Biology subjects

Ball, J.

Publications and source records attributed to Ball, J..

8 recordsLinked to original sources

bioRxiv2025

Evaluating anaesthetics for improving scientific research and welfare using larval zebrafish

Establishing anaesthesia for ensuring both animal welfare and compatibility with protocols required for different areas of scientific research is vital. Zebrafish (Danio rerio) are one of the most used animal models in research; however, little is known about the appropriateness of anaesthetic used for this species, especially for embryo-larval life stages. Using a combination of whole-brain functional imaging, quantification of cardiovascular performance, and behaviour, we explore the efficacy and tolerability of six widely used fish anaesthetics (2-phenoxyethanol, benzocaine, etomidate, MS222, isoeugenol and quinaldine sulfate) in larval zebrafish. We show that MS222 and quinaldine sulfate are the most suitable for achieving deep anaesthesia, while etomidate is better suited for studies focused on the cardiovascular system. Only quinaldine sulfate was found to be aversive. Our findings aid researchers for selecting the most suitable anaesthetic compounds and concentrations for their specific research goals, and the refinement of studies using anaesthesia in larval zebrafish.

physiology↗

bioRxiv2025

Untangling dopamine and glutamate in the ventral tegmental area

Ventral tegmental area (VTA) dopamine neurons are of great interest for their central roles in motivation, learning, and psychiatric disorders. While hypotheses of VTA dopamine neuron function posit a homogenous role in behavior (e.g., prediction error), they do not account for molecular heterogeneity. We find that glutamate-dopamine, nonglutamate-dopamine, and glutamate-only neurons are dissociable in their signaling of reward and aversion-related stimuli, prediction error, and electrical properties. In addition, glutamate-dopamine and nonglutamate-dopamine neurons differ in dopamine release dynamics. Aversion-related recordings of all dopamine neurons (not considering glutamate co-transmission) showed a mixed response that obscured dopamine subpopulation function. Within glutamate-dopamine neurons, glutamate and dopamine release had dissociable contributions toward reward and aversion-based learning and performance. Based on our results, we propose a new hypothesis on VTA dopamine neuron function: that dopamine neuron signaling patterns and their roles in motivated behavior depend on whether or not they co-transmit dopamine with glutamate.

neuroscience↗

bioRxiv2024

Ethanol down-regulates gastrula gene expression and cell movement, causing symptoms of foetal alcohol spectrum disorders

Foetal alcohol spectrum disorders (FASDs) occur in embryos when they are exposed to maternally supplied alcohol. To study the mechanisms of FASDs, the zebrafish embryo can serve as an excellent model as ethanol exposed zebrafish embryos exhibit common symptoms of human FASDs including microcephaly, incomplete neural plate closure, eye defects, craniofacial disorders and many other defects. Here we investigated the embryo development at gastrula stage when three germ layers develop with specific gene expressions and undergo dynamic cell movement including extension, convergence and epiboly, establishing the platform to form the head and body axis in the later development. Gastrula cell movement analyses using fluorescent transgenic zebrafish embryos revealed that ethanol induced dose dependent delay of extension, convergence and epiboly cell movement and associated gene expressions in all three germ layers. Our results suggest multiple targets of ethanol including gene expression and cell movement, consequently delay the key gene expression and cell localisation, causing irreversible developmental defects in the head and body axis formation.

pharmacology and toxicology↗

bioRxiv2023

Revisiting the origins of the Sobemovirus genus: a case for ancient origins of plant viruses

The discrepancy between short- and long-term rate estimates, known as the time-dependent rate phenomenon (TDRP), poses a challenge to extrapolating evolutionary rates over time and reconstructing evolutionary history of viruses. The TDRP reveals a decline in evolutionary rate estimates with the measurement timescale, explained empirically by a power-law rate decay, notably observed in animal and human viruses. A mechanistic evolutionary model, the Prisoner of War (PoW) model, has been proposed to address TDRP in viruses. Although TDRP has been studied in animal viruses, its impact on plant virus evolutionary history remains largely unexplored. Here, we investigated the consequences of TDRP in plant viruses by applying the PoW model to reconstruct the evolutionary history of sobemoviruses, plant pathogens with significant importance due to their impact on agriculture and plant health. Our analysis showed that the Sobemovirus genus dates back over four million years, indicating an ancient origin. We found evidence that supports deep host jumps to Poaceae, Fabaceae, and Solanaceae occurring between tens to hundreds of thousand years ago, followed by specialization. Remarkably, the TDRP-corrected evolutionary history of sobemoviruses was extended far beyond previous estimates that had suggested their emergence during the Neolithic period. By incorporating sequences collected through metagenomic analyses, the resulting phylogenetic tree showcases increased genetic diversity, reflecting a deep history of sobemovirus species with major radiation events taking place during the Neolithic period, suggesting rapid diversification in that period. Our findings make a case for the possibility of deep evolutionary origins of plant viruses.

evolutionary biology↗

bioRxiv2020

Variation in the expression of a transmembrane protein influences cell growth in Arabidopsis thaliana petals by altering auxin availability.

