Horizontal chromosome transfer and independent evolution drive diversification in Fusarium oxysporum f. sp. fragariae

1 Horizontal chromosome transfer and independent evolution drive diversification in Fusarium oxysporum f. sp. fragariae. Peter M. Henry*1, Dominique D.A. Pincot2, Bradley Jenner3, Celia Borrero4, Manuel Aviles4, Myeong-Hyeon Nam5, Lynn Epstein3, Steven J. Knapp2, Thomas R. Gordon3 1 United States Department of Agriculture, Agricultural Research Service, 1636 E. Alisal St. Salinas, California 93905 2 Department of Plant Sciences, University of California, One Shields Avenue, Davis, California 95616 3 Department of Plant Pathology, University of California, One Shields Avenue, Davis, California 95616 4 Dept. Ciencias Agroforestales, Escuela Técnica Superior de Ingeniería Agronómica, Universidad de Sevilla, Ctra. Utrera km 1, 41013 Sevilla, Spain 5 Strawberry Research Institute, Chungcheongnam-do Agricultural Research & Extension Services, Nonsan 32914, Korea * Peter Henry is the corresponding author. Email: [email protected] Word counts: • Main text (Introduction, Materials and Methods, Results, Discussion) = 6,444 • Introduction = 777 856 • Materials and Methods = 2,410 2430 • Results = 1,997 1,999 • Discussion = 1,260 1259 Figures: There are five figures in the main text, and all have color. There are no tables in the main text. 2 Summary (200 out of 200 words) • The genes required for host-specific pathogenicity in Fusarium oxysporum can be acquired through horizontal chromosome transfer (HCT). However, it is unknown if HCT commonly contributes to the diversification of pathotypes. • Using comparative genomics and pathogenicity phenotyping, we explored the role of HCT in the evolution of F. oxysporum f. sp. fragariae, the cause of Fusarium wilt of strawberry, with isolates from four continents. • We observed two distinct syndromes: one included chlorosis (“yellows-fragariae”) and the other did not (“wilt-fragariae”). All yellows-fragariae isolates carried a predicted pathogenicity chromosome, “chrY-frag”, that was horizontally transferred at least four times. ChrY-frag was associated with virulence on specific cultivars and encoded predicted effectors that were highly up-regulated during infection. ChrY-frag was not present in wilt-fragariae; isolates causing this syndrome evolved pathogenicity independently. All origins of F. oxysporum f. sp. fragariae occurred outside of the host’s native range. • Our data support the conclusion that HCT is widespread in F. oxysporum, but pathogenicity can also evolve independently. The absence of chrY-frag in wiltfragariae suggests that multiple, distinct pathogenicity chromosomes can confer the same host specificity. The wild progenitors of cultivated strawberry (Fragaria × ananassa) did not co-evolve with this pathogen, yet we discovered several sources of genetic resistance. Keywords Fragaria × ananassa, strawberry, horizontal chromosome transfer, convergent evolution 3 Introduction Fusarium oxysporum is a species complex containing many host-specific pathogenic forms (called formae speciales). Pathogenic strains of F. oxysporum cause devastating crop losses worldwide, but most formae speciales have poorly characterized evolutionary origins. This includes F. oxysporum f. sp. fragariae (Fof), which causes Fusarium wilt of strawberry (strawberry = Fragaria × ananassa Duchesne ex Rozier). This pathogen was first reported in eastern Australia in 1962 and soon thereafter in Japan (1969) and South Korea (1974) (Winks & Williams, 1965; Okamoto et al., 1970; Kim et al., 1982). New reports of this disease surged globally during the early 2000s, including in major fruit production regions in California (2006) and Spain (2014) (Borrero et al., 2017; Henry et al., 2017). The evolutionary processes leading to Fof’s emergence remain uncharacterized, and it is unknown if the expanding geographic range of this pathogen resulted from dispersal or independent evolution of pathogenicity. Although the exchange of DNA through meiotic recombination has never been documented for F. oxysporum (Taylor et al., 2015), genetic exchange can occur via horizontal chromosome transfer (HCT), a process involving the transfer of “accessory” chromosomes (Ma et al., 2010). F. oxysporum chromosomes can be categorized into two types: 1) eleven conserved chromosomes that are present in all strains, and 2) a variable number of “accessory”, or “lineage specific”, chromosomes that can be acquired via HCT (Ma et al., 2010, Zhang et al. 2020). For HCT to occur, two germinating spores fuse, a haploid nucleus from each of the two strains fuse, and one strain’s core chromosomes are systematically lost (Shahi et al. 2016). In plant pathogenic strains of F. oxysporum, accessory chromosomes that are acquired via HCT may have the genes required for host-specific pathogenicity (i.e. a pathogenicity chromosome). However, while the process of HCT is understood, there are few documented examples of HCT in nature, and it is unknown how frequently HCT has contributed to the diversity of strains that cause disease on a particular host. Many formae speciales, including Fof (Nagarajan et al., 2006; Paynter et al., 2016; Henry et al., 2017), are polyphyletic, and HCT provides an attractive explanation for this diversity. Where HCT occurred, virulence would be determined by the same genes; i.e., 4 those residing on a shared pathogenicity chromosome (Ma et al., 2010; van Dam et al., 2017; Li et al., 2020). However, given the vast genetic diversity observed in F. oxysporum (O’Donnell et al., 2009), it is plausible that the same host-specificity could be conferred by different repertoires of genes on non-homologous pathogenicity chromosomes. These pathogenicity-determinants could have accrued through independent processes of mutation (such as transposon activity, DNA copy error, etc.) and/or the acquisition of novel alleles through HCT. If true, polyphyly in a forma specialis could result from independently evolved genetic determinants of pathogenicity, not HCT alone. Isolates with different genetic determinants of host specificity could also cause distinct disease phenotypes. Such phenotypic distinctions have been observed; for example, F. oxysporum f. sp. melonis was differentiated into isolates that cause chlorosis (“yellows”) or that only cause wilting (“wilts”) (Jacobson & Gordon, 1988). It is not yet known if the “yellows” and “wilt” phenotypes of F. oxysporum f. sp. melonis resulted from independently evolved pathogenicity chromosomes. If so, the mechanisms responsible for inducing disease may differ, and genetic resistance may not function against both mechanisms. Deployment of genetically resistant cultivars has been the most effective strategy for management of Fusarium wilt in many crops. All characterized host resistance (R) genes for F. oxysporum wilt pathogens function by recognizing pathogen “avirulence” proteins and subsequently initiating defense responses (Ori et al., 1997; Joobeur et al., 2004; Diener & Ausubel, 2005; Lv et al., 2014; Catanzariti et al., 2016). Mutations in pathogen avirulence genes can render the resulting protein imperceptible by the cognate host resistance protein. When these mutations occur, the pathogen is once again able to cause disease. This “gene-for-gene” interaction is used to categorize pathogens into different “races” based on the reaction of cultivars with different susceptibility phenotypes. Of the few, well-documented avirulence genes in F. oxysporum, all are carried on pathogenicity chromosomes (Ma et al., 2010; Catanzariti et al., 2016; Schmidt et al., 2016). Therefore, the efficacy of resistance genes may not extend to strains that do not share the same pathogenicity chromosome. 5 The objective of the present study was to characterize the evolutionary processes responsible for the emergence and diversification of the pathogen causing Fusarium wilt of strawberry. It has been unknown if the expanding geographic range of this pathogen resulted from dispersal of a clonal strain, whether horizontal transfer of a pathogenicity chromosome occurred, and/or if pathogenicity evolved independently on multiple continents. To identify the processes that resulted in the emergence of Fof we: 1) sampled isolates at a global scale, including historic isolates from the sites of first reports and more recent outbreaks, 2) investigated the evolutionary relationships between representative isolates from each country with comparative genomics/transcriptomics, and 3) assessed the co-evolutionary framework of host and pathogen with comprehensive host resistance phenotyping. Here, we show that understanding the processes underlying pathogen diversification is important for the early identification of novel races and the development and deployment of genetic resistance to Fusarium wilt. Materials and Methods Isolate collection and initial characterization. Corresponding authors from 15 publications reporting Fof in seven countries were contacted for the isolates used in their studies. Isolates were additionally obtained from the Queensland Herbarium culture collection (Australia) and the National Agricultural and Food Research Organization Genebank (Japan). Isolate diversity was maximized by selecting representatives of the broadest variation in date of collection, region of origin, and genetically distinct groups (Additional File S1). To reduce redundancy in subsequent experiments, we identified clonally related isolates by multi-locus genotyping and a phenotypic test of clonality based on somatic compatibility. Isolates were determined to be compatible if complementary nitrate nonutilizing mutants formed wild-type growth when co-cultured