Biology subjects

Gilligan, C.

Publications and source records attributed to Gilligan, C..

7 recordsLinked to original sources

bioRxiv2026

Observation-masked neural posterior estimation for heterogeneous epidemiological surveillance data

Disease surveillance data are often sparse, irregularly timed and heterogeneous across observational units, creating challenges for inference in mechanistic epidemiological models. We present observation-masked neural posterior estimation (OM-NPE), a simulation-based Bayesian inference framework for such settings. The approach represents observations on a common temporal grid and records observation availability through a binary mask, enabling heterogeneous surveillance records to be analysed using a single amortised neural posterior estimator. We demonstrate OM-NPE using two contrasting epidemiological systems. First, we fit an effective SEIR model of Zika virus transmission to weekly sentinel surveillance data from six French Polynesian archipelagos during the 2013-14 outbreak. Second, we fit a stochastic compartmental model of Xylella fastidiosa spread to annual disease-severity observations from 17 olive groves in Apulia, Italy, each surveyed only two or three times over seven years. In both applications, OM-NPE recovered epidemiological parameters consistent with the assumed epidemiological and observation models, appropriately represented uncertainty, and generated posterior distributions in well under one second without retraining or Markov chain Monte Carlo sampling. Observation masking extends amortised Bayesian inference to heterogeneous longitudinal surveillance systems and supports rapid evaluation of alternative monitoring schedules.

systems biology↗

bioRxiv2026

A miRNA-mediated gene regulatory network supports seasonal plasticity in the temperate coral Astrangia poculata

Phenotypic plasticity is a critical strategy for sessile marine invertebrates that cannot escape changing environmental conditions. For corals facing intensifying climate change, the molecular mechanisms that generate and regulate acclimatory responses are central to understanding performance and persistence. MicroRNAs (miRNAs), small non-coding RNAs that regulate gene expression via translational repression and transcript degradation, are compelling candidates for mediating such plasticity, but their role in coral biology remains poorly characterized. Here, we use Astrangia poculata, a temperate coral that endures annual temperature ranges exceeding 25{degrees}C, to investigate the potential for miRNA-mediated plasticity across seasonal and thermal contexts. We exposed adult aposymbiotic colonies to ambient seasonal temperatures ([~]5-22{degrees}C) and a chronic +3{degrees}C warming treatment from February to August 2021, sampling monthly for physiological analyses and at three time points (February, June, August) for molecular analyses. Seasonal change drove significant shifts in photosynthesis, respiration, and soluble protein, whereas the +3{degrees}C treatment had minimal physiological effect. RNA-seq analysis identified the strongest response across seasons, with transcriptional functional enrichment shifting from protein homeostasis, and cellular integrity in the winter, to immunity, metabolism, and reproduction in the summer. We identified 51 miRNAs in A. poculata, 46 of which are novel to this species, providing the first characterization of the miRNA repertoire in this species. Target prediction and co-expression analyses revealed that while mRNA-miRNA networks maintain a stable infrastructure across seasons and treatments, specific interactions are rewired to drive seasonal biology. This dynamic regulation suppresses energy-intensive cell division and morphogenesis during winter quiescence, while shifting to regulate tissue remodeling and reproduction genes during the summer. These results establish miRNAs as seasonal gene regulators in a temperate coral and suggest that the molecular infrastructure underlying its plasticity may also confer resilience to moderate thermal stress.

Molecular Biology↗

bioRxiv2026

Cost-effective early detection of banana bunchy top disease: insights from spatio-temporal modelling in Benin

Banana bunchy top disease (BBTD), caused by banana bunchy top virus (BBTV), threatens food security and livelihoods across sub-Saharan Africa. Effective surveillance is critical for early detection, but in many regions, monitoring is constrained to short operational windows due to limited funding and laboratory capacity. When surveillance is restricted to a single calendar year, sampling effort must be carefully allocated to maximize early detection, yet quantitative guidance linking detection performance to cost is lacking. To address this, we simulated the spatio-temporal spread of BBTV in Benin and retrospectively evaluated country-level BBTD surveillance using a single-year cross-sectional survey design. We found that early detection is feasible but prohibitively expensive (USD 100,000 per year). Under a constrained budget of USD 10,000 per year, an optimal strategy - defined as reaching 75% mean detection probability earliest - was 500 sites with 10 samples per site, though this could delay BBTD detection by up to one year. Our integrated simulation - economic framework quantifies trade-offs between cost and detection likelihood, providing guidance for resource-efficient national-scale BBTD surveillance and a transferable approach for plant pathogen monitoring in smallholder systems.

plant biology↗

bioRxiv2025

Controlling Banana Bunchy Top Disease in Benin: crop protection strategies with socioeconomic perspectives

