Biology subjects

Nellist, C. F.

Publications and source records attributed to Nellist, C. F..

7 recordsLinked to original sources

bioRxiv2025

Hyperspectral image analysis for classification of multiple infections in wheat

Plant diseases can cause heavy yield losses in arable crops resulting in major economic losses. Effective early disease recognition is paramount for modern large-scale farming. Since plants can be infected with multiple concurrent pathogens, it is important to be able to distinguish and identify each disease to ensure appropriate treatments can be applied. Hyperspectral imaging is a state-of-the art computer vision approach, which can improve plant disease classification, by capturing a wide range of wavelengths before symptoms become visible to the naked eye. Whilst a lot of work has been done applying the technique to identifying single infections, to our knowledge, it has not been used to analyse multiple concurrent infections which presents both practical and scientific challenges. In this study, we investigated three wheat pathogens (yellow rust, mildew and Septoria), cultivating co-occurring infections, resulting in a dataset of 1,447 hyperspectral images of single and double infections on wheat leaves. We used this dataset to train four disease classification algorithms (based on four neural network architectures: Inception and EfficientNet with either a 2D or 3D convolutional layer input). The highest accuracy was achieved by EfficientNet with a 2D convolution input with 81% overall classification accuracy, including a 72% accuracy for detecting a combined infection of yellow rust and mildew. Moreover, we found that hyperspectral signatures of a pathogen depended on whether another pathogen was present, raising interesting questions about co-existence of several pathogens on one plant host. Our work demonstrates that the application of hyperspectral imaging and deep learning is promising for classification of multiple infections in wheat, even with a relatively small training dataset, and opens opportunities for further research in this area. However, the limited number of Septoria and yellow rust + Septoria samples highlights the need for larger, more balanced datasets in future studies to further validate and extend our findings under field conditions.

pathology↗

bioRxiv2024

Population genomics and molecular epidemiology of wheat powdery mildew in Europe

Agricultural diseases are a major threat to sustainable food production. Yet, for many pathogens we know exceptionally little about their epidemiological and population dynamics, and this knowledge gap is slowing the development of efficient control strategies. Here we study the population genomics and molecular epidemiology of wheat powdery mildew, a disease caused by the biotrophic fungus Blumeria graminis forma specialis tritici (Bgt). We sampled Bgt for two consecutive years, 2022 and 2023, from 22 countries in Europe and surrounding regions, and compiled a genomic dataset of 415 Bgt isolates. We found one single epidemic unit in the north of Europe, consisting of a highly homogeneous population. Conversely, the south of Europe hosts smaller local populations which are less interconnected. In addition, we show that the population structure can be largely predicted by the prevalent wind patterns. We identified several loci that were under selection in the recent past, including fungicide targets and avirulence genes. Some of these loci are common between populations, while others are not, suggesting different local selective pressures. We reconstructed the evolutionary history of one of these loci, AvrPm17, coding for an effector recognized by the wheat receptor Pm17. We found evidence for a soft sweep on standing genetic variation. Multiple AvrPm17 haplotypes, which can partially escape recognition by Pm17, spread rapidly throughout the continent upon its introduction in the early 2000s. We also identified a new virulent variant, which emerged more recently and can evade Pm17 resistance altogether. Overall, we highlight the potential of genomic surveillance in resolving the evolutionary and epidemiological dynamics of agricultural pathogens, as well as in guiding control strategies.

evolutionary biology↗

bioRxiv2021

Identification of novel genetic regions associated with resistance to European canker in apple

Resistance to Neonectria ditissima, the fungus causing European canker in apple, was studied in a multiparental population of apple scions using several phenotyping methods. The studied population consists of individuals from multiple families connected through a common pedigree. The degree of disease of each individual in the population was assessed in three experiments: artificial inoculations of detached dormant shoots, potted trees in a glasshouse and in a replicated field experiment. The genetic basis of the differences in disease was studied using a pedigree-based analysis (PBA). Three quantitative trait loci (QTL), on linkage groups (LG) 6, 8 and 10 were identified in more than one of the phenotyping strategies. An additional four QTL, on LG 2, 5, 15 and 16 were only identified in the field experiment. The QTL on LG2 and 16 were further validated in a biparental population. QTL effect sizes were small to moderate with 4.3 to 19 % of variance explained by a single QTL. A subsequent analysis of QTL haplotypes revealed a dynamic response to this disease, in which the estimated effect of a haplotype varied over the field time-points. Two groups of QTL-haplotypes could be distinguished, one that displayed increased effect and one with a constant effect across time-points. These results suggest that there are different modes of control of N. ditissima in the early stages of infection compared to later time-points of disease development. It also shows that multiple QTL will need to be considered to improve resistance to European canker in apple breeding germplasm.

