Phylogeography and population structure of the global, wide host-range hybrid pathogen Phytophthora × cambivora
IMA Fungus volume 14, Article number: 4 (2023)
Invasive, exotic plant pathogens pose a major threat to native and agricultural ecosystems. Phytophthora × cambivora is an invasive, destructive pathogen of forest and fruit trees causing severe damage worldwide to chestnuts (Castanea), apricots, peaches, plums, almonds and cherries (Prunus), apples (Malus), oaks (Quercus), and beech (Fagus). It was one of the first damaging invasive Phytophthora species to be introduced to Europe and North America, although its origin is unknown. We determined its population genetic history in Europe, North and South America, Australia and East Asia (mainly Japan) using genotyping-by-sequencing. Populations in Europe and Australia appear clonal, those in North America are highly clonal yet show some degree of sexual reproduction, and those in East Asia are partially sexual. Two clonal lineages, each of opposite mating type, and a hybrid lineage derived from these two lineages, dominated the populations in Europe and were predominantly found on fagaceous forest hosts (Castanea, Quercus, Fagus). Isolates from fruit trees (Prunus and Malus) belonged to a separate lineage found in Australia, North America, Europe and East Asia, indicating the disease on fruit trees could be caused by a distinct lineage of P. × cambivora, which may potentially be a separate sister species and has likely been moved with live plants. The highest genetic diversity was found in Japan, suggesting that East Asia is the centre of origin of the pathogen. Further surveys in unsampled, temperate regions of East Asia are needed to more precisely identify the location and range of the centre of diversity.
Exotic plant pathogens have repeatedly invaded forests and agricultural ecosystems worldwide. Increased human activity, including both increases in travel and plant trade, have been implicated in their accelerated global spread (Brasier 2008; Fisher et al. 2012; Santini et al. 2013; Wingfield et al. 2015). Prominent examples resulting in the deaths of tens of millions of trees include the spread of chestnut blight in the US; Dutch elm disease across Central Asia, Europe and North America; Phytophthora cinnamomi worldwide; the sudden oak death and sudden larch death pathogen in the US and Europe; and ash dieback in Europe (Brasier and Webber 2010; Grünwald et al. 2012; Landolt et al. 2016; Rigling and Prospero 2018; Shakya et al. 2021; Brasier et al. 2021). These invasions often eliminate foundation species substantially changing the plant community structure and function of ecosystems, which in turn can obliterate a forest’s ability to mitigate climate change (Seidl et al. 2018). Thus, understanding the evolutionary history, sources of potential migrants, and geographic origin of invasive pathogens will inform forest management and control strategies.
Phytophthora × cambivora (Petri) Buisman, originally named Blepharospora cambivora by Petri (1917), later transferred into Phytophthora by Buisman (1927), and classified as a hybrid by Jung et al. (2017a, b) is an invasive pathogen of broad concern. It is the principal causal agent of ink disease of sweet chestnut (Castanea sativa Mill.), together with P. cinnamomi Rands. The pathogen primarily infects the root system causing bark necroses which can spread to the collar and lower trunk resulting in extensive cortical lesions with black phloem exudates which also often stain the surrounding soil, giving rise to the common name of the disease (Vettraino et al. 2005; Jung et al. 2018b). Above-ground symptoms include wilting, chlorosis and microphylly (Vettraino et al. 2005; Jung et al. 2018b). Whilst most damaging and well known from sweet chestnut, P. × cambivora causes root and collar rots, aerial stem cankers, crown rots and severe mortality of a wide range of hosts, particularly members of the Fagaceae and many fruit trees in the Rosaceae and other horticultural species (Erwin and Ribeiro 1996; Jung et al. 1996, 2000, 2013, 2016, 2018b; Jung 2009). It has been found on over 40 host species across Europe, North America, Australia, parts of South America, Asia, as well as in numerous African countries (Erwin and Ribeiro 1996; CABI 2017). Severe damage to sweet chestnut was caused by P. × cambivora in the nineteenth and early twentieth centuries and since the 1990s a dramatic resurgence of ink disease has occurred, mainly in southern Europe, in some cases limiting the establishment of new groves of sweet chestnut (Vannini and Vettraino 2001; Vettraino et al. 2001, 2005; Fleisch 2002; Robin et al. 2006; Jung et al. 2018b). The involvement of P. × cambivora, particularly since c. 2000, in the widespread declines of beech (Fagus sylvatica) and oak (Quercus spp.) stands in central and northern Europe, the unexpected detection of the pathogen causing aerial cankers and xylem and shoot infections on beech (Brown and Brasier 2007; Černý et al. 2006; Corcobado et al. 2020; Jankowiak et al. 2013; Jung 2009; Jung et al. 2000, 2005, 2006, 2018a, b; Nechwatal et al. 2011; Telfer et al. 2015), reports on chinquapin (Chrysolepis chrysophylla) in North America (Saavedra et al. 2007), and persistent root and crown rot problems on fruit trees (Prunus spp. and Malus spp.) (Wilcox and Mircetich 1985; Erwin and Ribeiro 1996), illustrate the longstanding and serious economic and ecological impacts of the taxon.
Phytophthora × cambivora was probably among the first damaging invasive Phytophthora species to be introduced to Europe and North America, assumed to have arrived in Europe in the eighteenth century, yet almost nothing is known about its origin and mode of arrival (Crandall 1950; Peace 1962). In a rare population study of the species Oudemans and Coffey (1991) found all isolates from Europe to have a single multilocus isozyme genotype, whilst those from Australia were more variable, possibly suggesting an Australasian origin of the pathogen. Importations of plant pathogens are often limited in number of individuals and genetic variability when compared to populations in their centre of origin as a result of genetic bottlenecks (Goodwin 1997) and the rapid emergence of asexual clones of higher fitness in the new environment (Brasier 1995). For heterothallic species only one mating type may be introduced or survive, prohibiting sexual recombination and resulting in asexually reproducing clonal lineages (Goodwin 1997). Alternatively, certain clones may dominate due to particularly high fitness, even in the context of frequent sexual reproduction after introduction, giving the impression of a stronger introductory genetic bottleneck than may have truly occurred (Brasier and Kirk 2000). In contrast, native populations in their centre of origin often contain both mating types, reproduce sexually, and have high levels of genetic diversity. Some of the world’s most damaging Phytophthora pathogens such as P. infestans, P. cinnamomi, and P. ramorum exhibit this pattern (Goss et al. 2014; Jung et al. 2021; Shakya et al. 2021). For example, the potato late blight pathogen P. infestans, cause of the Irish potato famine, occurs as a diverse sexually recombining population in one of its hypothesized centres of origin in Mexico while clonal lineages cause devastating disease epidemics in Europe and North America (Cooke et al. 2012; Goss et al. 2014). However, other species do not strictly comply with this pattern, having populations with both mating types and high levels of genetic diversity, presumably from sexual reproduction, even in regions where they have been introduced, for example P. capsicii in the USA and South Africa (Lamour et al. 2012). Although the existence of the two mating types in Phytophthora has been known for 100 years, their exact functioning and molecular basis was unclear (Ashby 1922; Haasis and Nelson 1963). Sexual reproduction in the genus is under hormonal control and each mating type responds to the hormones, acyclic oxygenated diterpenes termed α1 and α2, produced by the opposite mating type to produce oospores (Tomura et al. 2017). Nonetheless, in several heterothallic Phytophthora species pure single isolate cultures have been found to self and produce oospores in response to a range of stimuli such as fungicides, long-term culture, compounds produced by root exudates, bacteria, and fungi (Mukerjee and Roy 1962; Brasier 1971, 1972; Ko 1981; Groves and Ristaino 2000; Jayasekera et al. 2007), including A2s of P. × cambivora (Brasier 1975). In addition, a change in mating type has been recorded in some heterothallic species, usually from A2 to A1 (Ko 1981; Ann and Ko 1989; Chandelier et al. 2014), and several self-fertile P. × cambivora isolates have changed to A2 after longterm storage (T. Jung, unpublished results). Recently, the first oomycete mating type locus was identified, with one mating type homozygous and the other heterozygous (Dussert et al. 2020). This is consistent with the Sansome (1980) model that one Phytophthora mating type (A2) is heterozygous and the other (A1) is homozygous; and that somatic segregation of the homozygote from the heterozygote type is restricted by chromosomal reciprocal translocation. Sansome (1980) also showed that the translocation was present in P. × cambivora. These findings help further explain the potential to change from the A2 to the A1 mating type, and indicate that even if a single mating type of an exotic heterothallic Phytophthora species is introduced to a region, sexual reproduction may still occur, either via stimuli that promote selfing or transformation to the other mating type. All considered, limited information is available on the behaviour, population structure and origin of the heterothallic P. × cambivora across its distribution range.
Interspecific hybridization is well known as an important evolutionary driving force in plants, animals and, increasingly, in fungal pathogens (Brasier 2001) and the genus Phytophthora, where six of the 12 clades are known to include hybrid taxa (Chen et al. 2022; Soltis et al. 2010; Soltis and Soltis 2000; Van Poucke et al. 2021). Hybridization can be homoploid, where the ploidy of the hybrid remains the same as that of the parents, or polyploid, where the entire genomes of each parent are retained and genome doubling occurs in the hybrid (Soltis and Soltis 2009). When polyploid hybridization is between different species it is known as alloploidy, whereas when it occurs between populations of the same species it is known as autopolyploidy (Soltis and Soltis 2000, 2009). Each of these hybridization processes have different genetic consequences for the resulting hybrids (Soltis and Soltis 2000, 2009). Hybridization is thus often accompanied by polyploidization, and although still poorly understood, these processes can infer a fitness advantage and increase adaptability, essential traits influencing the invasiveness of a species (Ellstrand and Schierenbeck 2000; Schierenbeck and Ellstrand 2008; Soltis et al. 2010). Polyploid hybrids can be better suited to specific environments and can exhibit an extended host range and enhanced vigour compared to their parents (Brasier et al. 1999; Bertier et al. 2013; Burgess 2015; Jung et al. 2017a, b). Alder decline, caused by P. × alni, is a recent example of a polyploid hybrid Phytophthora wreaking widescale ecological destruction (Husson et al. 2015). Recently Jung et al. (2017b) classified P. × cambivora as an interspecific hybrid due to multiple heterozygous positions in ITS, β-tubulin, and HSP90 gene sequences as well as evidence from cloned β-tubulin, and HSP90 sequences. Van Poucke et al. (2021) also considered the species to be an alloploid hybrid based on its large genome size determined by flow cytometry, comparison of the genome size and the number of GBS loci found, and the presence of a large number of triallelic loci. However, its ploidy level and origins remain unclear.
