Genomic and transcriptomic analyses of the tangerine pathotype of Alternaria alternata in response to oxidative stress
Bibliographic record
Abstract
The tangerine pathotype of Alternaria alternata produces the A. citri toxin (ACT) and is the causal agent of citrus brown spot that results in significant yield losses worldwide. Both the production of ACT and the ability to detoxify reactive oxygen species (ROS) are required for A. alternata pathogenicity in citrus. In this study, we report the 34.41 Mb genome sequence of strain Z7 of the tangerine pathotype of A. alternata. The host selective ACT gene cluster in strain Z7 was identified, which included 25 genes with 19 of them not reported previously. Of these, 10 genes were present only in the tangerine pathotype, representing the most likely candidate genes for this pathotype specialization. A transcriptome analysis of the global effects of H2O2 on gene expression revealed 1108 up-regulated and 498 down-regulated genes. Expressions of those genes encoding catalase, peroxiredoxin, thioredoxin and glutathione were highly induced. Genes encoding several protein families including kinases, transcription factors, transporters, cytochrome P450, ubiquitin and heat shock proteins were found associated with adaptation to oxidative stress. Our data not only revealed the molecular basis of ACT biosynthesis but also provided new insights into the potential pathways that the phytopathogen A. alternata copes with oxidative stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".