Recipient Organization
UNIVERSITY OF NEW HAMPSHIRE
51 COLLEGE RD SERVICE BLDG 107
DURHAM,NH 03824
Performing Department
Natural Resources and the Environment
Non Technical Summary
Beech bark disease (BBD) is common and widespread cankering disease of American beech that significantly reduces the ecological, aesthetic, and economic value of the forests in New Hampshire and beyond. BBD is referred to as a disease "complex" because symptoms are not specific to a single pathogen that causes disease symptoms. Rather, disease expression requires both an insect "predisposing agent" and the presence of one or more of at least three different species of fungi.Despite nearly a century of research, the details of how the fungal BBD pathogens vary and co-infect across the range of disease are not well known. This project proposes to use powerful genetic technologies to quantify fungal pathogen identity and abundance within infected and uninfected beech across a gradient of duration of infection with BBD. This work will also allow for the assessment of both how pathogens move through the landscape as well as to and from alternative hosts. Understanding patterns of natural selection in fungal pathogens and the development of repeatable assays for comparing variation in aggressiveness across the BBD range could likewise shed light on key management issues. This project also represents an important first step toward realizing a broader vision of developing a deeper understanding of beech resistance to BBD pathogens across the tree's range, with the potential to promote more effective management of the beech resource and to enhance current and ongoing breeding programs.
Animal Health Component
50%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
0%
Goals / Objectives
The overarching goal of this research is to develop the beech bark disease system as an emerging model for understanding pathogen-tree interactions and contemporary evolutionary change in a disease complex etiology (i.e., multiple predisposing factors and fungal causal agents). This long-term vision includes developing replicated beech common gardens containing multiple geographic provenances and putative resistance to BBD to better understand resistance and tolerance to disease in the Beech Bark Disease(BBD) system. Another key outcome of this project is to identify markers and/or traits in beech across its range that can enhance resistance breeding programs.Specific Objectives For the following three objectives, sampling will take place across a gradient of duration of infection with BBD while roughly matching latitude/climate. Additional funding is currently being sought to support the creation and maintenance of common gardens. The requested McIntire-Stennis funding forms a core component of this work, as currently a detailed understanding of the pathogens involved in BBD (and the ways in which they may interact) is conspicuously lacking. At a minimum, this information will aid forest managers by elucidating the role of the generalist N. ditissima (generally thought of as important primarily in the advancing front of the disease) with relevance for managing BBD in mixed stands as well as the role of spillover of N. ditissima in the population dynamics on non-beech hosts. Additionally, the potential utility of using fungal endophytes or hyperparasites as control measures for the cankering component of BBD will be explored.Provide a detailed account of geographic and within-tree patterns and consequences of co-infection by Neonectria species.Reconstruct patterns of gene flow and selection (among different hosts for N. ditissima and among sites and regions for both species) using whole-genome resequencing; examine patterns of movement and spread, reciprocal colonization to and from non-beech hosts, and potential for hybridization.Examine competition among fungal strains and species to better understand how variation in colonizing agent and/or co-infection influences disease aggressiveness, and how Neonectria species may either antagonize and/or synergize one another in variable ecological contexts.
Project Methods
Objective 1. Provide a detailed account of geographic and within-tree patterns and consequences of co-infection by Neonectria species.We have collections of beech bark and fungal pathogens from across the range, and from multiple hosts (in the case of the generalist N. ditissima), and from infected and asymptomatic bark across the gradient of duration of infection in eastern states but will augment these from key locations via direct sampling and sharing among collaborators. Fungal communities from over 200 bark plugs from across this range are currently being sequenced on an Illumina HiSeq using universal fungal primers targeting the ITS2 barcoding region for fungi. Sequencing the ITS2 region gives us a highly replicable list of all or most fungi present in the bark and allows us to estimate the occurrence (and co-occurrence) frequency of both Neonectria species. Results from this sequencing are currently being analyzed, though we proposed to collect and sequence additional samples, particularly from NH and from the edges of the range of the disease and beyond. This will provide a strong understanding of pathogen and tree bark endophyte communities and how they differ latitudinally and as a function of time since infestation with the invasive scale insect.We have sequenced over 50 single-spore isolates representing strains of Neonectria collected as spores within perithecia from across the same range using primers for ITS2, EF-α, and b-tubulin. ITS2 alone is sufficient to distinguish among N. ditissima and N. faginata, though the three regions together are needed to spot check for possible cryptic introduction of N. major or N. coccinea, currently known only from Europe.Objective 2. Reconstruct patterns of gene flow and selection (among different hosts for N. ditissima and among sites and regions for both species) using whole-genome resequencing; examine patterns of movement and spread, reciprocal colonization to and from non-beech hosts, and potential for hybridization.We have already produced an assembled genome for both Neonectria species using a combination of Minion Nanopore and Illumina technologies. We will perform whole-genome resequencing on selected strains collected from across the range of Beech Bark Disease (BBD) and will use single nucleotide polymorphism (SNP) analysis to examine population structure, evidence of geographic spread, hybridization, and selection. See "Molecular and statistical analyses" below for additional details.