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Evidence of Coevolution Between Cronartium harknessii Lineages and Their Corresponding Hosts, Lodgepole Pine and Jack Pine

    Affiliations
    Authors and Affiliations
    • Chandra H. McAllister1
    • Catherine I. Cullingham2
    • Rhiannon M. Peery1
    • Michael Mbenoun1
    • Eden McPeak1
    • Nicolas Feau3 4
    • Richard C. Hamelin3
    • Tod D. Ramsfield5
    • Colin L. Myrholm (retired)5
    • Janice E. K. Cooke1
    1. 1Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
    2. 2Department of Biology, Carleton University, Ottawa, Ontario, Canada
    3. 3Department of Forest Science, University of British Columbia, Vancouver, British Columbia, Canada
    4. 4Pacific Forestry Centre, Canadian Forest Service, Natural Resources Canada, Victoria, British Columbia, Canada
    5. 5Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, Edmonton, Alberta, Canada

    Published Online:https://doi.org/10.1094/PHYTO-09-21-0370-R

    Abstract

    Variation in rate of infection and susceptibility of Pinus spp. to the fungus Cronartium harknessii (syn. Endocronartium harknessii), the causative agent of western gall rust, has been well documented. To test the hypothesis that there is a coevolutionary relationship between C. harknessii and its hosts, we examined genetic structure and virulence of C. harknessii associated with lodgepole pine (P. contorta var. latifolia), jack pine (P. banksiana), and their hybrids. A secondary objective was to improve assessment and diagnosis of infection in hosts. Using 18 microsatellites, we assessed genetic structure of C. harknessii from 90 sites within the ranges of lodgepole pine and jack pine. We identified two lineages (East and West, FST = 0.677) associated with host genetic structure (r = 0.81, P = 0.001), with East comprising three sublineages. In parallel, we conducted a factorial experiment in which lodgepole pine, jack pine, and hybrid seedlings were inoculated with spores from the two primary genetic lineages. With this experiment, we refined the phenotypic categories associated with infection and demonstrated that stem width can be used as a quantitative measure of host response to infection. Overall, each host responded differentially to the fungal lineages, with jack pine exhibiting more resiliency to infection than lodgepole pine and hybrids exhibiting intermediate resiliency. Taken together, the shared genetic structure between fungus and host species, and the differential interaction of the fungal species with the hosts, supports a coevolutionary relationship between host and pathogen.

    Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

    Cronartium harknessii E. Meinecke (syn. Endocronartium harknessii (J.P. Moore) Y Hiratsuka; syn. Peridermium harknessii J. P. Moore), the causative agent of western gall rust (WGR), belongs to the order Peridermium (Basidiomycota), which includes many of the world’s most economically impactful plant pathogens (Pendleton et al. 2014; Vogler and Bruns 1998; Wingfield et al. 2004). C. harknessii is closely related to other pine stem and cone rusts in the family Cronartiaceae (Pendleton et al. 2014), including C. quercuum f. sp. fusiforme causing fusiform rust and C. ribicola (J.C. Fisch. in Rabh.) causing white pine blister rust (Sniezko et al. 2014). Unlike other closely related rust species, C. harknessii is considered autoecious and does not require an alternate host to complete its life cycle. This pine-to-pine infection route makes C. harknessii a “short-cycled species” (Vogler and Bruns 1998) and can result in rapid spread of this pathogen across its native range. The range of C. harknessii spans most of Canada and the United States (Hopkin et al. 1988; Ramsfield and Vogler 2010), occurring on both natural Pinus host species, including jack pine (P. banksiana), lodgepole pine (P. contorta var. latifolia), and ponderosa pine (P. ponderosa), as well as exotic hosts such as Scots pine (P. sylvestris) (Peterson 1960). The large geographical range of C. harknessii host species, as well as the diversity in host genetics and resistance (Wu et al. 1996; Wu and Ying 1998; Yanchuk et al. 1988; Yang et al. 1997, 1999), has created an environment in which a pathogen could rapidly evolve, supporting a coevolutionary relationship between the different tree species and the fungus (Reznick 2001). Coevolutionary relationships (for a review, see Burdon and Thrall 2009 and Occhipinti 2013) have previously been observed for rust fungi (Hart 1988), including studies of white pine blister rust, where host resistance and diverse landscape genetics of both the fungus and the host were observed (Kim et al. 2003; Richardson et al. 2008).

    Several studies have reported quantitative disease resistance to C. harknessii in lodgepole pine, jack pine. and their hybrids (Yanchuk et al. 1988; Yang et al. 1997, 1999), with some studies reporting more resistance to C. harknessii in jack pine than lodgepole pine (Wu and Ying 1998; Yang et al. 1997). Wu et al. (1996) also reported increased resistance in lodgepole × jack pine hybrids in the hybrid zone of Alberta relative to lodgepole pine. Major gene resistance and quantitative disease resistance in Pinus spp. to close relatives of C. harknessii have also been well documented, for example, southern pines (P. taeda, P. virginiana, P. elliottii, and P. palustris) resistance to C. quercuum f. sp. fusiforme (Schmidt et al. 2000; Sniezko et al. 2014; Wilcox et al. 1996) and P. lambertiana, P. monticola, P. strobiformis, and P. flexilis resistance to C. ribicola (Kinloch et al. 1970, 1999; Schoettle et al. 2014).

