Biology subjects

Morris, R. J.

Publications and source records attributed to Morris, R. J..

At least 19 recordsLinked to original sources

bioRxiv2026

The degree of subgenome expression bias in B. napus changes between cultivars, tissues and across time

Most extant plants show evidence of past polyploidization events in their genomes. Allopolyploids arise from hybridisation, resulting in the polyploid genome comprising subgenomes from different ancestors. Subsequent adaptation to their environment or selection pressure for specific traits has led to several allopolyploids exhibiting an unequal contribution from their subgenomes to their phenotype. Given the diversity of cultivars grown for different environments, it is possible that the associated regulatory changes may have given rise to different subgenome expression biases. Likewise, different tissues and developmental stages have distinct expression profiles that may correspond more strongly to one subgenome over the other(s). Here, we investigate different metrics for quantifying the contribution of each subgenome in space (tissue) and time (development) in cultivars of Brassica napus. Brassica napus has two subgenomes, A and C, from its ancestors Brassica rapa (A) and Brassica oleracea (C). We find that the C genome has higher overall expression than the A genome, whereas the average expression per gene is higher for the A genome. Direct comparison of homoeologous pairs reveals higher expression of genes on the C genome. We find that the degree of expression bias can change between cultivars, tissues and across time with bias quantification being strongly dependent on the metric. These findings help explain contradictory reports on expression bias and genome dominance. Significance statementWe demonstrate how different metrics of expression bias between subgenomes in polyploids can lead to conflicting inferences. We show that expression can be viewed as either A or C-biased, yet the differences are small, calling into question the relevance of subgenome dominance and expression bias in B. napus.

plant biology↗

bioRxiv2026

A Bayesian approach for identifying similar transcript dynamics using curve registration

Changes in gene expression over time can provide valuable insights into developmental processes and responses to the environment. Differences in expression may be indicative of potential differences in regulation. Comparing transcript dynamics may help identify correspondences between developmental stages within and between species, differences in the timing of key events during development, and transcriptional response to treatments or perturbations. A straightforward comparison between the dynamics is, however, hindered by measurements that were taken at different time points and over different timescales. To address this, we developed a statistical approach that seeks the optimal alignment between two time series as a function of a temporal shift and stretch. We validated our approach using simulated data and applied it to several transcriptome datasets, including comparisons between different plant species. Our development facilitates knowledge transfer from model systems to less studied species, the identification of modules of co-regulated genes, and the discovery of condition-specific, temporally differentially-expressed genes. The method is provided freely available as an R package.

bioinformatics↗

bioRxiv2025

Network analysis of flowering time genes suggests regulatory changes among SOC1 orthologues in response to cold in Brassica napus

Flowering plants respond to multiple environmental and endogenous cues to determine the timing of their transition from the vegetative to floral state. Most of our knowledge of the gene regulatory network (GRN) controlling flowering time has been derived from the model plant Arabidopsis thaliana. This knowledge needs to be translated to crop plants to support the development of varieties that can be grown in different and rapidly changing climatic conditions. However, due to increased genome complexity and limited prior knowledge, translation into crops is not always straightforward. Here, we present a study of the GRN controlling flowering time in Brassica napus (oilseed rape), an allotetraploid crop that is a close relative of Arabidopsis. Using a comparative transcriptomics approach, we show that the majority of the orthologous gene pairs have similar expression dynamics over development between Arabidopsis and Brassica napus. Some genes, however, have experienced regulatory changes, with flowering time genes in Brassica napus having higher than average differences in their expression profiles from their Arabidopsis orthologues. Despite these differences, the inferred GRN for flowering in Brassica napus exhibits a similar network topology to the network known in Arabidopsis. This is likely due to preferential retention of these genes in higher paralogue numbers, which allows subtle changes in the regulation of individual paralogues, while still conserving the overall regulatory structure through evolution. We discover and present a detailed analysis of one such example where orthologues of SUPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) have similar expression patterns under normal conditions, but different dynamics under cold temperature conditions, suggesting possible subfunctionalisation among paralogues in response to temperature change.

plant biology↗

bioRxiv2025

Assessing the robustness and resilience of subsistence ecosystem services using a socioecological network