Overall information on the origins, behaviour, population structure and ploidy levels of P. × cambivora worldwide remains limited. Although potentially native to East Asia, isolates of P. × cambivora from the region have been scarce, a situation improved by our 2017 survey of Phytophthora diversity in natural ecosystems of Japan during which numerous isolates were obtained with both morphological and ITS sequence resemblance to P. × cambivora. Based on this survey, we studied the global population structure of the pathogen including isolates from Europe, North and South America, Australia, and East Asia. We used genotyping-by-sequencing (GBS) to obtain genome-wide single nucleotide polymorphisms (SNPs) to characterize the global population structure of P. × cambivora and its reproductive mode across continents and infer a potential centre of origin. Recent and ancient hybridization events, variation in ploidy and the traces these events have left in the genome are discussed. This work provides novel insights into the emergence of pathogens through hybridization and migration.
Materials and methods
Isolate selection and DNA extraction
Phytophthora × cambivora sensu lato isolates were selected from across the pathogen’s reported range, covering North and South America, Australia, Asia, and Europe (Additional file 1: Table S1). Isolate selection was particularly focused on Europe, where the pathogen is widespread and problematic, and Japan, where a 2017 Phytophthora survey revealed a large number of isolates with ITS sequence similarities above 99% and morphological resemblance to P. × cambivora. Although sampling from certain continents was limited (e.g. only USA in North America, Chile in South America, predominantly Japan in East Asia) the isolates were taken to be representative of the region. Nine P. × alni isolates were included as an outgroup.
Mycelium for DNA extraction was obtained by growing isolates in 17 ml 5% clarified V8 juice broth for one week at 20 °C in a shake culture. Mycelium was then rinsed thoroughly with sterile distilled water and vacuum-dried on a Whatman No 1 filter (Maidstone, UK). DNA was extracted using the Nucleospin Plant II kit (Macherey–Nagel, Düren, Germany) with extraction buffer PL1, according to the manufacturer’s protocol, and eluted into 50 μl.
Genotyping-by-sequencing, read processing, SNP calling, and data filtering
GBS libraries were prepared following the approach of Elshire et al. (2011) and Poland et al. (2012), specifically using the detailed method described in Van Poucke et al. (2021). Briefly, this consisted of digestion of genomic DNA with PstI and HpaII, annealing of adaptors and barcodes, and fragment amplification. Sixty-four to 80 isolates, each with a unique barcode, were pooled and paired-end sequenced (2 × 150 bp) using an Illumina HiSeq4000 (San Diego, CA, USA).
The sequences were pre-processed using the custom made pipeline of Van Poucke et al. (2021), available at https://gitlab.com/ahaegeman/GBS_Phytophthora and at Zenodo with https://doi.org/10.5281/zenodo.3363287. This pipeline consisted of (1) demultiplexing of reads using GBSX v1.1.5 (Herten et al. 2015), (2) trimming of adapters using cutadapt v1.16 (Martin 2011) and FastX toolkit v0.0.14, (3) merging of forward and reverse reads with PEAR v0.9.8 (Zhang et al. 2014), and (4) quality filtering using FastX toolkit, prinseq-lite (Schmieder and Edwards 2011), OBITOOLS v1.2.5 (Boyer et al. 2016) and pairfq 0.14. A custom database of prokaryotes, fungi, the human genome (build 38), and all available Phytophthora genomes was created (Van Poucke et al. 2021) and used in a local BLAST search of the GBS loci. Isolates with more than 450 GBS tags with significant BLASTn hits (E < 1e−4) to non-Phytophthora sequences were considered potentially contaminated and removed from the dataset.
Subsequently a reference-based locus identification approach used BWA-MEM 0.7.15 (Li 2013) to map the pre-processed GBS reads to the P. × cambivora genome (isolate TJ0032, GCA_000443045.1) (Feau et al. 2016). The resulting sam file was converted to bam format, sorted, and indexed using samtools 1.9 (Li et al. 2009). As the P. × cambivora genome is large and consists of over 70,000 contigs it was divided into 20 blocks of contigs using seqtk-1.0 (https://github.com/lh3/seqtk). The GBS reads matching the contigs in each of the 20 genome blocks were extracted from the mapped bam file using GATK Reorder and variants called using GATK HaplotypeCaller v22.214.171.124 on each of the blocks (McKenna et al. 2010). The 20 individual gvcf files for each isolate were then combined into a single file using GATK CombineGVCFs. VCFR 1.10.0 (Knaus and Grünwald 2017) was used to remove loci with a read depth of < 5 and > 70 and loci with > 80% missing data, after which all individual isolate vcf files were combined using vcftools-0.1.15 (Danecek et al. 2011). Indels and non-polymorphic sites were removed and only bi-allelic SNPs retained using VCFR.
Analysis of genetic structure
Alleles in linkage disequilibrium can adversely affect many population clustering approaches and at best are redundant (Abdellaoui et al. 2013; Malomane et al. 2018; Calus and Vandenplas 2018; Privé et al. 2020). Therefore, for population structure analyses, linkage disequilibrium (LD) based SNP pruning and minor allele frequency (MAF) filtering were conducted in plink 1.9 (Chang et al. 2015; www.cog-genomics.org/plink/1.9/) using a 50 SNP window size, a 5 SNP step size, and a variance inflation factor [(1/(1 − r2)] of 1.5 (setting –indep 50 5 1.5) and a MAF of 5%. Additionally, only SNPs with < 5% missing data were retained. Four complementary population analysis methods were implemented: (1) STRUCTURE, (2) principal components analysis (PCA), (3) discriminant analysis of principal components (DAPC), and (4) maximum likelihood (ML) trees.
STRUCTURE 2.3.4 (Falush et al. 2003) implements a Bayesian, model-based clustering algorithm to assign individuals to a specified number of clusters (K), maximizing Hardy–Weinberg equilibrium and minimizing linkage disequilibrium within the clusters (Pritchard et al. 2000). To estimate the optimal number of clusters, 10 independent runs of K = 1–15 were carried out in STRUCTURE using no priors (i.e. no information on geographical location or host was provided). The Python utility StrAuto was used to parallelize the analysis (Chhatre and Emerson 2017). Each run had a burn-in of 100,000 iterations followed by 500,000 data-collecting iterations, used a model of correlated allele frequencies and with admixture among populations allowed. The optimal value of K was assessed using the ΔK method of (Evanno et al. 2005) in CLUMPAK (Kopelman et al. 2015), which was also used to align all optimum K STRUCTURE runs to the permutation with the highest H-value. The DISTRUCT version 1.1 program (Rosenberg 2004) was used to visualize the CLUMPP output.
To complement the Bayesian approach implemented in STRUCTURE, PCA, a method that makes no genetic assumptions (e.g. population model or data structure), was conducted in the R package adegenet 2.1.3 (Jombart and Ahmed 2011). To extend the PCA, a DAPC was also conducted in adegenet 2.1.3 (Jombart et al. 2010; Jombart and Ahmed 2011). The method is particularly suited to identifying clusters (K) of genetically related individuals as it minimizes variation within groups and maximizes variation between groups (Jombart et al. 2010). A sequential K-means procedure followed by an assessment of the Bayesian information criterion (BIC) to assess the optimal number of clusters precedes the DAPC analysis itself. Cross-validation was used to determine the optimal number of principal components retained in the analysis (Jombart and Collins 2015).
Phylogenetic trees are known to be inadequate at placing reticulate taxa, i.e. those derived from hybridization, introgression, or lateral gene transfer between two independent lineages (Dowling and Secor 1997; Gauthier and Lapointe 2007). Nevertheless, in some cases reticulate phylogenies can be partially revealed by traditional phylogenetic inference methods which can offer insights into the clustering of hybrid individuals if interpreted with caution (Posada and Crandall 2002). To this end RAxML v8.2.12 (Stamatakis 2014) was used to produce a maximum likelihood (ML) phylogenetic tree with the full dataset (i.e. prior to LD pruning and MAF filtering), with P. × alni used as an outgroup. All invariant SNPs were removed from the dataset using ascbias (https://github.com/btmartin721/raxml_ascbias). The GTRCAT model without rate heterogeneity with a correction for ascertainment bias (ASC_GTRCAT), together with the Lewis correction for ascertainment bias (asc-corr = lewis) were used and 1000 bootstrap replicates were performed. Figtree 1.4.4 was used to visualize the output (Rambaut 2018). For comparison a dendrogram was constructed using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), bitwise distance, and 100 bootstraps using poppr 2.9.3 (Kamvar et al. 2014) and ape 5.4-1 (Paradis and Schliep 2019).
Mating type and inferring the mode of reproduction
Isolates were paired with known tester strains of P. × cambivora TJ0029 (A2 mating type) and TJ0030 (A1) to determine their mating type. Plugs (5 mm diam.) were cut from actively growing V8-juice agar (V8A) cultures and placed on opposite sides of 45 mm Petri dishes containing clarified V8A and incubated at 20 °C in the dark. Oogonia formation was assessed after four weeks under a light microscope at ×80 magnification (Jung et al. 2011, 2017b).
The predominant mode of reproduction was inferred using the Index of Association (IA), a measure of linkage disequilibrium (Brown et al. 1980; Milgroom 1996). The IA was first calculated on 1000 simulated datasets with 0, 50, or 100% linkage representing sexual, semiclonal, and clonal populations. The simulated dataset contained 6767 loci (analogous to the P. × cambivora-related dataset) and was constructed using adegenet 2.1.3 (Jombart and Ahmed 2011); the IA was calculated in poppr 2.9.3 (Kamvar et al. 2014) on one third of the loci (i.e. 2256 loci). As a single SNP is unlikely to produce a new multilocus genotype, particularly as genotyping error and missing data are common in high throughput sequencing data, individual genotypes were collapsed into multilocus lineages using the average neighbour algorithm (genetic distance cutoff of 0.02900025) (Kamvar et al. 2015) implemented in poppr. The IA was calculated on the mulitilocus lineage dataset for each regional population (Australia, East Asia, Europe, and North America) and compared to that of the simulated datasets (Tabima et al. 2018). The South American population was excluded due to its small sample size. After testing the data for normality using the Shapiro–Wilk’s test a Kruskal–Wallis rank sum test and a posthoc rank comparison was conducted in R (R Development Core Team 2020).
Phylogenetic networks are more appropriate than phylogenetic trees for revealing relationships between reticulate taxa when recombination is suspected (Posada and Crandall 2001). SplitsTree v4.16.2 (Huson and Bryant 2006) was used to construct a phylogenetic network using the LD pruned and MAF filtered P. × cambivora-related only dataset implementing the neighbour-net and equal angle algorithms using uncorrected p-distances with heterozygous ambiguities averaged and normalized.