    Many studies have examined infection of Pinus species by C. harknessii and related Cronartium species with the goal of identifying and characterizing host resistance to the pathogen. In contrast, far fewer studies have investigated the underlying coevolutionary relationship of the PinusCronartium pathosystems, including the coevolutionary relationship of C. harknessii with lodgepole and jack pine. However, understanding such relationships is important for the long-term goals of breeding for durable resistance. In one of the only studies to examine the relationship of C. harknessii with lodgepole and jack pine at the population level, Li et al. (2001) used random amplified polymorphic DNA (RAPD) markers to genetically distinguish C. harknessii collected from lodgepole and jack pine. An early form of molecular markers, RAPD markers exhibit a number of limitations, including behavior as dominant markers (i.e., heterozygosity cannot be determined) and challenges with reproducibility (Pérez et al. 1998). The study also used a limited sampling design, analyzing 68 isolates sampled at 13 locations in western Canada. Finally, no genetic analyses of ancestry were conducted for the host pines to confirm the species designations. Because two of the sampling locations were located within the lodgepole pine × jack pine hybrid zone, which is now known to be considerably more complex than when the Li et al. (2001) study was carried out (Burns et al. 2019; Cullingham et al. 2012), it is possible that galls could have been collected from hybrid pines within these locations.

    Taking advantage of new molecular markers developed using genomic data, together with a more comprehensive understanding of the extent and mosaic nature of the lodgepole pine × jack pine hybrid zone (Burns et al. 2019; Cullingham et al. 2012), we tested the hypotheses that C. harknessii comprises two separately evolving lineages in the northern half of its range and that these lineages show the hallmarks of coevolution with their lodgepole and jack pine hosts. To address these hypotheses, we performed an analysis of the genetic structure of C. harknessii across Canada, ranging from western British Columbia to eastern Ontario and north to the Northwest Territories, using microsatellite loci developed from a draft genome assembly of C. harknessii. The resulting genetic structure of C. harknessii was then compared with the genetic structure of the two host species (Burns et al. 2019) using a community genetic approach (James et al. 2011) to determine whether genetic differentiation covaries with host genetic differences. We then used the fungal genetic data to select C. harknessii genetic material associated with either lodgepole pine or jack pine to carry out inoculation trials comparing relative virulence in lodgepole pine, jack pine, and lodgepole × jack pine hybrid provenance material. As part of this study, our aim was to improve assessment of infection in juvenile trees to decrease the time of assessing symptoms and to decrease the subjective nature of the disease scoring. To assess host–pathogen interactions and develop a refined phenotyping schema, we used the torn-needle method developed by Myrholm and Hiratsuka (1993), because of its increased effectiveness and reliability of spore delivery over that of other inoculation methods (Blenis and Hiratsuka 1986; Blenis and Pinnell 1988; Burnes et al. 1988; Myrholm and Hiratsuka 1993). Our premise was that early, visually discernable, and reliably detected symptoms of disease preceding gall formation will enable earlier scoring of more virulent pathogen variants and/or more susceptible host genotypes. We measured disease progression using this refined categorical visual index, adapted from Klein et al. (1991), as well as using stem as a continuous variable that can be more objectively measured. Evidence of shared genetic structure between the fungus and host species, and differential interaction of the fungal species with the hosts, would support the hypothesis of a coevolutionary relationship between host and pathogen.

    MATERIALS AND METHODS

    Fungal samples.

    A total of 425 single-gall samples of C. harknessii were included in this study. Samples were collected between May and July (2014 to 2016) from 90 sites within the distribution range of lodgepole pine and jack pine across six Canadian provinces and territories (Table 1). Most of the samples were collected as mature sporulating galls, from which spore propagules of the rust fungus were extracted following the procedure described by Ramsfield and Vogler (2010) and stored at –80°C. To supplement sample numbers from sites where not enough sporulating galls could be found, immature (nonsporulating) and late sporulating galls were also collected, and slices of the inner wood tissue were harvested from these and preserved at –80°C. Thus, 138 samples were made up of or included a substantial amount of inner gall wood tissue (Northwest Territories = 47, Alberta = 28, Manitoba = 24, British Columbia = 17, Saskatchewan = 17, Ontario = 5).

    TABLE 1. Sampling information for Cronartium harknessii samples collected and genotyped at 18 microsatellite locia

    Fungal DNA extraction and sample identity.

    DNA was extracted using the CTAB (hexadecyl trimethyl ammonium bromide)-based protocol as described by Roe et al. (2010), using ∼60 mg of starting material to improve extraction yields. Material for extraction was ground into a fine powder under liquid nitrogen using a Retsch MM301 Mixer Mill (Haan, Germany) for 90 s at 25 Hz, and inner gall tissue was ground by hand in liquid nitrogen using mortar and pestle. DNA yields and purity were assessed with Infinit M200 PRO NanoQuant spectrometer (Tecan Trading AG, Zurich, Switzerland), and working solutions were adjusted to ∼25 ɳg/µl for spore samples and ∼40 ɳg/µl for gall tissue samples. The identity of C. harknessii was confirmed for selected samples from various locations across the sampling area (Supplementary Table S1) by sequencing the ITS and IGS-1 regions of the ribosomal RNA gene cluster and comparing the sequences generated to records of C. harknessii and other related rust fungi in GenBank (sequencing methods are included in the supplementary material, Supplementary Fig. S1).

    Microsatellite development and typing.

