Cloning and Characterization of TaTGW-7A Gene Associated with Grain Weight in Wheat via SLAF-seq-BSA
Bibliographic record
Abstract
Thousand-grain weight (TGW) of wheat (Triticum aestivum L.) contributes significantly to grain yield. In the present study, a candidate gene associated with TGW was identified through specific-locus amplified fragment sequencing (SLAF-seq) of DNA bulks of recombinant inbred lines (RIL) derived from the cross between Jing 411 and Hongmangchun 21. The gene was located on chromosome 7A, designated as TaTGW-7A with a complete genome sequence and an open reading frame (ORF). A single nucleotide polymorphism (SNP) was present in the first exon between two alleles at TaTGW-7A locus, resulting in a Val to Ala substitution, corresponding to a change from higher to lower TGW. Cleaved amplified polymorphic sequence (CAPS) (TGW7A) and InDel (TG9) markers were developed to discriminate the two alleles TaTGW-7Aa and TaTGW-7Ab for higher and lower TGW, respectively. A major QTL co-segregating with TaTGW-7A explained 21.7–27.1% of phenotypic variance for TGW in the RIL population across five environments. The association of TaTGW-7A with TGW was further validated in a natural population and Chinese mini-core collections. Quantitative real-time PCR revealed higher transcript levels of TaTGW-7Aa than those of TaTGW-7Ab during grain development. High frequencies of the superior allele TaTGW-7Aa for higher TGW in Chinese mini-core collections (65.0%) and 501 wheat varieties (86.0%) indicated a strong and positive selection of this allele in wheat breeding. The molecular markers TGW7A and TG9 can be used for improvement of TGW in breeding programs.
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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".