Transcriptional regulation of the raffinose family oligosaccharides pathway in Sorghum bicolor reveals potential roles in leaf sucrose transport and stem sucrose accumulation
Bibliographic record
Abstract
Bioenergy sorghum hybrids are being developed with enhanced drought tolerance and high levels of stem sugars. Raffinose family oligosaccharides (RFOs) contribute to plant environmental stress tolerance, sugar storage, transport, and signaling. To better understand the role of RFOs in sorghum, genes involved in myo-inositol and RFO metabolism were identified and relative transcript abundance analyzed during development. Genes involved in RFO biosynthesis (SbMIPS1, SbInsPase, SbGolS1, SbRS) were more highly expressed in leaves compared to stems and roots, with peak expression early in the morning in leaves. SbGolS, SbRS, SbAGA1 and SbAGA2 were also expressed at high levels in the leaf collar and leaf sheath. In leaf blades, genes involved in myo-inositol biosynthesis (SbMIPS1, SbInsPase) were expressed in bundle sheath cells, whereas genes involved in galactinol and raffinose synthesis (SbGolS1, SbRS) were expressed in mesophyll cells. Furthermore, SbAGA1 and SbAGA2, genes that encode neutral-alkaline alpha-galactosidases that hydrolyze raffinose, were differentially expressed in minor vein bundle sheath cells and major vein and mid-rib vascular and xylem parenchyma. This suggests that raffinose synthesized from sucrose and galactinol in mesophyll cells diffuses into vascular bundles where hydrolysis releases sucrose for long distance phloem transport. Increased expression (>20-fold) of SbAGA1 and SbAGA2 in stem storage pith parenchyma of sweet sorghum between floral initiation and grain maturity, and higher expression in sweet sorghum compared to grain sorghum, indicates these genes may play a key role in non-structural carbohydrate accumulation in stems.
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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".