Comparative genome analysis to identify SNPs associated with high oleic acid and elevated protein content in soybean
Bibliographic record
Abstract
The objective of this study was to determine the genetic relationship between the oleic acid and protein content. The genotypes having high oleic acid and elevated protein (HOEP) content were crossed with five elite lines having normal oleic acid and average protein (NOAP) content. The selected accessions were grown at six environments in three different locations and phenotyped for protein, oil, and fatty acid components. The mean protein content of parents, HOEP, and NOAP lines was 34.6%, 38%, and 34.9%, respectively. The oleic acid concentration of parents, HOEP, and NOAP lines was 21.7%, 80.5%, and 20.8%, respectively. The HOEP plants carried both FAD2-1A (S117N) and FAD2-1B (P137R) mutant alleles contributing to the high oleic acid phenotype. Comparative genome analysis using whole-genome resequencing data identified six genes having single nucleotide polymorphism (SNP) significantly associated with the traits analyzed. A single SNP in the putative gene Glyma.10G275800 was associated with the elevated protein content, and palmitic, oleic, and linoleic acids. The genes from the marker intervals of previously identified QTL did not carry SNPs associated with protein content and fatty acid composition in the lines used in this study, indicating that all the genes except Glyma.10G278000 may be the new genes associated with the respective traits.
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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) | 0.001 | 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".