Association mapping identifies stable loci containing novel genes for developmental and reproductive traits in sorghum
Bibliographic record
Abstract
Landraces are ideal for identifying genes related to adaptation. The purpose of this study was to map and identify genes related to adaptation. We evaluated a mini core collection that broadly samples the global sorghum landrace gene pool for 11 traits in 4–12 environments. Association mapping with 6094 317 SNPs identified 70 loci for the 11 traits. The key findings include two panicle weight (PWt) and two grain yield (GY) loci overlapped, and two panicle length (PL) and two panicle width (PW) loci overlapped. Some loci for tiller number (TL), PL/PW, PWt, GY, and seed weight (SW) colocalized with previously mapped quantitative trait loci. We identified 33 candidate genes for TL, PL, PW, PWt, GY, SW, and MRC. The overlapping PWt and GY locus on chromosome 9 contained gibberellin receptor GID1 gene that regulates seed development. A TL locus on chromosome 1 that was consistently detected contained Sobic.001G152700 encoding a DUF1618 protein that was the sole horizontally transferred gene from sorghum to the parasitic Striga hermonthica, which was potentially related to environmental adaptation. These results are relevant for sorghum molecular breeding. Future studies are needed to functionally characterize the rich collection of novel candidate genes identified in this study. Key message We mapped 11 sorghum traits, identified 33 candidate genes, and found a grain yield gene ( GID1) that regulates seed development and a grass-specific tillering gene (DUF1618) transferred to Striga hermonthica.
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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 | 0.001 |
| 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".