Understanding the vulnerability of ecosystem services to environmental change and species loss is critical to supporting communities dependent on services for well-being and livelihoods. However, assessments of ecosystem service resilience often overlook the complexity of socioecological systems, including the cascading effects of species loss and adaptive responses of biodiversity and humans. We constructed a socioecological network representing ecosystem service provisioning in a tropical farming community, linking frugivore - plant interactions with provision of local services such as food and firewood, and simulated species loss under environmental change scenarios. We quantified the robustness of ecosystem services and identified key species and interaction pathways for such, and incorporated interaction rewiring into our simulations to assess the resilience of network and ecosystem services as species and humans adapt to environmental change. Ecosystem service provisioning in our network was generally robust to simulated species loss. On average, our network could withstand the loss of over 80% of species before collapsing, with the loss of all services occurring in only the most extreme environmental change scenarios. When service loss did occur, such as the loss of firewood, it was driven by secondary extinctions after loss of primary species propagated through the network. Interaction rewiring enhances ecosystem service resilience, allowing the loss of 18% more species before network collapse. Rewiring also altered the relative importance of individual species and their interaction pathways in maintaining resilient services. Species such as sago and coconut do not directly provide firewood and initially did not play an important role in maintaining robust firewood services with limited network connectivity. However, with rewiring these species helped maintain resilient firewood services in 20% more simulations, reflecting the importance of indirect interaction pathways and adaptivity. These findings demonstrate that 1) species can maintain resilient ecosystem services even when they do not directly provide the service and 2) the adaptive capacity of humans and biodiversity can substantially enhance ecosystem service resilience. Overall, our study provides a framework for more accurately assessing the consequences of species loss on ecosystem services and human livelihoods by explicitly accounting for socioecological complexity and adaptability.

ecology↗

bioRxiv2025

A deep learning model recapitulates position specific effects of plant regulatory sequences and suggests genes under complex regulation

Deep neural networks can be trained to predict gene expression directly from genomic sequence, thereby implicitly learning regulatory sequence patterns from scratch, minimizing the bias imposed by prior assumptions. A challenging, yet promising prospect is the extraction of novel insights into gene-regulatory mechanisms, by probing and interpreting such gene expression models. Using a branched convolutional neural network architecture trained on promoter and terminator sequences we predict gene expression for allopolyploid Brassica napus and the closely related model organism Arabidopsis thaliana. We validate the model by comparing predicted and measured expression across ecotypes. We also show that deep learning models can successfully capture the positional binding preferences of some transcription factor families, without having been trained on transcription factor binding data. Furthermore, we show that our model did not only detect local sequence patterns, but was also able to determine their function based on their positional context. We also found that increased prediction error correlated with additional more distal or epigenetic regulatory input. Our results demonstrate that deep learning can be used to understand the regulatory architecture of gene expression in plants. A better understanding of gene regulation in the context of polyploid genomes is of particular economic importance, due to their prevalence among major crops. In the future, we hope that such models may facilitate the targeted engineering of gene regulation in crops.

bioinformatics↗

bioRxiv2025

What is a differentially expressed gene?

The concept of Differentially Expressed Genes (DEGs) is central to RNA-Seq studies, yet their identification suffers from reproducibility issues. This is largely a consequence of the inherent biological and technical variation that cannot be captured with small numbers of replicates. When thresholds for p-values and log2 fold changes are introduced, this variability can propagate an incomplete description of the data, leading to differing interpretations. Here, we compare traditional binary DEG classification with a rank-based method, grounded in Bayesian statistics, using a published yeast dataset comprising over 40 replicates. This analysis reveals how the choice of thresholds and number of replicates results in discrepancies between studies and potentially interesting genes being overlooked. Furthermore, by comparing wild-type with wild-type samples, we show how variability in gene expression can be mistaken for differential expression. Evaluating current practices for navigating the accuracy-error trade-off in the search for differentially expressed genes leads us to advocate rank-based methods and Bayesian statistics to mitigate the limitations of binary classifications and communicate uncertainty.

bioinformatics↗

bioRxiv2025

A Bayesian framework for ranking genes based on their statistical evidence for differential expression