on a medium lacking reduced nitrogen (Correll et al., 1987). Wild-type growth indicates that intra-isolate hyphal fusion occurred, allowing for complementation and effective utilization of nitrate (Correll et al., 1987). We sequenced the translation elongation factor 1- α (EF-1 α ) and intergenic spacer (IGS) loci of all isolates as previously described by Henry et al. 6 (2017). Isolates with the same two-locus haplotype that were somatically compatible were considered clonally related. Pathogenicity assays with cultivars ‘Sweet Ann’ and ‘Ventana’. To confirm the reported characterization as forma specialis fragariae, we tested pathogenicity on strawberry for 31 putative Fof isolates that represented the observed spatiotemporal and genotypic diversity of clonal groups from each country. We additionally tested the pathogenicity of 7 putative non-pathogenic F. oxysporum isolates from strawberry fields. Pathogenicity tests were conducted with cultivars that are known to be susceptible (‘Sweet Ann’) and resistant (‘Ventana’) to Californian strains of Fof (Pincot et al., 2018). For each isolate, two fully colonized 100 cm potato dextrose agar (PDA) plates were blended with sterile, de-ionized water and mixed into #1 Sunshine mix (Sun Gro Horticulture, USA) in a 10 x 10 x 20 cm pot (L x W x H). A single plant that had broken dormancy was then planted in each pot (n = 4 per cultivar). Non-inoculated PDA plates were used for a negative control. This experiment was conducted twice. Plants were maintained in a growth chamber with a 12-hour photoperiod and 28°C high / 20°C low temperature settings for eight weeks. Disease severity was assessed at 4, 5, 6, 7, and 8 weeks post-inoculation (wpi) using a 1 to 5 ordinal rating system (Fig. S1). For isolates that did not cause chlorosis, ratings were based on the following symptoms: 1 = no symptoms, 2 = 0-25% of leaves wilted, 3 = 25-50% of leaves wilted, 4 = more than 50% of leaves wilted, and 5 = dead (all leaves wilted/brown). For isolates that caused chlorosis, the rating scale was: 1 = no symptoms, 2 = mild stunting, marginal chlorosis, 3 = youngest leaves fully chlorotic, 4 = outer leaves chlorotic, some wilting observed, and 5 = dead (all leaves were brown). At 8 wpi, or the time of plant mortality, four 2.5 cm sections from the base of petioles of each plant were surface sterilized with 1% sodium hypochlorite for two minutes and plated on Komada’s medium to confirm the recovery of the pathogen (Henry et al., 2017). Differences in symptom severity at 8 wpi on ‘Sweet Ann’ were compared between chlorosis-causing (yellows-fragariae), wilt-only causing (wilt-fragariae) isolates. The proportion of ‘Sweet Ann’ plants that were dead at 8 wpi was calculated for each isolate with data pooled across both experiments (n = 8). Plant mortality proportions were 7 arcsin square root transformed to achieve a normal distribution (package: ‘stats’, function: ‘qqnorm’), and Welch’s t-test was used to test the hypothesis that yellowsfragariae and wilt-fragariae isolate groups differed in mean mortality proportions at 8 wpi (package: ‘stats’, function: ‘t.test’) (R Core Team, 2013). Whole genome sequencing and assembly. To investigate the evolutionary relationships between Fof isolates, we generated whole genome assemblies for representatives of all clonal groups of this pathogen present in each country (35 total), 12 non-pathogenic isolates from strawberry plants or field soil, and one isolate of F. oxysporum f. sp. mori (the cause of Fusarium wilt of blackberry; Additional File S2; Table S1). DNA was extracted from lyophilized mycelia or conidia using a phenol-chloroform extraction protocol (Kaur et al., 2017). Libraries were prepared and sequenced on an Illumina NextSeq or HiSeq (150 bp, paired-end) at the University of California, Davis DNA Technologies Core Facility or at the Michigan State University Genomics Core Facility. SMRTBell libraries were additionally prepared for GL1080 and GL1381, size selected to fragments greater than 15 kbp, and sequenced on a Pacific Biosciences (PacBio) RSII at the DNA Technologies Core Facility (Davis, CA). The ProxiMeta high throughput chromatin conformation capture (Hi-C) library preparation kit (Phase Genomics; Seattle, WA) was used to prepare libraries from GL1381 and GL1080 germlings. Hi-C libraries were sequenced on an Illumina NovaSeq with 150 bp paired-end reads. Genomes were assembled for 48 isolates from 150 bp paired-end Illumina reads with the de novo A5 assembler (Tritt et al., 2012). Chromosome-level assemblies were additionally generated for isolates GL1080 and GL1381. First, PacBio reads were assembled by the HGAP3 pipeline in smrtanalysis (version 2.3.0) with default parameters (Chin et al., 2013) and error corrected with Pilon (version 1.23) from Bowtie2-mapped Illumina reads (version 2.3.4.1; Langmead & Salzberg, 2012; Walker et al., 2014). These assemblies were then scaffolded with Hi-C library reads (113 and 49 million reads for GL1080 and GL1381) using the ‘Proximo’ proprietary software from Phase Genomics, Inc (Seattle, WA). Scaffolded assemblies were gap-filled by PBJelly (version 15.8.24) with proovread error-corrected PacBio reads (version 2.14.0; English et al., 2012; Hackl et al., 2014). 