Julio Cesar Vega-Arreguin

Natural rubber supply depends almost entirely on one tropical tree, motivating development of temperate alternatives. Rubber dandelion ( Taraxacum kok-saghyz Rodin) is the leading candidate, with comparatively well characterized rubber biosynthesis pathways, but its large, repeat-rich genome has left breeding genomics far behind pathway biology. In response, we assembled OSU TarKok 3.0, a 1.19-Gb nuclear reference in which eight chromosome-scale scaffolds contain 98% of the sequence. Continuity within chromosomes improved markedly, with contig N50 rising from 1.3 to 37.8 Mb, and conserved gene-space recovery improved accordingly. Macrosynteny showed strong chromosome conservation within Taraxacum and, when compared to lettuce, displayed four nearly intact and four composite chromosomes, a signature compatible with descending dysploidy accompanied by rearrangement rather than a single end-to-end fusion. Across nine Cichorieae genomes, none of six surveyed rubber-related gene families was uniquely enlarged in rubber dandelion. Instead, a cis -prenyltransferase locus, a rubber transferase activator, and three small rubber particle protein genes were enriched in underground tissues and grouped with rubber elongation factor in a latex-associated co-expression module, favoring coordinated pathway deployment over species-specific family expansion. Intersecting uniquely mappable and nonrepetitive sequence defined the mappable genome, approximately 210 Mb or 18% of the assembly, within which markers can be interpreted allelically. Mapping in an independent F₂ family of 83 plants identified a chromosome 1 locus for filled-seed production under restricted cross-pollination, whereas herbicide response yielded no significant locus in this design. OSU TarKok 3.0 links chromosome reorganization, pathway deployment, and domestication traits into one framework for improving an outcrossing crop. Core Ideas: OSU TarKok 3.0 markedly improves within-chromosome continuity and conserved gene-space recovery. Repeat-aware defines a ∼210 Mb short-read mappable space (18% of the assembly), enabling reliable marker analysis. Four chromosomes retain conserved relationships, supporting dysploidy with rearrangement beyond simple fusion. No rubber-related gene family is uniquely expanded; rubber production reflects pathway coordination, not dosage. A chromosome 1 QTL for selfing-related filled-seed production overlaps the positional candidate g7174 . Plain Language Summary: As the global supply of natural rubber is dependent on one tropical tree, rubber dandelion has been proposed as a temperate alternative. Although scientists already understand many of the genes involved in its rubber production, breeding has been slowed by its large, highly repetitive genome. In response, we built OSU TarKok 3.0, a much more continuous genome that places 98% of the sequence on eight chromosomes. Comparison with related dandelions revealed broad chromosome conservation, while comparison with lettuce was consistent with rearrangements during the reduction from nine to eight chromosomes. Across nine members of the sunflower family, none of six rubber-related gene families were uniquely enlarged in rubber dandelion. Instead, genes involved in building rubber chains and particles were active together in underground tissues and latex-associated samples, suggesting that coordinated gene activity matters more than extra gene copies. We also identified ∼210 million base pairs, 18% of the genome, where short-read genetic markers can be interpreted reliably. Within that space, we mapped a chromosome 1 region associated with producing filled seed when cross-pollination was restricted. This region overlaps a candidate gene from a protein family involved in reproductive development in other plants, providing a testable target for improving seed production.

Plant–pathogen interactions are shaped by dynamic regulatory processes that control immune signaling. Among these, post-translational modifications (PTMs) play central roles in modulating protein activity, stability, and interaction networks. Increasing evidence indicates that Phytophthora effectors target PTM-dependent regulatory systems to suppress host immunity and promote infection. Here, we synthesize current knowledge on how Phytophthora virulence factors manipulate post-translational regulation through two mechanistically distinct strategies: (i) canonical mechanisms, involving direct enzymatic modification of host proteins or the recruitment of host PTM-modifying enzymes, and (ii) non-canonical mechanisms, in which effectors alter the activity, organization, or localization of PTM-associated regulatory systems without directly inducing covalent modification. These processes frequently involve protein–protein interactions and oligomerization-dependent regulation that reshape signaling complexes and enzymatic accessibility. By distinguishing effector-mediated PTM induction from regulatory interference, we provide a mechanistic framework for interpreting how diverse virulence strategies converge on the control of immune signaling pathways, including those governing reactive oxygen species production, transcriptional regulation, hormone signaling, and cell death. We further highlight current limitations in mechanistic understanding and emphasize the need for integrative approaches combining structural biology and proteomics to resolve how effectors reprogram host signaling systems.

