Biology subjects

Kelly, L. J.

Publications and source records attributed to Kelly, L. J..

6 recordsLinked to original sources

bioRxiv2026

Development of the 4TREE SNP array, a forest multispecies array to enhance European Breeding and conservation programs in pine, poplar and ash.

Within the framework of the European Adaptive BREEDING for Better FORESTs project (B4EST, https://b4est.eu/), we have developed genotyping tools for Poplar, Ash, and Pine forest tree species. SNP arrays are attractive genotyping tools because of the user-friendly genotype calling system and the robust transferability among laboratories. Here we describe the development of an Axiom SNP array for Pinus pinaster (13,407 SNPs), Pinus pinea (5,671 SNPs), Poplar spp. (13,408 SNPs), and Fraxinus spp. (13,407 SNPs) based on a two-step process. We first assembled a high-density (>100,000 SNPs/species) screening array that served to test a large panel of candidate SNPs on a diversity panel involving at least 120 individual trees per species or species group. In the second step, we selected and combined the most informative SNPs to build the final 50,000 SNP 4TREE array. This approach resulted in high genotyping success rates, including for species lacking previously validated high-quality SNP resources. The 4TREE SNP array provides a valuable and transferable genomic tool to support genomic prediction, breeding, and adaptive management of forest tree species.

genomics↗

bioRxiv2025

European ash pangenome reveals widespread structural variation and a diverse genetic basis for low ash dieback susceptibility

European Ash (Fraxinus excelsior) is a keystone forest tree species, whose populations are being decimated by ash dieback disease (ADB). Uncovering the genetic basis of low susceptibility to this devastating disease relies on a comprehensive understanding of genetic variation present in F. excelsior. A linear reference genome from a single individual cannot contain the total sequence variability within a species, including its genic regions; a pangenome more fully captures total sequence content. In this study, we developed a F. excelsior pangenome reference using a new chromosomal-level phased linear reference genome, and de novo assemblies and long-read data from a geographically diverse set of fifty F. excelsior samples, with particular focus on individuals showing low ADB susceptibility. We identified 362,965 structural variants (SVs) present in more than three individuals, including 174Mb of sequence absent from the linear reference genome (22% of the linear reference size). We demonstrated that failing to explicitly link SVs with gene sequences can lead to substantial overestimation of dispensable genes (those that vary in their presence/absence between individuals) due to variability in the annotation process. Controlling for this reduced the fraction of the genome estimated as dispensable from 35.9% to 8.7%, identifying 3,412 high-confidence dispensable genes, including 141 annotated with gene ontology terms associated with defence response. We used the pangenome to analyse existing genomic data from over 1,200 individuals to identify loci associated with reduced susceptibility to ADB. This revealed 220 single nucleotide polymorphisms (SNPs) showing allele frequency shifts between healthy and highly damaged pools of individuals that are broadly consistent across the mainly UK seed sources sampled, explicitly demonstrating the existence of a shared genetic component to low ADB susceptibility.

genomics↗

bioRxiv2025

Molecular convergence analyses identify candidate genes for low susceptibility to the ash dieback pathogen

Non-native pests and pathogens increasingly threaten global forest ecosystems. An understanding of the genomic basis of low susceptibility in the natural hosts of such pests and pathogens, with which they share a coevolutionary history, can enhance restoration efforts by facilitating the selection of individuals carrying beneficial alleles. Within the genus Fraxinus (ash trees) low susceptibility to the fungal pathogen Hymenoscyphus fraxineus, the causative agent of the ash dieback disease (ADB) epidemic, is observed in three independent lineages of known or plausible natural hosts. Here, we seek to elucidate the genetic basis of this trait, which is key to the future survival of Fraxinus excelsior populations in Europe, using a molecular convergence approach. We analysed 4,300 protein-coding loci for amino acid convergence between lineages with low susceptibility. After filtering for potential false positives, we find 62 genes that have a signal of excess convergence between Fraxinus lineages with low ADB susceptibility. Eleven of these loci have additional evidence for a role in defence against fungal pathogens, with a further 17 linked to more general immunity or defence, or other functions relevant to the response against ADB such as cell wall biogenesis. The candidate loci discovered here complement those reported by previous genomic studies of F. excelsior, and can be targeted in efforts to mitigate the devastation caused by this deadly disease by informing breeding programmes involving hybridisation and marker-assisted back-crossing. Our study demonstrates the benefit of genomic analyses incorporating natural hosts, when seeking to tackle biotic threats to naive host populations. Significance StatementKnowledge of the genomic basis of variation in susceptibility to emerging forest pests and pathogens can provide the foundation for interventions to mitigate such threats, but studies restricted to the analysis of naive host populations may miss relevant genomic loci that could be present in coevolved hosts. Using comparative genomic analyses for the detection of molecular convergence between lineages of ash trees with low susceptibility to ash dieback, incorporating known and plausible natural hosts, we detect novel candidate loci for defence against this disease. Our findings can be used to support efforts to tackle one of the worlds worst forest pathogens and demonstrate the value of integrating genomic data from coevolved hosts when aiming to identify the basis of low susceptibility to biotic threats.