8 Core genome phylogenetic analysis. We analyzed the core genome phylogenetic relationships between the 48 new assemblies and 91 previously published F. oxysporum genome assemblies (n = 139 total). BUSCO (version 2.0) was run for every genome, and 2,718 orthologues were identified as single copy in every genome (Simao et al., 2015). Each of the 2,718 genes were aligned with MUSCLE (version 3.8), and the alignments were concatenated (Edgar, 2004; Simao et al., 2015). The maximum likelihood phylogeny of the concatenated alignment was determined by RAxML (version 8.2.12) using the general time reversible model with gamma correction and 1,000 bootstrap replicates (Stamatakis, 2014). Phylograms were visualized by ggtree (version 1.14.6; Yu et al., 2017). Gene and transposon annotation. The in vitro and in planta transcriptome of F. oxysporum f. sp. lycopersici 4287 was previously sequenced (GenBank accession: GCA_000149955.2; van Dam et al., 2016). We used HISAT2 (version 2.1.0) to align these reads to the reference genome (GenBank accession: GCA_000149955.2) with a maximum intron length of 6 kbp (Kim et al., 2019). Cufflinks (version 2.2.1) was used to assemble and merge transcripts (Trapnell et al., 2010). Assembled transcripts were used as evidence by CodingQuarry (version 2.0) to generate the gene models used during annotation (Testa et al., 2015). Using these pre-trained gene models, we annotated all other genomes included in this analysis with CodingQuarry (n = 139 genomes, in ‘default’ and ‘pathogen mode’). Secreted proteins were predicted by SignalP4.1 (run mode = ‘best’) and EffectorP versions 1.0 and 2.0 were used for effector prediction (Nielsen, 2017; Sperschneider et al., 2018). Repeatmodeler (v1.0.11) and Repeatmasker (v.4.0.8) were used to annotate transposable elements (Tarailo-Graovac & Chen, 2009). Miniature impala transposons were identified by TIRmite (version 1.1.3) run four separate times with TIR alignments that collectively represent the breadth of miniature impala diversity (TIRmite: https://github.com/Adamtaranto/TIRmite; ‘mimp_finder.py’ from Repertoire v6: https://github.com/SamuelBrinker/Repertoire_v6). Read mapping and coverage analysis. We identified conserved sequences in Fof by mapping reads to the GL1080 and GL1381 chromosome-level genomes. Raw reads 9 were filtered with HTStream to remove predicted PCR duplicates (hts_SuperDeduper), remove Phi-X sequences (hts_SeqScreener), trim adapters (hts_AdapterTrimmer), trim ends to an average quality value of ‘20’ (hts_QWindowTrim), and remove N’s from the ends of reads (hts_NTrimmer). To ensure consistent read depth when mapping, 5.5 Gbp of quality-filtered reads were extracted for each isolate (approximately 100x coverage; reformat.sh from BBTools). These reads were aligned with BWA-MEM (version 0.7.17-r1188; Li & Durbin, 2009). Bedtools (version 2.29.0) function ‘genomecov’ calculated the coverage of reads at each position in the genome, and regions with coverage greater than 9 were considered ‘present’ (Quinlan & Hall, 2010). To identify conserved sequences, coverage files were compared by bedtools ‘intersect - v’. To identify unique sequences, we used bedtools ‘subtract’. Variant calling and SNP analysis. Because BUSCO genes were not evenly distributed among the chromosomes, we used variant calling to investigate the phylogeny of specific chromosomes and test for linkage disequilibrium. We called variants with freebayes (version 1.3.1) using the following parameters: “--ploidy 1 --min-base-quality 20 --min-coverage 10 --min-alternate-fraction 0.4 --haplotype-length 0” (Garrison & Marth, 2012). The output was filtered by vcftools to remove indels, require at least 70% of samples to have a genotype call, and exclude sites with minor allele count less than 2. The resulting SNPs were filtered by bedtools ‘intersect’ to remove SNPs that were not in regions with read coverage by all yellows-fragariae isolates. We used the vcflib function ‘vcfrandomsample’ to randomly extract SNPs from core chromosomes. Genotype calls were extracted into fasta formatted files by the ‘allele-seq’ function of VCFriend (https://github.com/bnjenner/VCFriend). Maximum likelihood phylogenetic analysis was conducted with RAxML (version 8.2.12) correcting for ascertainment bias with the following parameters: “-m ASC_GTRCAT -V --asc-corr=lewis” (Stamatakis, 2014). Statistical support for each phylogeny was tested with 1,000 bootstrap replicates. For