Biology subjects

Thrall, P. H.

Publications and source records attributed to Thrall, P. H..

4 recordsLinked to original sources

bioRxiv2025

PhyloControl: a phylogeny visualisation platform for risk analysis in weed biological control

O_LIPhylogenetic distance is a key measure used to develop species lists for host specificity tests that delimit the fundamental and realised host range of candidate weed biocontrol agents to meet the assumptions of the centrifugal phylogenetic method. Plant pathogens and insects, even those with broad host ranges, exhibit some degree of phylogenetic conservatism in their host plant associations. Thorough host-specificity testing is crucial to minimise the risk of off-target damage by biocontrol agents to native and economically important plant species. To facilitate this, host test lists need to be developed from an understanding of evolutionary relationships, usually visualised as a phylogenetic tree generated from genetic data, together with plant functional traits and geospatial information. Currently, the process of obtaining a host test list is not standardised, and the manual steps are time-consuming and challenging. C_LIO_LIWe introduce a user-friendly visualisation tool called PhyloControl to aid researchers in their decision-making during biocontrol risk analysis. PhyloControl integrates taxonomic data, molecular data, spatial data, and plant traits in an intuitive interactive interface, empowering biocontrol practitioners to summarise, visualise and analyse data efficiently. C_LIO_LIComprehensively sampled phylogenetic trees are often unavailable, and older published phylogenies often lack branch resolution and support, which increases uncertainty. PhyloControl includes a workflow implemented through Quarto notebooks in R that allows users to download publicly available DNA sequences and perform phylogenetic analyses. The modular workflow also incorporates species distribution modelling to predict the current and potential extent of target weed species. C_LIO_LIPhyloControl will streamline the development of biocontrol host tests lists to support risk analysis and decision making in classical weed biological control. C_LI

plant biology↗

bioRxiv2022

Durable resistance or efficient disease control?Adult Plant Resistance (APR) at the heart of the dilemma

AO_SCPLOWBSTRACTC_SCPLOWAdult plant resistance (APR) is an incomplete and delayed protection of plants against pathogens. At first glance, such resistance should be less efficient than classical major-effect resistance genes, which confer complete resistance from seedling stage, to reduce epidemics. However, by allowing some leaky levels of disease, APR genes are predicted to be more durable than major genes because they exert a weaker selection pressure on pathogens towards adaptation to resistance. However, the impact of partial efficiency and delayed mode of action of APR on the evolutionary and epidemiological outcomes of resistance deployment has never been tested. Using the demogenetic, spatially explicit, temporal, stochastic model landsepi, this study is a first attempt to investigate how resistance efficiency, age at the time of resistance activation and target pathogenicity trait jointly impact resistance durability and disease control at the landscape scale. Our numerical experiments explore the deployment of APR in a simulated agricultural landscape, alone or together with a major resistance gene. As a case study, the mathematical model has been parameterised for rust fungi (genus Puccinia) of cereal crops, for which extensive data are available. Our simulations confirm that weak efficiency and delayed activation of APR genes reduce the selection pressure applied on pathogens and their propensity to overcome resistance, but do not confer effective protection. On the other hand, stronger APR genes (which increase selection pressure on the pathogen) may be quickly overcome but have the potential to provide some disease protection in the short-term. This is attributed to strong competition between different pathogen genotypes and the presence of fitness costs of adaptation, especially when APR genes are deployed together with a major resistance gene via crop mixtures or rotations.

