Genome-Wide Association Study of Waterlogging Tolerance in Barley (Hordeum vulgare L.) Under Controlled Field Conditions
Bibliographic record
Abstract
Waterlogging is one of the main abiotic stresses severely reducing barley grain yield. Barley breeding programs focusing on waterlogging tolerance require an understanding of genetic loci and alleles in the current germplasm. In this study, 247 worldwide spring barley genotypes grown under controlled field conditions were genotyped with 35,926 SNPs with minor allele frequency (MAF) > 0.05. Significant phenotypic variation in each trait, including biomass, spikes per plant, grains per plant, kernel weight per plant, plant height and chlorophyll content, was observed. A genome-wide association study (GWAS) based on linkage disequilibrium (LD) for waterlogging tolerance was conducted. Population structure analysis divided the population into three subgroups. A mixed linkage model using both population structure and kinship matrix (Q+K) was performed. We identified 17 genomic regions containing 51 significant waterlogging-tolerance-associated markers for waterlogging tolerance response, accounting for 5.8-11.5% of the phenotypic variation, with a majority of them localized on chromosomes 1H, 2H, 4H, and 5H. Six novel QTL were identified and eight potential candidate genes mediating responses to abiotic stresses were located at QTL associated with waterlogging tolerance. To our awareness, this is the first GWAS for waterlogging tolerance in a worldwide barley collection under controlled field conditions. The marker-trait associations could be used in the marker-assisted selection of waterlogging tolerance and will facilitate barley breeding.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".