the index of association test of linkage disequilibrium, variants were called by freebayes with a minimum minor allele frequency of 3 and no “--haplotype-length” limit. For this analysis, we used a clone corrected dataset that included 11 distinct genotypes of yellows-fragariae. Variants were randomly subsampled with the vcflib 16 transferred twice between Y2, Y3, and Y4; and chrY-frag.T1 transferred between Y2 and Y7 (Fig. 4; Fig. S6). These predicted HCT events were further supported by differences in read coverage of chrY-frag.T1381 and chrY-frag.T1080 by putative recipients. For example, GL1080 is in the Y1 group, but isolate Fo160609 (Y6) had 99% coverage of the 2.96 Mbp chrY-frag.T1080 and 98.1% identical alleles at SNP sites (Fig. S7,S8). Similarly, GL1381 is in the Y3 group, but >97% coverage and high sequence similarity of chrY-frag.T1381 were observed for both Y4 isolates (NRF0833 and NRF0995; >98% identical) and two Y2 isolates (MAFF305557 and MAFF305558; >87.7% identical; Fig. S7,S9). Two other Y2 isolates (GL1315 and GL1268) had >90% identical SNPs with a Y7 isolate (MAFF744009) and a nearly identical coverage pattern for chrY-frag.T1381 and chrY-frag.T1080, suggesting that chrY- frag.T1 was shared between these strains (Fig. S7-S9). In contrast, other yellowsfragariae isolates had coverage for 70-86% of different chrY-frag types, and other clade 2B isolates had less than 75% coverage. Although F. oxysporum is considered to be asexual, we looked for evidence of meiosis with an index of association test of linkage equilibrium. We conducted the index of association test on a clone-corrected dataset of yellows-fragariae isolates and discovered strong signatures of linkage disequilibrium on all chromosomes, including chrY-frag (P = 0.001 for all chromosomes; Fig. S10). This indicates that meiosis is unlikely to explain the presence of chrY-frag in diverse F. oxysporum genotypes. ChrY-frag was probably polyphyletic before the first report of Fusarium wilt of strawberry. Phylogeny and sequence similarity suggest chrY-frag was present in multiple F. oxysporum genotypes before Fusarium wilt of strawberry was observed in Japan circa 1969 (Okamoto et al., 1970). Within 20 years of the first report, the isolates MAFF305557 (Y2), MAFF744009 (Y7), and MAFF727510 (Y8) were each recovered with distinct chrY-frag types: T1381, T1, and T3, respectively (Fig. 4). If the level of divergence between chrY-frag.T1381 in Y3 and Y2 genotypes is typical for genetic drift over ~20 years (Fig. 4, Fig. S7,S9), then all types of chrY-frag could not have descended from a common ancestor after the observation of this pathogen in 1969. 17 ChrY-frag carries multiple effectors that are highly expressed during infection. GL1381’s in planta transcriptome suggests that the expression of genes on chrY-frag is associated with strawberry root infection. In total, 31 genes on chrY-frag.T1381 were differentially expressed in planta at 6- or 13-days post-inoculation compared with in vitro (adjusted P-value <0.05, log-fold change >1.5 or < -1.5) (Fig. 3, Additional File S6; Table S6). These genes were located in conserved regions among yellows-fragariae and were highly up-regulated, with 4.3 to 14.8 log-fold change in expression at 13-days post inoculation (Fig. 3, Additional File S6). Using EffectorP (version 1 and/or 2), 12 of the 31 up-regulated genes on chrY-frag.T1381 were predicted to be effectors, including a homolog of SIX6 (Additional File S6; Sperschneider et al., 2018). Eight of these genes were present in all yellows-fragariae isolates. In contrast, only eight genes on lineagespecific chromosomes LS2 (2.70 Mbp) or LS3 (2.21 Mbp) were differentially expressed in planta, despite these chromosomes having a combined length (4.91 Mbp) that is almost double that of chrY-frag.T1381 (2.75 Mbp) (Additional File S6; Fig. S3). No differentially expressed genes on LS2 or LS3 were conserved among all yellowsfragariae isolates (Additional File S6). The observed expression pattern supports the hypothesis that chrY-frag.T1381 carries the genes necessary for host-specific pathogenicity. Differential host responses are associated with the presence of chrY-frag. Comparative genomics revealed that chrY-frag was only present in yellows-fragariae isolates; this chromosome was largely missing in strains of wilt-fragariae (Table S5). Given the transcriptomic results, we postulated that chrY-frag conferred common virulence/avirulence factors among the yellows-fragariae isolates. If true, host susceptibility would be more similar for yellows-fragariae isolates than between isolates of yellows- and wilt-fragariae. Therefore, we hypothesized that isolates of yellows-fragariae from distinct monophyletic groups would have a similar cultivar host range, despite differences in core genome phylogeny. To test our hypothesis, we determined the phenotypic response of 25, diverse strawberry genotypes to four yellows-fragariae isolates (representing Y1/T1080, Y2/T1, Y3/T1381, and Y8/T3) and two wilt-fragariae isolates (representing W2 and W3). 