Tailoring Camelina Seed Fatty Acid Composition via Fast Neutron Mutagenesis
Bibliographic record
Abstract
Despite its minor status as an oilseed, Camelina sativa is a crop with the potential to reach greater levels of production in Canada due to its unique seed oil composition, relatively low input requirements, and availability of both spring and winter varieties. The limited genetic diversity of the species presents a challenge for camelina improvement through breeding. The aim of this study was to induce genetic variations in camelina’s genome through Fast Neutron (FN) irradiation applied to seeds in a dose gradient ranging from 7.1 to 49.5 Gy. A range of mutations should be caused following FN irradiation including deletions, point mutations, and rearrangements due to DNA damage and subsequent repair. In germination assays of FN-irradiated seeds, FN irradiation had no impact on germination, but higher doses of irradiation resulted in plants with a slower maturity. A FN mutagenesis population was established from irradiated camelina seeds for phenotypic and genotypic characterization. Male sterility and toothed leaf margin of irradiated camelina were observed based on visual observations. Seed fatty acids were analyzed and lineages with altered fatty acid composition, such as high C18:3 and low C20:1, were identified. To study novel genotypes, genotyping by sequencing was applied. An approach was designed and implemented that utilized Illumina sequence technology for generating large amounts of genome sequence data, in conjunction with Oxford Nanopore Technologies (ONT) sequencing for validation. One mutant lineage FN49-38 was characterized whose total very long chain fatty acid composition was 19.6%, a relatively lower percentage than of wild type (23.9%). This lineage carried a genomic DNA deletion of approximately 1.2kb spanning the 5' UTR (untranslated region) and the front half of the FAE1B-ORF (open reading frame) detected through Illumina sequencing, which was validated by ONT sequencing. Furthermore, the accuracy and authenticity of the deletion were confirmed by Sanger sequencing of the cloned mutant gene amplified by PCR (polymerase chain reaction) using specific primers flanking the mutated region. The ONT data was used to review and correct the current annotation of the FAE1 gene on chromosomes 11 and 12. A backcrossing experiment was conducted and confirmed that the deletion was linked to the reduced very long chain fatty acid composition phenotype.
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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".