Non–redundancy of Rice Mutant Library for Male Gametogenesis Confirmed by Bulked Segregants Analysis Using Illumina BeadsArray
Bibliographic record
Abstract
Mutant resources play a crucial role in unraveling the genetic network controlling traits of interest.In this study, we focused on pollen-sterile mutants as important genetic resources for understanding the genetic regulation of male gametogenesis.We employed high-throughput genotyping technologies using Illumina BeadArray to map the responsible genes for male gametogenesis in rice; four SPOROPHYTIC POLLEN STERILITY (SPS2, SPS3, SPS4, SPS7) and four GAMETOPHYTIC POLLEN STERILITY (GPS1, GPS2, GPS9, GPS10).Using 287 single nucleotide polymorphism (SNP) markers, we detected polymorphisms between the japonica cultivar Taichung 65 (T65) and Hinohikari.Bulked segregant analysis (BSA) based on DNA marker analysis was performed to identify candidate markers tightly linked to the causal genes.The analysis revealed candidate markers for each mutant line, such as Mk240 for SPS2 and Mk94 and Mk126 for GPS1.Linkage mapping using the PCR-based markers confirmed the map positions of these candidate markers.Our study demonstrates the utility of high-throughput genotyping technologies combined with BSA for the genetic characterization of mutant stocks.The identified candidate markers provide valuable resources for future studies aiming to understand the molecular mechanisms underlying pollen development and male gametogenesis in rice.The systematic gathering and reduction of redundancy in pollen sterile mutants are essential for a comprehensive understanding of the molecular networks involved in post-meiotic male gametogenesis.
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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) | 0.001 | 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) | 0.002 | 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".