Biology subjects

Cavers, S.

Publications and source records attributed to Cavers, S..

12 recordsLinked to original sources

bioRxiv2026

Metabarcode and transcriptome datasets of Pinus sylvestris to assess fungal phyllosphere and disease dynamics.

Understanding how host-microbiome interactions influence tree disease is critical for understanding forest resilience. Here, we present foliar microbiome ITS2 metabarcoding transcriptomic datasets from Pinus sylvestris to investigate susceptibility to Dothistroma needle blight (DNB), a globally important foliar disease caused by Dothistroma septosporum. We hypothesised that host genotype shapes foliar microbial communities and their interactions, thereby influencing disease outcomes. Samples were collected from a progeny-provenance field trial in the south of Scotland representing a broad spectrum of disease susceptibilities. The dataset comprises ITS2 metabarcoding samples from 200 genotypes across three timepoints and RNAseq samples from 48 genotypes across two timepoints. Sampling captured key stages of pathogen exposure and disease progression. Both standardised and bespoke protocols were used for nucleotide extraction, sequencing, and quality control, including multiple negative and positive controls. These datasets, available in the European Nucleotide Archive (project accession PRJEB88228), enable analysis of temporal dynamics in foliar fungal communities, host-microbiome transcriptional responses, and genotype-dependent variation in disease susceptibility.

bioinformatics↗

bioRxiv2026

A decade of disease survey data in a progeny-provenance trial: Dothistroma needle blight in Scots pine

Longitudinal data on disease susceptibility in forest trees are rare but essential for understanding host-pathogen dynamics and genetic variation in susceptibility traits. We present a long-term multisite common garden dataset quantifying susceptibility of Scots pine (Pinus sylvestris) to Dothistroma needle blight. The dataset comprises annual disease assessments collected from the same trees across 11 years, spanning 168 families and 21 Scottish provenances. This design enables partitioning of genetic and environmental sources of variation, evaluation of temporal stability in host response, and estimation of variance components and narrow-sense heritability of susceptibility. The data support analyses of phenotypic plasticity, provenance-level responses, and interactions between disease susceptibility and other adaptive traits. This resource will facilitate predictive modelling of host susceptibility under current and future environmental conditions.

ecology↗

bioRxiv2025

Genomic signatures of climate-driven (mal)adaptation in an iconic conifer, the English yew (Taxus baccata L.)

The risk of climate maladaptation is increasing for numerous species, including trees. Developing robust methods to assess population maladaptation remains a critical challenge. Genomic offset approaches aim to predict climate maladaptation by characterising the genomic changes required for populations to maintain their fitness under changing climates. In this study, we assessed the risk of climate maladaptation in European populations of English yew (Taxus baccata), a long-lived tree with a patchy distribution across Europe, the Atlas Mountains, and the Near East, where many populations are small or threatened. We found evidence suggesting local climate adaptation by analysing 8,616 SNPs in 475 trees from 29 European T. baccata populations, with climate explaining 18.1% of genetic variance and 100 unlinked climate-associated loci identified via genotype- environment association (GEA). Then, we evaluated the deviation of populations from the overall gene-climate association to assess variability in local adaptation or different adaptation trajectories across populations and found the highest deviations in low latitude populations. Moreover, we predicted genomic offsets and successfully validated these predictions using fitness proxies assessed in plants from 26 populations grown in a comparative experiment. Finally, we integrated information from current local adaptation, genomic offset, historical genetic differentiation and effective migration rates to show that Mediterranean and high-elevation T. baccata populations face higher vulnerability to climate change than low-elevation Atlantic and continental populations. Our study demonstrates the practical use of the genomic offset framework in conservation genetics, offers insights for its further development, and highlights the need for a population-centred approach that incorporates additional statistics and data sources to credibly assess climate vulnerability in wild plant populations.

genomics↗

bioRxiv2024

Evidence of genetic isolation and differentiation among historically fragmented British populations of common juniper, Juniperus communis L.

Habitat fragmentation and populations isolation pose a threat to the genetic diversity and adaptability of many species. The common juniper, Juniperus communis L., a keystone species for juniper scrub habitat and one of only three conifers that are native to the UK, has been in decline for more than a century in the UK and across its European range. Remnant UK juniper populations are now highly fragmented and often small, which has raised concerns for their resilience, especially in the face of climate change and the introduction of novel pathogens, such as Phytophthora austrocedri. This work presents a baseline genetic survey of native UK juniper populations and compares patterns of diversity between populations and among three population centres in southern England, the Lake District, and Scotland using both Single Nucleotide Polymorphism (SNP) and Simple Sequence Repeat (SSR) genetic markers. The aim was to evaluate the standing genetic diversity of native juniper stands, the impacts of habitat fragmentation, and to determine whether juniper populations are genetically isolated from one another. We found that juniper populations, while not completely isolated from one another, face substantial barriers to gene flow, especially between the three population centres. These centres also show different patterns of genetic diversity, indicating varying levels of internal gene flow and inbreeding. Our findings can form a baseline from which to monitor the effectiveness of conservation activities, prioritize populations of concern, and guide genetic rescue efforts.