Nodes in implicit networks, such as those generated by Splitstree, do not represent ancestral taxa, whereas those in explicit networks do (Solís-Lemus and Ané 2016). For explicit network generation under the multispecies network coalescent (MSNC) Phylonetworks (Solís-Lemus and Ané 2016; Solís-Lemus et al. 2017) was used. Two representative isolates were chosen from each group (Additional file 1: Table S1), together with P. × alni as an outgroup, and concordance factors (CF) generated from the LD pruned and MAF filtered SNP dataset using the novel approach of Olave and Meyer (2020). A species tree was reconstructed under the multispecies coalescent (MSC) using the SVDquartets program (Chifman and Kubatko 2014) implemented in PAUP* version 4a168 (Swofford 2021). This species tree was used as the starting point for SNaQ (Solís-Lemus and Ané 2016), implemented in Phylonetworks, which was used to estimate the best network with a range of possible hybrid nodes allowed (from 0 to 6). Ten independent SNaQ searches were performed for each number of hybrid nodes tested, retaining those with the highest pseudolikelihood value.
To complement the estimates of ancestry coefficients provided by the population clustering methods and the results of the phylogenetic networks, a formal test of hybridization based on site pattern frequencies was implemented in HyDe (Blischak et al. 2018). HyDe considers a rooted, four-taxon network including an outgroup, in this case P. × alni, and a triplet of ingroup populations to detect hybridization based on phylogenetic invariants arising under the coalescent model (Blischak et al. 2018). An advantage over Patterson’s D-statistic (Patterson et al. 2012), popularly known as the ABBA-BABA test, is that it intrinsically accommodates multiple individuals per population while at the same time estimating the inheritance parameter, γ, that quantifies the genomic contributions of the parents to the hybrid (Kong and Kubatko 2020). All possible triplet combinations (i.e. using all 12 population groups) were tested and hypotheses considered significant at α < 0.05 after a Bonferonni correction with γ between 0 and 1 and Z-scores > 3.
Ploidy was inferred from GBS data using a number of methods. Gbs2ploidy 1.0 (Gompert and Mock 2017) was used to infer ploidy based on allelic ratios of heterozygous SNPs and to group isolates by ploidy level. The ratios of allele depths at heterozygous positions were also plotted to infer ploidy using vcfR 1.12.0 (Knaus and Grünwald 2017, 2018). The full dataset (i.e. prior to LD pruning and MAF filtering) was used with indels removed but with non-bi-allelic alleles retained. Diploids are expected to have alleles in a ratio of 1:2, triploids in a ratio of 1:3 (or 2:3) and tetraploids in a ratio of 1:4. The plots were organized by population group. Chromosome specific ploidy levels were not investigated due to the unassembled nature of the P. × cambivora reference genome and very high number of scaffolds (Feau et al. 2016).
A total of 296 P. × cambivora-related isolates from 26 countries were included in the study. An additional nine isolates of P. × alni were used as an outgroup. After removing loci with > 80% missing data and indels, and retaining only biallelic polymorphic SNPs, 408,666 SNPs remained in the P. × cambivora-related and P. × alni dataset, with 381,021 in the P. × cambivora-related dataset. After LD pruning, MAF filtering and removing loci with over 5% missing data 6,767 SNPs were retained in the final P. × cambivora-related dataset.
Populations are strongly structured by continent
Global populations of P. × cambivora were highly structured by geographic region (Fig. 1). Most population groups were confined to a single continent, yet three population groups (DAPC1, 4mixed, and 9) were intercontinental and together made up the majority of isolates from Europe, North America and Australia (Fig. 2). The STRUCTURE analysis revealed clear, multilevel clustering with support for hybrid clusters, probably intraspecific hybrid clusters (Fig. 1). Preliminary assessment of delta K suggested only two clusters (Additional file 2: Fig. S1) which split a main group of P. × cambivora isolates from non-Asian regions (Europe, North and South America, and Australia), including the neo-type of the species, from a group of Asian and non-Asian isolates. However, based on the geography and prior knowledge of hybridization higher values of K were investigated (Additional file 3: Fig. S2, Fig. 1). The most informative number of clusters was five with distinct clusters apparent; increasing the number of clusters beyond this led to artificial splitting of single individuals into two clusters. Some isolates were admixed at all values of K and a number of admixed isolates formed fixed groups (e.g. DAPC5, DAPC11) and had stable admixture ratios.
The PCA (Additional files 4 and 5: Figs. S3 and S4), K-means clustering and assessment of the BIC from the DAPC analysis (Additional file 6: Fig. S5), and ML tree (Additional file 7: Fig. S6), revealed clear groups of isolates corresponding to those of the STRUCTURE results (Fig. 1), yet the DAPC groups split one of the STRUCTURE clusters into subgroups (DAPC groups 2, 3, 4, 6, 10). As all clustering methods produced similar groupings, the DAPC group names, which provided the highest level of substructuring, were retained for ease of reference. The sole exception to this was DAPC4 which in the STRUCTURE analysis showed consisted of some ‘pure’ isolates with a high membership probability to the group and some highly admixed isolates with a much lower membership probability to the group, with a clear gap in membership probabilities between these subgroups (i.e. no isolates with a membership probability > 0.66 and < 0.76). Therefore, the DAPC4 group was split into the more ‘pure’ DAPC4 (i.e. membership probability to STRUCTURE cluster 1 ≥ 0.76) and DAPC4mixed (i.e. membership probability to structure cluster 1 ≤ 0.66) solely for ease of visualization of the groups and results (Fig. 1).
Sexual populations are found in Asia, whereas North American, Australian, and European populations are predominantly clonal
All isolates were self-sterile and produced oogonia with one of the two tester strains (A1 mating type isolate TJ0030 from DAPC1 and A2 isolate TJ0029 from DAPC9). Many groups consisted of a single mating type (Additional file 1: Table S1). DAPC1, DAPC7, DAPC8, and DAPC11 consisted entirely of A1 isolates (except for a single isolate in DAPC11 forming oogonia in pairings with both mating types). In contrast, DAPC5 and DAPC9 consisted entirely of A2 isolates. Groups DAPC2, DAPC3, DAPC4 (both subgroups), DAPC6, and DAPC10 contained both A1 and A2 isolates; these groups are closely related (see Fig. 1, Additional file 7: Fig. S6) and have a significant contribution from STRUCTURE cluster 1 (orange in Fig. 1).
The regional tests for linkage disequilibrium showed that the European and Australian populations reproduced clonally (Fig. 3). The North American population was highly clonal, yet indicated limited sexual reproduction occurs, as the IA was lower than that of the simulated data for a purely clonal population and strongly deviated from the European and Australian populations. In contrast the IA of the East Asian population was between a semiclonal and purely sexual population, i.e. it reproduced partially sexually.
Recent and ancestral sexual hybridization are evident
The Splitstree network analysis (Fig. 4) revealed similar patterns to those of the population clustering analyses while highlighting gene exchange and the intraspecific hybrid nature of some groups (e.g. DAPC5) and isolates (represented by boxes in the network).
The SNaQ results indicated a bifuricating tree was a poor fit to the data. The pseudolikelihood increased sharply from h = 0 to h = 1, while increasing the number of hybridization events above two resulted in small (from 2 to 3 hybridization events) or negligible (> 3 hybridization events) increases in pseudolikelihood values (Additional file 8: Fig. S7). This suggests that the best-fitting phylogenetic model involved one hybridization event. The hybrid group is DAPC5 with contributions from DAPC1 and DAPC9 (Fig. 5). The contribution of DAPC9 to the hybrid DAPC5, γ = 0.437, in the Phylonetworks result is similar to the contribution of DAPC9 to DAPC5 in the STRUCTURE results (i.e. mean membership coefficient of 0.385).
The HyDe results are striking in the number of significant hybrid groups found (Additional file 9: Table S2). The clearest, most supported hybrid (the highest Z-score of 39.885) is DAPC5 with parental groups DAPC1 and 9 with a γ of 0.4. This γ value is similar to the STRUCTURE ancestral membership probabilities and the Phylonetworks γ value. Of note is that DAPC9 (P. × cambivora neo-type group) was also very often classed as a hybrid population (Z-score 15.119–4.879). Noteworthy is that groups DAPC2, 6 and 3 were never classed as hybrid groups.
Evidence of variable ploidy levels
Although the inference of ploidy analysis based on inferred ratios of minor and major allele frequency using read depth data for each isolate was not well resolved, there is evidence of variable ploidy. Two ploidy levels were apparent from the gbs2ploidy analysis (Fig. 6). Groups DAPC2, 3, and 6, together with a few isolates of DAPC4 (both subgroups) formed one ploidy group, with all other isolates falling into the second ploidy group. The plots of allele ratios indicated that the isolates in DAPC groups 2, 3 and 6 were diploid, having a clear peak at a 1:2 allelic ratio (inset Fig. 6). All other groups were potentially polyploid or aneuploid. Most isolates had a broad peak with an unclear ploidy level (Additional file 10: Fig. S8), although some isolates had peaks close to a 1:3 ratio suggesting triploidy (inset Fig. 6).
Our work provides novel insights into the global phylogeography and evolutionary history of P. × cambivora. Populations were highly structured by continent. The greatest diversity of groups was found in Japan, where both mating types also occurred. A comparison of simulated and observed index of association values suggests that reproduction in Japan is partially sexual, albeit with an important clonal component. Such a pattern would be expected in a native oomycete population that reproduces both sexually via oospores and asexually via zoospores. Together with the higher diversity of groups, it indicates that Japan lies within the centre of origin of P. × cambivora. Furthermore, the higher resistance of Asian chestnut species (Castanea crenata and C. mollissima) and hybrids between Asian and European chestnut to ink disease (Cristinzio and Grassi 1993; Salesses et al. 1993; Pereira et al. 1995; Fernández-López et al. 2001), consistent with co-evolution of Asian chestnuts with P. × cambivora, also indicates temperate Asia is the origin of the pathogen.
In contrast, populations in Europe, Australia, and North America were dominated by three clonal lineages and reproduced clonally, with apparently no, or only very limited, sexual reproduction. A highly diverse, sexually reproducing population is often a characteristic of pathogen populations at their centre of origin. When introduced elsewhere they often undergo genetic bottlenecks, resulting in a small number of clonally reproducing lineages, particularly Phytophthora pathogens (cf. Brasier 1995; Goodwin 1997), though these patterns may become altered by additional introductions and by recombination events. The devastating late potato blight pathogen, P. infestans, exemplifies this pattern with a diverse, sexual population in Mexico, its probable centre of origin, while elsewhere clonally reproducing lineages cause considerable economic damage (Goss et al. 2014; Hansen et al. 2016; Knaus et al. 2020). Similar patterns occur in the forest dieback pathogens P. cinnamomi and P. ramorum, where natural populations at their centre of origin in East and Southeast Asia are highly diverse and partially sexual, containing both mating types, and the panglobal invasive lineages are clonal (Goss et al. 2009; Van Poucke et al. 2012; Shakya et al. 2021; Jung et al. 2021).
