Identification of differentially expressed proteins of a new rice mutant with albino green-revertible trait in the seedling stage
Bibliographic record
Abstract
Chlorophyll-deficient mutants have been employed to study the mechanism of chlorophyll and chloroplast biogenesis in plants. We found a new chlorophyll-deficient mutant rice line (W02S) whose leaves, unlike those of its isogenic line (Peiai64S), became etiolated at the two-leaf stage and turned green at the three-leaf stage. 2-D gel electrophoresis was performed, and proteins that were differentially expressed between W02S and Peiai64S were selected for MALDI-TOF MS analysis. A total of 44 highly differentially expressed proteins were collected from the two-leaf stage of W02S. These 44 proteins can be classified into 10 categories, 15 were novel and unknown functional proteins, 6 proteins participated in the EMP-TCA-ETC pathway, and 4 proteins were involved in the in signal transduction. Four representative protein spots were selected for real-time quantitative PCR analysis. The mRNA levels of three genes encoding an enolase, a chloroplast 29 kDa ribonucleoprotein and a proteasome alpha subunit were significantly increased in the samples from the two-leaf stage of W02S, indicating that a substantial proportion of protein changes is the consequence of altered mRNA levels during the seedling stages of the mutant rice. These findings provide new insights into the mechanisms for chlorophyll-deficient mutant rice and other plants as well.Key words: Oryza sativa L., 2-D gel , real time PCR, chlorophyll-deficient mutant
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".