Identification and Localization of Quantitative Trait Loci (QTL) and Genes Associated with Oil Concentration in Soybean [Glycine max (L.) Merrill] Seed
Bibliographic record
Abstract
Soybean [Glycine max (L.) Merr.] seed is a major source of edible oil in the world and the main renewable raw material for biodiesel production in North America. Oil, which on average accounts for 20% of the soybean seed weight, is a complex quantitative trait controlled by many genes with mostly minor effects and influenced by environmental conditions. Because of its quantitative nature, the seed oil concentration may have an indirect effect on other economically important and agronomic traits such as seed yield and protein concentration. Increasing the oil concentration in soybean has been given more attention in recent years due to increasing demand for both edible oil and feedstock. To achieve this objective, it is important to understand the genetic control of the oil accumulation and its relationship with other traits. The main objectives of this thesis were to identify quantitative trait loci (QTL) and genes involved in oil biosynthesis in soybean. Two recombinant inbred line (RIL) populations were developed from crosses between moderately high oil soybean cultivars with high seed yield and protein concentration. In a population of 203 F3:6 RILs from a cross of ‘OAC Wallace’ and ‘OAC Glencoe’, a total of 11 genomic regions located on nine different chromosomes were identified as associated with oil concentration using multiple QTL mapping (MQM) and single-factor ANOVA. Among the 11 oil-associated QTL, four QTL were also validated in a population of 211 F3:5 RILs from a cross of ‘RCAT Angora’ and ‘OAC Wallace’. There were six oil QTL identified in this study that were co-localized with seed protein QTL and four for seed yield QTL. The oil-beneficial allele of the QTL tagged by marker Sat_020, on Chromosome 9, was positively associated with seed protein concentration. The oil-enhancing alleles at markers Satt001 and GmDGAT2B were positively correlated with seed yield. In this study, three sequence mutations were also discovered in either the coding or non-coding regions of three DGAT soybean genes (GmDGAT2B, GmDGAT2C, and GmDGAT1B) between ‘OAC Wallace’ and ‘OAC Glencoe’ that showed significant effects on some of the traits evaluated. GmDGAT2B showed significant association with seed oil and yield across different environments. The oil-favorable allele of the gene GmDGAT2B from ‘OAC Glencoe’ was also positively correlated with seed yield. GmDGAT2C was associated with seed yield, whereas GmDGAT1B showed significant effects on seed yield and protein concentration. However, neither of these two genes showed any association with seed oil. The yield-enhancing allele of GmDGAT1B showed negative association with protein concentration. The identification of oil QTL that were either positively associated with seed yield and protein or neutral to both traits and the development of new gene-based markers will facilitate marker-assisted breeding to develop high oil soybean cultivars with high yield and minimal effect on protein concentration.
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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".