The North American and Australian populations of P. × cambivora were principally composed of a diverse, admixed group (DAPC4mixed) also found in Europe and East Asia. The occurrence of the group across so many continents attests to its success as an invasive pathogen. However, isolates of this group were not found on chestnut species, but were common on fruit trees (Prunus and Malus spp.). Indeed most of the reports of P. × cambivora on fruit trees originate from the USA and Australia, as well as East Asia, not from Europe (Mircetich and Matheron 1976; Suzui and Hoshino 1979; Bumbieris and Wicks 1980; Wilcox and Mircetich 1985; Oudemans and Coffey 1991; Browne et al. 1995; Jee et al. 1997; Wicks et al. 1997). It therefore appears plausible that the dieback of fruit trees historically attributed to P. × cambivora is not due to the P. × cambivora lineages (i.e. DAPC9, DAPC1 and DAPC5) traditionally associated with ink disease in Europe, but to the related group DAPC4mixed (and possibly the closely related group DAPC4). Indeed, these latter groups could even constitute a separate sister species of P. × cambivora. A dataset from a larger group of P. × cambivora isolates from diseased fruit trees would be needed to thoroughly explore whether a separate taxon is responsible for the damage, together with host range and virulence assessments in comparative inoculation trials. Additionally, simpler identification of these groups would be highly desirable, e.g. using single or multi-locus barcodes based on Sanger sequences and/or morphological attributes.
The majority of isolates causing ink disease on chestnut and dieback of fagaceous tree hosts belonged to two clonal lineages (DAPC1 and DAPC9), each of an opposite mating type, and a clearly distinguishable hybrid group (DAPC5) between these two lineages. The two parental groups (DAPC1 and DAPC9) are widespread, occurring in Europe and Australia (both groups) and in North and South America (only DAPC9). They are known to sporulate well and have survived for many years; thus, they have proven themselves to be successful and evolutionarily fit entities. The formation of a manifest hybrid group between them, with no backcrosses, together with their distinctiveness suggests the two parental groups are independent lineages separated by substantial evolutionary time, although evidently not long enough for barriers to sexual reproduction to arise. A similar situation has been described for P. ramorum, with each of the twelve known lineages comprising a single mating type and separated by up to c. 1.6 million years (Goss et al. 2009; Jung et al. 2021; Van Poucke et al. 2012). A number of these lineages have been independently introduced to Europe and North America where they are responsible for two of the most devastating recent forest epidemics, sudden larch death and sudden oak death, respectively (Brasier and Webber 2010; Grünwald et al. 2012; Van Poucke et al. 2012).
Although P. × cambivora reproduces mainly clonally in Europe, the occurrence of a hybrid group between the two principal clonal lineages on the continent indicates that some sexual outcrossing has occasionally occurred. Furthermore, the restriction of the hybrid group (DAPC5) to regions where both parental groups co-occur, and the fact that all members of the hybrid group appear to be first generational hybrids, indicates the hybridization event took place in situ. This situation suggests that the DAPC5 hybrid group is either relatively new, unstable, or has slightly reduced fitness when compared to the parental groups. It is unlikely for novel hybrids to have the same fitness as their parents, very often they have reduced fitness and perish, whilst occasionally they have increased fitness and persist. With plant pathogens in general the host is usually the site or niche where fitness differences will be critical (Brasier 2001). With Ophiostoma novo-ulmi in North America dominant clonal lineages recombine but the recombinants are apparently unable to compete in fitness with the clones (Milgroom and Brasier 1997; Brasier and Kirk 2000). A prominent example of increased fitness in a hybrid is P. × alni, which is much more aggressive to Alnus and, hence, more widespread and abundant than its parent species P. × multiformis and P. uniformis (Brasier and Kirk 2001; Husson et al. 2015; Jung et al. 2018b). Increased fitness is a pre-requisite for persistence of novel hybrids, otherwise they will be outcompeted by their parents unless separated by geography, ecological niche, or a genetic barrier. An assessment of the relative fitness and virulence of DAPC1, DAPC9, and DAPC5 on their main tree hosts would allow a more detailed appraisal of their threat to forests.
Given that there is prior evidence that P. × cambivora is a hybrid (Jung et al. 2017b; Van Poucke et al. 2021) it was expected that many isolates in this study would also be of hybrid origin. However, the only undisputed hybrid group with both parents known was DAPC5; although many groups displayed evidence of admixture they were not confirmed as hybrids with known parents. Detection of hybridization using phylogenetic invariants revealed significant results for many of the triplets (non-negligible γ values from 0.3 to 0.6), and such a large number of significant triplets often indicates ancestral hybridization, with the signal of admixture retained in many of the groups (Blischak 2021). Ancestral hybridization events negatively affect γ estimates and spurious results are known to occur if hybrids are included as parents (Blischak and Kubatko 2019; Kong and Kubatko 2020). Therefore, although it is evident that hybridization, most likely in the form of sexual outcrossing, has played a crucial role in the evolutionary history of P. × cambivora, the parental taxa were not in this study. They may exist in unsampled areas elsewhere in East Asia. Although extensive surveys in Taiwan and Vietnam found no P. × cambivora-related isolates in natural ecosystems (Jung et al. 2017a, 2020) large areas of temperate China remain to be explored for Phytophthora diversity and could harbour additional P. × cambivora-related groups.
The high ploidy level of many of the groups is also consistent with an ancestral hybrid origin of P. × cambivora, as polyploidy is linked to ancient hybridization events (Bertier et al. 2013). Both Jung et al. (2017b) and Van Poucke et al. (2021) found evidence of polyploidy in P. × cambivora yet were unable to confirm the ploidy level of the species. Although some groups are clearly diploid (DAPC2, DAPC3, DAPC6) and never occur as hybrid groups in the hybridization analysis, variable ploidy is suggested in most of the other groups. Polyploids often exhibit a shift in ecological tolerances and seem to be more frequent in human-disturbed, competitive habitats than their diploid relatives whilst also having a greater potential for habitat colonization and expansion into novel niches (Baduel et al. 2018; Ehrendorfer 1980; Otto and Whitton 2000; Pandit et al. 2006; Soltis and Soltis 2000). Thus polyploidy can infer a fitness advantage and increased adaptability, and, in some environments, has been shown to accelerate evolutionary adaptation (Ramsey 2011; Selmecki et al. 2015; Baduel et al. 2018). Aquatic habitats provide conditions for continuous asexual reproduction and spread of oomycetes via zoospores and thus decrease the need for long-term survival and genetic adaptations to host populations and changing environmental conditions via sexually derived oospores (Brasier et al. 2003; Jung et al. 2011). Apparently, aquatic conditions also facilitate allopolyploid hybridizations and confer selective advantages for hybrids, as demonstrated by the abundance of allopolyploid hybrids from Phytophthora Clades 6, 7a and 9 in river systems of Chile, South Africa, Taiwan, Vietnam and Western Australia (Hüberli et al. 2013; Nagel et al. 2013; Oh et al. 2013; Burgess 2015; Jung et al. 2017a, b, 2018a, 2020). In the present study, many P. × cambivora-related isolates in Japan, Portugal and Chile also were recovered from forest streams.
Nonetheless, whole genome duplication and polyploidy can result in developmental disruption, not least in meiosis therefore many polyploids are restricted to vegetative or other forms of asexual reproduction (Otto and Whitton 2000; Schinkel et al. 2016; Herben et al. 2017; Baduel et al. 2018). This is particularly suitable for a pathogen undergoing rapid range expansion, with major disease epidemics often associated with prolific asexual reproduction (Ashu and Xu 2015; Drenth et al. 2019). This is also the case for Phytophthora infestans, with Knaus et al. (2020) revealing that typically, major late blight epidemics of potato are caused by triploid, clonally reproducing lineages, as opposed to diploid sexually reproducing populations at the pathogen’s centre of origin. Intraspecific variation in ploidy, as well as copy number variation, were also reported in other Phytophthora species (Bertier et al. 2013; Barchenger et al. 2017; Knaus et al. 2020). Bertier et al. (2013) believe this increase in P. infestans ploidy level was due to hybridization between divergent genotypes of the species. Such a pattern may also fit the P. × cambivora populations presented in this study, e.g. with groups DAPC1 and DAPC9 becoming globally invasive polyploid clonal lineages, and the increased ploidy level in many of the groups due to hybridization between genotypes. Yet polyploidy is not without its challenges and in time many polyploids undergo diploidization (Hollister 2015; Baduel et al. 2018). However, different classes of genes and sequences are retained preferentially, with others more likely to be returned to diploid status, a feature known as ‘biased fractionation’ (Wendel et al. 2018). This phenomenon is known to have occurred in some Phytophthora species (Martens and Van de Peer 2010) and may account for the unclear ploidy levels of many of the P. × cambivora isolates. Thus, parts of the genome may be diploid and other parts triploid or tetraploid. The fact that P. × cambivora has a functional heterothallic breeding system and produces ample viable oospores, whereas most true triploids are effectively sterile, suggests the genome is not a full triploid. This is in keeping with the ancient hybridization events detected in most of the groups. Alternatively, heterokaryosis, having multiple genetically distinct nuclei in a cell, could be the cause of the ambiguous ploidy levels of many of the isolates. Heterokaryosis has been found in a range of oomycete and, specifically, Phytophthora species (Long and Keen 1977; Catal et al. 2010; Bertier et al. 2013; Fletcher et al. 2019) and indeed for some P. × cambivora isolates using flow cytometry (Jung et al. 2017b).
This study indicates that the highly diverse, sexually recombining population of P. × cambivora in Japan is most probably endemic and lies within the centre of origin of the pathogen. Populations in Europe, Australia, and North America are dominated by a number of introduced clonal lineages. The finding that the majority of isolates causing ink disease of Castanea comprise a few clonal lineages may simplify management of the disease, as radically different genotypes are unlikely to arise, even though the direct parents of these groups were not found. Conversely, another group causing damage to fruit trees found in East Asia, North America, Australia and Europe could constitute a separate sister species to P. × cambivora. Further research is called for to compare the virulence on key hosts of the major P. × cambivora groups found, while strengthening biosecurity to prevent further global movement of these diverse groups. To partially address this issue a soil infestation pathogenicity trial including Fagus sylvatica and representative isolates from all 11 DAPC groups is currently underway. This study draws attention to the complex ploidy levels of P. × cambivora and the formative role ancient hybridization events have played in the history of this species. These traits have served the species well, enabling it to become a globally successful pathogen, and highlight the continued biosecurity threat this pathogen poses, particularly through recombination and hybridization between long separated groups.