\Additional sampling: Beech is the only known host for N. faginata, though sampling non-beech hosts exhibiting cankering symptoms on other trees could potentially reveal an unknown cryptic host. Amplification and spillover of N. ditissima from non-beech hosts where is frequently occurs has been hypothesized to increase BBD infection, though definitive tests are lacking. We propose to sample cankers of common tree species (mostly black and yellow birch where infections are abundant) from New Hampshire and West Virginia using intensive surveys as well as opportunistically from throughout the range. This will allow us to estimate the frequency of pathogen movement between beech and non-beech hosts, and to infer the role of alternate hosts on BBD dynamics from a genetic and ecological perspective.Molecular and statistical analyses: DNA will be extracted from single-spore isolates collected from across the range of BBD and prepared and submitted to UNH's Hubbard Genome Center for processing. Illumina HiSeq whole genome shotgun sequencing outputs will be filtered for data quality and assembled against existing high-quality scaffold using custom python and bash scripts. Genome alignment will be performed using Bowtie2 (Langmead and Salzberg 2012). We will perform single nucleotide polymorphism (SNP) discovery, processing in various population genomics software programs including fastSTRUCTURE (Raj et al. 2014). We will then construct and statically examine alternative hypotheses for the speed, timing, and directionality of geographic or among-host spread using Approximate Bayesian Computation implemented in the program DIYABC (Cornuet et al. 2014). We will evaluate among the competing hypotheses that Neonectria spp. colonized beech and the BBD system one or a few times and then spread along with the scale insect v. that these species are omnipresent in the forest and move regularly from beech to non-beech hosts. We will also use a landscape genomics approach to help elucidate barriers or pathways to the potential spread of fungi in this system. Finally, we will examine signals of selection using McDonald-Kreitman and related tests (Booker et al. 2017) across important gradients (i.e., climate, latitude, duration of infestation, etc.).Objective 3. Examine how co-infection may influence disease aggressiveness on trees and how Neonectria species may either antagonize and/or synergize one another in variable ecological contexts using laboratory fungal interaction assays.Fungal culturing: Neonectria strains will be studied as pure culture and in competition assays by pairing strains of both species on a plate and quantifying outcomes of competition at four temperatures (22, 24, 28, and 30oC) on a minimum of three agar substrates (1%, Malt Extract Agar [MEA], 2% MEA, and Potato Dextrose Agar). Additional substrates using ground beech phloem will also be piloted. Other factors to be tested include priority effects (which fungus establishes first), strain geographic origin and apparent aggressiveness as measured by cankering severity on source trees, susceptibility to the parasitic fungus, Gonatorhodiella highlei), etc. Performance and competitive outcomes between N. faginata and N. ditissima will also be examined in the presence of a third potential competitor (Fusarium concolor) frequently detected in our dataset.Characterize the outcome of co-occurrence of Neonectria pathogens as potentially synergistic or antagonistic. These assays will consider combined growth potential versus inhibition in inter-strain and interspecies pairing and will track qualitative aspects of these interactions (i.e., overgrowth of one fungus by another, vegetative anastomosis and/or mating, production of a chemical boundary zone, etc.).We will compare disease severity on trees known to be infected with each of the Neonectria pathogens with trees with known co-infection (based on amplicon sequencing) using field observations across multiple locations and scale insect densities in a statistically rigorous way, considering variable bark anatomy and past necrosis as covariates in our analyses. We will also collect bark samples from infected trees to quantify potentially relevant aspects of bark phenotype on growth, aggressiveness, and localized symptom severity, including the extent and pattern of periderm (bark) necrosis, the frequency and extent of vascular cambium necrosis, sclerid (fiber) cell density, bark thickness, etc. These assessments will be carried out using a combination of microtome thin sections embedded in resin or paraffin and appropriately stained, and using a microCT scanner (recently acquired by the UNH Instrumentation Center) which can rapidly assess internal and external features of bark based on minute differences in density.Booker, T. R., B. C. Jackson, and P. D. Keightley. 2017.Detecting positive selection in the genome. BMC Biol 15:98.Cornuet, J. M., et al. 2014. DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data. Bioinformatics 30:1187-1189.Langmead, B., and S. Salzberg. 2012. Fast gapped-read alignment with Bowtie 2. Nature Methods 9:357-359.Raj, A., M. Stephens, and J. K. Pritchard. 2014. fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197:573-589.