18 We used geographic, historic, and genotypic data (inferred from the octoploid Affymetrix® FanaSNP 50k array) to maximize diversity in the strawberry accessions tested (Hardigan et al., 2020). Ultimately, we selected 23 F. × ananassa hybrids and two F. virginiana ecotypes (Fig. 5A; Additional File S7-S8). Consistent with our hypothesis, we observed that the presence of chrY-frag is more predictive of cultivar susceptibility than core genome phylogeny. For example, the Y3 and Y8 core genomes are more closely related to W2 than Y1 and Y2 (Fig. 2) but have greater similarity in cultivar host range with the yellows-fragariae isolates (Fig. 5B; Fig. S11). Between 80-96% of the strawberry accessions were consistently resistant or susceptible between yellows-fragariae isolates (Fig. S11). In contrast, only 52-68% of disease phenotypes were consistent between any yellows- and wilt-fragariae isolate (Fig. 5B; Fig. S11). Therefore, cultivar host range is largely associated with the presence or absence of chrY-frag. Discussion Using isolates from multiple continents that were collected over time, including at the first reports of Fusarium wilt until present, we reconstruct the evolutionary and dispersal history of Fof. Of the two distinct syndromes we observed, yellows-fragariae isolates caused greater disease severity and were more widespread than wilt-fragariae isolates. Our data suggest that genes on chrY-frag confer the pathogenicity phenotype to yellowsfragariae isolates, and horizontal transfer of chrY-frag has led to a polyphyletic distribution of this chromosome. The characterization of chrY-frag as a mobile pathogenicity chromosome is supported by the conservation of chrY-frag among yellows-fragariae, in planta expression patterns, the association between its presence and host resistance/susceptibility phenotypes, and characteristic features that it shares with previously identified mobile pathogenicity chromosomes (Ma et al., 2010; Schmidt et al., 2013; van Dam et al., 2017; Li et al., 2020). We harnessed natural variation in the pathogen population to discover this chromosome; it was the only lineage specific chromosome present in eight core genome phylogenetic groups of yellows-fragariae. ChrY-frag was horizontally transferred at least four times, resulting in the diversification of this pathogen group. Experimental transfer of this chromosome in vitro and 19 characterization of recipients’ pathogenicity phenotypes would provide an additional test of our hypothesis that HCT occurred among yellows-fragariae strains. Pathogenicity in Australian and Spanish wilt-fragariae isolates appears to have evolved independently from yellows-fragariae, without chrY-frag (Notes S1, Notes S2). This inference is primarily supported by: 1) sequences on chrY-frag that were conserved among yellows-fragariae were mostly absent in wilt-fragariae (Table S5), and 2) we discovered no evidence of sympatry between wilt- and yellows-fragariae, which would have been necessary for HCT to occur (Fig. S11-S12). Furthermore, among isolates classified as wilt-fragariae, pathogenicity on strawberry appears to have evolved independently in both Spain and Australia. We observed no overlap in genotypic groups between these countries that could have provided evidence for dispersal. Both Spanish and Australian wilt-fragariae isolates are likely to possess other pathogenicity chromosomes that were not identified in the present study. Other formae speciales have been classified into “yellows” and “wilt” syndromes (Edel- Hermann & Lecompte, 2019). To our knowledge, this is the first time that “yellows” and “wilt” syndromes have been shown to be caused by independently evolved pathogen genotypes that do not share a pathogenicity chromosome. Our results confirm that disease phenotyping can facilitate the identification of evolutionarily distinct groups within a forma specialis. Host resistance is a critical tool for disease management in many Fusarium wilt pathosystems, including Fusarium wilt of strawberry (Koike & Gordon, 2015). Here, we show that isolates with a common pathogenicity chromosome have similar cultivar host ranges, despite differences in core genome phylogeny. Therefore, differentiating between pathogen genotypes that emerged from transfer of a common pathogenicity chromosome versus a different pathogenicity chromosome has important implications for the identification and deployment of host resistance. We observed a unique pattern of resistance/susceptibility for all six Fof genotypes we tested for pathogenicity on 25 diverse strawberry accessions (Fig. 5B). This result suggests there are undiscovered