Biology subjects

Denby, K.

Publications and source records attributed to Denby, K..

10 recordsLinked to original sources

bioRxiv2026

CONSERVATION AND DIVERGENCE WITHIN THE ARABIDOPSIS TPL/TPR COREPRESSOR FAMILY

The TOPLESS (TPL) and TOPLESS-RELATED (TPR1-TPR4) corepressors, collectively the Arabidopsis TPX family, are recruited by client proteins to regulate nearly every major plant regulatory program. Here, we dissect the conservation and divergence between paralogs using a combination of higher-order genetics, transcriptomics, and a synthetic repression assay. TPL, TPR1, and TPR4 were found to act as the primary repressors for many pathways, while TPR2 and TPR3 played a lesser or sometimes opposite regulatory role. Natural variation in the EAR-binding pocket subdivided the family into three subtypes: TPL/TPR1, TPR2/TPR3 and TPR4, and this variation at least partially explained observed differences between mutant phenotypes. In addition, cell-type-specific expression of EAR-containing effectors were used to tune root architecture, providing a possible route to engineering other TPX-regulated pathways. These results suggest a model where the TPX family balances robustness under stable conditions with the need for flexibility during cell fate transitions or stress responses.

plant biology↗

bioRxiv2025

Accurately Programming Complex Light Regimes with Multi-channel LEDs

BackgroundAdvances in LED lighting technologies have allowed researchers to explore increasingly complex light regimes. This has given us greater insight into plants responses to dynamic light, including seasonality and fluctuating conditions, rather than the discrete (i.e. on / off) lighting previously explored. However, there is a need for methods to accurately program multi-channel / waveband LED lighting systems. ResultsWe present a multi-step, multidimensional algorithm to accurately program LED lights. This algorithm accounts for non-linearity between intensity settings and irradiance output, as well as bleedthrough between channels of different wavebands. Our algorithm out-performs other methods which treat waveband channels as independent variables, more accurately predicting intensity settings to achieve a desired irradiance when using multiple LED channels. ConclusionsThis algorithm allows the community to accurately program complex light regimes to probe plant responses to dynamically changing light spectra. We have made this algorithm available to the plant science community as an R package, LightFitR (available on GitHub at: https://github.com/ginavong/LightFitR).

plant biology↗

bioRxiv2025

Pathogenicity and genome assembly of a Pythium aphanidermatum isolate causing damping-off in amaranth in controlled environment agriculture

Several species of Pythium are destructive soilborne pathogens, causing root rot and damping-off of seedlings and posing significant challenges in controlled environment agriculture (CEA). In this study, four isolates (PT2-1-1, PT2-1-2, PT5, and PT6) were obtained from infected amaranth seedlings and confirmed as P. aphanidermatum through morphology and ITS rDNA sequencing. These isolates dramatically reduced the root length of amaranth seedlings in plate-based pathogenicity assays. In soil-based post-emergence assays, damping-off symptoms were prevalent, with disease incidence reaching up to 100% in susceptible amaranth genotypes. Genome sequencing of isolate PT2-1-1 yielded a 51.55 Mb assembly consisting of 120 contigs, with 14,453 predicted protein-coding genes, including a diverse set of plant cell wall-degrading enzymes with a likely role in host invasion. Analysis of the predicted P. aphanidermatum secretome revealed potential intracellular and apoplastic effectors, including Crinkler and YxSL[RK] effectors; no RxLR effectors were detected. This work provides a second genome assembly for P. aphanidermatum as well as demonstrating variation in pathogenicity of this isolate on different amaranth accessions. Together these pave the way for investigation of pathogen-host interaction and identification of key virulence and defence strategies.

plant biology↗

bioRxiv2024

Harnessing light heterogeneity to optimise controlled environment agriculture

Yield is impacted by the environmental conditions that plants are exposed to. Controlled environmental agriculture provides growers with an opportunity to fine-tune environmental conditions for optimising yield and crop quality. However, space and time constraints will limit the number of experimental conditions that can be tested, which will in turn limit the resolution to which environmental conditions can be optimised. Here we present an innovative experimental approach that utilises the existing heterogeneity in light quantity and quality across a vertical farm to evaluate hundreds of environmental conditions concurrently. It proposes a three-phase workflow for identifying critical light variables, which can guide targeted improvements in yield and energy use. Using an observational study design, we identify features in light quality that are most predictive of biomass in different microgreens crops (kale, radish and sunflower) that may inform future iterations of lighting technology development for vertical farms. The findings suggest that light quality, rather than just light intensity, plays a crucial role in uniform crop yields and that light sensitivities are variety-specific, highlighting the importance of tailored light recipes for different crops.

