Complete genomes of grapevine downy mildew reveal effector cluster evolution driven by complex structural variations

Abstract

Plasmopara viticola, the causal agent of grapevine downy mildew, exhibits substantial intraspecific variation in pathogenicity and genetic diversity, yet the genomic features underlying this variation remain incompletely characterized. Here, we sequenced and assembled two P. viticola isolates, PvH (from Vitis vinifera) and PvS (from V. amurensis), using PacBio HiFi sequencing, and performed comparative genomic analysis. Two complete genome assemblies (17 chromosomes) of P. viticola (PvH: 115.3 Mb; PvS: 113.0 Mb) were generated and revealed that nearly 90% of the putative effectors exist as local duplicated gene clusters. Comparative genomics uncovered distinct intraspecific expansion, deletion, and diversification of putative effectors driven by local segmental, tandem, and proximal duplication events in P. viticola. Specifically, PvH exhibited a ~1.4-fold increase in CRNs (PvH: 237; PvS: 183; PV221: 169) and harbored 35 strain-specific CRNs. These differential effectors were predominantly clustered in complex structural variation hotspots (SVs, duplication and inversion). Notably, 104 putative effectors-including 21 RxLRs, 59 CRNs, and 24 CAZymes-were located within inversion regions. Together, our results highlight a highly dynamic genome architecture in P. viticola, in which SV and local gene duplication are closely associated with effector diversification. This study provides a genome-resolved comparative framework for understanding intraspecific genomic diversity in P. viticola and establishes a foundation for future population-level and functional investigations.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (2023YFD1401405), the China Agricultural Research System (CARS-29), the Expert Workstation Project in Yunnan Province (202305AF150129), and Central Public-interest Scientific Institution Basal Research Fund (82025X131).

Author contributions

Y.-Q. Liu, X.-Q. Huang, Z.-Y. Wang, Q. Wang, H. Zhang, and L.-Z. Zhou conceived and designed the experiments. L.-Z. Zhou, S.-W. Cui, and F.-F. Kong carried out experiments and performed the bioinformatic analyses. L.-Z. Zhou and X.-Q. Huang wrote the initial manuscript. Y.-Q. Liu, X.-Q. Huang, Y.-F. Zhou, F. Du, and S.-D. Li revised and contributed to the rewriting of sections of the manuscript.

Data availability

The newly assembled P. viticola (PvH and PvS) genomes, along with all raw sequencing data-including HiFi reads, Illumina DNA reads, and RNA-seq data-of both PvH and PvS have been submitted to NCBI with project no. PRJNA1145503. Gene and effector annotation of P. viticola PvH and PvS assemblies are available on Zenodo [https://doi.org/10.5281/zenodo.17873764].

Conflicts of interest statement

The authors declare that they have no competing interests.

Supplementary material

Supplementary material is available at Horticulture Research online.

References

[1] Paineau M, Minio A, Mestre P, et al. Multiple deletions of candidate effector genes lead to the breakdown of partial grapevine resistance to downy mildew. New Phytol. 2024; 243: 1490-505.

[2] Dvořák E, Dumartinet T, Mazet ID, et al. Parallel adaptation and admixture drive the evolution of virulence in the grapevine downy mildew pathogen. PLoS Pathog. 2026; 22: e1014041.

[3] Gessler C, Pertot I, Perazzolli M . Plasmopara viticola: a review of knowledge on downy mildew of grapevine and effective disease management . Phytopathol Mediterr. 2011; 50: 3-44.

[4] Delmas CEL, Dussert Y, Delière L, et al. Soft selective sweeps in fungicide resistance evolution: recurrent mutations without fitness costs in grapevine downy mildew. Mol Ecol. 2017; 26: 1936-51.

[5] Delmotte F, Mestre P, Schneider C, et al. Rapid and multiregional adaptation to host partial resistance in a plant pathogenic oomycete: evidence from European populations of Plasmopara viticola, the causal agent of grapevine downy mildew . Infect Genet Evol. 2014; 27: 500-8.