evolutionary biology↗

bioRxiv2018

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs quickly after resistance is deployed, resulting in significant crop losses and a continuing need to develop new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolution of pathogen populations and thus increase genetic resistance durability. These strategies mainly rely on varying different combinations of resistance sources across time (crop rotations) and space. The spatial scale of deployment can vary from multiple resistance sources occurring in a single cultivar (pyramiding), in different cultivars within the same field (cultivar mixtures) or in different fields (mosaics). However, experimental comparison of the efficiency (i.e. ability to reduce disease impact) and durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of landscape-scale deployment strategies presents major logistical challenges.\n\nTherefore, we developed a spatially explicit stochastic model able to assess the epidemiological and evolutionary outcomes of the four major deployment options described above, including both qualitative resistance (i.e. major genes) and quantitative resistance traits against several components of pathogen aggressiveness: infection rate, latent period duration, propagule production rate, and infectious period duration. This model, implemented in the R package landsepi, provides a new and useful tool to assess the performance of a wide range of deployment options, and helps investigate the effect of landscape, epidemiological and evolutionary parameters.\n\nThis article describes the model and its parameterisation for rust diseases of cereal crops, caused by fungi of the genus Puccinia. To illustrate the model, we use it to assess the epidemiological and evolutionary potential of the combination of a major gene and different traits of quantitative resistance. The comparison of the four major deployment strategies described above will be the objective of future studies.\n\nAuthor summaryThere are many recent examples which demonstrate the evolutionary potential of plant pathogens to overcome the resistances deployed in agricultural landscapes to protect our crops. Increasingly, it is recognised that how resistance is deployed spatially and temporally can impact on rates of pathogen evolution and resistance breakdown. Such deployment strategies are mainly based on the combination of several sources of resistance at different spatiotemporal scales. However, comparison of these strategies in a predictive sense is not an easy task, owing to the logistical difficulties associated with experiments involving the spread of a pathogen at large spatio-temporal scales. Moreover, both the durability of a strategy and the epidemiological protection it provides to crops must be assessed since these evaluation criteria are not necessarily correlated. Surprisingly, no current simulation model allows a thorough comparison of the different options. Here we describe a spatio-temporal model able to simulate a wide range of deployment strategies and resistance sources. This model, implemented in the R package landsepi, facilitates assessment of both epidemiological and evolutionary outcomes across simulated scenarios. In this work, the model is used to investigate the combination of different sources of resistance against fungal diseases such as rusts of cereal crops.

evolutionary biology↗

bioRxiv2018

Larger legume plants host a greater diversity of symbiotic nitrogen-fixing bacteria

A major goal in microbial ecology is to understand the factors that structure bacterial communities across space and time. For microbes that have symbiotic relationships with plants, an important factor that may influence their communities is host size or age, yet this has received little attention.\n\nUsing tree diameter size as a proxy for age, we quantified the diversity of rhizobia that associate with an endemic legume, Acacia acuminata, of variable size across a climate gradient in southwest Australia. We examined the 16S rRNA diversity (V1-V3 hypervariable region) of rhizobia at the taxonomic level and at higher sequence level diversity within taxonomic groups.\n\nWe identified 3 major taxonomic clades that associated with Acacia acuminata: Bradyrhizobiaceae, Rhizobiaceae, and Burkholderiaceae. Within these groups, we found extensive genetic variability, especially within Bradyrhizobiaceae. Using binomial multivariate statistical models that controlled for other factors that affect plant size and rhizobia community structure (climate and local soil characteristics), we determined that soil sampled at the base of larger Acacia trees was much more likely to contain a greater number of taxonomic clades and cryptic genetic variants within the Rhizobiaceae clade.\n\nDespite strong influences of climate and highly heterogeneous soil conditions on rhizobial diversity, our results show that host tree size is a prominent factor in structuring nitrogen-fixing symbionts diversity across a large landscape. The identification of a positive relationship between plant host size and microbial diversity raise interesting questions about the role of plant host size in driving ecological processes that govern microbial community assembly. Specifically, our results suggest that hosts may modify the habitat of their surrounding soil to enhance growth (niche construction hypothesis) or that symbiotic microbes have large differences in dispersal capability. Our results also suggest that host plants may be analogous to islands, where larger legume hosts may accumulate diversity over time, through migration opportunities or in situ diversification. From a practical perspective, including plant size as an additional variable may assist sampling and analyses designs of future soil microbial studies.

ecology↗