    A customized Python script (available upon request) was used to scan the 92.0-Mb draft genome of C. harknessii (GCA_000500795) for bi- to hexa-nucleotide tandem sequences with at least three repeats. For each of the 3,654 loci detected, a pair of oligonucleotide PCR primers were predicted within the 150-bp flanking regions using Primer3 web software vers. 4.0.0 (Koressaar and Remm 2007; Untergasser et al. 2012), with the following parameters: optimum Tm = 60°C and of 18- to 23-bp primer lengths. A set of 48 markers with di-, tri- or tetra-nucleotide repeat motifs were initially selected and evaluated for PCR amplification and polymorphism. Each marker was chosen from a unique assembly scaffold and included a perfect tandem repeat motif, with a minimum of nine, eight, and six counts for di-, tri- and tetra-nucleotide motifs, respectively.

    The 48 selected markers were screened against a panel of 22 exploratory samples of C. harknessii from British Columbia, Alberta, and Saskatchewan. A mock control made up of DNA from healthy jack pine tissue was also included to ensure that markers did not amplify the host DNA. A cost-effective approach with fluorescent-labeled M13 universal primer (5′-TGTAAAACGACGGCCAGT-3′) (Schuelke 2000) was used for genotyping. The sequence-specific reverse primer was also modified by attaching a GTTT “PIG-tail” to its 5′ end to improve genotyping accuracy (Brownstein et al. 1996). All primers were ordered from Integrated DNA Technologies (Coralville, Iowa) and four fluorescent labels (FAM, NED, PET, and VIC) were used.

    From the 45 markers, we identified 18 microsatellite markers that were amplified in two multiplex panels of nine markers each (Supplementary Table S2). Genotyping of population samples was carried out in 15 μl of PCR reactions containing 1.5 µl of 10× ThermoPol Buffer (New England BioLabs, Ipswich, MA), 1.5 µl of dNTPs (2 mM each) (Invitrogen, Waltham, MA), 0.48 µl of forward primer (2.5 µM), 0.48 µl of reverse primer and M13 primer (10 µM), Taq DNA polymerase (BioLabs), and 1.5 µl of DNA template. PCR cycling conditions were as follows: 5 min of initial denaturation at 94°C, followed by 30 cycles of 30 s at 94°C, 45 s at 58°C, and 45 s at 72°C, then eight cycles of 30 s at 94°C, 45 s at 53°C, and 45 s at 72°C, and 10 min of final extension at 72°C. Reaction products were pooled according to two multiplex panels of nine markers each; thereafter, 2.5 µl of each pool was mixed with 0.25 µl of GeneScan 500 LIZ size standard (Applied Biosystems, Waltham, MA) and 8 µl of HI-DI Formamide and run on an ABI 3730 DNA Analyzer (Applied Biosystems). Results were analyzed with GeneMapper v4.0 (Applied Biosystems).

    Microsatellite and community ecology analyses.

    Before analysis of genetic data, the microsatellite dataset was clone corrected in R ver. 4.0.4 (R Core Team 2021) using the poppr package ver. 2.9.1 (Kamvar et al. 2014) to ensure only one representative of each multilocus genotype was included. We used the genetic distance option for clone correction to make sure individuals with missing data were not included as unique genotypes. To identify populations without a priori knowledge, we used STRUCTURE ver. 2.3.4, using the admixture model (Falush et al. 2003; Pritchard et al. 2000), with allele frequencies correlated, and examined likelihoods for K = 1 to 5, with five iterations each of 100,000 burn in Markov Chain Monte Carlo (MCMC), and 250,000 data collection MCMC. We examined the resulting output using STRUCTURE HARVESTER (Earl and vonHoldt 2012) to identify populations based on both the mean log likelihood (Ln) probability of the data (Pritchard et al. 2000), and the ΔK statistic (Evanno et al. 2005). We further examined the clusters identified in STRUCTURE (using the same parameters as above, except testing K = 1 to 10 for one of the clusters, see Results) to detect additional hierarchical population structure. We generated a principal component analysis (PCA) plot and a distance-based network in R to confirm the clustering solution using the vegan package ver. 2.5-4 (Dixon 2003; Oksanen et al. 2018) and poppr, respectively. Additionally, we used the find.clusters, Bayesian information criterion (BIC) and percent variation methods, and dapc functions in the R package adegenet ver. 2.1.3 (Jombart et al. 2010). We estimated genetic diversity using Shannon’s index (Shannon 1948), Simpson’s index (Simpson 1949), and a measure of evenness (E5; Ludwig and Reynolds 1988) using rarefaction and all samples in poppr for each of the identified clusters (see Results). Genetic differentiation among clusters was estimated in Arlequin 3.5 using the FST like estimator (Excoffier and Lischer 2010). Significant linkage identified via the index of association (IA) (Brown et al. 1980) and r¯d (Agapow and Burt 2001) was used to determine whether clonal versus sexual reproduction was more likely within C. harknessii using 999 permutations. To determine the most likely reproductive mode, we examined multilocus linkage in a hierarchical fashion: the entire dataset, within each main lineage, and within sublineages. Genetic differentiation and linkage were estimated using the clone-corrected data.

    To examine whether the observed genetic structure was spatially associated with host species lodgepole pine and jack pine, we paired fungal samples with previously genotyped pine samples. Pine genotypes were generated using 28 species discriminating single nucleotide polymorphisms developed to refine their spatial distribution (for genotyping details, see Burns et al. 2019). We grouped fungal and pine samples based on geographic proximity using ArcMap10.5 (ESRI, Redlands, CA), where samples within 100 km were considered a sampling site (and <100 km when within the lodgepole × jack pine hybrid zone). We examined genetic population structure for both pine and fungus using PCA of the site-specific allele frequencies using the package vegan in R. To examine whether the host species’ genetic structure was in concordance with the fungal population structure, we compared the resulting PCA plots using a Procrustes transformation (Gower 1975). This transformation calculates a correlation-type coefficient “r” that indicates whether the plots share the same structure.

