Genome-Wide Identification of Chalcone Reductase Gene Family in Soybean: Insight into Root-Specific GmCHRs and Phytophthora sojae Resistance
Bibliographic record
Abstract
Soybean (Glycine max [L.] Merr) is one of the main grain legumes worldwide. Soybean farmers lose billions of dollars’ worth of yield annually due to root and stem rot disease caused by the oomycete Phytophthora sojae. Many strategies have been developed to combat the disease however these methods have proven ineffective in the long term. A more cost effective and durable approach is to select a trait naturally found in soybean that can increase resistance. One such trait is the increased production of phytoalexin glyceollins in soybean. Glyceollins are isoflavonoids, synthesized via the legume-specific branch of general phenylpropanoid pathway. The first key enzyme exclusively involved in glyceollin synthesis is chalcone reductase (CHR) which coacts with chalcone synthase for the production of isoliquirigenin chalcone, the precursor for glyceollin biosynthesis. Here we report the identification of 14 putative CHR genes in soybean where 11 of them are predicted to be functional. Our results show that GmCHRs display tissue-specific gene expression, and that only root-specific GmCHRs are induced upon P. sojae infection. Among 4 root-specific GmCHRs, GmCHR2A is located near a QTL that is linked to P. sojae resistance suggesting GmCHR2A as a novel locus for partial resistance that can be utilized for resistance breeding.
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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".