The RNA interference (RNAi) pathway is an epigenetic mechanism that has recently gained attention for its role in regulating the virulence of plant pathogens. However, little is known about this gene silencing pathway in Phytophthora capsici , a broad-host-range pathogen that affects many important food crops. In the present study, we identified key genes and proteins involved in the synthesis, transport, and processing of sRNAs using in silico approaches based on the reference genome and proteome, and through transcriptional analysis of P. capsici . Our results showed that the P. capsici genome encodes Dcl1, Dcl2, Exportin-5, Rdr, and six Ago proteins, suggesting the presence of a complete RNAi pathway in this pathogen. These genes were syntenic and phylogenetically related to those of other oomycetes in the genus Phytophthora . We also analyzed their expression levels after infecting chili pepper and broccoli across two generations, revealing different expression patterns depending on the infection history of the pathogen. To our knowledge, this is the first report on the EXPORTIN-5 gene in P. capsici and other oomycetes. Additionally, the expression of all these RNAi-related genes in the pathogen after isolation from different hosts suggests that the host may influence the RNAi pathway of P. capsici . This study paves the way for functional studies to confirm the role of RNAi in regulating virulence in P. capsici .

Understanding how plant pathogens modulate the rhizosphere microbiota is essential to integrated disease management. Here, the compositional and functional shifts in the avocado rhizosphere bacteriome induced by Phytophthora cinnamomi were assessed to identify bacterial taxa enriched in the symptomatic condition and elucidate the microbial functions modulated by the infection. Metabarcoding and metatranscriptomics analyses revealed that Phytophthora root rot (PRR) induced compositional shifts in bacterial communities, leading to the enrichment of members of MND1, RB41, and Nitrospira. Functional analysis showed that this enrichment might be due to the release of nutrients following root rot, as carbohydrate metabolism was stimulated in rhizobacterial communities of infected trees. Moreover, the relative abundance of transcripts from genes associated with stress response and cell signaling increased in some of the most active genera in the rhizosphere of PRR-symptomatic trees, suggesting their potential to mitigate the adverse effects of infection. These findings highlight the need to combine compositional and functional microbiome data to differentiate between taxa attracted by nutrient release and those contributing to the plant defense. The interactions of beneficial bacterial taxa with the pathogen should be further studied, as they may constitute promising biocontrol agents.

Motivation: RNA interference (RNAi) is a powerful tool for gene silencing across research, therapeutics, and agriculture. However, designing long double-stranded RNAs (dsRNAs) remains challenging because each dsRNA produces many small interfering RNAs (siRNAs), which can collectively introduce substantial off-target effects. Existing tools often lack the ability to account for cumulative off-target interactions, to incorporate thermodynamic modeling, or to accept custom transcriptome inputs, limiting their applicability and accuracy. Results: Here, we present SIREN, an open-source pipeline designed to streamline RNAi construct design. SIREN integrates siRNA generation, thermodynamically informed off-target prediction, scoring of dsRNA candidates based on cumulative off-target effects, and primer design for in vitro synthesis. It accepts user-defined transcriptomes for context-specific analysis and provides adjustable sensitivity settings balancing accuracy and computational demands. Benchmarking across plant, oomycete, and human transcriptomes demonstrates predictable scaling with target length and shows that optional speed modes can reduce runtime while preserving a substantial fraction of high-sensitivity designs and high-risk off-target rankings in many cases. Qualitative validation in Phytophthora capsici confirms that SIREN effectively identifies highly specific RNAi constructs with no detectable off-target phenotypes in host plants. Availability and implementation: SIREN is implemented in Python and available under an open-source license at https://github.com/pablovargasmejia/SIREN.

Understanding how plant pathogens modulate the rhizosphere microbiota is essential to integrated disease management. Here, we assessed the compositional and functional shifts in the avocado rhizosphere bacteriome induced by Phytophthora cinnamomi to elucidate the microbial functions modulated by the infection and identify taxa potentially recruited by the plant as a defense response. Through metabarcoding with metatranscriptomics, we showed that Phytophthora root rot (PRR) induced compositional shifts in bacterial communities, leading to the enrichment of members of MND1, RB41 and Nitrospira . Functional analysis showed that this enrichment may be due to the release of nutrients following root rot, as carbohydrate metabolism was stimulated in rhizobacterial communities of infected trees. We detected evidence of a cry-for-help strategy by the infected plant, as the most active genera in the rhizosphere of PRR-symptomatic trees up-regulated genes associated with stress response and cell signaling, suggesting that they were recruited to mitigate the adverse effects of infection. Our findings highlight the need to combine compositional and functional microbiome data to differentiate between taxa attracted by nutrient release and those actively recruited by the plant. The interactions of the latter with the pathogen should be further studied, as they may constitute promising biocontrol agents.