Advances in sequencing technologies have revolutionised our ability to capture the complete RNA profile in tissue samples, allowing for comparative analyses of RNA levels between developmental processes, environmental responses, or treatments. However, quantifying changes in gene expression remains challenging, given inherent biological variability and technological limitations. To address this, we introduce a Bayesian framework for differential gene expression (DGE) analysis. Our framework unifies and streamlines a complex analysis, typically involving parameter estimations and multiple statistical tests, into a concise mathematical equation. This allows statistical evidence for differential expression to be computed rapidly and transparently. We show how this approach can be used to evaluate variabilty of individual genes between replicates. A comparison of our framework with existing tools revealed differences that can be explained by commonly employed thresh-olds in other packages. This motivated us to explore ranking genes based on their statistical evidence as opposed to a binary classification as DEGs. Our analysis leads us to advocate the use of Bayes factors within a rank-based approach. This framework offers enhanced computational efficiency and delivers a transparent way to analyse, interpret and communicate DGE results.

bioinformatics↗

bioRxiv2024

Rapid in situ forming PEG hydrogels for mucosal drug delivery

In situ gelling polymeric biomaterials have proven useful as drug delivery vehicles to enable sustained release at sites of disease or injury. However, if delivered to mucosal tissues, such as the eyes, nose, gastrointestinal, and cervicovaginal tract, these gels must also possess the ability to adhere to an epithelium coated in mucus. Towards this end, we report a new rapid in situ gelling polyethylene glycol-based hydrogel. Unlike other chemistries that enable rapid gel formation which form via irreversible covalent bonds, we use a bio-reducible linker allowing the gels to be naturally degraded over several days once administered. We identified a set of 6 lead formulations, which rapidly form into disulfide-linked PEG hydrogels in 30 seconds or less. These rapidly forming PEG hydrogels were also able to conform and adhere to mucosal tissues via PEG-mucin entanglements and hydrogen bonding. Controlled release of protein-based cargoes from the PEG gels was achieved over several hours whereas 40 nm nanoparticle-based cargos were retained over 24 hours. We also found these rapid in situ forming PEG gels were well-tolerated by mammalian cells. These studies support further testing and development of rapid in situ forming PEG gels for drug delivery to improve therapeutic retention and efficacy at mucosal sites.

bioengineering↗

bioRxiv2024

Re-analysis of mobile mRNA datasets highlights challenges in the detection of mobile transcripts from short-read RNA-Seq data

Short-read RNA-Seq analyses of grafted plants have led to the proposal that large numbers of mRNAs move over long distances between plant tissues, acting as potential signals. The detection of transported transcripts by RNA-Seq is both experimentally and computationally challenging, requiring successful grafting, delicate harvesting, rigorous contamination controls and data processing approaches that can identify rare events in inherently noisy data. Here, we perform a meta-analysis of existing datasets and examine the associated bioinformatic pipelines. Our analysis reveals that technological noise, biological variation and incomplete genome assemblies give rise to features in the data that can distort the interpretation. Taking these considerations into account, we find that a substantial number of transcripts that are currently annotated as mobile are left without support from the available RNA-Seq data. Whilst several annotated mobile mRNAs have been validated, we cannot exclude that others may be false positives. The identified issues may also impact other RNA-Seq studies, in particular those using single nucleotide polymorphisms (SNPs) to detect variants.

plant biology↗

bioRxiv2024

Targeted engineering of the phase separating PARCL protein

PARCL is a plant-specific RNA-binding protein (RBP) that exhibits chaperone activity, is abundant in the phloem, intrinsically disordered, and contains a prion-like domain (PLD). PARCL proteins have been observed to form large biomolecular condensates in vivo and in vitro. Biomolecular condensates are membraneless compartments, wherein biomolecules become partitioned from their surrounding liquid environment into liquid droplets with their own composition, dynamics, and function. Which molecular properties drive phase separation is of great interest for targeted engineering efforts. Here, we present results on residue interactions derived from simulations of PARCL using course-grained molecular dynamics with the HPS-Urry model. We adjust the parameters of the simulations to allow the inclusion of folded eYFP tags, since fluorescent tags are often used in phase separation experiments for visualising droplets, yet have not been included in simulations to date. While still simulating phase separation, these trajectories suggest minor changes to droplet and network structure when proteins contain eYFP. By analysing the residues of the PARCL molecules that come within contact distance in the simulations, we identify which individual residues drive phase separation. To experimentally validate these findings, we introduced mutations of the most contacted residues and could indeed confirm that these mutations prevent the formation of condensate droplets. To investigate the RNA-binding of PARCL, we added microRNA to the simulation and find a short region of PARCL consistently making contact with the miRNA, which is also in agreement with predictions and experiments. We discuss the implications of our findings in terms of model-guided engineering of biomolecular condensates.

