illuminants using the Bayes rule, the maximum a posteriori, the observed image data, and prior illuminant information. The prior is obtained from light measurements and Macbeth ColorChecker charts located on the scene. ResultsThe ColorBayes algorithm improved the accuracy of plant color on images taken by an indoor plant phenotyping system. Compared with existing approaches, it gave the most accurate metric results when correcting images from a dataset of Arabidopsis thaliana images. The software is available at https://github.com/diloc/Color_correction.git.

plant biology↗

bioRxiv2021

Single Cell App: An App for Single Cell RNA-sequencing Data Visualization, Comparison and Discovery

The Single Cell App is a cloud-based application that allows visualisation and comparison of scRNA-seq data and is scalable according to use. Users upload their own or publicly available scRNA-seq datasets after pre-processing to be visualised using a web browser. The data can be viewed in two colour modes, Cluster - representing cell identity, and Values - level of expression, and data queried using keyword or gene identification number(s). Using the app to compare four different studies we determined that some genes frequently used as cell-type markers are in fact study specific. Phosphate transporter and hormone response genes were exemplary investigated with the app. This showed that the apparent cell specific expression of PHO1;H3 differed between GFP-tagging and scRNA-seq studies. Some phosphate transporter genes were induced by protoplasting, they retained cell specificity, indicating that cell specific stress responses (i.e. protoplasting). Examination of the cell specificity of hormone response genes revealed that 132 hormone responsive genes display restricted expression and that the jasmonate response gene TIFY8 is expressed in endodermal cells which differs from previous reports. It also appears that JAZ repressors have cell-type specific functions. These differences, identified using the Single Cell App, highlight the need for resources to enable researchers to find common and different patterns of cell specific gene expression. Thus, the Single Cell App enables researchers to form new hypothesis, perform comparative studies, allows for easy re-use of data for this emerging technology to provide novel avenues to crop improvement.

plant biology↗

bioRxiv2021

Insights into opium poppy (Papaver spp.) genetic diversity from genotyping-by-sequencing analysis

Opium poppy (Papaver somniferum) is one of the worlds oldest medicinal plants and a versatile model system to study secondary metabolism. However, our knowledge of its genetic diversity is limited, restricting utilization of the available germplasm for research and crop improvement. We used genotyping-by-sequencing to investigate the extent of genetic diversity and population structure in a collection of poppy germplasm consisting of 91 accessions originating in 30 countries of Europe, North Africa, America, and Asia. We identified five genetically distinct subpopulations using discriminate analysis of principal components and STRUCTURE analysis. Most accessions obtained from the same country were grouped together within subpopulations, likely a consequence of the restriction on movement of poppy germplasm. Alkaloid profiles of accessions were highly diverse, with morphine being dominant. Phylogenetic analysis identified genetic groups that were largely consistent with the subpopulations detected and that could be differentiated broadly based on traits such as number of branches and seed weight. These accessions and the associated genotypic data are valuable resources for further genetic diversity analysis, which could include definition of poppy core sets to facilitate genebank management and use of the diversity for genetic improvement of this valuable crop.

plant biology↗

bioRxiv2020

Developmental Normalization of Phenomics Data Generated by High Throughput Plant Phenotyping Systems

BackgroundSowing time is commonly used as the temporal reference for Arabidopsis thaliana (Arabidopsis) experiments in high throughput plant phenotyping (HTPP) systems. This relies on the assumption that germination and seedling establishment are uniform across the population. However, individual seeds have different development trajectories even under uniform environmental conditions. This leads to increased variance in quantitative phenotyping approaches. We developed the Digital Adjustment of Plant Development (DAPD) normalization method. It normalizes time-series HTPP measurements by reference to an early developmental stage and in an automated manner. The timeline of each measurement series is shifted to a reference time. The normalization is determined by cross-correlation at multiple time points of the time-series measurements, which may include rosette area, leaf size, and number. ResultsThe DAPD method improved the accuracy of phenotyping measurements by decreasing the statistical dispersion of quantitative traits across a time-series. We applied DAPD to evaluate the relative growth rate in A. thaliana plants and demonstrated that it improves uniformity in measurements, permitting a more informative comparison between individuals. Application of DAPD decreased variance of phenotyping measurements by up to 2.5 times compared to sowing-time normalization. The DAPD method also identified more outliers than any other central tendency technique applied to the non-normalized dataset.

plant biology↗

bioRxiv2019

Integrated Multi-omic Framework of the Plant Response to Jasmonic Acid

Understanding the systems-level actions of transcriptional responses to hormones provides insight into how the genome is reprogrammed in response to environmental stimuli. Here, we investigate the signaling pathway of the hormone jasmonic acid (JA), which controls a plethora of critically important processes in plants and is orchestrated by the transcription factor MYC2 and its closest relatives in Arabidopsis thaliana. We generated an integrated framework of the response to JA that spans from the activity of master and secondary-regulatory transcription factors, through gene expression outputs and alternative splicing to protein abundance changes, protein phosphorylation and chromatin remodeling. We integrated time series transcriptome analysis with (phospho)proteomic data to reconstruct gene regulatory network models. These enable us to predict previously unknown points of crosstalk from JA to other signaling pathways and to identify new components of the JA regulatory mechanism, which we validated through targeted mutant analysis. These results provide a comprehensive understanding of how a plant hormone remodels cellular functions and plant behavior, the general principles of which provide a framework for analysis of cross-regulation between other hormone and stress signaling pathways.

plant biology↗

bioRxiv2018

AgriSeqDB: an online RNA-Seq database for functional studies in agriculturally relevant plant species

BackgroundThe genome-wide expression profile of genes in different tissues/cell types and developmental stages is a vital component of many functional genomic studies. Transcriptome data obtained by RNA-sequencing (RNA-Seq) is often deposited in public databases that are made available via data portals. Data visualization is one of the first steps in assessment and hypothesis generation. However, these databases do not typically include visualization tools and establishing one is not trivial for users who are not computational experts. This, as well as the various formats in which data is commonly deposited, makes the processes of data access, sharing and utility more difficult. Our goal was to provide a simple and user-friendly repository that meets these needs for datasets from major agricultural crops.\n\nDescriptionAgriSeqDB (https://expression.latrobe.edu.au/agriseqdb), is a database for viewing, analysing and interpreting developmental and tissue/cell-specific transcriptome data from several species, including major agricultural crops such as wheat, rice, maize, barley and tomato. The disparate manner in which public transcriptome data is often warehoused and the challenge of visualizing raw data are both major hurdles to data reuse. The popular eFP browser does an excellent job of presenting transcriptome data in an easily interpretable view, but previous implementation has been mostly on a case-by-case basis. Here we present an integrated visualisation database of transcriptome datasets from six species that did not previously have public-facing visualisations. We combine the eFP browser, for gene-by-gene investigation, with the Degust browser, which enables visualisation of all transcripts across multiple samples. The two visualisation interfaces launch from the same point, enabling users to easily switch between analysis modes. The tools allow users, even those without bioinformatics expertise, to mine into datasets and understand the behaviour of transcripts of interest across samples and time. We have also incorporated an additional graphic download option to simplify incorporation into presentations or publications.\n\nConclusionPowered by eFP and Degust browsers, AgriSeqDB is a quick and easy-to-use platform for data analysis and visualization in five crops and Arabidopsis. Furthermore, it provides a tool that makes it easy for researchers to share their datasets, promoting research collaborations and dataset reuse.

genomics↗