[6] Martínez JR, Miclot AS, Dvořák E, et al. A multivirulent Plasmopara viticola strain from Cilaos on Réunion Island breaks down Rpv1, Rpv3.1 and Rpv10 mediated resistance of grapevine . bioRxiv. 2025.09.02.673614.

[7] Paineau M, Mazet ID, Wiedemann-Merdinoglu S, et al. The characterization of pathotypes in grapevine downy mildew provides insights into the breakdown of Rpv3, Rpv10, and Rpv12 factors in grapevines. Phytopathology. 2022; 112: 2329-40.

[8] Peressotti E, Wiedemann-Merdinoglu S, Delmotte F, et al. Breakdown of resistance to grapevine downy mildew upon limited deployment of a resistant variety. BMC Plant Biol. 2010; 10: 147.

[9] Wingerter C, Eisenmann B, Weber P, et al. Grapevine Rpv3-, Rpv10- and Rpv12-mediated defense responses against Plasmopara viticola and the impact of their deployment on fungicide use in viticulture . BMC Plant Biol. 2021; 21: 470.

[10] Rouxel M, Mestre P, Baudoin A, et al. Geographic distribution of cryptic species of Plasmopara viticola causing downy mildew on wild and cultivated grape in eastern North America . Phytopathology. 2014; 104: 692-701.

[11] Rouxel M, Mestre P, Comont G, et al. Phylogenetic and experimental evidence for host-specialized cryptic species in a biotrophic oomycete. New Phytol. 2013; 197: 251-63.

[12] Fontaine MC, Labbé F, Dussert Y, et al. Europe as a bridgehead in the worldwide invasion history of grapevine downy mildew, Plasmopara viticola . Current Biology. 2021; 31: 2155-2166.e4.

[13] Zhang H, Kong F, Wang X, et al. Tetra-primer ARMS PCR for rapid detection and characterisation of Plasmopara viticola phenotypes resistant to carboxylic acid amide fungicides . Pest Manag Sci. 2017; 73: 1655-60.

[14] Yin L, Zhang Y, Hao Y, et al. Genetic diversity and population structure of Plasmopara viticola in China . Eur J Plant Pathol. 2014; 140: 365-376.

[15] Huang X. Genomics diversity and phylogenetic analysis of Plasmopara viticola of Chinese wild and Eurasian Vitis species . PhD dissertation, Chinese Academy of Agricultural Sciences, Beijing, China. 2020.

[16] Brilli M, Asquini E, Moser M, et al. A multi-omics study of the grapevine-downy mildew (Plasmopara viticola) pathosystem unveils a complex protein coding- and noncoding-based arms race during infection . Sci Rep. 2018; 8: 757.

[17] Dussert Y, Gouzy J, Richart-Cervera S, et al. Draft genome sequence of Plasmopara viticola, the grapevine downy mildew pathogen . Genome Announc. 2016; 4: e00987-16.

[18] Dussert Y, Mazet ID, Couture C, et al. A high-quality grapevine downy mildew genome assembly reveals rapidly evolving and lineage-specific putative host adaptation genes. Genome Biol Evol. 2019; 11: 954-69.

[19] Yin L, An Y, Qu J, et al. Genome sequence of Plasmopara viticola and insight into the pathogenic mechanism . Sci Rep. 2017; 7: 46553.

[20] Long Q, Cao S, Huang G, et al. Population comparative genomics discovers gene gain and loss during grapevine domestication. Plant Physiol. 2024; 195: 1401-13.

[21] Wang X, Liu Z, Zhang F, et al. Integrative genomics reveals the polygenic basis of seedlessness in grapevine. Curr Biol. 2024; 34: 3763-3777.e5.

[22] Chen JY, Liu C, Gui YJ, et al. Comparative genomics reveals cotton-specific virulence factors in flexible genomic regions in Verticillium dahliae and evidence of horizontal gene transfer from Fusarium . New Phytol. 2018a; 217: 756-70.