biophysics↗

bioRxiv2023

Integrated Phenomics and Genomics reveals genetic loci associated with inflorescence growth in Brassica napus

A fundamental challenge to the production of climate-resilient crops is how to measure dynamic yield-relevant responses to the environment, such as growth rate, at a scale which informs mechanistic understanding and accelerates breeding. The timing, duration and architectural characteristics of inflorescence growth are crucial for optimising crop productivity and have been targets of selection during domestication. We report a robust and versatile procedure for computationally assessing environmentally-responsive flowering dynamics. In the oilseed crop, Brassica napus, there is wide variation in flowering response to winter cold (vernalization). We subjected a diverse set of B. napus accessions to different vernalization temperatures and monitored shoot responses using automated image acquisition. We developed methods to computationally infer multiple aspects of flowering from this dynamic data, enabling characterisation of speed, duration and peaks of inflorescence development across different crop types. We input these multiple traits to genome- and transcriptome-wide association studies, and identified potentially causative variation in a priori phenology genes (including EARLY FLOWERING3) for known traits and in uncharacterised genes for computed traits. These results could be used in marker assisted breeding to design new ideotypes for improved yield and better adaptation to changing climatic conditions.

plant biology↗

bioRxiv2023

Delayed development of basal spikelets in wheat explains their increased floret abortion and rudimentary nature

Wheat (Triticum aestivum L.) breeding efforts have increased grain yield predominantly by raising grain numbers per spikelet, rather than grain weight or spikelet number. However, across a single spike large differences exist in the number of grains per spikelet. The central spikelets produce the highest number of grains in any given genotype while apical and basal spikelets are less productive. Basal spikelets are delayed in development just after initiation and are smaller and less advanced than central spikelets already by the glume primordium stage. However, basal spikelets continue to develop and produce florets until much later in the wheat growth cycle. The precise timings or the cause of their growth cessation, and subsequent abortion, is largely unknown. In this study we investigated the underlying causes of rudimentary basal spikelet abortion. We investigated basal spikelet development in four UK winter wheat varieties as well as a set of near-isogenic lines for VRT-A2 (VEGETATIVE TO REPRODUCTIVE TRANSITION 2) using shading applications in the field. We propose that basal spikelet abortion is likely the consequence of complete floret abortion as both occur at the same time and have the same response to shading treatments. Furthermore, we found that the developmental age of florets pre-abortion is an important factor for their likelihood to survive and develop viable seed. Previously, it had been proposed that reduced assimilate availability in the base of the spike leads to increased abortion. Re-analysis of published data alongside data presented here, however, does not support this model. We found that rather than assimilate availability, it is the reduced developmental age of basal florets before abortion that correlates with increased abortion. Using the floret Waddington developmental stage pre-abortion, we were able to predict final grain set per spikelet across the spike, alongside the characteristic gradient in number of grains from basal to central spikelets. We found that advancing past Waddington stage 5.5 seems to be important for floret survival and that most florets in basal spikelets had not reached this stage at the onset of floret abortion. The abortion of all florets could therefore be the reason for their rudimentary appearance in the mature spike, suggesting that basal spikelet abortion is simply the consequence of all florets inside the spikelet being aborted and thus all other spikelet structures (e.g., lemma, rachilla, glume) also ceasing to develop. Future efforts to improve spikelet homogeneity across the spike could thus focus on improving basal spikelet establishment and increasing floret development rates pre-abortion.

plant biology↗

bioRxiv2022

Non-cell-autonomous HSC70.1 chaperone displays homeostatic feed-back regulation by binding its own mRNA

