Genome-wide association analysis reveals genetic variations and candidate genes associated with salt tolerance related traits in Gossypium hirsutum
Bibliographic record
Abstract
Abstract Background Cotton is more resistant to salt and drought stresses as compared to other field crops, which makes itself as a pioneer industrial crop in saline-alkali lands. However, abiotic stresses still negatively affect its growth and development significantly. It is therefore important to breed salt tolerance varieties which can help accelerate the improvement of cotton production. The development of molecular markers linked to causal genes has provided an effective and efficient approach for improving salt tolerance. Results In this study, a genome-wide association study (GWAS) of salt tolerance related traits at seedling stage was performed based on 2 years of phenotype identification for 217 representative upland cotton cultivars by genotyping-by-sequencing (GBS) platform. A total of 51,060 single nucleotide polymorphisms (SNPs) unevenly distributed among 26 chromosomes were screened across the cotton cultivars, and 25 associations with 27 SNPs scattered over 12 chromosomes were detected significantly (−log 10 p > 4) associated with three salt tolerance related traits in 2016 and 2017. Among these, the associations on chromosome A13 and D08 for relative plant height (RPH), A07 for relative shoot fresh matter weight (RSFW), A08 and A13 for relative shoot dry matter weight (RSDW) were expressed in both environments, indicating that they were likely to be stable quantitative trait loci (QTLs). A total of 12 salt-induced candidate genes were identified differentially expressed by the combination of GWAS and transcriptome analysis. Three promising genes were selected for preliminary function verification of salt tolerance. The increase of GH_A13G0171-silenced plants in salt related traits under salt stress indicated its negative function in regulating the salt stress response. Conclusions These results provided important genetic variations and candidate genes for accelerating the improvement of salt tolerance in cotton.
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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".