Physiological and molecular insights into the resilience of biological nitrogen fixation to applied nitrogen in Saccharum spontaneum, wild progenitor of sugarcane
Why this work is in the frame
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Bibliographic record
Abstract
Excessive use of nitrogen (N) fertilizer for sugarcane cultivation is a significant cause of greenhouse gas emission. N use-efficiency (NUE) of sugarcane is relatively low, and considerable effort is now directed to exploit biological nitrogen fixation (BNF) in sugarcane. We hypothesize that genetic base-broadening of sugarcane using high-BNF Saccharum spontaneum , a wild progenitor of sugarcane, will help develop N-efficient varieties. We found remarkable genetic variation for BNF and growth in S. spontaneum accessions, and BNF in some accessions remained highly resilient to inorganic N application. Physiological and molecular analyses of two S. spontaneum accessions with high-BNF capacity and growth, namely G152 and G3, grown under N replete and low N conditions showed considerable similarity for total N, NH 4 -N, soluble sugar, indoleacetic acid, gibberellic acid, zeatin and abscisic acid content; yet, they were strikingly different at molecular level. Global gene expression analysis of G152 and G3 grown under contrasting N supply showed genotype effect explaining much of the gene expression variation observed. Differential gene expression analysis found an over-representation of carbohydrate and amino acid metabolism and transmembrane transport genes in G152 and an enrichment of lipid metabolism and single-organism processes genes in G3, suggesting that distinctly divergent metabolic strategies are driving N-related processes in these accessions. This was attested by the remarkable variation in carbon, N, amino acid and hormone metabolism-related gene expression in G152 and G3 under high- and low-N supply. We conclude that both accessions may be achieving similar BNF and growth phenotypes through overlapping but distinctly different biochemical and molecular mechanisms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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