genetics↗

bioRxiv2021

Comparative analysis of host-associated variation in Phytophthora cactorum

Phytophthora cactorum is often described as a generalist pathogen, with isolates causing disease in a range of plant species. It is the causative agent of two diseases in the cultivated strawberry, crown rot (CR; causing whole plant collapse) and leather rot (LR; affecting the fruit). In the cultivated apple, P. cactorum causes girdling bark rots on the scion (collar rot) and rootstock (crown rot), as well as necrosis of the fine root system (root rot) and fruit rots. We investigated evidence for host specialisation within P. cactorum through comparative genomic analysis of 18 isolates. Whole genome phylogenetic analysis provided genomic support for discrete lineages within P. cactorum, with well supported non-recombing clades for strawberry CR and apple infecting isolates specialised to strawberry crowns and apple tissue. Isolates of strawberry CR are genetically similar globally, while there is more diversity in apple-infecting isolates. We sought to identify the genetic basis of host specialisation, demonstrating gain and loss of effector complements within the P. cactorum phylogeny, representing putative determinants of host boundaries. Transcriptomic analysis highlighted that those effectors found to be specific to a single host or expanded in the strawberry lineage are amongst those most highly expressed during infection of strawberry and give a wider insight into the key effectors active during strawberry infection. Many effectors that had homologs in other Phytophthoras that have been characterised as avirulence genes were present but not expressed in our tested isolate. Our results highlight several RxLR-containing effectors that warrant further investigation to determine whether they are indeed virulence factors and host-specificity determinants for strawberry and apple. Furthermore, additional work is required to determine whether these effectors are suitable targets to focus attention on for future resistance breeding efforts.

microbiology↗

bioRxiv2019

Genomic investigation of the strawberry pathogen Phytophthora fragariae indicates pathogenicity is determined by transcriptional variation in three key races

The oomycete Phytophthora fragariae is a highly destructive pathogen of cultivated strawberry (Fragaria x ananassa), causing the root rotting disease, red core. The host-pathogen interaction has a well described gene-for-gene resistance relationship, but to date neither candidate avirulence nor resistance genes have been identified. We sequenced a set of American, Canadian and UK isolates of known race type, along with three representatives of the closely related pathogen of the raspberry (Rubus idaeus), Phytophthora rubi, and found a clear population structure, with a high degree of nucleotide divergence seen between some race types and abundant private variation associated with race types 4 and 5. In contrast, between isolates defined as UK races 1, 2 & 3 (UK1-2-3) there was no evidence of gene loss or gain; or the presence of insertions/deletions (INDELs) or Single Nucleotide Polymorphisms (SNPs) within or in proximity to putative pathogenicity genes could be found associated with race variation. Transcriptomic analysis of representative UK1-2-3 isolates revealed abundant expression variation in key effector family genes associated with pathogen race; however, further long read sequencing did not reveal any long range polymorphisms to be associated with avirulence to race UK2 or UK3 resistance, suggesting either control in trans or other stable forms of epigenetic modification modulating gene expression. This work reveals the combined power of population resequencing to uncover race structure in pathosystems and in planta transcriptomic analysis to identify candidate avirulence genes. This work has implications for the identification of putative avirulence genes in the absence of associated expression data and points towards the need for detailed molecular characterisation of mechanisms of effector regulation and silencing in oomycete plant pathogens.

genomics↗

bioRxiv2018

Bioinformatic characterisation of the effector repertoire of the strawberry pathogen Phytophthora cactorum

The oomycete pathogen Phytophthora cactorum causes crown rot, a major disease of cultivated strawberry. We report the draft genome of P. cactorum isolate 10300, cultured from symptomatic Fragaria x ananassa tissue. Our analysis revealed that there are a large number of genes encoding putative secreted effectors in the genome, including nearly 200 RxLR domain containing effectors, 77 Crinklers (CRN) grouped into 38 families and numerous apoplastic effectors, such as phytotoxins (PcF proteins) and necrosis inducing proteins. As in other Phytophthora species, the genomic environment of many RxLR and CRN genes differed from core eukaryotic genes, a hallmark of the two-speed genome. We found genes homologous to known Phytophthora infestans avirulence genes including Avr1, Avr3b, Avr4, Avrblb1 and AvrSmira2 indicating effector sequence conservation between Phytophthora species of Clade 1A and 1C. The reported P. cactorum genome sequence and associated annotations represent a comprehensive resource for avirulence gene discovery in other Phytophthora species from Clade 1 and will facilitate effector informed breeding strategies in other crops.

pathology↗

bioRxiv2018

Quantitative Trait Loci Controlling Phytophthora cactorum Resistance in the Cultivated Octoploid Strawberry (Fragaria x ananassa)

The cultivated strawberry, Fragaria x ananassa (Fragaria spp.) is the most economically important global soft fruit. Phytophthora cactorum, a water-borne oomycete causes economic losses in strawberry production globally. A bi-parental cross of octoploid cultivated strawberry segregating for resistance to P. cactorum, the causative agent of crown rot disease, was screened using artificial inoculation. Multiple resistance quantitative trait loci (QTL) were identified and mapped. Three major effect QTL (FaRPc6C, FaRPc6D and FaRPc7D) explained 36% of the variation observed and in total, the detected QTL explained 86% of the variation observed. There were no epistatic interactions detected between the three major QTLs. Testing a subset of the mapping population progeny against a range of P. cactorum isolates revealed no major differences in host response, however, some lines showed higher susceptibility than predicted, indicating that additional undetected factors may affect the expression of some quantitative resistance loci. Using historic crown rot disease score data from strawberry accessions, a preliminary genome-wide association study of 114 individuals revealed additional loci associated with resistance to P. cactorum. Mining of Fragaria vesca Hawaii 4 v1.1 genome revealed candidate resistance genes in the QTL regions.

plant biology↗