Availability of data and materials
Abdellaoui A, Hottenga J-J, de Knijff P, Nivard MG, Xiao X, Scheet P, Brooks A, Ehli EA, Hu Y, Davies GE, Hudziak JJ, Sullivan PF, van Beijsterveldt T, Willemsen G, de Geus EJ, Penninx BWJH, Boomsma DI (2013) Population structure, migration, and diversifying selection in the Netherlands. Eur J Hum Genet 21:1277–1285. https://doi.org/10.1038/ejhg.2013.48
Ann P-J, Ko W-H (1989) Effect of chloroneb and ethazol on mating type of Phytophthora parasitica and P. cinnamomi. Bot Bull Acad Sin 30:207–210
Ashby SF (1922) Oospores in cultures of Phytophthora faberi. Kew Bull 1922(9):257–262
Ashu EE, Xu J (2015) The roles of sexual and asexual reproduction in the origin and dissemination of strains causing fungal infectious disease outbreaks. Infect Genet Evol 36:199–209. https://doi.org/10.1016/j.meegid.2015.09.019
Baduel P, Bray S, Vallejo-Marin M, Kolář F, Yant L (2018) The “Polyploid Hop”: shifting challenges and opportunities over the evolutionary lifespan of genome duplications. Front Ecol Evol. https://doi.org/10.3389/fevo.2018.00117
Barchenger DW, Lamour KH, Sheu Z-M, Shrestha S, Kumar S, Lin S-W, Burlakoti R, Bosland PW (2017) Intra- and Intergenomic variation of ploidy and clonality characterize Phytophthora capsici on Capsicum sp. in Taiwan. Mycol Progress 16:955–963. https://doi.org/10.1007/s11557-017-1330-0
Bertier L, Leus L, D’hondt L, de Cock AWAM, Höfte M (2013) Host adaptation and speciation through hybridization and polyploidy in Phytophthora. PLoS ONE 8:e85385. https://doi.org/10.1371/journal.pone.0085385
Blischak PD (2021) pblischak-HyDe/Lobby. https://gitter.im/pblischak-HyDe/Lobby. Accessed 22 Apr 2021
Blischak P, Kubatko L (2019) HyDe Documentation Release 0.4.1a. 25
Blischak PD, Chifman J, Wolfe AD, Kubatko LS (2018) HyDe: a Python package for genome-scale hybridization detection. Syst Biol 67:821–829. https://doi.org/10.1093/sysbio/syy023
Boyer F, Mercier C, Bonin A, Le Bras Y, Taberlet P, Coissac E (2016) obitools: a unix-inspired software package for DNA metabarcoding. Mol Ecol Resour 16:176–182. https://doi.org/10.1111/1755-0998.12428
Brasier C (1971) Induction of sexual reproduction in single A2 isolates of Phytophthora species by Trichoderma viride. Nat New Biol 231:283
Brasier C (1972) Observations on the sexual mechanism in Phytophthora palmivora and related species. Trans Br Mycol Soc 58:237–251. https://doi.org/10.1016/S0007-1536(72)80153-0
Brasier C (1975) Stimulation of sex organ formation in Phytophthora by antagonistic species of Trichoderma. I. The effect in vitro. New Phytol 74:183–194. https://doi.org/10.1111/j.1469-8137.1975.tb02604.x
Brasier C (1995) Episodic selection as a force in fungal microevolution with special reference to clonal speciation and hybrid introgression. Can J Bot 73:1213–1221
Brasier C (2001) Rapid evolution of introduced plant pathogens via interspecific hybridization. Bioscience 51:123–133
Brasier C (2008) The biosecurity threat to the UK and global environment from international trade in plants. Plant Pathol 57:792–808. https://doi.org/10.1111/j.1365-3059.2008.01886.x
Brasier C, Kirk SA (2000) Survival of clones of NAN Ophiostoma novo-ulmi around its probable centre of appearance in North America. Mycol Res 104:1322–1332
Brasier C, Kirk SA (2001) Comparative aggressiveness of standard and variant hybrid alder phytophthoras, Phytophthora cambivora and other Phytophthora species on bark of Alnus, Quercus and other woody hosts. Plant Pathol 50:218–229. https://doi.org/10.1046/j.1365-3059.2001.00553.x
Brasier C, Webber J (2010) Sudden larch death. Nature 466:824–825. https://doi.org/10.1038/466824a
Brasier C, Cooke DEL, Duncan JM (1999) Origin of a new Phytophthora pathogen through interspecific hybridization. PNAS 96:5878–5883. https://doi.org/10.1073/pnas.96.10.5878
Brasier C, Cooke DEL, Duncan JM, Hansen EM (2003) Multiple new phenotypic taxa from trees and riparian ecosystems in Phytophthora gonapodyides-P. megasperma ITS Clade 6, which tend to be high-temperature tolerant and either inbreeding or sterile. Mycol Res 107:277–290. https://doi.org/10.1017/S095375620300738X
Brasier C, Franceschini S, Forster J, Kirk S (2021) Enhanced outcrossing, directional selection and transgressive segregation drive evolution of novel phenotypes in hybrid swarms of the Dutch elm disease pathogen ophiostoma novo-ulmi. J Fungi 7:452. https://doi.org/10.3390/jof7060452
Brown AV, Brasier CM (2007) Colonization of tree xylem by Phytophthora ramorum, P. kernoviae and other Phytophthora species. Plant Pathol 56:227–241. https://doi.org/10.1111/j.1365-3059.2006.01511.x
Brown AHD, Feldman MW, Nevo E (1980) Multilocus structure of natural populations of Hordeum spontaneum. Genetics 96:523–536
Browne GT, Mircetich SM, Cummins JN (1995) Relative resistance of eighteen selections of Malus spp. to three species of Phytophthora. Phytopathology 85:72. https://doi.org/10.1094/Phyto-85-72
Buisman CJ (1927) Root rots caused by Phycomycetes. Rev Appl Mycol 6:380–381
Bumbieris M, Wicks T (1980) Phytophthora cambivora associated with apple trees in South Australia. Austral Plant Pathol 9:114. https://doi.org/10.1071/APP9800114
Burgess TI (2015) Molecular characterization of natural hybrids formed between five related indigenous clade 6 Phytophthora species. PLoS ONE 10:e0134225. https://doi.org/10.1371/journal.pone.0134225
CABI (2017) Phytophthora cambivora (root rot of forest trees). http://www.cabi.org/isc/datasheet/40956. Accessed 23 Aug 2017
Calus MPL, Vandenplas J (2018) SNPrune: an efficient algorithm to prune large SNP array and sequence datasets based on high linkage disequilibrium. Genet Sel Evol. https://doi.org/10.1186/s12711-018-0404-z
Catal M, King L, Tumbalam P, Wiriyajitsomboon P, Kirk WW, Adams GC (2010) Heterokaryotic nuclear conditions and a heterogeneous nuclear population are observed by flow cytometry in Phytophthora infestans. Cytometry A 77A:769–775. https://doi.org/10.1002/cyto.a.20888
Černý K, Gregorová B, Strnadová V, Holub V (2006) The genus Phytophthora on woody plants—findings in 2005. In: Damaging agents in forest of Czechia 2005/2006. Strnady, pp 20–26
Chandelier A, Heungens K, Werres S (2014) Change of mating type in an EU1 lineage isolate of Phytophthora ramorum. J Phytopathol 162:43–47. https://doi.org/10.1111/jph.12150
Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience. https://doi.org/10.1186/s13742-015-0047-8
Chen Q, Bakhshi M, Balci Y, Broders KD, Cheewangkoon R, Chen SF, Fan XL, Gramaje D, Halleen F, Horta Jung M, Jiang N, Jung T, Májek T, Marincowitz S, Milenković I, Mostert L, Nakashima C, Nurul Faziha I, Pan M, Raza M, Scanu B, Spies CFJ, Suhaizan L, Suzuki H, Tian CM, Tomšovský M, Úrbez-Torres JR, Wang W, Wingfield BD, Wingfield MJ, Yang Q, Yang X, Zare R, Zhao P, Groenewald JZ, Cai L, Crous PW (2022) Genera of phytopathogenic fungi: GOPHY 4. Stud Mycol 101:417–564. https://doi.org/10.3114/sim.2022.101.06
Chhatre VE, Emerson KJ (2017) StrAuto: automation and parallelization of STRUCTURE analysis. BMC Bioinform 18:192. https://doi.org/10.1186/s12859-017-1593-0
Chifman J, Kubatko L (2014) Quartet inference from SNP data under the coalescent model. Bioinformatics 30:3317–3324. https://doi.org/10.1093/bioinformatics/btu530
Cooke DEL, Cano LM, Raffaele S, Bain RA, Cooke LR, Etherington GJ, Deahl KL, Farrer RA, Gilroy EM, Goss EM, Grünwald NJ, Hein I, MacLean D, McNicol JW, Randall E, Oliva RF, Pel MA, Shaw DS, Squires JN, Taylor MC, Vleeshouwers VGAA, Birch PRJ, Lees AK, Kamoun S (2012) Genome analyses of an aggressive and invasive lineage of the Irish Potato Famine Pathogen. PLOS Pathogens 8:e1002940. https://doi.org/10.1371/journal.ppat.1002940
Corcobado T, Cech TL, Brandstetter M, Daxer A, Hüttler C, Kudláček T, Horta Jung M, Jung T (2020) Decline of European beech in Austria: involvement of Phytophthora spp. and contributing biotic and abiotic factors. Forests 11:895. https://doi.org/10.3390/f11080895
Crandall BS (1950) The distribution and significance of the chestnut root rot Phytophthoras, P. cinnamomi and P. cambivora. Plant Dis Report 6:194–196
Cristinzio G, Grassi G (1993) Assessing resistance to ink disease (caused by Phytophthora cambivora and Phytophthora cinnamomi) in chestnut cultivars. Monti e Boschi 44:54–58
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, Durbin R, 1000 Genomes Project Analysis Group (2011) The variant call format and VCFtools. Bioinformatics 27:2156–2158. https://doi.org/10.1093/bioinformatics/btr330
Dowling TE, Secor CL (1997) The role of hybridization and introgression in the diversification of animals. Annu Rev Ecol Syst 28:593–619. https://doi.org/10.1146/annurev.ecolsys.28.1.593
Drenth A, McTaggart AR, Wingfield BD (2019) Fungal clones win the battle, but recombination wins the war. IMA Fungus 10:18. https://doi.org/10.1186/s43008-019-0020-8
Dussert Y, Legrand L, Mazet ID, Couture C, Piron M-C, Serre R-F, Bouchez O, Mestre P, Toffolatti SL, Giraud T, Delmotte F (2020) Identification of the first oomycete mating-type locus sequence in the grapevine downy mildew pathogen, Plasmopara viticola. Curr Biol 30:3897-3907.e4. https://doi.org/10.1016/j.cub.2020.07.057
Ehrendorfer F (1980) Polyploidy and distribution. In: Lewis WH (ed) Polyploidy: biological relevance. Springer, Boston, pp 45–60
Ellstrand NC, Schierenbeck KA (2000) Hybridization as a stimulus for the evolution of invasiveness in plants? Proc Natl Acad Sci 97:7043–7050. https://doi.org/10.1073/pnas.97.13.7043
Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6:e19379. https://doi.org/10.1371/journal.pone.0019379
Erwin DC, Ribeiro OK (1996) Phytophthora diseases worldwide. American Phytopathological Society (APS Press), St. Paul
Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x
Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587
Feau N, Taylor G, Dale AL, Dhillon B, Bilodeau GJ, Birol I, Jones SJM, Hamelin RC (2016) Genome sequences of six Phytophthora species threatening forest ecosystems. Genomics Data 10:85–88. https://doi.org/10.1016/j.gdata.2016.09.013
Fernández-López J, Vazquez-Ruiz-de-Ocenda RA, Díaz-Vázquez R, Pereira-Lorenzo S (2001) Evaluation of resistance of Castanea sp. clones to Phytophthora sp. using excised chestnut shoots. For Snow Landsc Res 76:451–454
Fisher MC, Henk DA, Briggs CJ, Brownstein JS, Madoff LC, McCraw SL, Gurr SJ (2012) Emerging fungal threats to animal, plant and ecosystem health. Nature 484:186–194. https://doi.org/10.1038/nature10947
Fleisch MR (2002) Vers une recrudescence de la maladie de l’encre du chataignier en foret? Les Cahiers du DSF (La Sante des Forets (France) en 2000 et 2001) Min Agri Alim Peche Aff Rur (DERF). Paris 1:63–66
Fletcher K, Gil J, Bertier LD, Kenefick A, Wood KJ, Zhang L, Reyes-Chin-Wo S, Cavanaugh K, Tsuchida C, Wong J, Michelmore R (2019) Genomic signatures of heterokaryosis in the oomycete pathogen Bremia lactucae. Nat Commun 10:2645. https://doi.org/10.1038/s41467-019-10550-0
Gauthier O, Lapointe F-J (2007) Hybrids and phylogenetics revisited: a statistical test of hybridization using quartets. Syst Bot 32:8–15. https://doi.org/10.1600/036364407780360238
Gompert Z, Mock KE (2017) Detection of individual ploidy levels with genotyping-by-sequencing (GBS) analysis. Mol Ecol Resour 17:1156–1167. https://doi.org/10.1111/1755-0998.12657
Goodwin SB (1997) The population genetics of Phytophthora. Phytopathology 87:462–473
Goss EM, Carbone I, Grünwald NJ (2009) Ancient isolation and independent evolution of the three clonal lineages of the exotic sudden oak death pathogen Phytophthora ramorum. Mol Ecol 18:1161–1174. https://doi.org/10.1111/j.1365-294X.2009.04089.x
Goss EM, Tabima JF, Cooke DEL, Restrepo S, Fry WE, Forbes GA, Fieland VJ, Cardenas M, Grunwald NJ (2014) The Irish potato famine pathogen Phytophthora infestans originated in central Mexico rather than the Andes. Proc Natl Acad Sci 111:8791–8796. https://doi.org/10.1073/pnas.1401884111
Groves CT, Ristaino JB (2000) Commercial fungicide formulations induce in vitro oospore formation and phenotypic change in mating type in Phytophthora infestans. Phytopathology 90:1201–1208. https://doi.org/10.1094/PHYTO.2000.90.11.1201
Grünwald NJ, Garbelotto M, Goss EM, Heungens K, Prospero S (2012) Emergence of the sudden oak death pathogen Phytophthora ramorum. Trends Microbiol 20:131–138. https://doi.org/10.1016/j.tim.2011.12.006
Haasis FA, Nelson RR (1963) Studies on the biological relationship of species of Phytophthora as measured by oospore formation in intra-and interspecific crosses. Plant Dis Report 47:5–7
Hansen ZR, Everts KL, Fry WE, Gevens AJ, Grünwald NJ, Gugino BK, Johnson DA, Johnson SB, Judelson HS, Knaus BJ, McGrath MT, Myers KL, Ristaino JB, Roberts PD, Secor GA, Smart CD (2016) Genetic variation within clonal lineages of Phytophthora infestans revealed through genotyping-by-sequencing, and implications for late blight epidemiology. PLoS ONE 11:e0165690. https://doi.org/10.1371/journal.pone.0165690
Herben T, Suda J, Klimešová J (2017) Polyploid species rely on vegetative reproduction more than diploids: a re-examination of the old hypothesis. Ann Bot 120:341–349. https://doi.org/10.1093/aob/mcx009
Herten K, Hestand MS, Vermeesch JR, Van Houdt JK (2015) GBSX: a toolkit for experimental design and demultiplexing genotyping by sequencing experiments. BMC Bioinform 16:73. https://doi.org/10.1186/s12859-015-0514-3
Hollister JD (2015) Polyploidy: adaptation to the genomic environment. New Phytol 205:1034–1039. https://doi.org/10.1111/nph.12939
Hüberli D, Hardy GEStJ, White D, Williams N, Burgess TI (2013) Fishing for Phytophthora from Western Australia’s waterways: a distribution and diversity survey. Austral Plant Pathol 42:251–260. https://doi.org/10.1007/s13313-012-0195-6
Huson DH, Bryant D (2006) Application of phylogenetic networks in evolutionary studies. Mol Biol Evol 23:254–267. https://doi.org/10.1093/molbev/msj030
Husson C, Aguayo J, Revellin C, Frey P, Ioos R, Marçais B (2015) Evidence for homoploid speciation in Phytophthora alni supports taxonomic reclassification in this species complex. Fungal Genet Biol 77:12–21. https://doi.org/10.1016/j.fgb.2015.02.013
Jankowiak R, Banach J, Balonek A (2013) Susceptibility of Polish provenances and families of pedunculate oak (Quercus robur L.) to colonisation by Phytophthora cambivora. For Res Pap 74:161–170. https://doi.org/10.2478/frp-2013-0016
Jayasekera AU, McComb JA, Shearer BL, Hardy GESJ (2007) In planta selfing and oospore production of Phytophthora cinnamomi in the presence of Acacia pulchella. Mycol Res 111:355–362. https://doi.org/10.1016/j.mycres.2006.11.003
Jee H-J, Cho W-D, Kim W-G (1997) Phytophthora diseases of apple in Korea: II. Occurrence of an unusual fruit rot caused by P. cactorum and P. cambivora. Korean J Plant Pathol 13:145–151
Jombart T, Ahmed I (2011) adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27:3070–3071
Jombart T, Devillard S, Balloux F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet 11:94
Jombart T, Collins C (2015) A tutorial for Discriminant Analysis of Principal Components (DAPC) using adegenet 2.0. 0
Jung T (2009) Beech decline in Central Europe driven by the interaction between Phytophthora infections and climatic extremes. For Pathol 39:73–94. https://doi.org/10.1111/j.1439-0329.2008.00566.x
Jung T, Blaschke H, Neumann P (1996) Isolation, identification and pathogenicity of Phytophthora species from declining oak stands. Eur J for Pathol 26:253–272. https://doi.org/10.1111/j.1439-0329.1996.tb00846.x
Jung T, Blaschke H, Oßwald W (2000) Involvement of soilborne Phytophthora species in Central European oak decline and the effect of site factors on the disease. Plant Pathol 49:706–718. https://doi.org/10.1046/j.1365-3059.2000.00521.x
Jung T, Hudler GW, Jensen-tracy SL, Griffiths HM, Fleischmann F, Osswald W (2005) Involvement of Phytophthora species in the decline of European beech in Europe and the USA. Mycologist 19:159–166. https://doi.org/10.1017/S0269-915X(05)00405-2
Jung T, Hudler GW, Jensen-Tracy SL, Griffiths HM, Fleischmann F, Osswald W (2006) Involvement of Phytophthora species in the decline of European beech in Europe and the USA. MYT 19:159. https://doi.org/10.1017/S0269915X05004052
Jung T, Stukely MJC, Hardy GEStJ, White D, Paap T, Dunstan WA, Burgess TI (2011) Multiple new Phytophthora species from ITS Clade 6 associated with natural ecosystems in Australia: evolutionary and ecological implications. Pers Mol Phylogeny Evol Fungi 26:13–39. https://doi.org/10.3767/003158511X557577
Jung T, Colquhoun IJ, Hardy GEStJ (2013) New insights into the survival strategy of the invasive soilborne pathogen Phytophthora cinnamomi in different natural ecosystems in Western Australia. For Pathol 43:266–288. https://doi.org/10.1111/efp.12025
Jung T, Orlikowski L, Henricot B, Abad-Campos P, Aday AG, Aguín Casal O, Bakonyi J, Cacciola SO, Cech T, Chavarriaga D, Corcobado T, Cravador A, Decourcelle T, Denton G, Diamandis S, Doğmuş-Lehtijärvi HT, Franceschini A, Ginetti B, Green S, Glavendekić M, Hantula J, Hartmann G, Herrero M, Ivic D, Horta Jung M, Lilja A, Keca N, Kramarets V, Lyubenova A, Machado H, di San M, Lio G, Mansilla Vázquez PJ, Marçais B, Matsiakh I, Milenkovic I, Moricca S, Nagy ZÁ, Nechwatal J, Olsson C, Oszako T, Pane A, Paplomatas EJ, Pintos Varela C, Prospero S, Rial Martínez C, Rigling D, Robin C, Rytkönen A, Sánchez ME, Sanz Ros AV, Scanu B, Schlenzig A, Schumacher J, Slavov S, Solla A, Sousa E, Stenlid J, Talgø V, Tomic Z, Tsopelas P, Vannini A, Vettraino AM, Wenneker M, Woodward S, Peréz-Sierra A (2016) Widespread Phytophthora infestations in European nurseries put forest, semi-natural and horticultural ecosystems at high risk of Phytophthora diseases. For Pathol 46:134–163. https://doi.org/10.1111/efp.12239
Jung T, Chang TT, Bakonyi J, Seress D, Pérez-Sierra A, Yang X, Hong C, Scanu B, Fu CH, Hsueh KL, Maia C, Abad-Campos P, Léon M, Horta Jung M (2017a) Diversity of Phytophthora species in natural ecosystems of Taiwan and association with disease symptoms. Plant Pathol 66:194–211. https://doi.org/10.1111/ppa.12564
Jung T, Horta Jung M, Scanu B, Seress D, Kovács GM, Maia C, Pérez-Sierra A, Chang T-T, Chandelier A, Heungens K, Van Poucke K, Abad-Campos P, Léon M, Cacciola SO, Bakonyi J (2017b) Six new Phytophthora species from ITS Clade 7a including two sexually functional heterothallic hybrid species detected in natural ecosystems in Taiwan. Pers Mol Phylogeny Evol Fungi 38:100–135. https://doi.org/10.3767/003158517X693615
Jung T, Durán A, Sanfuentes von Stowasser E, Schena L, Mosca S, Fajardo S, González M, Navarro Ortega AD, Bakonyi J, Seress D, Tomšovský M, Cravador A, Maia C, Horta Jung M (2018a) Diversity of Phytophthora species in Valdivian rainforests and association with severe dieback symptoms. For Pathol 48:e12443. https://doi.org/10.1111/efp.12443
Jung T, Pérez-Sierra A, Durán A, Horta Jung M, Balci Y, Scanu B (2018b) Canker and decline diseases caused by soil- and airborne Phytophthora species in forests and woodlands. Pers Mol Phylogeny Evol Fungi 40:182–220. https://doi.org/10.3767/persoonia.2018.40.08