    Plant tissue, experimental design, and inoculation.

    To examine the interaction between different sources of the fungal pathogen and disease progression in lodgepole, jack pine, and lodgepole × jack pine hybrids, we obtained pine seed from the Alberta Tree Improvement and Seed Centre (ATISC) (Smoky Lake, Alberta, Canada) and the National Tree Seed Centre (Fredericton, New Brunswick, Canada). Seeds were obtained for five provenances: Jacobie Creek (lodgepole pine; British Columbia), Shelter Creek (lodgepole pine; Alberta), Blue Ridge (lodgepole pine × jack pine hybrids; Alberta), Stoney Mountain (jack pine; Alberta), and Cyril Lake (jack pine; Ontario). An overview of the seed origin, provenance, and species can be found in Table 2. We selected Alberta provenances based on the hybrid zone delineation by Cullingham et al. (2012) to ensure accurate species assignment. Species assignments for Alberta provenances were confirmed by ATISC.

    TABLE 2. Overview of pine seed provenances used in this studya

    Seeds were surface sterilized in 1% vol/vol sodium hypochlorite (bleach) according to Groome et al. (1991), then placed in sterile stratification boxes between moistened Versa-Pak germination paper (Seedburo, Des Plaines, IL) and subjected to moist chilling in the dark at 4°C for 2 weeks. Moist-chilled seeds were surface sterilized using the same protocol before sowing in 6- × 12-cell styroblocks (61 cu. in/cavity, Beaver Plastics, Spruce Grove, Canada) containing a prewetted 2:1 peat/vermiculite mixture. Two to three seeds were sown per cavity, then lightly covered with dry vermiculite. The experiment was carried out in a controlled environment growth chamber with illumination of 180 μmol, 16 h photoperiod, 22°C days/16°C nights, and 55% humidity. Styroblocks were enclosed in tented clear polyethylene bags for the first 2 weeks to create the high humidity conditions facilitating germination. After removal of the styroblocks from the bags, seedlings were fertilized weekly with 0.5 g liter−1 per block N-P-K, 20-20-20, for the remainder of the experiment, with seedlings being watered as needed. Plants were culled to one seedling/cell 3 weeks after sowing. A fully randomized blocked design was used for the experiment, with n = 165 cells/provenance.

    Eight weeks after sowing, plants were inoculated using the torn-needle method described by Myrholm and Hiratsuka (1993) with one of three treatments: 1) “mock” inoculum, consisting of only talc powder; 2) “C.harkWEST” inoculum, consisting of C. harknessii spores obtained from multiple galls on lodgepole pine near Hinton, Alberta; or 3) “C.harkEAST” inoculum, consisting of a mix of genetically identical C. harknessii spores from the E1 lineage (see Results) obtained from jack pine in northern Ontario. All spores were mixed together in a 3:1 ratio with talc (spores/talc) before inoculation. A total of 50 to 55 seedlings per provenance were inoculated with each of the three treatments. Directly after inoculation, blocks were moistened with water, covered with clear polyethylene bags as described above to increase humidity and facilitate infection, and incubated at 16°C in the dark for 2 days (Myrholm and Hiratsuka 1993). After 48 h, bags were removed, and previously described lighting and temperature conditions were reinstated for the remainder of the experiment. Directly after inoculation, remaining spores were tested for germination rates by plating on 1.5% water agar at ambient temperature. After 24 h, both C.harkWEST and C.harkEAST inoculum showed average germination rates of 23%.

    To examine potential differences between host pine species, including environmental factors, and disease progression we conducted a phenology study covering a west to east transect through Alberta. Six sites were visited multiple times for 7 weeks, and gall stage was recorded (Supplementary Table S3).

    Phenotyping.

    Plants were phenotyped weekly for WGR disease progression from 8 to 26 weeks postinoculation (wpi) using a categorical visual assessment scale based on that of Klein et al. (1991). This modified scale included subcategories of the categories used by Klein et al. (1991), giving a total of 10 phenotypes. A brief description of each phenotypic category can be found in Table 3 and images are shown in Supplementary Figure S2.

    TABLE 3. Enhanced phenotypic scale of western gall rust disease progression in young pine seedlings inoculated via the torn-needle method described by Myrholm and Hiratsuka (1993)

    To develop a quantitative, more objective means to phenotype disease severity, we measured stem width and dry weight of seedlings at 26 wpi. Plants were cut at the base of the hypocotyl, just above the soil, and terminal buds were removed. Stems were carefully stripped of all needles, lateral branches, and buds before taking stem-width measurements using a digital caliper (Marathon, No. CO 030200). Measurements were taken at the base of the hypocotyl as well as at either the point of inoculation or at the point of greatest stem width associated with the developing gall. In a small number of cases where swelling and gall formation extended to the base of the stem, hypocotyl base measurements were exchanged for measurements taken below the removed terminal bud. Data were expressed as a difference in stem width, calculated by subtracting the base hypocotyl measurement from the point of inoculation/point of greatest stem width. Stems were flash frozen in liquid nitrogen after caliper measurements.

