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 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) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".