BackgroundThe same species of plant can exhibit highly diverse sizes and shapes of organs that are genetically determined. Defining genetic variation underlying this morphological diversity is an important objective in evolutionary studies and it also helps identify the functions of genes influencing plant growth and development. Extensive screens of mutagenised Arabidopsis populations have identified multiple genes and mechanisms affecting organ size and shape, but relatively few studies have exploited the rich diversity of natural populations to identify genes involved in growth control. ResultsWe screened a relatively well characterised collection of Arabidopsis thaliana ecotypes for variation in petal size. Association analyses identified sequence and gene expression variation on chromosome 4 that made a substantial contribution to differences in petal area. Variation in expression of At4g16850 (named as KSK), encoding a hypothetical protein, had a substantial role on variation in organ size by influencing cell size. Over-expression of KSK led to larger petals with larger cells and promoted the formation of stamenoid features. The expression of auxin-responsive genes known to limit cell growth was reduced in response to KSK over-expression. ANT expression was also reduced in KSK over-expression lines, consistent with altered floral identities. Auxin availability was reduced in KSK over-expressing cells, consistent with changes in auxin-responsive gene expression. KSK may therefore influence auxin availability during petal development. ConclusionsUnderstanding how genetic variation influences plant growth is important for both evolutionary and mechanistic studies. We used natural populations of Arabidopsis thaliana to identify sequence variation in a promoter region of Arabidopsis ecotypes that mediated differences in the expression of a previously uncharacterised membrane protein. This variation contributed to altered auxin availability and cell size during petal growth.

plant biology↗

bioRxiv2019

AirSurf-Lettuce: an aerial image analysis platform for ultra-scale field phenotyping and precision agriculture using computer vision and deep learning

Aerial imagery is regularly used by farmers and growers to monitor crops during the growing season. To extract meaningful phenotypic information from large-scale aerial images collected regularly from the field, high-throughput analytic solutions are required, which not only produce high-quality measures of key crop traits, but also support agricultural practitioners to make reliable management decisions of their crops. Here, we report AirSurf-Lettuce, an automated and open-source aerial image analysis platform that combines modern computer vision, up-to-date machine learning, and modular software engineering to measure yield-related phenotypes of millions of lettuces across the field. Utilising ultra-large normalized difference vegetation index (NDVI) images acquired by fixed-wing light aircrafts together with a deep-learning classifier trained with over 100,000 labelled lettuce signals, the platform is capable of scoring and categorising iceberg lettuces with high accuracy (>98%). Furthermore, novel analysis functions have been developed to map lettuce size distribution in the field, based on which global positioning system (GPS) tagged harvest regions can be derived to enable growers and farmers precise harvest strategies and marketability estimates before the harvest.

bioinformatics↗

bioRxiv2018

CropMonitor: a scalable open-source experiment management system for distributed plant phenotyping and IoT-based crop management

BackgroundHigh-quality plant phenotyping and climate data lay the foundation of phenotypic analysis as well as genotype-by-environment interactions, which is important biological evidence not only to understand the dynamics between crop performance, genotypes, and environmental factors, but also for agronomists and farmers to monitor crops in fluctuating agricultural conditions. With the rise of Internet of Things technologies in recent years, many IoT-based remote sensing devices have been applied to phenotyping and crop monitoring that generate big plant-environment datasets every day; however, it is still technically challenging to calibrate, annotate, and aggregate big data effectively, especially when they were generated in multiple locations, and often at different scales.\n\nFindingsCropSurveyor is a PHP and SQL based server platform, which provides automated data collation, storage, device and experiment management through IoT-based sensors and distributed plant phenotyping workstations. It provides a two-component solution for monitoring biological experiments and networked devices, with interfaces specifically designed for distributed IoT devices and centralised data servers. Data transfer is performed automatically though an HTTP accessible RESTful API installed on both device-side and server-side of the CropSurveyor system, which synchronise daily representative crop growth images for quick and visual-based crop assessment, as well as detailed microclimate readings for GxE studies. CropSurveyor also supports the comparison of historical and ongoing crop performance whilst different experiments are being conducted.\n\nConclusionsAs an open-source experiment and data management system, CropSurveyor can be used to maintain and collate important crop performance and microclimate datasets captured by IoT sensors and distributed phenotyping installations. It provides near real-time environmental and crop growth monitoring in addition to historical and current data comparison through a single cloud-ready server system. Accessible both locally in the field through smart devices and remotely in an office using a PC, CropSurveyor has been used in wheat field experiments for prebreeding since 2016 and has the potential to enable scalable crop management and IoT-style agricultural practices in the near future.

plant biology↗

bioRxiv2018

Natural variation in expression of the HECT E3 ligase UPL3 influences seed size and crop yields in Brassica napus by altering regulatory gene expression.

Identifying genetic variation that increases crop yields is a primary objective in plant breeding. We have used association analyses of Brassica napus (oilseed rape/canola) accessions to identify variation in the expression of a HECT E3 ligase gene, BnaUPL3.C03, that influences seed size and final yield. We establish a mechanism in which UPL3 mediates the proteasomal degradation of LEC2, a master regulator of seed maturation. Reduced UPL3 expression increases LEC2 protein levels and prolongs expression of lipid biosynthetic genes and seed maturation. Natural variation in BnaUPL3.C03 expression has not yet been exploited in current Brassica napus breeding lines and can therefore be used as a new approach to maximize future yields in this important oil crop.

plant biology↗