    Quantitative phenotypic data (stem width and stem weight) were analyzed to examine their relationship to visual disease phenotype using analysis of variance. Data were examined using the Shapiro-Wilk test for normality and transformed using Box-Cox before these analyses. After significant association between qualitative phenotype categories and quantitative data (see Results), we used a Tukey’s posthoc test to further explore this relationship. We then used linear regression to assess whether the two quantitative phenotypes were highly correlated. After linear regression, we used stem-width measures to examine the effect of treatment and provenance using a generalized linear mixed effect model (GLMM) implemented in the lme4 package ver. 1.1-26 (Bates et al. 2015), controlling for experimental block effects (random effect) using a Gaussian distribution with a log link. For treatment, effects were measured based on comparison with the mock, whereas for the provenances, they were measured in comparison with Jacobie Creek. Analyses were conducted in R 3.3.2, with the exception of the GLMM (conducted in R 4.0.4).

    RESULTS

    Microsatellite and community ecology analyses.

    We generated genotypes for 411 C. harknessii samples using 18 microsatellite loci. The percentage of missing data was low (1.2%), and there were no more than three loci missing for any individual genotype, that is, 339 individuals had complete genotypes. After clone correction, a total of 124 unique genotypes were represented. Using these genotypes, we identified two population clusters with STRUCTURE, which we will define as “East” (N = 50) and “West” (N = 74) for the remainder of the article. This was supported by ΔKK2 = 4,460), likelihood, and Q-value plots (Fig. 1); genetic differentiation was highly significant among clusters (FST = 0.677, P = 0.001). STRUCTURE analysis of the East and West populations separately indicated that the West population was one single cluster, whereas the East was comprised of additional clusters (Fig. 1). Two and three clusters were supported for the East cluster, which we examined further using PCA, a genetic distance network, and discriminant analysis of principal components (DAPC). The PCA and network clearly demonstrated there were two clusters (Supplementary Fig. S3), whereas the third cluster was weakly defined. The DAPC find.clusters BIC plot did not present a clear solution for which K was most supported. Using the interpretation from the authors of the program, we chose to investigate K = 3 and K = 4 (Supplementary Fig. S4). In both DAPC analyses, we retained 18 PCs (which explained at least 80% of the variation), and we retained all discriminant functions. DAPC de novo assigned clusters for K = 3 and K = 4 were an exact match to the substructure found with STRUCTURE and PCA analyses. Differentiation among clusters was significant (P = 0.001), with differentiation greatest between the East and West clusters (E1-West = 0.816, E2-West = 0.775, E3-West = 0.815), whereas differentiation within in the East clusters was also high (E1-E2 = 0.0.756, E1-E3 = 0.730, E2-E3 = 0.763). We present the geographic distribution for three East clusters, which demonstrates some geographic partitioning; however, individuals from each cluster were often colocated (Fig. 2). The West cluster comprised 183 individuals and 74 genetic clones, whereas the East cluster had 228 individuals and only 50 clones. Diversity and evenness were higher in the West cluster than in the East clusters (Table 4). Measures of linkage disequilibrium were significant using the entire dataset (IA = 7.073, P = 0.001) and for the East cluster (IA = 3.572, P = 0.001); however, linkage was not significant at the lowest hierarchical level (West, East 1, East 2, and East 3) (Table 4).

    Fig. 1.

    Fig. 1. Cronartium harknessii STRUCTURE results for all samples (top panel), the East cluster (middle panel), and the West cluster (bottom panel). Each individual is represented by a bar along the x-axis. Included are the admixture plots, which include ancestry coefficients (y-axis) for individuals (x-axis) and the ΔK/mean probability plots for each analysis (number of K tested: 1 to 5, 1 to 10 for the West). The number of populations supported for all the data were K = 2, K = 2 and 3 for the East and K = 1 for the West.

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    Fig. 2.

    Fig. 2. Distribution and population structure for all Cronartium harknessii samples, with sample sizes at each site represented by the size of the circle (N = 7 to 31). Included in the inset is the Procrustes plot, which shows the amount of error (indicated by the arrows) between the principal component analysis positioning of the C. harknessii sample sites versus lodgepole pine and jack pine sample sites. Colors of the points correspond to the C. harknessii lineages (blue = East, yellow = West). WGR, western gall rust, Cronartium harknessii.

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    TABLE 4. Genetic diversity and multilocus linkage estimates for Cronartium harknessii across the entire dataset (All), the highest hierarchical clusters (East, West), and the clusters identified in the East (E1, E2, and E3)a

    We selected 280 pine samples that had been previously genotyped from over 900 samples (Burns et al. 2019). These individuals were located less than l100 km from our fungal samples (N = 166), which resulted in 14 sampling groups (Supplementary Fig. S5). PCA of the allele frequencies for both datasets were generated and found to be significantly correlated based on a Procrustes analysis (r = 0.81, P = 0.001; Fig. 2). The East population of C. harknessii was aligned with jack pine, whereas the West population was aligned with lodgepole pine.

    Phenotyping.