[23] Li K, Jiang W, Hui Y, et al. Gapless indica rice genome reveals synergistic contributions of active transposable elements and segmental duplications to rice genome evolution. Mol Plant. 2021; 14: 1745-56.

[24] Müller MC, Praz CR, Sotiropoulos AG, et al. A chromosome-scale genome assembly reveals a highly dynamic effector repertoire of wheat powdery mildew. New Phytol. 2019; 221: 2176-89.

[25] Shi X, Cao S, Wang X, et al. The complete reference genome for grapevine (Vitis vinifera L.) genetics and breeding . Hortic Res. 2023; 10: uhad061.

[26] Lo Presti L, Kahmann R . How filamentous plant pathogen effectors are translocated to host cells. Curr Opin Plant Biol. 2017; 38: 19-24.

[27] Dong S, Raffaele S, Kamoun S . The two-speed genomes of filamentous pathogens: waltz with plants. Curr Opin Genet Dev. 2015; 35: 57-65.

[28] Wang Q, Jiang C, Wang C, et al. Characterization of the two-speed subgenomes of Fusarium graminearum reveals the fast-speed subgenome specialized for adaption and infection . Front Plant Sci. 2017; 8: 140.

[29] Ayala-Usma DA, Cárdenas M, Guyot R, et al. A whole genome duplication drives the genome evolution of Phytophthora betacei, a closely related species to Phytophthora infestans . BMC Genomics. 2021; 22: 795.

[30] Morales-Cruz A, Ali SS, Minio A, et al. Independent whole-genome duplications define the architecture of the genomes of the devastating west African cacao black pod pathogen Phytophthora megakarya and its close relative Phytophthora palmivora . G3 (Bethesda). 2020; 10: 2241-55.

[31] Chen S, Zhou Y, Chen Y, et al. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018b; 34: i884-90.

[32] de Jonge R, Bolton MD, Kombrink A, et al. Extensive chromosomal reshuffling drives evolution of virulence in an asexual pathogen. Genome Res. 2013; 23: 1271-82.

[33] Hartmann FE, Croll D . Distinct trajectories of massive recent gene gains and losses in populations of a microbial eukaryotic pathogen. Mol Biol Evol. 2017; 34: 2808-22.

[34] Xiang G, Yin X, Niu W, et al. Characterization of CRN-like genes from Plasmopara viticola: searching for the most virulent ones . Front Microbiol. 2021; 12: 632047.

[35] Xiang J, Cheng J, Wei L, et al. Functional analysis of the Nep1-like proteins from Plasmopara viticola . Plant Signal Behav. 2022; 17: 2000791.

[36] Yin L, Li X, Xiang J, et al. Characterization of the secretome of Plasmopara viticola by de novo transcriptome analysis . Physiol Mol Plant Pathol. 2015; 91: 1-10.

[37] Yin X, Fu Q, Shang B, et al. An RxLR effector from Plasmopara viticola suppresses plant immunity in grapevine by targeting and stabilizing VpBPA1 . Plant J. 2022; 112: 104-14.

[38] Yin X, Shang B, Dou M, et al. The nuclear-localized RxLR effector PvAvh74 from Plasmopara viticola induces cell death and immunity responses in Nicotiana benthamiana . Front Microbiol. 2019; 10: 1531.

[39] Dvořák E, Mazet ID, Couture C, et al. Recombination landscape and karyotypic variations revealed by linkage mapping in the grapevine downy mildew pathogen Plasmopara viticola . G3 (Bethesda). 2025; 15: jkae259.

[40] Voglmayr H, Greilhuber J . Genome size determination in peronosporales (Oomycota) by Feulgen image analysis. Fungal Genet Biol. 1998; 25: 181-95.

[41] Emms DM, Kelly S . OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019; 20: 238.

[42] Bourras S, McNally KE, Ben-David R, et al. Multiple Avirulence loci and allele-specific effector recognition control the Pm3 race-specific resistance of wheat to powdery mildew. Plant Cell. 2015; 27: 2991-3012.

