MicroRNA identification and expression analysis of wheat thermo-sensitive male sterile line BNS366 for fertility transformation
Bibliographic record
Abstract
Introduction Thermo-sensitive male sterile lines are the key element in the two-line hybrid system of wheat; some specific microRNAs (miRNAs) are involved in the development of anthers in plants, being an important cause of male sterility. Bai-Nong Sterility 366 (BNS366) is an excellent material for the study of thermo-sensitive male sterility, but no information is available on the role of miRNAs in regulating fertility in BNS366. Methods In this study, miRNAs in the pollen mother cell periods and the tetrad periods of the low-temperature sterile and normal fertile anthers of BNS366 were characterized using RNA sequencing (RNA-seq). Results MiRNA sequencing identified 22 differentially expressed known miRNAs and eight novel miRNAs with the largest differential expression folds. The prediction of target genes of the 30 miRNAs yielded 25 target genes, which were highly expressed in wheat spike, and mainly regulated by 13 miRNAs. Gene Ontology (GO) analysis showed that these target genes mainly related to DNA replication and transcription. Five miRNAs (miR9662a, miR5062, miR9662b, miR9653a, and miR9672b) showed opposite expression patterns with their respective potential target genes in BNS366 anther of different fertility. TraesCS5D02G192700 is a potential target gene for miR5062 and encodes an argonaute protein, which functions in meiotic prophase germ cell development and maintenance of meiosis. Conclusion Our findings suggest that the miR5062-argonaute module may plays a pivotal role in the fertility transformation of BNS366. Based on these results, the miRNA-target gene regulatory network involved in the fertility restoration of BNS366 at low temperatures was proposed.
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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) | 0.000 | 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 | 0.001 |
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".