    Visual analysis of all seedlings from 8 to 26 wpi showed that mock inoculated individuals displayed a variety of phenotypes from complete wound healing to overall stem swelling not associated with the point of inoculation. These phenotypes correlate with categories 0, 1a, 2a, and 3a in the phenotypic index developed for this study (Table 3; Supplementary Fig. S2). Phenotypes 0, 1a, 2a, and 3a were observed in both mock and C. harknessii inoculated individuals but did not lead to gall formation, and thus were not included in further analyses. Gall formation (phenotype 3d) was reliably preceded by phenotypes 2c (necrotic canker), 3b (swelling without discoloration), and 3c (swelling with discoloration) and were relatively straightforward to identify. In contrast, phenotypes 1b (vibrant discoloration) and 2b (discolored, indented, and/or scab-like canker), although not occurring in mock individuals and therefore likely associated with infection, were more subjective measures and did not progress to gall formation in all instances. Progression of gall maturation along a transect within Alberta encompassing pure lodgepole and jack pine stands and within the lodgepole × jack hybrid zone showed a trend toward earlier maturation in jack pine-dominated locations, followed by locations within the hybrid zone, then the lower elevation lodgepole pine stands surveyed in this study (Fig. 3).

    Fig. 3.

    Fig. 3. Progression of gall maturation monitored along a transect of pine depicted from west to east. The westernmost locations represent lodgepole pine, [William A. Switzer Provincial Park (WASPP), W. McLeod River Provincial Recreation Area (W MRPRA), and E. McLeod River (E MRPRA)]; the intermediate locations represent lodgepole × jack pine hybrids [Windfall and Bridge Lakes Natural Area (BLNA)], and the easternmost location represents jack pine (Conklin Rd). Sampling sites are ordered from west at the top of the plot to east at the bottom of the plot. Host species assignments are based on the analyses of Burns et al. (2019). Gall stage was recorded during Spring 2021 at these six sites. Week count was initiated at the first observed occurrence of aecia starting to develop at a site and continued until aeciospores were either present or had been released.

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    In inoculation experiments, a proportion of individuals developed galls regardless of provenance or C. harknessii spore origin (C.harkWEST or C.harkEAST) from 8 to 26 wpi (Fig. 4; Supplementary Fig. S5). The number of individuals per provenance that developed phenotypes related to disease, including galls, followed the pattern of jack pine < hybrid < lodgepole pine for both sources of inocula. Inoculation of jack pine with C.harkEAST led to a greater proportion of individuals developing disease-associated phenotypes earlier and a greater proportion of individuals developing galls than inoculation with C.harkWEST. Individuals from the Cyril Lake provenance inoculated with C.harkWEST showed virtually no gall formation, whereas those inoculated with C.harkEAST led to approximately 40% of seedlings exhibiting galls by 26 wpi. Inoculation of hybrids (Blue Ridge provenance) resulted in ∼50% of seedlings exhibiting galls by 26 wpi with both inocula. Lodgepole pine from both Shelter Creek and Jacobie Creek started to exhibit gall formation at 15 wpi for the C.harkWEST inocula and over 75% exhibited galls by 26 wpi. The C.harkEAST was not as virulent in lodgepole pine, with galls starting to show at week 20, with <60% of seedlings exhibiting galls in both provenances at 26 wpi.

    Fig. 4.

    Fig. 4. Percentage of lodgepole, hybrid (lodgepole × jack), and jack pine seedlings from five provenances showing disease progression every 2 weeks from 8 to 26 weeks postinoculation (wpi). Spores for inoculation were harvested from sporulating galls near Hinton, Alberta, Canada (C.harkWEST inoculum) or northern Ontario, Canada (C.harkEAST inoculum). Seedlings were phenotyped using the new phenotypic scale designed in this study (Table 2; Supplementary Fig. S2). Mock inoculated seedlings were not included because they did not display these phenotypic categories. N = 34 to 44 for each provenance per treatment over time.

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    Differences in stem width (N = 589, df = 8, F = 92.48, P < 0.001) and stem dry weight (N = 172, df = 8, F = 19.20, P < 0.001) measured at 26 wpi (Fig. 5A and B; Supplementary Fig. S6) were statistically significant across qualitative disease phenotypes (Fig. 5A and B) following normalization using Box-Cox power transformation (Supplementary Fig. S7). Tukey’s posthoc tests indicated that gall formation (phenotype 3d) had both significantly higher stem-width difference and dry weight relative to all other phenotypes. Smaller but still significant increases in both quantitative parameters were also observed in relation to phenotype 3c (swelling with necrosis or discoloration), compared with the other phenotype categories. Linear regression analysis comparing the difference in stem-width and dry-weight data showed a positive correlation R2adj = 0.41 (Fig. 5C, N = 172). Therefore, we focused on using stem width difference as a quantitative rather than categorical measure of C. harknessii infection.

    Fig. 5.

    Fig. 5. Assessment of western gall rust infection using novel quantitative measures, stem-width difference (mm), and dry weight (mg), relative to traditional qualitative phenotypic indexing using one-way analysis of variance and mixed effect model analyses. Tukey’s posthoc tests were used to assess significant differences among groups A and B, α = 0.05. A, Stem-width differences (mm) at 26 weeks postinoculation (wpi) (y-axis) versus qualitative disease phenotype (x-axis). B, Dry weight from a subset of samples collected at 26 wpi (y-axis) versus qualitative disease phenotype (x-axis). C, Linear regression analysis of the normalized quantitative data, difference in stem width (mm) versus dry weight (mg).