plant biology↗

bioRxiv2023

Identification of Lactuca sativa transcription factors impacting resistance to Botrytis cinerea through predictive network inference

Lettuce is susceptible to a wide range of plant pathogens including the fungal pathogens Botrytis cinerea and Sclerotinia sclerotiorum, causal agents of grey mould and lettuce drop, respectively. Chemical control is routinely used but there is an urgent need to develop varieties with enhanced resistance given the economic and environmental costs of preventative pesticide sprays, the prevalence of fungicide-resistant isolates of both pathogens in the field, and the increasing withdrawal of approved fungicides through legislation. Resistance against Botrytis cinerea and Sclerotinia sclerotiorum is quantitative, governed by multiple small-medium impact loci, with plant responses involving large-scale transcriptional reprogramming. The elucidation of the gene regulatory networks (GRNs) mediating these responses will not only identify key transcriptional regulators but also interactions between regulators and show how the defence response is fine-tuned to a particular pathogen. We generated high-resolution (14 time points) time series expression data from lettuce leaves following mock-inoculation or inoculation with B. cinerea, capturing the dynamics of the transcriptional response to infection. Integrating this data with a time series dataset from S. sclerotiorum infection of lettuce identified a core set of 4362 genes similarly differentially expressed in response to both pathogens. Using the expression data for these core genes (with additional single time point data from 21 different lettuce accessions) we inferred a GRN underlying the lettuce defence response to these pathogens. Using the GRN, we have predicted and validated key regulators of lettuce immunity, identifying both positive (LsBOS1) and negative (LsNAC53) regulators of defence against B. cinerea, as well as downstream target genes. These data provide a high level of detail on defence-induced transcriptional change in a crop species and a GRN with the ability to predict transcription factors mediating disease resistance both in lettuce and other species.

plant biology↗

bioRxiv2022

Identification of genetic loci in lettuce mediating quantitative resistance to fungal pathogens

Lactuca sativa L. (lettuce) is an important leafy vegetable crop grown and consumed globally. Chemicals are routinely used to control major pathogens, including the causal agents of grey mould (Botrytis cinerea) and lettuce drop (Sclerotinia sclerotiorum). With increasing prevalence of pathogen resistance to fungicides and environmental concerns, there is an urgent need to identify sources of genetic resistance to B. cinerea and S. sclerotiorum in lettuce. We demonstrated genetic variation for quantitative resistance to B. cinerea and S. sclerotiorum in a set of 97 diverse lettuce and wild relative accessions, and between the parents of lettuce mapping populations. Transcriptome profiling across multiple lettuce accessions enabled us to identify genes with expression correlated with resistance, predicting the importance of post-transcriptional gene regulation in the lettuce defence response. We identified five genetic loci influencing quantitative resistance in a F10 mapping population derived from a Lactuca serriola (wild relative) x lettuce cross, which each explained 5-10% of the variation. Differential gene expression analysis between the parent lines, and integration of data on correlation of gene expression and resistance in the diversity set, highlighted potential causal genes underlying the quantitative trait loci. Key MessageWe demonstrate genetic variation for quantitative resistance against important fungal pathogens in lettuce and its wild relatives, map loci conferring resistance and predict key molecular mechanisms using transcriptome profiling.

plant biology↗

bioRxiv2021

A high resolution single molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

BackgroundAccurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single molecule long read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation or incomplete cDNA synthesis. ResultsWe present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 160k transcripts - twice that of the best current Arabidopsis transcriptome and including over 1,500 novel genes. 79% of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We developed novel methods to determine splice junctions and transcription start and end sites accurately. Mis- match profiles around splice junctions provided a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identified high confidence transcription start/end sites and removed fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provided higher resolution of transcript expression profiling and identified cold- and light-induced differential transcription start and polyadenylation site usage. ConclusionsAtRTD3 is the most comprehensive Arabidopsis transcriptome currently available. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single molecule sequencing analysis from any species.

