小麦低分子量谷蛋白亚基基因5′侧翼保守序列染色体组特异性DNA变异的分析及验证
Bibliographic record
Abstract
根据33个低分子量麦谷蛋白亚基(LMW-GS)基因5′侧翼序列的相似性进行聚类分析, 可将其划分成8个类群, 这与基于N末端推导氨基酸序列进行的类群划分结果完全一致. 序列比对发现, 各类群基因5′侧翼保守序列间存在DNA多态性, 共发现34个多态性位点, 其中18个为潜在单核苷酸多态性位点(SNPs, single nucleotide polymorphisms). 除1个LMW-GS类群之外, 其余7个类群的5′侧翼序列均具有类群特异性DNA变异位点. 根据类群间的DNA多态性对这7个类群设计了特异引物, 利用普通小麦(Triticum aestivum L.)品种中国春及其第1同源群双端体系对其进行染色体定位分析, 揭示了1AS, 1BS和1DS上分别有第2, 1和4类群. 对PCR产物的克隆测序进一步验证了不同染色体组上的LMW-GS基因类群间5′侧翼序列具有特异性. 这些结果表明, LMW-GS基因的编码区及其5′侧翼保守序列可能是协调进化的. 本文报道的7对引物可对7类LMW-GS基因的完整编码区进行特异扩增, 因而能在小麦复杂的遗传背景下有目的地对某一类LMW-GS基因进行分离克隆, 这有助于弄清单个LMW-GS对小麦品质的贡献. 同时, 在小麦育种中, 这些标记对于有效地选择与品质密切相关的LMW-GS组分有一定应用价值.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".