Mapping and candidate genes associated with saccharification yield in sorghum
Bibliographic record
Abstract
Sorghum (Sorghum bicolor (L.) Moench) is a high-yielding, stress tolerant energy crop for lignocellulosic-based biofuel production. Saccharification is a process by which hydrolytic enzymes break down lignocellulosic materials to fermentable sugars for biofuel production, and mapping and identifying genes underlying saccharification yield is an important first step to genetically improve the plant for higher biofuel productivity. In this study, we used the ICRISAT sorghum mini core germplasm collection and 14 739 single nucleotide polymorphism markers to map saccharification yield. Seven marker loci were associated with saccharification yield and five of these loci were syntenic with regions in the maize genome that contain quantitative trait loci underlying saccharification yield and cell wall component traits. Candidate genes from the seven loci were identified but must be validated, with the most promising candidates being β-tubulin, which determines the orientation of cellulose microfibrils in plant secondary cell walls, and NST1, a master transcription factor controlling secondary cell wall biosynthesis in fibers. Other candidate genes underlying the different saccharification loci included genes that play a role in vascular development and suberin deposition in plants. The identified loci and candidate genes provide information into the factors controlling saccharification yield and may facilitate increasing biofuel production in sorghum.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".