[43] Dutheil JY, Mannhaupt G, Schweizer G, et al. A tale of genome compartmentalization: the evolution of virulence clusters in smut fungi. Genome Biol Evol. 2016; 8: 681-704.

[44] Yilmaz F, Karageorgiou C, Kim K, et al. Reconstruction of the human amylase locus reveals ancient duplications seeding modern-day variation. Science. 2024; 386: eadn0609.

[45] Zhang Z, Zhang X, Tian Y, et al. Complete telomere-to-telomere genomes uncover virulence evolution conferred by chromosome fusion in oomycete plant pathogens. Nat Commun. 2024; 15: 4624.

[46] Matson MEH, Liang Q, Lonardi S, et al. Karyotype variation, spontaneous genome rearrangements affecting chemical insensitivity, and expression level polymorphisms in the plant pathogen Phytophthora infestans revealed using its first chromosome-scale assembly . PLoS Pathog. 2022; 18: e1010869.

[47] Cox MP, Guo Y, Winter DJ, et al. Chromosome-level assembly of the Phytophthora agathidicida genome reveals adaptation in effector gene families . Front Microbiol. 2022; 13: 1038444.

[48] Ali SS, Shao J, Lary DJ, et al. Phytophthora megakarya and P. palmivora, closely related causal agents of cacao black pod rot, underwent increases in genome sizes and gene numbers by different mechanisms . Genome Biol Evol. 2017; 9: 536-57.

[49] Lofgren LA, Nguyen NH, Vilgalys R, et al. Comparative genomics reveals dynamic genome evolution in host specialist ectomycorrhizal fungi. New Phytol. 2021; 230: 774-92.

[50] Abraham Leen N, Oggenfuss U, Croll D . Population-level transposable element expression dynamics influence trait evolution in a fungal crop pathogen. MBio. 2024; 15: e02840-23.

[51] Nakamoto AA, Joubert PM, Krasileva KV . Intraspecific variation of transposable elements reveals differences in the evolutionary history of fungal phytopathogen pathotypes. Genome Biol Evol. 2023; 15: evad206.

[52] Sampaio AM, Croll D . Transposable elements create distinct genomic niches for effector evolution among Magnaporthe oryzae lineages . BMC Biol. 2025; 23: 282.

[53] Huang X, Wang X, Zhou L, et al. TaqMan-MGB PCR method for rapid detection of QoI fungicide resistance in Chinese populations of Plasmopara viticola . Plant Dis. 2023; 107: 3007-13.

[54] Cheng H, Concepcion GT, Feng X, et al. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat Methods. 2021; 18: 170-5.

[55] Altschul SF, Gish W, Miller W, et al. Basic local alignment search tool. J Mol Biol. 1990; 215: 403-10.

[56] Simão FA, Waterhouse RM, Ioannidis P, et al. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015; 31: 3210-2.

[57] Fletcher K, Shin OH, Clark KJ, et al. Ancestral chromosomes for family Peronosporaceae inferred from a telomere-to-telomere genome assembly of Peronospora effusa . Mol Plant Microbe Interact. 2022; 35: 450-63.

[58] Fletcher K, Gil J, Bertier LD, et al. Genomic signatures of heterokaryosis in the oomycete pathogen Bremia lactucae . Nat Commun. 2019; 10: 2645.

[59] Wang Y, Tang H, DeBarry JD, et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012; 40: e49.

[60] Li H . Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics. 2018; 34: 3094-100.

[61] Fang Y, Coelho MA, Shu H, et al. Long transposon-rich centromeres in an oomycete reveal divergence of centromere features in Stramenopila-Alveolata-Rhizaria lineages. PLoS Genet. 2020; 16: e1008646.

[62] Flynn JM, Hubley R, Goubert C, et al. RepeatModeler2 for automated genomic discovery of transposable element families. Proc Natl Acad Sci U S A. 2020; 117: 9451-7.

[63] Holt C, Yandell M . MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects. BMC Bioinform. 2011; 12: 491.

