QTL mapping to identify loci and candidate genes associated with freezing tolerance trait in Camelina sativa
Bibliographic record
Abstract
Lack of freezing tolerance is a major constraint for the production of agronomically important Brassica species, particularly in the Northern Great Plains (NGP) of the United States and Canada. However, within the Brassicaceae family, winter germplasm of camelina have shown excellent freezing tolerance and overwinter potential in the NGPs. Differences in freezing tolerance between a winter variety (Joelle) and a spring variety (C046) of camelina appear to be controlled by a small number of dominant or co-dominant genes. To unravel the genetic mechanisms for the differences in freezing tolerance, 254 Recombinant Inbred Lines (RILs) were developed using reciprocal crosses between these two camelina varieties. The RIL population was phenotyped at the F7 stage for freezing tolerance under controlled conditions and genotyped by whole-genome skim sequencing. A one-way ANOVA test revealed a significant ( P < 0.001) difference exists among the RILs for freezing tolerance. A significant and strong correlation (r = 0.60, P < 0.001) was also observed between freezing tolerance and flowering time, indicating that regulation of flowering time might also influence freezing tolerance in camelina. A de novo linkage map was constructed using 4507 SNP markers covering a total of 1208.5 cM map distance with an average of 0.3 cM distances between the markers, which formed 20 linkage groups representing the 20 chromosomes (Chr) of C. sativa . The QTL analyses using three different programs revealed significant loci on Chr 8 , 11, 13, 16 and 18 with LOD threshold value of over 3.5 for freezing tolerance. The QTL peaks with the greatest LOD values of 20.7 and 26.8 were observed at Chr 8 and Chr 13 and accounted for 18.3 % and 25.3 % of the phenotypic variation respectively. A total of 3369 annotated camelina genes were identified within ±50 Kb from the consensus QTL intervals generated from the output of the three mapping programs. Among them, 125 were transcription factors including twelve MIKC_MADS on Chr 8, 11, 13, 16 and 18 and two that annotate as the floral regulators FLOWERING LOCUS C ( FLC ) on Chr 8 and 13, an orthologue of MADS AFFECTING FLOWERING 3 and 4 ( MAF4 and MAF3 ) of arabidopsis on Chr18, and an orthologue of SHORT VEGETATIVE PHASE ( SVP ) on Chr 16 . Although many of the candidate genes identified near the freezing tolerance QTLs have previously been associated with flowering time, further studies are needed to help unravel how these genes impact freezing tolerance mechanisms and improve freezing tolerance in camelina and other Brassica crop species.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".