Genetic variation and structural diversity in major seed proteins among and within Camelina species
Bibliographic record
Abstract
MAIN CONCLUSION: Genetic variation in seed protein composition, seed protein gene expression and predictions of seed protein physiochemical properties were documented in C. sativa and other Camelina species. Seed protein diversity was examined in six Camelina species (C. hispida, C. laxa, C. microcarpa, C. neglecta, C. rumelica and C. sativa). Differences were observed in seed protein electrophoretic profiles, total seed protein content and amino acid composition between the species. Genes encoding major seed proteins (cruciferins, napins, oleosins and vicilins) were catalogued for C. sativa and RNA-Seq analysis established the expression patterns of these and other genes in developing seed from anthesis through to maturation. Examination of 187 C. sativa accessions revealed limited variation in seed protein electrophoretic profiles, though sufficient to group the majority into classes based on high MW protein profiles corresponding to the cruciferin region. C. sativa possessed four distinct types of cruciferins, named CsCRA, CsCRB, CsCRC and CsCRD, which corresponded to orthologues in Arabidopsis thaliana with members of each type encoded by homeologous genes on the three C. sativa sub-genomes. Total protein content and amino acid composition varied only slightly; however, RNA-Seq analysis revealed that CsCRA and CsCRB genes contributed > 95% of the cruciferin transcripts in most lines, whereas CsCRC genes were the most highly expressed cruciferin genes in others, including the type cultivar DH55. This was confirmed by proteomics analyses. Cruciferin is the most abundant seed protein and contributes the most to functionality. Modelling of the C. sativa cruciferins indicated that each type possesses different physiochemical attributes that were predicted to impart unique functional properties. As such, opportunities exist to create C. sativa cultivars with seed protein profiles tailored to specific technical applications.
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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".