Heat shock proteins of the HSC70/HSP70 family are evolutionarily conserved chaperones that are involved in protein folding, protein transport and RNA binding. Arabidopsis HSC70 chaperones are thought to act as housekeeping chaperones and as such are involved in many growth-related pathways. Whether Arabidopsis HSC70 binds RNA and its function has remained an open question. Here, we show that the HSC70.1 chaperone binds its own mRNA via its C-terminal Short Variable Region (SVR) and inhibits its own translation. We propose that this negative protein-transcript feedback loop may establish an on-demand chaperone pool that allows for a rapid response to stress. Furthermore, we show that the SVR encoding RNA region is necessary for HSC70.1 transcript mobility to distant tissues and that HSC70.1 transcript and not protein mobility is required to rescue root growth and flowering time of hsc70 mutants. In summary, it seems that the Arabidopsis HSC70.1 chaperone can form a complex with its own transcript to regulate its translation and that both protein and transcript can act in a non-cell-autonomous manner maintaining chaperone homestasis between tissues.

plant biology↗

bioRxiv2021

High expression of VRT2 during wheat spikelet initiation increases the number of rudimentary basal spikelets

Spikelets are the fundamental building blocks of Poaceae inflorescences and their development and branching patterns determine the various inflorescence architectures and grain yield of grasses. In wheat, the central spikelets produce the most and largest grains, while spikelet size gradually decreases acro- and basipetally, giving rise to the characteristic lanceolate shape of wheat spikes. The acropetal gradient correlates with the developmental age of spikelets, however the basal spikelets are developed first and the cause of their small size and rudimentary development is unclear. Here, we adapted G&T-seq, a low-input transcriptomics approach, to characterise gene expression profiles within spatial sections of individual spikes before and after the establishment of the lanceolate shape. We observed larger differences in gene expression profiles between the apical, central and basal sections of a single spike than between any section belonging to consecutive developmental timepoints. We found that SVP MADS-box transcription factors, including VRT-A2, are expressed highest in the basal section of the wheat spike and display the opposite expression gradient to flowering E-class SEP1 genes. Based on multi-year field trials and transgenic lines, we show that higher expression of VRT-A2 in the basal sections of the spike is associated with increased numbers of rudimentary basal spikelets. Our results, supported by computational modelling, suggest that the delayed transition of basal spikelets from vegetative to floral developmental programmes results in the lanceolate shape of wheat spikes. This study highlights the value of spatially resolved transcriptomics to gain new insights into developmental genetics pathways of grass inflorescences. One sentence summaryLarge transcriptional gradients exist within a wheat spike and are associated with rudimentary basal spikelet development, resulting in the characteristic lanceolate shape of wheat spikes.

plant biology↗

bioRxiv2021

Bayesian optimisation for yield in high-dimensional trait-space identifies crop ideotypes in Oil Seed Rape

The improvement of crop yield has long been a major breeding target and is increasingly becoming a goal in many areas of plant research. Yield has been shown to be a complex trait, depending on multiple genes, plant architecture and plant-environment interactions. This complexity is frequently reduced by focussing on contributing factors to yield (yield traits). However, a quantitative understanding of the interplay between yield traits, and the effect of these relationships on yield is largely unexplored. Consequently, the extent to which crop varieties achieve their optimal morphology in a given environment and how this impacts on seed yield is unknown. Here we use causal inference to model the hierarchically structured effects of 27 macro and micro yield traits on each other over the course of plant development, and on seed yield in Spring and Winter oilseed rape plants. We perform Bayesian optimisation on the modelled yield potential, identifying the morphology of ideotype plants which are expected to be higher yielding than the existing varieties in the studied panels. We find that existing Spring varieties occupy the optimal regions of trait-space, but that potentially high yielding strategies are unexplored in extant Winter varieties. In addition to concrete recommendations for varietal improvement in oilseed rape, this work provides a novel, general methodological framework for the study of crop breeding as an optimisation problem.

plant biology↗

bioRxiv2021

Lipid-induced polymorphic amyloid fibrils formation by α-synuclein.