The small RNA (sRNA) pathway is an epigenetic mechanism that has recently gained attention due to its suggested role in regulating virulence of plant pathogens. This gene silencing process has been observed in certain species of the oomycete genus Phytophthora . However, little is known about this pathway in Phytophthora capsici , a pathogen with a broad host range that affects many important food crops. In the present study, using bioinformatics approaches on the reference genome, transcriptome, and proteome of P. capsici , we identified and analyzed key genes and proteins involved in the synthesis, transport, and processing of sRNAs. Our results showed that the P. capsici genome encodes a DCLα, DCLβ, exportin-5A, RDR, and six AGO proteins, suggesting the presence of a complete sRNA pathway in this pathogen. These genes were syntenic, structurally similar, and phylogenetically related to other oomycetes of the genus Phytophthora . We also analyzed their expression levels after infecting chili pepper and broccoli across two generations, revealing different expression patterns depending on the pathogen infection history. To our knowledge, this is the first report showing the presence of the exportin-5A gene in P. capsici and other oomycetes. Additionally, the expression of all these sRNA-related genes in the pathogen isolated from different hosts suggests that the host may influence the epigenetic regulation of P. capsici via the sRNA pathway. This study paves the way for functional studies to confirm the role of the sRNA pathway in regulating virulence in P. capsici .

Motivation: RNA interference (RNAi) is a powerful tool for gene silencing across biological research, therapeutics, and agriculture. While siRNA design has benefited from advances in thermodynamic modeling and machine learning, comprehensive tools for designing long double-stranded RNAs (dsRNAs) with minimized off-target effects remain limited. Results: Here, we present SIREN, an open-source Python pipeline designed to streamline RNAi construct design. SIREN integrates siRNA generation, thermodynamically-informed off-target prediction, scoring of dsRNA candidates based on cumulative off-target effects, and primer design for in vitro synthesis. It accepts user-defined transcriptomes for context-specific analysis and provides adjustable sensitivity settings balancing accuracy and computational demands. Benchmarking with plant, oomycete, and human transcriptomes demonstrates SIREN’s efficient scalability and the practical utility of medium sensitivity, recovering over 75% of high-sensitivity targets with significantly reduced computing times. Experimental validation in Phytophthora capsici confirms that SIREN effectively identifies highly specific RNAi constructs with no detectable off-target phenotypes in host plants. Availability and implementation: SIREN is implemented in Python 3 and available under an open-source license at https://github.com/pablovargasmejia/SIREN ; installer via PyPI: https://pypi.org/project/siren-rnai/ .

Phytophthora capsici is a broad-host-range oomycete phytopathogen responsible for economic losses in crops worldwide. Previous transcriptomic analyses have focused mainly on plant responses to infection. However, the transcriptional adaptations of the phytopathogen to different host species remain poorly understood. In this study, we investigated the transcriptomic response of P. capsici during early infection in Cucumis sativus, Cucumis melo, Capsicum annuum CM334, and Solanum lycopersicum by RNA-seq and multiphoton microscopy. Focusing on crown infections since it is the natural entry point for the pathogen. Our results reveal striking host-specific infection strategies. In tomato, rapid necrosis at 12-27 hours post-inoculation was associated with early metabolic reprogramming and effector repression. In contrast, cucurbits exhibited delayed necrosis (36-102 hpi), supporting extensive host intracellular colonization and upregulation of carbohydrate metabolism pathways. Partially resistant CM334 chili pepper restricted pathogen proliferation, with P. capsici displaying transcriptional signatures indicative of metabolic stress. In addition, effector expression is tightly regulated, with the differential deployment of RxLR, NLP, and CRN families across hosts. Comparative transcriptomics highlights metabolic reprogramming as a key determinant of infection success, with P. capsici fine-tuning its gene expression to exploit host-specific vulnerabilities. These findings provide novel insights into P. capsici adaptive strategies in soil-borne infections and underscore the importance of targeting crown infection sites for disease management. Future research should integrate host transcriptomics and functional studies to elucidate the molecular determinants of host specificity.