Proteomic analysis of the seeds of transgenic rice lines and the corresponding nongenetically modified isogenic variety
Bibliographic record
Abstract
BACKGROUND: An isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analysis was employed to study the seeds of two genetically modified (GM) rice lines, T2A-1 and T1C-19, and their nontransgenic isogenic variety, MH63, to investigate the unintended effects of genetic modification. RESULTS: A total of 3398 proteins were quantitatively identified. Seventy-seven differentially abundant proteins (DAPs) were identified in the T2A-1/MH63 comparison, and 70 and 7 of these DAPs were upregulated and downregulated, respectively. A pathway enrichment analysis showed that most of these DAPs participated in metabolic pathways and protein processing in endoplasmic reticulum and were ribosome components. Some 181 DAPs were identified from the T1C-19/MH63 comparison, and these included 115 upregulated proteins and 66 downregulated proteins. The subsequent pathway enrichment analysis showed that these DAPs mainly participated in protein processing in endoplasmic reticulum and carbon fixation in photosynthetic organisms and were ribosome components. None of these DAPs were identified as new unintended toxins or allergens, and only changes in abundance were detected. Fifty-four co-DAPs were identified in the seeds of the two GM rice lines, and protein-protein interaction analysis of these co-DAPs demonstrated that some interacting proteins were involved in protein processing in endoplasmic reticulum and metabolic pathways, whereas others were identified as ribosome components. Representative co-DAPs and proteins related to nutrients were analyzed using qRT-PCR to determine their transcriptional levels. CONCLUSIONS: The results suggested that the seed proteomic profiles of the two GM rice lines studied were not substantially altered from those of their natural isogenic control. © 2020 Society of Chemical Industry.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".