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    To further evaluate the use of difference in stem width as a quantitative measure of C. harknessii infection, a generalized linear mixed model was used to analyze effects on difference in stem width by provenance, treatment (mock, C.harkWEST, or C.harkEAST), and provenance by treatment interaction, while controlling for block. The mixed model would not converge with the provenance by treatment interaction; therefore, we examined this interaction using a generalized linear model. There were two significant interactions: C.harkWEST with Cyril Lake (t = –3.184, P < 0.01) and with Stoney Mountain (t = –2.927, P < 0.01). The mixed linear model examining provenance and treatment as individual fixed effects with block as a random effect indicates the two lineages had significant effects on stem width compared with the mock (P < 0.001), and the provenances had significantly different stem widths, with jack pine < hybrid pine < lodgepole pine (Table 5; Fig. 6A). To summarize, inoculation with either C.harkWEST or C.harkEAST significantly increased stem-width difference relative to the mock inoculated individuals in both lodgepole pine provenances (Shelter Creek and Jacobie Creek) (Fig. 6A). In contrast, inoculation with C.harkEAST but not C.harkWEST resulted in significant increases in stem-width difference in both jack pine provenances (Stoney Mountain and Cyril Lake), whereas inoculation with C.harkWEST but not C.harkEAST led to significant increases in stem-width difference for the hybrid provenance (Blue Ridge). These results for stem-width differences mirror the trends observed for the percentage of galls formed across provenances for the two inocula (Fig. 6B). No significant differences were observed between mock inoculated individuals across provenances.

    TABLE 5. Results from generalized linear mixed model of a full factorial growth chamber experiment examining the impact of five pine provenances and three inoculation treatments on difference in stem width in seedlings 26 weeks postinoculationa

    Fig. 6.

    Fig. 6. Effect of spore source and pine seed provenance on both difference in stem width (mm) and proportion of galls when lodgepole, hybrid (lodgepole × jack), and jack pine seedlings are mock inoculated (M) or treated with C.harkWEST (W) or C.harkEAST (E). A, Difference in stem width (mm) (stem width at inoculation point or point of greatest swelling minus the stem width at base of hypocotyl) was measured at 26 weeks postinoculation (wpi), and a Tukey’s posthoc test was used to determine significance among groups (N = 589, α = 0.05), with uppercase letters comparing treatments within a provenance and lowercase letters comparing a single treatment across provenances. B, Proportion of total seedlings showing striated galls at 26 wpi for each of the 15 treatments.

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    DISCUSSION

    In Canada, lodgepole pine and jack pine are economically and environmentally important pine species. C. harknessii does not often cause mortality in mature pines, but it can result in timber volume reduction as a result of defects and weak points leading to stem breakage and can have mortality impacts on juvenile trees (Woods et al. 2000). Given that much of the lodgepole pine distribution in North America has been impacted by mountain pine beetle (Audley et al. 2020; Hodge et al. 2017), the age structure has shifted to juvenile trees, which are more susceptible to major stem damage (Woods et al. 2010). Combining this with impacts of climate change and the increase in replanting of harvested natural forest areas, C. harknessii has the potential to become an even more significant pathogen in Canada and the United States (Kliejunas 2011). Management of C. harknessii in this changing landscape is dependent upon understanding the diversity of C. harknessii in natural populations, determining whether coevolution of pathogen and host species is occurring and how this relates to virulence of the pathogen because deployment of resistant stock has been identified as a key management strategy for this pathogen (Weng et al. 2015).

    Our microsatellite data support previous RAPD data identifying two genetic lineages of C. harknessii (Li et al. 2001). Although these two lineages are significantly differentiated and strong linkage suggests there is no sexual reproduction between the East and West, ITS and IGS-1 sequencing does not support the recognition of these lineages as distinct species (Supplementary Fig. S1). In agreement with Yang et al. (1999), we found that the geographic range of each lineage is highly correlated with the geographic ranges of their host species. Our results conflict with Li et al. (2001) because we found the West lineage to be more genetically diverse than the East lineage. However, the East lineage showed more genetic structure, including additional lineages. The lineages in the east did not show strong geographic structuring, but we do note that the E1 lineage was only found in the east, whereas E2 and E3 lineages were found both in the central and eastern portions of the C. harknessii range (Fig. 2). We also did not find evidence of sexual reproduction among the East lineages despite finding individuals from different lineages in similar locations, which warrants additional investigation into potential differences in virulence.

    Using a community genetics approach, we were able to investigate the relationship of C. harknessii lineages and host species within the mosaic hybrid zone, where lodgepole pine transitions to jack pine. Yang et al. (1999) hypothesized that there are differing levels of gene exchange and recombination between fungal lineages in the hybrid zone causing differences in levels of infection in areas of close proximity. In this study, the C. harknessii western genetic lineage was never found on jack pine, nor was the C. harknessii eastern genetic lineage found on lodgepole pine. Indeed, the two lineages were never found together at a single sampling location. Also, several of our gall collection locations were within or near the approximated hybrid zone, and we did not detect any evidence of sexual reproduction between the lineages. These data suggest the two lineages are distinct to each host species. However, additional intensive sampling in the hybrid zone would be required to determine whether fungal recombinants occur between the two lineages when they are in close proximity.