Many proteins that self-assemble into amyloid and amyloid-like fibres can adopt polymorphic forms. These forms have been observed both in vitro and in vivo and can arise through variations in the steric-zipper interactions between {beta}-sheets, variations in the arrangements between protofilaments, and differences in the number of protofilaments that make up a given fibre class. Different polymorphs which arise from the same precursor molecule not only exhibit different levels of toxicity, but importantly can contribute to different disease conditions. In this work, we show that in the presence of 1,2-dimyristoyl-sn-glycero-3-phospho-L-serine, a highly abundant lipid in the plasma membrane of neurons, the aggregation of -synuclein is markedly accelerated and yields a diversity of polymorphic forms under identical experimental conditions. This morphological diversity includes thin and curly amyloid fibrils, helical and twisted ribbons, nanotubes and flat sheets. TEM analysis of fibrils sampled from the early stage of the growth phase shows the presence of helical and twisted ribbons, indicating that these morphological variants form at the early stages of aggregation. Total internal reflection fluorescence microscopy (TIRFM) indicated the presence of lipids collocated with the mature fibrils. This finding has important implication as the presence of -synuclein with co-localized high lipid content has been reported in Lewy bodies, the pathological hallmark of Parkinsons disease and other synucleinopathies. Thus, the present study demonstrates that an interface, such as that provided by a lipid membrane, can not only modulate the kinetics of -synuclein amyloid aggregation but also plays an important role in the formation of morphological variants by incorporating lipid molecules in the process of amyloid fibril formation.

biophysics↗

bioRxiv2021

Colletotrichum higginsianum effectors exhibit cell to cell hypermobility in plant tissues and modulate intercellular connectivity amongst a variety of cellular processes

Multicellular organisms exchange information and resources between cells to co-ordinate growth and responses. In plants, plasmodesmata establish cytoplasmic continuity between cells to allow for communication and resource exchange across the cell wall. Some plant pathogens use plasmodesmata as a pathway for both molecular and physical invasion. However, the benefits of molecular invasion (cell-to-cell movement of pathogen effectors) are poorly understood. To begin to investigate this and identify which effectors are cell-to-cell mobile, we performed a live imaging-based screen and identified 15 cell-to-cell mobile effectors of the fungal pathogen Colletotrichum higginsianum. Of these, 6 are "hypermobile", showing cell-to-cell mobility greater than expected for a protein of its size. We further identified 3 effectors that can indirectly modify plasmodesmal aperture. Transcriptional profiling of plants expressing hypermobile effectors implicate them in a variety of processes including senescence, glucosinolate production, cell wall integrity, growth and iron metabolism. However, not all effectors had an independent effect on virulence. This suggests a wide range of benefits to infection gained by the mobility of C. higginsianum effectors that likely interact in a complex way during infection.

plant biology↗

bioRxiv2020

Density and temperature controlled fluid extraction in a bacterial biofilm is determined by poly-γ-glutamic acid production

A hallmark of microbial biofilms is the self-production of extracellular matrix that encases the cells resident within the community. The matrix provides protection from the environment, while spatial heterogeneity of expression influences the structural morphology and colony spreading dynamics. Bacillus subtilis is a model bacterial system used to uncover the regulatory pathways and key building blocks required for biofilm growth and development. Previous reports have suggested that poly-{gamma}-glutamic acid (PGA) production is suppressed during biofilm formation and does not play a major role in biofilm morphology of the undomesticated isolate NCIB 3610. In this work we report on the observation of multiple travelling fronts that develop during the early stage of B. subtilis colony biofilm formation. We find the emergence of a highly motile population of bacteria that is facilitated by the extraction of fluid from the underlying agar substrate. Motility develops behind a moving front of fluid that propagates from the boundary of the biofilm towards the interior. The extent of proliferation is strongly modulated by the presence of extracellular polysaccharides (EPS). We trace the origin of this moving front of fluid to the production of PGA. We find that PGA production is correlated with higher temperatures, resulting in a mature biofilm morphology that is distinct from the biofilm architecture typically associated with B. subtilis. Our results suggest that B. subtilis NCIB 3610 produces distinct biofilm matrices in response to environmental conditions.

microbiology↗