Dissecting the molecular basis of variability for flowering time in <i>Camelina sativa</i>
Bibliographic record
Abstract
Abstract Camelina sativa is an important polyploid oilseed crop with multiple favorable agronomic traits. Capturing the leaf transcriptome of 48 accessions of C. sativa suggests allelic variation for gene expression levels and notably sub-genome dominance, both of which could provide opportunities for crop improvement. Flowering time (FT) is a crucial factor affecting the overall yield of crops. However, our understanding of the molecular mechanisms underlying FT regulation in C. sativa are still limited, partly due to its complex allohexaploid genome. In this study, weighted gene co-expression network analysis (WGCNA), expression quantitative trait loci (eQTL) analysis and transcriptome-wide association study (TWAS) were employed to explore the FT diversity among 48 C. sativa accessions and dissect the underlying molecular basis. Our results revealed a FT-related co-expressed gene module highly enriched with SOC1 s and SOC1 -like genes, and identified 10 significant FT-associated single nucleotide polymorphisms (SNPs) defining three haplotype groups; thus providing a molecular basis for future genetic improvements in C. sativa breeding.
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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 | 0.001 | 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".