    The mechanism leading to differentiation into distinct genetic lineages likely includes intrinsic and extrinsic factors. For intrinsic factors, none of the lineages show evidence of sexual reproduction between them. This will limit opportunities for admixture between the lineages. For extrinsic factors, environmental gradients, including daily temperatures during the early growing season, and elevation can influence phenology in this pathosystem (Yang et al. 1997), which can lead to asynchronous sporulation of C. harknessii across the zone of lodgepole × jack pine introgression. These environmental gradients also influence the host species, which can further promote asynchronous sporulation. Elevation, moisture, and temperature shape the zone of lodgepole and jack pine introgression (Burns et al. 2019; Cullingham et al. 2012), and they influence growth within species (O’Reilly and Owens 1989; Wang et al. 2003). C. harknessii sporulation needs to be timed to the new growth and extension of leaders (Moltzan et al. 2001). Based on monitoring throughout the 2021 season, gall maturation in sites from lodgepole pine-dominated western Alberta was later than jack pine-dominated sites in eastern Alberta. From this, we hypothesize that asynchrony in sporulation has contributed to the observed genetic distinction between the two primary lineages of C. harknessii. There is limited information on the sexual reproduction of this species; therefore, additional investigation will be required to understand the factors that limit sexual reproduction among different lineages.

    The genetic differentiation between the eastern and western lineages of C. harknessii was accompanied by differences in virulence, which in turn differed according to host species. Each of the two C. harknessii lineages was most virulent on their geographically associated host species: the West lineage (C.harkWEST) caused more disease on lodgepole pine than jack pine, whereas the East lineage (C.harkEAST) caused more disease on jack pine than lodgepole pine. When virulence on the nongeographically associated host species was considered, the East lineage (C.harkEAST) was more virulent on lodgepole pine than the West lineage (C.harkEAST) was on jack pine. Jack pine showed the greatest resistance to infection regardless of the pathogen source.

    Differences between the pine species response to the fungal strains suggest that there is a host genetic component to fungal resistance. Our findings further indicate that genetic resistance to C. harknessii in both lodgepole pine and jack pine is quantitative, in agreement with previous studies (Klein et al. 1991; Weng et al. 2015; Wu et al. 1996; Yang et al. 1997). Our observation that lodgepole × jack pine hybrid seedlings exhibited a proportion of gall development for both C. harknessii lineages intermediate between that of lodgepole and jack pine suggests genetic loci controlling resistance in pine trees are genes with traditional Mendelian inheritance (Li and Yeh 2002). Finally, the gradient in resistance to C. harknessii observed in lodgepole pine could be associated with introgression of alleles underlying resiliency from jack pine into lodgepole pine (Cullingham et al. 2013; Fraser et al. 2016).

    With strong evidence of a genetic component to resistance, there is an opportunity for identifying genetic resistance markers for breeding programs. Our refined disease index customized for the torn-needle method enables more rapid identification of quantitatively resistant families in screening trials, which can be carried out on seedlings that have only just commenced epicotyl growth. We additionally have validated differential stem width as a quantitative measure of disease development after C. harknessii inoculation of young seedlings. Phenotypes that can be assessed using a continuous, quantitative variable such as differential stem width often lead to better model performance in quantitative genomic analyses than do categorical variables such as disease indices (Kizilkaya et al. 2014), increasing the ability of breeders to ascertain meaningful breeding values. Development of this detailed qualitative categorical assessment of disease progression, which can be employed in tandem with our new quantitative measure of disease progression, provides the necessary tools for in-depth, quantitative genetic analyses of C. harknessii resistance in lodgepole and jack pine on young seedlings. These tools will provide valuable input to breeding programs as consistent, easily discernable, early indicators of susceptibility to C. harknessii and for deploying resilient seedlings after harvest and large-scale disturbances, including fire and forest insects.

    Conclusion.

    Coupling genetic data from field-collected samples with growth chamber experiments, we have provided additional evidence supporting the previously defined relationship of C. harknessii genetic lineages with pine host species, lodgepole pine, and jack pine. Growth chamber experiments allowed us to control for environmental variation that the hosts experience on the landscape, which can affect fungal pathogenicity (Heineman et al. 2010); by controlling this, we demonstrated that the two C. harknessii lineages have different levels of virulence, and the hosts have varied levels of resistance. Our findings provide the clearest evidence to date of these two C. harknessii lineages exhibiting a coevolutionary history with lodgepole and jack pine, with a genetic component contributing to both pathogen virulence and host resistance in this complex pathosystem.

    ACKNOWLEDGMENTS

    We thank Lindsay Robb of the Alberta Tree Improvement and Seed Centre (Alberta Ministry of Agriculture, Forestry and Rural Economic Development) and Dale Simpson of the National Tree Seed Centre (Natural Resources Canada, Canadian Forest Service) for their assistance in providing seed used in this study; Roger Brett, Brad Tomm, and Taylor Scarr of Natural Resources Canada, Canadian Forest Service, Alex Woods of the British Columbia Ministry of Forests, and Rory McIntosh of Saskatchewan Ministry of Environment who provided galls; Marion Mayerhofer, Samson Osadolor, and Laura Manerus of the University of Alberta, who collected phenology data; Corey Davis and the Molecular Biology Service Unit for guidance on microsatellite genotyping; and Andy Benowicz and Deogratias Rweyongeza of the Alberta Ministry of Agriculture, Forestry and Rural Economic Development for support, expertise, and project advice.

    The author(s) declare no conflict of interest.

    LITERATURE CITED

    C. McAllister and C. Cullingham contributed equally to this work.

    Data Availability: Genetic data for lodgepole pine, jack pine, and C. harknessii are available on Dataverse: https://dataverse.scholarsportal.info/dataverse/ualberta.

    Funding: Funding for this research was provided to J. E. K. Cooke through grants from Alberta Agriculture and Forestry and Alberta Innovates Bio Solutions (grant AIBIO 14-009) and the Natural Sciences and Engineering Research Council of Canada Strategic Grants Program (STPGP 52100-18).

    The author(s) declare no conflict of interest.