Analysis of expressed sequence tags from roots of resistant soybean infected by the soybean cyst nematode
Bibliographic record
Abstract
The soybean cyst nematode (SCN) Heterodera glycines is the most devastating pest of soybean in the U.S.A. The resistance response elicited by SCN in soybean is complex, and genes involved in the response to a large extent are unknown and not well characterized. We constructed cDNA libraries made from mRNA extracted from roots of the resistant soybean Glycine max L. Merr. 'Peking' at 12 h, 2 to 4 days, and 6 to 8 days post inoculation with the soybean cyst nematode, population NL1-RHp, similar to race 3. Expressed sequence tag analysis of the libraries provides rapid discovery of genes involved in the response of soybean to the nematode. A total of 3454 cDNA clones were examined from the three libraries, of which 25 cDNAs were derived from nematode RNA. The levels of certain stress-induced genes such as SAM22 and glutathione S-transferase (GST8) were elevated in the SCN-infected roots relative to uninoculated roots. Early defense response genes, particularly ascorbate peroxidase and lipoxygenase, were abundant in the 12-h library. By 6-8 days, the expression of most of those genes was not as abundant, whereas genes coding for unknown proteins and stress-induced proteins continued to be highly expressed. These ESTs and associated information will be useful to scientists examining gene and protein interactions between nematodes and plants.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".