Jung T, Scanu B, Brasier C, Webber J, Milenković I, Corcobado T, Tomšovský M, Pánek M, Bakonyi J, Maia C, Bačová A, Raco M, Rees H, Pérez-Sierra A, Horta Jung M (2020) A survey in natural forest ecosystems of vietnam reveals high diversity of both new and described Phytophthora taxa including P. ramorum. Forests 11:93. https://doi.org/10.3390/f11010093
Jung T, Horta Jung M, Webber JF, Kageyama K, Hieno A, Masuya H, Uematsu S, Pérez-Sierra A, Harris AR, Forster J, Rees H, Scanu B, Patra S, Kudláček T, Janoušek J, Corcobado T, Milenković I, Nagy Z, Csorba I, Bakonyi J, Brasier C (2021) The destructive tree pathogen Phytophthora ramorum originates from the laurosilva forests of East Asia. J Fungi 7:226. https://doi.org/10.3390/jof7030226
Kamvar ZN, Tabima JF, Grünwald NJ (2014) Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2:e281. https://doi.org/10.7717/peerj.281
Kamvar ZN, Brooks JC, Grünwald NJ (2015) Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Front Genet. https://doi.org/10.3389/fgene.2015.00208
Knaus BJ, Grünwald NJ (2017) vcfr: a package to manipulate and visualize variant call format data in R. Mol Ecol Resour 17:44–53. https://doi.org/10.1111/1755-0998.12549
Knaus BJ, Grünwald NJ (2018) Inferring variation in copy number using high throughput sequencing data in R. Front Genet. https://doi.org/10.3389/fgene.2018.00123
Knaus BJ, Tabima JF, Shakya SK, Judelson HS, Grünwald NJ (2020) Genome-wide increased copy number is associated with emergence of dominant clones of the Irish potato famine pathogen Phytophthora infestans. Mbio. https://doi.org/10.1128/mBio.00326-20
Ko WH (1981) Reversible change of mating type in Phytophthora parasitica. Microbiology 125:451–454. https://doi.org/10.1099/00221287-125-2-451
Kong S, Kubatko LS (2020) Comparative performance of popular methods for hybrid detection using genomic data. Bioinformatics
Kopelman NM, Mayzel J, Jakobsson M, Rosenberg NA, Mayrose I (2015) Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour 15:1179–1191. https://doi.org/10.1111/1755-0998.12387
Lamour KH, Stam R, Jupe J, Huitema E (2012) The oomycete broad-host-range pathogen Phytophthora capsici. Mol Plant Pathol 13:329–337. https://doi.org/10.1111/j.1364-3703.2011.00754.x
Landolt J, Gross A, Holdenrieder O, Pautasso M (2016) Ash dieback due to Hymenoscyphus fraxineus: what can be learnt from evolutionary ecology? Plant Pathol 65:1056–1070. https://doi.org/10.1111/ppa.12539
Li H (2013) Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997 [q-bio]
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079. https://doi.org/10.1093/bioinformatics/btp352
Long M, Keen NT (1977) Evidence for heterokaryosis in Phytophthora megasperma var. sojae. Phytopathology 670–674
Malomane DK, Reimer C, Weigend S, Weigend A, Sharifi AR, Simianer H (2018) Efficiency of different strategies to mitigate ascertainment bias when using SNP panels in diversity studies. BMC Genomics 19:22. https://doi.org/10.1186/s12864-017-4416-9
Martens C, Van de Peer Y (2010) The hidden duplication past of the plant pathogen Phytophthora and its consequences for infection. BMC Genomics 11:353. https://doi.org/10.1186/1471-2164-11-353
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. Embnet J 17:10–12. https://doi.org/10.14806/ej.17.1.200
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010) The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303. https://doi.org/10.1101/gr.107524.110
Milgroom MG (1996) Recombination and the multilocus structure of fungal populations. Annu Rev Phytopathol 34:457–477
Milgroom MG, Brasier CM (1997) Potential diversity of vegetative compatibility types of Ophiostoma novo-ulmi in North America. Mycologia 89:722–726
Mircetich SM, Matheron ME (1976) Phytophthora root and crown rot of cherry trees. Phytopathology 66:549. https://doi.org/10.1094/Phyto-66-549
Mukerjee N, Roy BA (1962) Microbial influence on the formation of oospores in culture of Phytophthora parasitica var. sabdariffae. Phytopathology 52:583–584
Nagel JH, Gryzenhout M, Slippers B, Wingfield MJ, Hardy GEStJ, Stukely MJC, Burgess TI (2013) Characterization of Phytophthora hybrids from ITS clade 6 associated with riparian ecosystems in South Africa and Australia. Fungal Biol 117:329–347. https://doi.org/10.1016/j.funbio.2013.03.004
Nechwatal J, Hahn J, Schönborn A, Schmitz G (2011) A twig blight of understorey European beech (Fagus sylvatica) caused by soilborne Phytophthora spp. For Pathol 41:493–500. https://doi.org/10.1111/j.1439-0329.2011.00711.x
Oh E, Gryzenhout M, Wingfield BD, Wingfield MJ, Burgess TI (2013) Surveys of soil and water reveal a goldmine of Phytophthora diversity in South African natural ecosystems. IMA Fungus 4:123–131. https://doi.org/10.5598/imafungus.2013.04.01.12
Olave M, Meyer A (2020) Implementing large genomic single nucleotide polymorphism data sets in phylogenetic network reconstructions: a case study of particularly rapid radiations of cichlid fish. Syst Biol 69:848–862. https://doi.org/10.1093/sysbio/syaa005
Otto SP, Whitton J (2000) Polyploid incidence and evolution. Annu Rev Genet 34:401–437. https://doi.org/10.1146/annurev.genet.34.1.401
Oudemans P, Coffey MD (1991) Isozyme comparison within and among worldwide sources of three morphologically distinct species of Phytophthora. Mycol Res 95:19–30
Pandit MK, Tan HTW, Bisht MS (2006) Polyploidy in invasive plant species of Singapore. Bot J Linn Soc 151:395–403. https://doi.org/10.1111/j.1095-8339.2006.00515.x
Paradis E, Schliep K (2019) ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35:526–528. https://doi.org/10.1093/bioinformatics/bty633
Patterson N, Moorjani P, Luo Y, Mallick S, Rohland N, Zhan Y, Genschoreck T, Webster T, Reich D (2012) Ancient admixture in human history. Genetics 192:1065–1093. https://doi.org/10.1534/genetics.112.145037
Peace TR (1962) Pathology of trees and shrubs: with special reference to Britain. Clarendon Press, Oxford
Pereira JG, Valdiviesso T, de Abreu CP, de Sousa AJT (1995) Chestnut ink disease. Appraisal of the sensitivity of chestnut clones to ink disease. Phytoma 477:50–52
Petri L (1917) Ricerche sulla morfologia e biologia della Blepharospora cambivora, parassita del castagno. Atti Reale Accad Dei Lincei Rend Delle Classi Di Sci Fisiche Mat Nat 5:297–299
Poland JA, Brown PJ, Sorrells ME, Jannink J-L (2012) Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS ONE 7:e32253. https://doi.org/10.1371/journal.pone.0032253
Posada D, Crandall KA (2001) Intraspecific gene genealogies: trees grafting into networks. Trends Ecol Evol 16:37–45. https://doi.org/10.1016/S0169-5347(00)02026-7
Posada D, Crandall KA (2002) The effect of recombination on the accuracy of phylogeny estimation. J Mol Evol 54:396–402. https://doi.org/10.1007/s00239-001-0034-9
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959
Privé F, Luu K, Blum MGB, McGrath JJ, Vilhjálmsson BJ (2020) Efficient toolkit implementing best practices for principal component analysis of population genetic data. Bioinformatics 36:4449–4457. https://doi.org/10.1093/bioinformatics/btaa520
R Development Core Team (2020) R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria
Rambaut A (2018) FigTree. In: Figtree, a graphical viewer of phylogenetic trees. http://tree.bio.ed.ac.uk/software/figtree/. Accessed 2 Mar 2021
Ramsey J (2011) Polyploidy and ecological adaptation in wild yarrow. PNAS 108:7096–7101. https://doi.org/10.1073/pnas.1016631108
Rigling D, Prospero S (2018) Cryphonectria parasitica, the causal agent of chestnut blight: invasion history, population biology and disease control. Mol Plant Pathol 19:7–20. https://doi.org/10.1111/mpp.12542
Robin C, Morel O, Vettraino A-M, Perlerou C, Diamandis S, Vannini A (2006) Genetic variation in susceptibility to Phytophthora cambivora in European chestnut (Castanea sativa). For Ecol Manag 226:199–207. https://doi.org/10.1016/j.foreco.2006.01.035
Rosenberg NA (2004) DISTRUCT: a program for the graphical display of population structure. Mol Ecol Notes 4:137–138. https://doi.org/10.1046/j.1471-8286.2003.00566.x
Saavedra A, Hansen EM, Goheen DJ (2007) Phytophthora cambivora in Oregon and its pathogenicity to Chrysolepis chrysophylla. For Pathol 37:409–419. https://doi.org/10.1111/j.1439-0329.2007.00515.x
Salesses G, Ronco L, Chauvin J-E, Chapa J (1993) Amelioration genetique du chataignier. Mise au point de tests d’evaluation du comportement vis-a-vis de la maladie de l’encre. Arboricult Fruit 23
Sansome ER (1980) Reciprocal translocation heterozygosity in heterothallic species of Phytophthora and its significance. Trans Br Mycol Soc 74:175–185
Santini A, Ghelardini L, De Pace C, Desprez-Loustau ML, Capretti P, Chandelier A, Cech T, Chira D, Diamandis S, Gaitniekis T, Hantula J, Holdenrieder O, Jankovsky L, Jung T, Jurc D, Kirisits T, Kunca A, Lygis V, Malecka M, Marcais B, Schmitz S, Schumacher J, Solheim H, Solla A, Szabò I, Tsopelas P, Vannini A, Vettraino AM, Webber J, Woodward S, Stenlid J (2013) Biogeographical patterns and determinants of invasion by forest pathogens in Europe. New Phytol 197:238–250. https://doi.org/10.1111/j.1469-8137.2012.04364.x
Schierenbeck KA, Ellstrand NC (2008) Hybridization and the evolution of invasiveness in plants and other organisms. Biol Invasions 11:1093. https://doi.org/10.1007/s10530-008-9388-x
