Genetic diversity of maize kernel starch-synthesis genes with SNAPs
Bibliographic record
Abstract
Measuring genetic diversity in populations of a crop species is very important for understanding the genetic structure of and subsequently improving the crop species by genetic manipulation. Single-nucleotide amplified polymorphisms (SNAPs) among and within maize populations of waxy, dent, and sweet corns at 25 single-nucleotide polymorphism (SNP) sites in 6 kernel starch-synthesis genes (sh2, bt2, su1, ae1, wx1, and sh1) were determined. Because of the intensive selection of some favorable alleles in starch-synthesis genes during the breeding process, and the resultant strong linkage disequilibrium (LD), the number of haplotypes in each population was far less than expected. Subsequent phenetic clustering analysis with the SNAPs indicated that the dent, waxy, and sweet corns formed distinct subclusters, except in a few incidences. LD was surveyed among SNAPs of intragenic, intergenic, and intrachromosomal SNPs in whole and subpopulations, which revealed that some SNAPs showed high LD with many other SNAPs, but some SNAPs showed low or no significant LD with others, depending on the subpopulation, indicating that these starch genes have undergone different selection in each subpopulation during the breeding process. Because the starch synthesis genes used in this study are important in maize breeding, the genetic diversity, LD, and accessions having rare SNAP alleles might be valuable in maize improvement programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".