genetics↗

bioRxiv2024

Not like other conifers: evaluation of phenotypic diversity in British common juniper, Juniperus communis, indicates genetic isolation and local adaptations among remnant populations

Habitat fragmentation and genetic isolation pose threats to the genetic diversity and resilience of natural populations. Protecting the genetic diversity of populations, and the processes that sustain it, optimises their ability to adapt to changing conditions and new threats: conservation efforts with this specific goal are known as "dynamic conservation." The common juniper, Juniperus communis, is a keystone species that provides habitat and resources for many plants and animals. It is a highly polymorphic species, and across its natural range it grows in a variety of habitats and growth forms. Juniper populations have been shrinking and becoming increasingly fragmented for over a century in the UK and elsewhere in Europe, raising concerns about the genetic diversity present in juniper populations and their ability to adapt to changing conditions, or their adaptive potential. This paper presents an analysis of the partitioning of phenotypic diversity among regions, populations and families from 16 UK populations assessed in a common garden trial. Our findings suggest high phenotypic variation among populations compared to the variation among families within populations, indicating barriers to gene flow between juniper populations, relatively homogenous populations and, consequently, potentially reduced adaptive potential. This information is a useful baseline for conservation managers and can also help to infer the genetic diversity and adaptive potential of populations.

genetics↗

bioRxiv2024

Significant and persistent carryover effects in Scots pine

After tracking Scots pine plants from germination to 15 years old, through contrasting early life environments, we observed significant and persistent carryover effects. Groups of plants from common genetic backgrounds were raised in distinct nursery environments, and growth and phenology traits were measured repeatedly once trees had established in their field sites. Growth and phenology differences were evident for 10 and 6 years post-transplantation to the field, respectively. There was a clear interaction between site of origin and carryover effect, indicating that local adaptation also played a role. Given the increasing rate of tree planting initiatives being undertaken around the world in the name of the climate and biodiversity crises, and the strong dependence on those initiatives of nursery-grown plants, our finding of strong carryover effects of the early life environment has significant implications.

ecology↗

bioRxiv2024

Tree nursery environments and their effect on early trait variation

Despite the major role of nurseries in raising young plants and trees prior to transplantation, not enough is known about how the nursery climate impacts the growth and development of plants from germination through to maturity. It is important for forestry practitioners to understand the effect that different nursery environments may have on early stage growth as these may exceed differences due to genetic variation and can confound the use of early stage traits for selection. Here, a replicated progeny-provenance experiment of the economically and ecologically important species Scots pine (Pinus sylvestris L.) was established in three environmentally distinct nurseries in Scotland and traits including survival, growth, form and phenology were measured. Temperature variation and photoperiod were the only uncontrolled environmental variables during this period, and their effect on measured traits was found to be significant among nurseries from the first growing season onwards. Trait interactions were not consistent between nurseries, indicating that the effectiveness of using proxy traits to select for desirable characteristics may depend on the environment in which the trees are grown. This study is the first in a series that will examine trait variation in Scots pine from seedlings to mature trees and highlights the importance of carefully considering and accounting for the nursery environment when growing trees for subsequent transplantation.

ecology↗

bioRxiv2024

Evaluating genomic offset predictions in a forest tree with high population genetic structure

Predicting how tree populations will respond to climate change is an urgent societal concern. An increasingly popular way to make such predictions is the genomic offset (GO) approach, which aims to use genomic and climate data to identify populations that may experience climate maladaptation in the near future. More precisely, GO tries to represent the change in allele frequencies required to maintain the current gene-climate relationships under climate change. However, the GO approach has major limitations and, despite promising validation of its predictions using height data from common gardens, it still lacks broad empirical testing. In the present study, we evaluated the consistency and empirical validity of GO predictions in maritime pine (Pinus pinaster Ait.), a tree species from southwestern Europe and North Africa with a marked population genetic structure. First, gene-climate relationships were estimated using 9,817 SNPs genotyped in 454 trees from 34 populations; and candidate SNPs potentially involved in climate adaptation were identified. Second, GO was predicted using four methods, namely Gradient Forest (GF), Redundancy Analysis (RDA), latent factor mixed model (LFMM) and Generalised Dissimilarity Modeling (GDM), two sets of SNPs (candidate and control SNPs) and five climate general circulation models (GCMs) to account for uncertainty in future climate predictions. Last, the empirical validity of GO predictions was evaluated within a Bayesian framework by estimating the associations between GO predictions and two independent data sources: mortality data from National Forest Inventories (NFI), and mortality and height data from five common gardens in contrasting environments. We found high variability in GO predictions across methods, SNP sets and GCMs. Regarding validation, GO predictions with GDM and GF (and to a lesser extent RDA) based on the candidate SNPs showed the strongest and most consistent associations with mortality rates in common gardens and NFI plots. We found almost no association between GO predictions and tree height in common gardens, most likely due to the overwhelming effect of population genetic structure on tree height in this species. Our study demonstrates the imperative to validate GO predictions with a range of independent data sources before they can be used as informative and reliable metrics in conservation or management strategies.

