Molecular mapping of five soybean genes involved in male-sterility, female-sterility
Bibliographic record
Abstract
In soybean, asynaptic and desynaptic mutants lead to abnormal meiosis and fertility reduction. Several male-sterile, female-sterile mutants have been identified and studied in soybean, however, some of these mutants have not been mapped to locations on soybean chromosomes. The objectives of this study were to molecularly map five male-sterile, female-sterile genes (st2, st4, st5, st6, and st7) in soybean and compare the map locations of these genes with already mapped sterility genes. Microsatellite markers were used in bulked segregant analyses to locate all five male-sterile, female-sterile genes to soybean chromosomes, and markers from the corresponding chromosomes were used on F2 populations to generate genetic linkage maps. The st2, st4, st5, st6, and st7 genes were located on molecular linkage group (MLG) B1 (chromosome 11), MLG D1a (chromosome 01), MLG F (chromosome 13), MLG B2 (chromosome 14), and D1b (chromosome 02), respectively. The st2, st4, st5, st6, and st7 genes were flanked to 10.3 (∼ 399 kb), 6.3 (∼ 164 kb), 3.9 (∼ 11.8 Mb), 11.0 (∼ 409 kb), and 5.3 cM (∼ 224 kb), and the flanked regions contained 57, 17, 362, 52, and 17 predicted genes, respectively. Future characterization of candidate genes should facilitate identification of the male- and female-fertility genes, which may provide vital insights on structure and function of genes involved in the reproductive pathway in soybean.
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 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) | 0.000 | 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) | 0.001 | 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 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".