SummaryO_LIThis study combines satellite mapping, field surveillance, farmer surveys, and disease modelling to assess BBTV dynamics across Benin. It provides the first national-scale map of banana cultivation in Benin and identifies high-risk areas for targeted intervention. C_LIO_LIThe study highlights the dominance of informal networks for exchange of planting material ([~]80% of farmers), limited farmer awareness of BBTV ([~]60% unaware), and low recognition of symptoms or transmission routes, all of which contribute to the spread and persistence of disease. C_LIO_LIAlthough women represented only a quarter of respondents, they demonstrated comparable levels of market orientation and access to planting materials and land. The findings call for spatially targeted, socially informed BBTV management strategies that integrate clean planting material systems, farmer education, and accessible control methods. C_LIO_LIBBTV was detected in 140 out of 747 fields surveyed, with the highest prevalence in the humid southern regions. No cases were found in the northern Sudanian zone, reflecting known agroecological patterns of disease distribution. C_LIO_LIModelling of three control strategies - decapitation, uprooting, and injection - revealed injection as most effective nationally (70% reduction in disease incidence), while uprooting was most effective in vulnerable communities with high disease pressure. C_LIO_LIThe study reveals an interconnected system in which socioeconomic vulnerability, informal seed networks, limited disease awareness, and spatial clustering of banana cultivation collectively drive BBTV dynamics in Benin, highlighting the need for epidemiologically effective, socially informed, and spatially targeted interventions. C_LI Societal Impact StatementBanana and plantain are critical for food security and income generation in West Africa, particularly for smallholder farmers in countries such as Benin. However, banana bunchy top virus (BBTV) poses a major threat to sustainable production. This study integrates high-resolution remote sensing, field epidemiology, mathematical modelling, and socioeconomic analysis to improve understanding of the spread of BBTV and to evaluate the effectiveness of different disease control strategies. Our findings reveal that BBTV risk is highest in southern Benin, where socioeconomic vulnerability is also greatest. Low disease awareness, limited adoption of effective control methods and informal exchange of planting material exacerbate this risk. By identifying priority areas and strategies tailored to local social, economic, and agroecological contexts, this research offers a roadmap for designing targeted, sustainable BBTV management programs. These insights can support smallholder resilience, reduce disease burden, and safeguard banana-based livelihoods across sub-Saharan Africa.

plant biology↗

bioRxiv2025

Environment-dependent selection impacts heritable developmental stability and trait canalization in rice

Canalization, or the maintenance of trait values regardless of environmental or genetic variability, is fundamentally important for maintaining developmental stability. While this concept was described decades ago, we still know relatively little about how canalization is influenced by environmental stress, how it is shaped by natural selection, and the genetic underpinnings of canalization. In this study, we examined natural selection on microenvironmental canalization in rice (Oryza sativa) in wet and dry field conditions. We measured developmental stability in genetically identical replicates obtained from geographically widespread Indica and Japonica rice accessions, providing precise estimates of canalization in thousands of plants. We found that drought stress decreased canalization, showing that stress can increase instability. We also found evidence that canalization can evolve, given that canalization of several traits was heritable and under selection. We further uncovered specific genes underlying canalization, with genetic mapping and functional genetic experiments showing that the bZIP transcription factor-encoding gene OsTGA5/rTGA2.3, which is part of a module that balances stress response and plant growth, regulates canalization of several traits in an environment-dependent manner. At a genome-wide scale, canalization was associated with lower gene expression stochasticity at an earlier life stage, indicating that expression variation can reduce canalization and increase instability. Trait canalization was also positively correlated to temperature at accessions source environments, suggesting that selection on canalization can vary among environments. Overall, our study provides novel insights into the molecular genetic basis of environmental differences in developmental stability and how it might be shaped by selection. SignificanceMechanisms stabilizing organismal development in response to genetic mutations or environmental stressors (canalization) have been reported for numerous animals and plants, but their underlying genetic basis and whether they may be shaped by selection remain unclear. Here, we report patterns of drought-induced trait decanalization in populations of rice (Oryza sativa) grown in field environments. We determined that trait canalization is heritable and can evolve separately from trait means. We identified the gene OsTGA5, part of a regulatory module shaping trade-offs between growth and stress responses, as impacting trait canalization. Plants with less noisy gene expression and evolving in warmer environments display greater developmental stability, contributing to the notion that canalization in rice may be adaptive.

evolutionary biology↗

bioRxiv2022

Modelling the spread and mitigation of an emerging vector-borne pathogen:citrus greening in the U.S.

Predictive models, based upon epidemiological principles and fitted to surveillance data, play an increasingly important role in shaping regulatory and operational policies for emerging outbreaks. Data for parameterising these strategically important models are often scarce when rapid actions are required to change the course of an epidemic invading a new region. We provide a flexible toolkit for landscape-scale disease management, which is applicable to a range of emerging pathogens including vector-borne pathogens for both endemic and invading epidemic vectors. We use the toolkit to analyse and predict the spread of Huanglongbing disease or citrus greening in the U.S. We estimate epidemiological parameters using survey data from one region (Texas) and show how to transfer and test parameters to construct predictive spatio-temporal models for another region (California). The models are used to screen effective coordinated and reactive management strategies for different regions.

ecology↗

bioRxiv2019

When does a minor outbreak become a major epidemic? Linking the risk from invading pathogens to practical definitions of a major epidemic

Forecasting whether or not initial reports of disease will be followed by a severe epidemic is an important component of disease management. Standard epidemic risk estimates involve assuming that infections occur according to a branching process and correspond to the probability that the outbreak persists beyond the initial stochastic phase. However, an alternative assessment is to predict whether or not initial cases will lead to a severe epidemic in which available control resources are exceeded. We show how this risk can be estimated by considering three practically relevant potential definitions of a severe epidemic; namely, an outbreak in which: i) a large number of hosts are infected simultaneously; ii) a large total number of infections occur; and iii) the pathogen remains in the population for a long period. We show that the probability of a severe epidemic under these definitions often coincides with the standard branching process estimate for the major epidemic probability. However, these practically relevant risk assessments can also be different from the major epidemic probability, as well as from each other. This holds in different epidemiological systems, highlighting that careful consideration of what constitutes a severe epidemic in an ongoing outbreak is vital for accurate risk quantification.

ecology↗