[64] Kim D, Paggi JM, Park C, et al. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019; 37: 907-15.

[65] Grabherr MG, Haas BJ, Yassour M, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011; 29: 644-52.

[66] Brůna T, Hoff KJ, Lomsadze A, et al. BRAKER2: automatic eukaryotic genome annotation with GeneMark-EP+ and AUGUSTUS supported by a protein database. NAR Genom Bioinform. 2021; 3: lqaa108.

[67] Stanke M, Schöffmann O, Morgenstern B, et al. Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinform. 2006; 7: 62.

[68] Altschul SF, Madden TL, Schäffer AA, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997; 25: 3389-402.

[69] Törönen P, Medlar A, Holm L . PANNZER2: a rapid functional annotation web server. Nucleic Acids Res. 2018; 46: W84-8.

[70] Cantalapiedra CP, Hernández-Plaza A, Letunic I, et al. eggNOG-mapper v2: functional annotation, Orthology assignments, and domain prediction at the metagenomic scale. Mol Biol Evol. 2021; 38: 5825-9.

[71] Jones P, Binns D, Chang HY, et al. InterProScan 5: genome-scale protein function classification. Bioinformatics. 2014; 30: 1236-40.

[72] Eddy SR . Profile hidden Markov models. Bioinformatics. 1998; 14: 755-63.

[73] Moriya Y, Itoh M, Okuda S, et al. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007; 35: W182-5.

[74] Li H . Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997.

[75] Danecek P, Bonfield JK, Liddle J, et al. Twelve years of SAMtools and BCFtools. Gigascience. 2021; 10: giab008.

[76] Dyrløv Bendtsen J, Nielsen H, von Heijne G, et al. Improved prediction of signal peptides: SignalP 3.0. J Mol Biol. 2004; 340: 783-95.

[77] Sperschneider J, Williams AH, Hane JK, et al. Evaluation of secretion prediction highlights differing approaches needed for oomycete and fungal effectors. Front Plant Sci. 2015; 6: 1168.

[78] Hallgren J, Tsirigos K, Pedersen MD, et al. DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks. bioRxiv. 2022.

[79] Sperschneider J, Dodds PN, Singh KB, et al. ApoplastP: prediction of effectors and plant proteins in the apoplast using machine learning. New Phytol. 2018; 217: 1764-78.

[80] McGowan J, Fitzpatrick DA . Genomic, network, and phylogenetic analysis of the oomycete effector arsenal. mSphere. 2017; 2: e00408-17.

[81] Tabima JF, Grünwald NJ . effectR: an expandable R package to predict candidate RxLR and CRN effectors in oomycetes using motif searches. Mol Plant Microbe Interact. 2019; 32: 1067-76.

[82] Katoh K, Standley DM . MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013; 30: 772-80.

[83] Zhang H, Yohe T, Huang L, et al. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2018; 46: W95-W101.

[84] Quinlan AR, Hall IM . BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010; 26: 841-2.

[85] Meguerditchian C, Ergun A, Decroocq V, et al. Pipeline to detect the positional and directional relationship between transposable elements and adjacent genes in host genome. Peer Community J. 2021; 1: e48.

[86] Marçais G, Delcher AL, Phillippy AM, et al. MUMmer4: a fast and versatile genome alignment system. PLoS Comput Biol. 2018; 14: e1005944.

[87] Goel M, Sun H, Jiao WB, et al. SyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies. Genome Biol. 2019; 20: 277.

[88] Wang K, Li M, Hakonarson H . ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010; 38: e164-4.

[89] Krzywinski M, Schein J, Birol I, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009; 19: 1639-45.

[90] Price MN, Dehal PS, Arkin AP . FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol. 2009; 26: 1641-50.

[91] Letunic I, Bork P . Interactive tree of life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 2019; 47: W256-w259.

[92] Yang Z . PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007; 24: 1586-91.

[93] De Bie T, Cristianini N, Demuth JP, et al. CAFE: a computational tool for the study of gene family evolution. Bioinformatics. 2006; 22: 1269-71.