Soybean aphids exploit abscisic acid signaling to suppress jasmonate defense responses
Bibliographic record
Abstract
Summary Soybean aphids ( Aphis glycines ) can induce susceptibility on soybean ( Glycine max ) during colonization. However, the mechanism for this process is not known. Based on previous transcriptome analyses, we hypothesized that aphids block effective jasmonate (JA) defenses by inducing an antagonistic abscisic acid (ABA) signal. To test this hypothesis, we used a combination of gene expression analyses, measurements of hormone levels, and aphid bioassays on plants with reduced expression of ABA-related genes. Aphid feeding attenuated JA responses in soybean plants and facilitated the growth of a chewing herbivore. Aphid-treated plants had increased levels of cis -JA but not biologically active JA-isoleucine, and aphid feeding induced expression of genes associated with JA-Ile catabolism. In parallel, aphid-feeding induced higher levels of ABA. ABA treatment and knockdown lines impaired in ABA biosynthesis ( aba2 -RNAi) or signaling ( scof-1 -RNAi), showed that ABA suppressed wound-induced JA responses. Aphid populations were significantly reduced on ABA-deficient plants and aphid-regulated attenuation of JA signaling was abolished in these lines. Remarkably, plants defective in ABA signaling had increased JA signaling in the absence of stressors. Our results indicate that, in soybean, the ABA pathway is necessary to control basal levels of JA and soybean aphids exploit this ABA-JA antagonism to suppress plant defenses.
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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 | 0.000 |
| 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) | 0.001 | 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".