Schinkel CCF, Kirchheimer B, Dellinger AS, Klatt S, Winkler M, Dullinger S, Hörandl E (2016) Correlations of polyploidy and apomixis with elevation and associated environmental gradients in an alpine plant. AoB PLANTS. https://doi.org/10.1093/aobpla/plw064
Schmieder R, Edwards R (2011) Quality control and preprocessing of metagenomic datasets. Bioinformatics 27:863–864. https://doi.org/10.1093/bioinformatics/btr026
Seidl R, Klonner G, Rammer W, Essl F, Moreno A, Neumann M, Dullinger S (2018) Invasive alien pests threaten the carbon stored in Europe’s forests. Nat Commun 9:1626. https://doi.org/10.1038/s41467-018-04096-w
Selmecki AM, Maruvka YE, Richmond PA, Guillet M, Shoresh N, Sorenson AL, De S, Kishony R, Michor F, Dowell R, Pellman D (2015) Polyploidy can drive rapid adaptation in yeast. Nature 519:349–352. https://doi.org/10.1038/nature14187
Shakya SK, Grünwald NJ, Fieland VJ, Knaus BJ, Weiland JE, Maia C, Drenth A, Guest DI, Liew ECY, Crane C, Chang T-T, Fu C-H, Minh Chi N, Quang Thu P, Scanu B, von Stowasser ES, Durán Á, Horta Jung M, Jung T (2021) Phylogeography of the wide-host range panglobal plant pathogen Phytophthora cinnamomi. Mol Ecol 30:5164–5178. https://doi.org/10.1111/mec.16109
Solís-Lemus C, Ané C (2016) Inferring phylogenetic networks with maximum pseudolikelihood under incomplete lineage sorting. PLoS Genet 12:e1005896. https://doi.org/10.1371/journal.pgen.1005896
Solís-Lemus C, Bastide P, Ané C (2017) Phylonetworks: a package for phylogenetic networks. Mol Biol Evol 34:3292–3298. https://doi.org/10.1093/molbev/msx235
Soltis PS, Soltis DE (2000) The role of genetic and genomic attributes in the success of polyploids. PNAS 97:7051–7057. https://doi.org/10.1073/pnas.97.13.7051
Soltis PS, Soltis DE (2009) The role of hybridization in plant speciation. Annu Rev Plant Biol 60:561–588. https://doi.org/10.1146/annurev.arplant.043008.092039
Soltis DE, Buggs RJA, Doyle JJ, Soltis PS (2010) What we still don’t know about polyploidy. Taxon 59:1387–1403. https://doi.org/10.1002/tax.595006
Stamatakis A (2014) RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30:1312–1313. https://doi.org/10.1093/bioinformatics/btu033
Suzui T, Hoshino Y (1979) Collar rot of apple caused by Phytophthora cambivora (Petri) Buism. Jpn J Phytopathol 45:344–352. https://doi.org/10.3186/jjphytopath.45.344
Swofford DL (2021) PAUP* (*Phylogenetic Analysis Using PAUP), Version 4a168, 2021. http://phylosolutions.com/paup-test/
Tabima JF, Coffey MD, Zazada IA, Grünwald NJ (2018) Populations of Phytophthora rubi show little differentiation and high rates of migration among states in the western United States. MPMI 31:614–622. https://doi.org/10.1094/MPMI-10-17-0258-R
Telfer KH, Brurberg MB, Herrero M-L, Stensvand A, Talgø V (2015) Phytophthora cambivora found on beech in Norway. For Path 45:415–425. https://doi.org/10.1111/efp.12215
Tomura T, Molli SD, Murata R, Ojika M (2017) Universality of the Phytophthora mating hormones and diversity of their production profile. Sci Rep 7:5007. https://doi.org/10.1038/s41598-017-05380-3
Van Poucke K, Franceschini S, Webber JF, Vercauteren A, Turner JA, McCracken AR, Heungens K, Brasier C (2012) Discovery of a fourth evolutionary lineage of Phytophthora ramorum: EU2. Fungal Biol 116:1178–1191. https://doi.org/10.1016/j.funbio.2012.09.003
Van Poucke K, Haegeman A, Goedefroit T, Focquet F, Leus L, Horta Jung M, Nave C, Redondo MA, Husson C, Kostov K, Lyubenova A, Christova P, Chandelier A, Slavov S, de Cock A, Bonants P, Werres S, Palau JO, Marçais B, Jung T, Stenlid J, Ruttink T, Heungens K (2021) Unravelling hybridization in Phytophthora using phylogenomics and genome size estimation. IMA Fungus 12:16. https://doi.org/10.1186/s43008-021-00068-w
Vannini A, Vettraino AM (2001) Ink disease in chestnuts: impact on the European chestnut. For Snow Landsc Res 76:345–350
Vettraino AM, Natili G, Anselmi N, Vannini A (2001) Recovery and pathogenicity of Phytophthora species associated with a resurgence of ink disease in Castanea sativa in Italy: Ink disease in sweet chestnut in Italy. Plant Pathol 50:90–96. https://doi.org/10.1046/j.1365-3059.2001.00528.x
Vettraino AM, Morel O, Perlerou C, Robin C, Diamandis S, Vannini A (2005) Occurrence and distribution of Phytophthora species in European chestnut stands, and their association with Ink Disease and crown decline. Eur J Plant Pathol 111:169–180. https://doi.org/10.1007/s10658-004-1882-0
Wendel JF, Lisch D, Hu G, Mason AS (2018) The long and short of doubling down: polyploidy, epigenetics, and the temporal dynamics of genome fractionation. Curr Opin Genet Dev 49:1–7. https://doi.org/10.1016/j.gde.2018.01.004
Wicks TJ, Lee TC, Scott ES (1997) Phytophthora crown rot of almonds in Australia 1. EPPO Bull 27:501–506. https://doi.org/10.1111/j.1365-2338.1997.tb00673.x
Wilcox WF, Mircetich SM (1985) Pathogenicity and relative virulence of seven Phytophthora spp. on Mahaleb and Mazzard cherry. Phytopathology 75:221–226
Wingfield MJ, Brockerhoff EG, Wingfield BD, Slippers B (2015) Planted forest health: the need for a global strategy. Science 349:832–836. https://doi.org/10.1126/science.aac6674
Zhang J, Kobert K, Flouri T, Stamatakis A (2014) PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30:614–620. https://doi.org/10.1093/bioinformatics/btt593
Computational resources were supplied by the project “e-Infrastruktura CZ” (e-INFRA LM2018140) provided within the program Projects of Large Research, Development and Innovations Infrastructures. The authors thank Cristiana Maia (CCMAR, Faro, Portugal) for support in collecting samples in Portugal. The authors also acknowledge Tomáš Kudláček, Milica Raco, Ivan Milenković, Zoltan Nagy, Josef Janoušek, Aneta Bačová, and Henrieta Ďatková (all Mendel University in Brno, Czech Republic) for much appreciated technical support.
Adherence to national and international regulations
The importation and use of isolates adhered to the regulations related to National Plant Health and Quarantine, and the Nagoya Protocol to the Convention on Biological Diversity.
This research was funded by the European Regional Development Fund, Project Phytophthora Research Centre Reg. No. CZ.02.1.01/0.0/0.0/15_003/0000453. The Portuguese Science and Technology Foundation (FCT) co-funded the European BiodivERsA project "RESIPATH: Responses of European Forests and Society to Invasive Pathogens" (BIODIVERSA/0002/2012) during which the Phytophthora survey in Portugal was performed. Travel and subsistence for C.M.B. in Japan ws funded by Brasier Consultancy.
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
. Details of P. × cambivora-related isolates used in this study including population group, geographic location, mating type, isolate codes used in other culture collections, and STRUCTURE membership probabilities for each K = 5 cluster.
. Delta K plot of the STRUCTURE analysis, showing K = 2 as the best clustering of isolates.
. Bayesian clustering of P. × cambivora-related isolates inferred using the programme STRUCTURE at K = 2, K = 3, K = 4, and K = 5. Each isolate is represented by a vertical line partitioned into coloured sections that represent the isolate’s estimated membership fractions in each cluster. Black lines separate isolates from different DAPC groups (see main text for details).
. Principal components analysis of P. × cambivora isolates. Only the first two principal components are shown, which explain 26.1% and 12.5% of the variance, respectively. Ellipse colours represent DAPC groups; the mating type of each group is given in parentheses. The barplot inset shows the percentage of variance explained by each principal component.
. Principal components analysis of P. × cambivora-related isolates displayed using the second and fourth principal components which more easily differentiates groups DAPC2, DAPC4mixed ≤ 0.66, DAPC4 ≥ 0.76, and DAPC6. Ellipse colours represent DAPC groups.
. Scatterplot of the discriminant analysis of principal components (DAPC) of P. × cambivora-related isolates. Individual isolates are represented by dots that are coloured by their DAPC group. At the bottom right, the PCA eigenvalues are represented, with the number of principal components used in the optimized analysis in black. At the top right, the Discriminant Analysis (DA) eigenvalues are displayed.
. Maximum likelihood tree of P. × cambivora-related isolates inferred using RAxML and 1,000 bootstraps. The tree was rooted using P. × alni as an outgroup (not shown). Coloured vertical bars represent the DAPC group colour used in other figures.
. Pseudolikelihood profile with increasing number of hybridization events (hmax) allowed, obtained with the Species Networks applying Quartets (SNaQ) pipeline.
. Table of results of the population-level hybridization detection analyses conducted in HyDe. Only significant results are shown, with their p-value, Z-score and Gamma value.
. Distribution (histogram) of allele balance values for all Phytophthora × cambivora isolates by DAPC groups. The frequency of the most abundant heterozygous allele is displayed in light blue, the frequency of the second most abundant heterozygous allele is displayed in dark blue. Expectations of the allele balance are displayed on the x-axis.
About this article
Cite this article
Mullett, M.S., Van Poucke, K., Haegeman, A. et al. Phylogeography and population structure of the global, wide host-range hybrid pathogen Phytophthora × cambivora. IMA Fungus 14, 4 (2023). https://doi.org/10.1186/s43008-023-00109-6
- Invasive pathogen
- Population genetics