evolutionary biology↗

bioRxiv2023

Synchronous effective population size changes and genetic stability of forest trees through glacial cycles

The effect of past environmental changes on the demography and genetic diversity of natural populations remains a contentious issue and has rarely been investigated across multiple, phylogenetically distant species. Here, we performed comparative population genomic analyses and demographic inferences for seven widely distributed and ecologically contrasted European forest tree species based on concerted sampling of 164 populations across their natural ranges. For all seven species, the effective population size, Ne, increased or remained stable over many glacial cycles and up to 15 million years in the most extreme cases. Hence, surprisingly, the drastic environmental changes associated with the Pleistocene glacial cycles have had little impact on the level of genetic diversity of dominant forest tree species, despite major shifts in their geographic ranges. Based on their trajectories of Ne over time, the seven tree species can be divided into three major groups, highlighting the importance of life history and range size in determining synchronous variation in genetic diversity, over time. Altogether, our results indicate that forest trees were able to retain their evolutionary potential over very long periods of time despite strong environmental changes. One-Sentence SummaryPopulation genomic analyses reveal that forest trees retained their evolutionary potential over the Quaternary.

evolutionary biology↗

bioRxiv2022

Phenotypic trait variation in a long-term, multisite common garden of Scots pine in Scotland

Multisite common garden experiments, exposing common pools of genetic diversity to a range of environments, allow quantification of plastic and genetic components of trait variation. For tree species, such studies must be long term as they typically only express mature traits after many years. As well as evaluating standing genetic diversity, these experiments provide an ongoing test of genetic variation against changing environmental conditions and form a vital resource for understanding how species respond to abiotic and biotic variation. Finally, quantitative assessments of phenotypic variation are essential to pair with rapidly accumulating genomic data to advance understanding of the genetic basis of trait variation, and its interaction with climatic change. We describe a multisite, population-progeny, common garden experiment of the economically and ecologically important tree species, Scots pine, collected from across its native range in Scotland and grown in three contrasting environments. Phenotypic traits, including height, stem diameter and budburst were measured over 14 growing seasons from nursery to field site. The datasets presented have a wide range of applications.

ecology↗

bioRxiv2021

Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research

Scots pine (Pinus sylvestris) is the most widespread coniferous tree in the boreal forests of Eurasia and has major economic and ecological importance. However, its large and repetitive genome presents a challenge for conducting genome-wide analyses such as association studies and genomic selection. We present a new 50K SNP genotyping array for Scots pine research, breeding programs, and other applications. To select the SNP set, we first genotyped 480 Scots pine samples on a 407 540 SNP screening array, and identified 47 712 high-quality SNPs for the final array (called PiSy50k). Here, we provide details of the design and testing, as well as allele frequency estimates from the discovery panel, functional annotation, tissue-specific expression patterns, and expression level information for the SNPs or corresponding genes, when available. We validated the performance of the PiSy50k array using samples from breeding populations from Finland and Scotland. Overall, 39 678 (83.2%) SNPs showed low error rates (mean = 0.92%). Relatedness estimates based on array genotypes were consistent with the expected pedigrees, and the amount of Mendelian error was negligible. In addition, array genotypes successfully discriminate Scots pine populations from different geographic origins. The PiSy50k array will be a valuable tool for future genetic studies and forestry applications. Significance statementScots pine is an evolutionary, economically and ecologically impressive coniferous species but its gigantic genome has limited studying e.g. the genetic basis of its functional trait variation. We have developed a genotyping array that facilitates Scots pine genetic research and linking its trait variation to genetic polymorphisms and gene expression levels across the genome.

genomics↗

bioRxiv2020

Identifying and testing marker-trait associations for growth and phenology in three pine species

In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 SNPs from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments.

plant biology↗