plant biology↗

bioRxiv2020

Time series transcriptomics reveals a BBX32-directed control of dynamic acclimation to high light in mature Arabidopsis leaves

The photosynthetic capacity of mature leaves increases after several days exposure to constant or intermittent episodes of high light (HL) and is manifested primarily as changes in chloroplast physiology. This is termed dynamic acclimation but how it is initiated and controlled is unknown. From fully expanded Arabidopsis leaves, we determined HL-dependent changes in transcript abundance of 3844 genes in a 0-6h time-series transcriptomics experiment. It was hypothesised that among such genes were those that contribute to the initiation of dynamic acclimation. By focussing on HL differentially expressed transcription (co-)factor (TF) genes and applying dynamic statistical modelling to the temporal transcriptomics data, a gene regulatory network (GRN) of 47 predominantly photoreceptor-regulated (co)-TF genes was inferred. The most connected gene in this network was B-BOX DOMAIN CONTAINING PROTEIN32 (BBX32). Plants over-expressing BBX32 were strongly impaired in dynamic acclimation and displayed perturbed expression of genes involved in its initiation. These observations led to demonstrating that as well as regulation of dynamic acclimation by BBX32, CRYPTOCHROME1, LONG HYPOCOTYL5, CONSTITUTIVELY PHOTOMORPHOGENIC1 and SUPPRESSOR OF PHYA-105 are also important regulators of this process. Additionally, the BBX32-centric GRN provides a view of the transcriptional control of dynamic acclimation distinct from other photoreceptor-regulated processes, such as seedling photomorphogenesis.

plant biology↗

bioRxiv2020

Downy Mildew effector HaRxL21 interacts with the transcriptional repressor TOPLESS to promote pathogen susceptibility

Hyaloperonospora arabidopsidis (Hpa) is an oomycete pathogen causing Arabidopsis downy mildew. Effector proteins secreted from the pathogen into the plant play key roles in promoting infection by suppressing plant immunity and manipulating the host to the pathogens advantage. One class of oomycete effectors share a conserved RxLR motif critical for their translocation into the host cell. Here we characterize the interaction between an RxLR effector, HaRxL21 (RxL21), and the Arabidopsis transcriptional co-repressor Topless (TPL). We establish that RxL21 and TPL interact via an EAR motif at the C-terminus of the effector, mimicking the host plant mechanism for recruiting TPL to sites of transcriptional repression. We show that this motif, and hence interaction with TPL, is necessary for the virulence function of the effector. Furthermore, we provide evidence that RxL21 uses the interaction with TPL, and its close relative TPL-related 1, to repress plant immunity and enhance host susceptibility to both biotrophic and necrotrophic pathogens.

plant biology↗

bioRxiv2019

Transcriptional Dynamics of the Salicylic Acid Response and its Interplay with the Jasmonic Acid Pathway

The phytohormone salicylic acid (SA) is a central regulator of plant immunity. Antagonistic and synergistic actions between SA and other defense-associated hormones like jasmonic acid (JA) play key roles in determining the outcome of the plant immune response. To obtain a deeper understanding of SA-mediated transcriptional reprogramming and SA/JA crosstalk, we generated a high-resolution time series of gene expression from Arabidopsis leaves treated with SA alone and a combination of SA and methyl JA (MeJA), sampled at 14 time points over a 16-h period. We found that approximately one-third of the Arabidopsis genome was differentially expressed in response to SA, and temporal changes in gene expression could be partitioned into 45 distinct clusters of process-specific coregulated genes, linked to specific cis-regulatory elements and binding of transcription factors (TFs). Integration of our expression data with information on TF-DNA binding allowed us to generate a dynamic gene regulatory network model of the SA response, recovering known regulators and identifying novel ones. We found that 12% of SA-responsive genes and 69% of the MeJA-responsive genes exhibited antagonistic or synergistic expression levels in the combination treatment. Multi-condition co-clustering of the single- and combined-hormone expression profiles predicted underlying regulatory mechanisms in signal integration. Finally, we identified the TFs ANAC061 and ANAC090 as negative regulators of SA pathway genes and defense against biotrophic pathogens. Collectively, our data provide an unprecedented level of detail about transcriptional changes during the SA response and SA/JA crosstalk, serving as a valuable resource for systems-level network studies and functional plant defense studies.

plant biology↗