Population genomics of sorghum (<i>Sorghum bicolor</i>) across diverse agroclimatic zones of Niger
Bibliographic record
Abstract
Improving adaptation of staple crops in developing countries is important to ensure food security. In the West African country of Niger, the staple crop sorghum (Sorghum bicolor) is cultivated across diverse agroclimatic zones, but the genetic basis of local adaptation has not been described. The objectives of this study were to characterize the genomic diversity of sorghum from Niger and to identify genomic regions conferring local adaptation to agroclimatic zones and farmer preferences. We analyzed 516 Nigerien accessions for which local variety name, botanical race, and geographic origin were known. We discovered 144 299 single nucleotide polymorphisms (SNPs) using genotyping-by-sequencing (GBS). We performed discriminant analysis of principal components (DAPC), which identified six genetic groups, and performed a genome scan for loci with high discriminant loadings. The highest discriminant coefficients were on chromosome 9, near the putative ortholog of maize flowering time adaptation gene Vgt1. Next, we characterized differentiation among local varieties and used a genome scan of pairwise F ST values to identify SNPs associated with specific local varieties. Comparison of varieties named for light- versus dark-grain identified differentiation near Tannin1, the major gene responsible for grain tannins. These findings could facilitate genomics-assisted breeding of locally adapted and farmer-preferred sorghum varieties for Niger.
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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".