SoyMAGIC: An Unprecedented Platform for Genetic Studies and Breeding Activities in Soybean
Bibliographic record
Abstract
L.). We have established an eight-parent MAGIC population, comprising 721 recombinant inbred lines (RILs), through conical inter-mating of eight soybean lines. The parental lines were genetically diverse elite cultivars carrying different agronomic and seed composition characteristics, including amino acids and fatty acids, as well as oil and protein concentrations. This study aimed to introduce soybean MAGIC (SoyMAGIC) population as an unprecedented platform for genotypic and phenotypic investigation of agronomic and seed quality traits in soybean. The RILs were evaluated for important seed composition traits using replicated field trials during 2020 and 2021. To measure the seed composition traits, near-infrared reflectance (NIR) was employed. The RILs were genotyped using genotyping-by-sequencing (GBS) method to decipher the genome and discover single-nucleotide polymorphic (SNP) markers among the RILs. A high-density linkage map was constructed through inclusive composite interval mapping (ICIM). The linkage map was 3,770.75 cM in length and contained 12,007 SNP markers. Chromosomes 11 and 18 were recorded as the shortest and longest linkage groups with 71.01 and 341.15 cM in length, respectively. Observed transgressive segregation of the selected traits and higher recombination frequency across the genome confirmed the capability of MAGIC population in reshuffling the diversity in the soybean genome among the RILs. The assessment of haplotype blocks indicated an uneven distribution of the parents' genomes in RILs, suggesting cryptic influence against or in favor of certain parental genomes. The SoyMAGIC population is a recombined genetic material that will accelerate further genomic studies and the development of soybean cultivars with improved seed quality traits through the development and implementation of reliable molecular-based toolkits.
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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".