Comparative Genomics Reveals Insight into Virulence Strategies of Plant Pathogenic Oomycetes
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Bibliographic record
Abstract
The kingdom Stramenopile includes diatoms, brown algae, and oomycetes. Plant pathogenic oomycetes, including Phytophthora, Pythium and downy mildew species, cause devastating diseases on a wide range of host species and have a significant impact on agriculture. Here, we report comparative analyses on the genomes of thirteen straminipilous species, including eleven plant pathogenic oomycetes, to explore common features linked to their pathogenic lifestyle. We report the sequencing, assembly, and annotation of six Pythium genomes and comparison with other stramenopiles including photosynthetic diatoms, and other plant pathogenic oomycetes such as Phytophthora species, Hyaloperonospora arabidopsidis, and Pythium ultimum var. ultimum. Novel features of the oomycete genomes include an expansion of genes encoding secreted effectors and plant cell wall degrading enzymes in Phytophthora species and an over-representation of genes involved in proteolytic degradation and signal transduction in Pythium species. A complete lack of classical RxLR effectors was observed in the seven surveyed Pythium genomes along with an overall reduction of pathogenesis-related gene families in H. arabidopsidis. Comparative analyses revealed fewer genes encoding enzymes involved in carbohydrate metabolism in Pythium species and H. arabidopsidis as compared to Phytophthora species, suggesting variation in virulence mechanisms within plant pathogenic oomycete species. Shared features between the oomycetes and diatoms revealed common mechanisms of intracellular signaling and transportation. Our analyses demonstrate the value of comparative genome analyses for exploring the evolution of pathogenesis and survival mechanisms in the oomycetes. The comparative analyses of seven Pythium species with the closely related oomycetes, Phytophthora species and H. arabidopsidis, and distantly related diatoms provide insight into genes that underlie virulence.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it