The Application of Molecular Markers to Accelerate the Recovery of Cytoplasmic and Nuclear Male Sterility in South African Onion (Allium cepa L.) Hybrid Parental Lines
Bibliographic record
Abstract
Male sterility is important to prevent self-pollination and loss of the onion hybrid genotype. Classic methods require 4-8 years of progeny testing before the cytoplasm type can be determined. An accurate and time-saving method was needed. Various types of markers were tested for application to South African onion parental lines of hybrid cultivars, and which could determine male sterility and maintainer genotypes accurately and easily with large numbers of samples. Five cytoplasmic (5’cob, orfA501, orf725, IGS and cob-type 2) and four nuclear markers (jnurf13, isotig34671_610, isotig30856_1351 and isotig29186_1830) were sourced. Genomic DNA was isolated from onion seedlings and young leaves growing from bulbs in the Agricultural Research Council (ARC) research field. PCR marker amplification products were separated by agarose or denaturing polyacrylamide gel electrophoresis (PAGE) gels. Real-time polymerase chain reaction (PCR) was performed with custom TaqMan® SNP genotyping assays containing primer/probe pairs designed to detect single nucleotide polymorphisms (SNPs) linked to the nuclear Ms locus. OrfA501 proved useful as a presence/absence marker for cytoplasmic male sterility, while TaqMan® SNP genotyping assays were superior to the jnurf13 nuclear marker in terms of rapid throughput. PCR molecular markers and custom TaqMan® SNP genotyping assays were efficient in screening the onion lines rapidly and accurately for their cytoplasmic and nuclear male sterility genotype. These methods reduced the time to identify the correct genotype of male sterile and maintainer lines, gave accurate genotypic information and proved to be useful on a larger scale. These molecular marker methods will facilitate the production of the correct seed for commercialization of onion lines worldwide.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".