gene-for-gene interactions that could ultimately 20 demonstrate that each of these Fof genotypes is a different race. Here we propose race designations only where a differential interaction between the pathogen and a specific R-gene has been documented, following the commonly used convention (Bus et al., 2011). In strawberry, only one Fusarium wilt resistance locus, FW1, has been identified (Pincot et al., 2018). We report for the first time the existence of Fof “race 2” isolates that overcome FW1-mediated resistance. The existence of this new race underscores the need to identify novel sources of resistance and breed them into commercially available cultivars. Fortunately, our data suggest that numerous sources of resistance are available in hybrid cultivars and wild ecotypes. This is an unexpected finding, because we did not discover evidence of host-pathogen co-evolution. Fragaria × ananassa is an allooctoploid (2n = 8x = 56) resulting from chance hybridization between F. chiloensis (L. Miller) and F. virginiana (Duchesne), approximately 300 years before present (Darrow, 1966; Edger et al., 2019). The native ranges of the wild octoploid progenitors span diverse biomes across North and South America (Staudt, 1988). The origins of Fof in Europe, Asia, and Australia were separated by oceans from the natural range of these octoploid progenitors. This suggests that Fof did not co-evolve with its host and emerged from a host shift or host jump after the introduction of F. × ananassa. Therefore, F. chiloensis and F. virginiana should lack co-evolved defenses that are specific to the Fof isolates we recovered. Consistent with this expectation, we found a wild F. virginiana ecotype that was susceptible to all pathogen genotypes (Fig. 5B). Why F. chiloensis and F. virginiana carry genes that confer resistance to a non-coevolved pathogen remains unclear. It is possible that genetic resistance evolved in response to genes in sympatric microorganisms that have homologs in Fof. The selection pressures that led to the assembly of pathogenicity-enabling genes on chrY-frag remain unknown. Presumably, proto-pathogenicity chromosomes have been under selection for millennia in natural ecosystems. Given their role in plant infection, pathogenicity chromosomes could have initially evolved to facilitate asymptomatic, systemic colonization of native plants (Gordon & Martyn, 1997). These strains could have emerged as pathogens through host shifts/jumps after the introduction of naïve 21 agricultural crops, as has been postulated here for Fof and previously for formae speciales vasinfectum and cubense (Davis et al., 1996; Ploetz & Pegg, 1997; Wang et al., 2004). Regardless of chrY-frag’s evolutionary origin, strains carrying this chromosome would have been amplified by widespread cultivation of strawberries. Our data suggest this chromosome was present in multiple core genome backgrounds before the first report of Fusarium wilt in Japan. However, commercial strawberry production began in Japan and South Korea in the early 20th century, long before the first observation of the disease in 1969 (Yoshida, 2013; Lee, 2014). If chrY-frag already existed in natural ecosystems, it could have taken several decades for strawberries to be planted in a field with a chrY-frag-carrying strain. Furthermore, initial inoculum densities were likely to be low, and many successive crops may have been required for disease to become apparent. Circumstances such as these could account for the delay between the introduction of strawberry agriculture and the first report of disease in 1969. Once abundant in strawberry production fields, isolates with chrY-frag were dispersed between Japan, South Korea, California, and Western Australia, presumably on infected nursery plants (Notes S2; Fig S17; Okamoto et al., 1970; Nam et al., 2011; Pastrana et al., 2019). In contrast, we found no evidence that wilt-fragariae strains from eastern Australia or Spain have spread to other countries since their emergence. We show that HCT promoted diversification of Fof, but pathogenic genotypes also emerged independently, without receiving the same pathogenicity chromosome. These data support the hypothesis that HCT is prevalent in F. oxysporum and has contributed to the evolution of many economically important plant pathogenic forms. The predicted pathogenicity chromosome chrY-frag is likely to have been present in multiple phylogenetic groups before Fusarium wilt of strawberry was observed in Japan. Knowledge of past HCT events informed an efficient approach to testing for host resistance; we found that the cultivar host range was more similar for isolates that shared a pathogenicity chromosome than for independently evolved pathogen genotypes. Geographic isolation suggests that all pathogenic lineages lack a history of co-evolution with F. × ananassa