Achyut R. Adhikari
University of Hawaii at Mānoa
Honolulu, Hawaii, United States
Koon-Hui Wang
University of Hawai'i at Mānoa
Honolulu, Hawaii, United States
Michael B. Kantar
Associate Professor
University of Hawaiʻi at Manoa, Honolulu, HI, USA
Honolulu, Hawaii, United States
Miaoying Tian, PhD
Distinguished Professor
University of Georgia
Tifton, Georgia, United States
Roshan R. Manandhar
Assistant Extension Agent - Invasive Species
University of Hawaii at Manoa
Lihue, Hawaii, United States
Phytopythium helicoides, is a genomically underexplored oomycete increasingly linked to root, crown, and stem rots, as well as leaf blight, in economically important crops such as avocado. To investigate its pathogenic potential, we sequenced, assembled and analyzed the genome of isolate HI-avo, recovered from symptomatic avocado roots in Hawaiʻi. De novo assembly using SPAdes yielded a 58.6 Mb genome with 98% BUSCO completeness. EffectorO-ML predicted 930 candidate effectors in HI-avo, the highest number among currently sequenced isolates. Orthogroup analysis identified 309 core groups shared across all three genomes, with 31 unique to HI-avo, 20 to PF-he2, and 2 to CBS286.31. The HI-avo-specific orthogroups included 68 unique effectors enriched in YxSL[RK] and CHXC motifs, which serve as non-canonical translocation signal, rather than the classical RxLR motif present in effectors of many oomycetes. Domain annotations showed high divergence, with 91% of effector-associated domains being isolate-specific. HI-avo effectors included 57 unique domains, with the most frequent including papain-like cysteine endopeptidase, cytochrome P450 superfamily, and glycoside hydrolase family 37, all of which are commonly implicated in host colonization and virulence. Collectively, these findings establish HI-avo as a genomically distinct, effector-rich lineage of P. helicoides, providing valuable insights into host adaptation and virulence. This genomic resource provides a foundation for comparative studies and the development of rapid, genome-informed diagnostics for disease management.