evolutionary biology↗

bioRxiv2024

Combined phylogenetic and geographic data can predict plant-pest interactions with high accuracy

O_LINon-native plant pests can pose major threats to biodiversity, with destructive ecological and economic consequences. The ability to predict future threats would allow limited resources to be concentrated on managing the most serious risks. C_LIO_LIWe build a Bayesian model to predict hosts at risk from Agrilus, a beetle genus of over 3,000 species including one of the worlds worst tree pests, using phylogenetic and geographic relationships between known and potential hosts. C_LIO_LIWe assess risk to Quercus (oak), their most common host, by predicting the probability of over 7,000 possible oak-Agrilus interactions to identify species at risk and inform future prevention efforts. Our model detects known hosts with 83.6% accuracy under Leave-One-Out cross-validation, and successfully classifies novel hosts of Agrilus species in new areas, indicating strong predictive performance on independent or misclassified data. Geographic proximity is a strong predictor of host sharing, with likelihood declining rapidly with distance. In general, hosts cluster phylogenetically, with a tendency for closely related oaks to share the same Agrilus species. C_LIO_LIOur approach uses readily available data and could be implemented to assess Agrilus interactions with other plant genera, and extended to additional host-pest systems to help prioritise counter measures against threats worldwide. C_LI

ecology↗

bioRxiv2019

Genes for ash tree resistance to an insect pest identified via comparative genomics

Genome-wide discovery of candidate genes for functional traits within a species typically involves the sequencing of large samples of phenotyped individuals1, or linkage analysis through multiple generations2. When a trait occurs repeatedly among phylogenetically independent lineages within a genus, a more efficient approach may be to identify genes via detection of amino acid residues shared by species possessing that trait3,4. Here, by taking this approach, we identify candidate loci in the genus Fraxinus (ash trees) for resistance to the emerald ash borer beetle (EAB; Agrilus planipennis), a pest species that appears innocuous to otherwise healthy ash in its native East Asian range5 but is highly destructive in North America6 and poses a threat to ash trees in Europe7. Assembling whole genome sequences for 24 diploid species and subspecies of ash, and estimating resistance to EAB for 26 taxa from egg bioassays, we find 53 genes containing amino acid variants shared between two or more independent Fraxinus lineages with EAB-resistant species, that are unlikely to be due to chance or undetected paralogy. Of these, seven genes have putative roles relating to the phenylpropanoid biosynthesis pathway and 17 are potentially connected to herbivore recognition, defence signalling or programmed cell death. We also find that possible loss-of-function mutations among our 53 candidate genes are more frequent in susceptible species, than in resistant ones. Patterns of polymorphism for the EAB-associated amino acid variants in ash trees representing different European populations suggest that selection may be able to enhance their resistance to EAB.

evolutionary biology↗

bioRxiv2019

Genomic basis of European ash tree resistance to ash dieback fungus

Populations of European ash trees (Fraxinus excelsior) are being devastated by the invasive alien fungus Hymenoscyphus fraxineus, which causes ash dieback (ADB). We sequenced whole genomic DNA from 1250 ash trees in 31 DNA pools, each pool containing trees with the same ADB damage status in a screening trial and from the same seed-source zone. A genome-wide association study (GWAS) identified 3,149 single nucleotide polymorphisms (SNPs) associated with low versus high ADB damage. Sixty-one of the 203 most significant SNPs were in, or close to, genes with putative homologs already known to be involved in pathogen responses in other plant species. We also used the pooled sequence data to train a genomic prediction (GP) model, cross-validated using individual whole genome sequence data generated for 75 healthy and 75 damaged trees from a single seed source. Using the top 30% of our genomic estimated breeding values from 200 SNPs, we could predict tree health with over 90% accuracy. We infer that ash dieback resistance in F. excelsior is a polygenic trait that should respond well to both natural selection and breeding, which could be accelerated using GP.

evolutionary biology↗