and its wild progenitors. However, we identified 22 demographically and genetically diverse sources of resistance to this pathogen. Our results highlight the potential for comparative genomics of naturally diverse populations to reveal the evolutionary forces driving pathogen emergence and diversification. Acknowledgments. We thank Sam Koehler, Sukhwinder Kaur, Lia Lopez, Michelle Haugland, Mariel Munji, Samuel Brinker, Polly Goldman, and Shawn Melendy for providing technical assistance, and Dr. Matthew Settles for providing general guidance on bioinformatics. Dr. Haruhisa Suga, Michelle Paynter, Dean Beasley, and Dr. Youn- Sig Kwak are thanked for sending isolates of F. oxysporum f. sp. fragariae. We thank Joshua Puckett and the University of California, Davis Foundation Plant Services for providing tissue culture-derived strawberry plants for transcriptomics experiments. Thanks to our funding sources: the National Science Foundation Graduate Research Fellowship Program, the California Strawberry Commission, National Institute of Food and Agriculture (NIFA) Specialty Crops Research Initiative (#2017-51181-26833), pilot grants from the University of California, Davis, Bioinformatics and DNA Technologies Core Facilities, and Ministerio de Ciencia, Innovación y Universidades of Spain Project, Ref: RTI2018-094537-B-I00. The authors have no conflicts of interest to declare regarding the research conducted or publication of this article. 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The sequence alignment map format and SAMtools. Bioinformatics 25. Li J, Fokkens L, van Dam P, Rep M. 2020. Related mobile pathogenicity chromosomes in Fusarium oxysporum determine host range on cucurbits. Molecular Plant Pathology 21: 761-776. 32 Fig. 3. Synteny, sequence conservation, and differential expression of genes on chrY- frag.T1381 and chrY-frag.T1080. Z. For GL1381, the log-fold change of in planta up-regulated genes is shown by green bars on a scale from 0 to 15. Y. Red lines indicate the position of miniature impala transposable elements. Black tic marks occur every 100 kbp on the outside of the ideogram. X. The proportion of each 10 kbp window covered by DNA transposons (red), LTR transposons (orange), LINEs (purple), or predicted genes (blue). Black lines indicate the position of sequences that are conserved in yellowsfragariae and are in no other F. oxysporum clade 2B isolate. W. The proportion of each 10 kbp window with coverage in all yellows-fragariae isolates; green ≥ 0.66, 0.6 > orange ≥ 0.34, red < 0.33. Links. Reciprocal best BLAST hits between predicted genes in the yellows-fragariae conserved regions of the two chromosomes are connected by red bands. Orange triangles indicate the positions of yellows-fragariae-specific detection loci identified by Suga et al. (2013) and Burkhardt et al. (2019). 33 Fig. 4. Incongruence between the phylogeny of chrY-frag.T1080 and core chromosomes. Single nucleotide polymorphisms (SNPs) were called by freebayes (version 1.3.1) on chrY-frag.T1080 and eleven core chromosomes from all 27 yellows-fragariae isolates. Genotype calls were concatenated for both datasets (chrY-frag and combined core chromosomes), and the maximum likelihood phylogeny was inferred by RAxML with correction for ascertainment bias. Nodes with a filled circle have 100% bootstrap support. The chrY-frag type (T1080, T1080B, T1381, T1, T2, and T3) is color-coded and indicated adjacent to its corresponding clade. The monophyletic yellows-fragariae groups (Y1-Y8) are indicated next to their corresponding branches on the core genome phylogeny. Four predicted HCT events are indicated with solid, colored lines between branches of the core genome phylogenetic tree. 34 Fig. 5. Genetic relatedness and resistance/susceptibility phenotypes of diverse strawberry accessions inoculated with Fusarium oxysporum f. sp. fragariae. A. Principal components analysis (PCA) of 501 strawberry accessions estimated from the genotypes of 31,212 SNP markers assayed with the Affymetrix® FanaSNP 50K Array. The source and taxonomic classification of each accession is color-coded; “UCD” indicates cultivars developed at the University of California, Davis, and “Non-UCD” indicates cultivars that were developed at other breeding programs. Numbers correspond to the 25 cultivars phenotyped for resistance to six isolates of F. oxysporum f. sp. fragariae; their aliases are provided above the figure. B. Disease phenotype of 25 strawberry accessions (columns) tested for resistance to six isolates of F. oxysporum f. sp. fragariae (rows). Disease severity was rated on a 1 to 5 ordinal scale, where 1 = symptomless and 5 = dead. Isolate cultivar combinations that had a least-squares mean disease severity score greater than or equal to 2.5 were considered “susceptible” (red), and below 2.5 “resistant/tolerant” (green). 35