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BEYOND THE GROVE: UNVEILING THE ECOLOGY AND DIVERSITY OF X-DISEASE, ‘CANDIDATUS PHYTOPLASMA PRUNI’, STRAINS IN EXTRA-ORCHARD ENVIRONMENTS
Thesis

BEYOND THE GROVE: UNVEILING THE ECOLOGY AND DIVERSITY OF X-DISEASE, ‘CANDIDATUS PHYTOPLASMA PRUNI’, STRAINS IN EXTRA-ORCHARD ENVIRONMENTS

Mason Chad Hoskins
Master of Science (MS), Washington State University
12/2025
DOI:
https://doi.org/10.7273/000008305
pdf
Hoskins - Thesis30.97 MB
Embargoed Access, Embargo ends: 08/26/2026 CC BY V4.0

Abstract

Chokecherry Genotypes Multi-locus sequence analysis Commercial orchards Candidatus Phytoplasma Pruni
Commercial cherry growers throughout North America have experienced significant crop losses over the last decade due to an outbreak of X-disease, caused by ‘Candidatus Phytoplasma pruni’ (Harper et al. 2023). The X-disease phytoplasma is part of ‘Ca. Phytoplasma’ 16SrIII group. This group comprises 23 subgroups determined on the basis of 16S rRNA sequence similarity, with true ‘Ca. P. pruni’ strains belonging to subgroup “A” and ‘Ca. P. pruni’-related strains classified into the remaining 22 subgroups (Davis et al. 2013). In previous epidemics, this phytoplasma was thought to have originated in uncultivated Prunus spp. adjacent to orchards (Stoddard 1938). Building on recent research into the diversity of ‘Ca. P. pruni’--which identified seven distinct genotypes, five associated with commercial Prunus spp. and two specific to uncultivated Prunus spp. (Molnar et al. 2024)--I aimed to test that hypothesis by determining which genotypes were present in cultivated vs. uncultivated Prunus spp. across the western and mountain states of the United States during the 2023 and 2024 growing seasons. Additionally, I aimed to understand the placement of these ‘Ca. P. pruni’ strains within the broader context of the ‘Ca. Phytoplasma’ 16SrIII group. Chokecherry (Prunus virginiana) samples (n = 518) were collected across 13 states and tested for ‘Ca. P. pruni’ presence using a species-specific quantitative real-time PCR assay (Wright et al. 2021), followed by rapid genotype identification using the partial putative immunodominant (imp) gene (Alessio et al. 2025). Multi-locus sequence analysis (MLSA) was performed using the 16S, partial secY translocase, partial secA translocase, imp, and partial elongation factor (Ef-Tu) genes to increase the resolution of strain relationships and genetic diversity (Bertaccini et al. 2022). Metagenomic analysis also was conducted to better understand strain relationships at the highest resolution. I found that ‘Ca. P. pruni’ presence was almost universal in chokecherry across the western and midwestern states. MLSA revealed clear geographic segregation among strains found in uncultivated Prunus spp., but not among strains in commercial orchards in most states. This pattern suggests that strain introductions into orchards may occur independently of native uncultivated Prunus spp. populations. Several novel strain populations also were identified, indicating that this phytoplasma is more genetically diverse than previously recognized. Notably, the Rocky Mountains emerged as a potential barrier to strain movement, with increased strain diversification observed on the western side of the mountains compared to the eastern side. I present an additional 29 genomes representing the 16SrIII group, expanding coverage of the ‘Ca. P. pruni’ subgroup A. Metagenomic analyses indicated distinct grouping among the strains in the 16SrIII group, and revealed that some ‘Ca. P. pruni’-related strains (as classified by 16S rRNA analysis) fall below the established average nucleotide identity (ANI) threshold of 95% for species delineation using genomes (Bertaccini et al. 2022). In addition to these genetic differences, these strains possess distinct biological characteristics, including differences in primary host range, putative insect vectors, and geographic origins that are not shared with classical X-disease strains. This highlights the need to reconsider their taxonomic classification and to incorporate biological criteria into taxonomic frameworks (Wei and Zhao 2022).

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