Transcriptomic analysis between self- and cross-pollinated pistils of tea plants (Camellia sinensis)
Bibliographic record
Abstract
Self-incompatibility (SI) is a major barrier that obstructs the breeding process in most horticultural plants including tea plants (Camellia sinensis). The aim of this study was to elucidate the molecular mechanism of SI in tea plants through a high throughput transcriptome analysis. In this study, the transcriptomes of self- and cross-pollinated pistils of two tea cultivars ‘Fudingdabai’ and ‘Yulv’ were compared to elucidate the SI mechanism of tea plants. In addition, the ion components and pollen tube growth in self- and cross-pollinated pistils were investigated. Our results revealed that both cultivars had similar pollen activities and cross-pollination could promote the pollen tube growth. In tea pistils, the highest ion content was potassium (K+), followed by calcium (Ca2+), magnesium (Mg2+) and phosphorus (P5+). Ca2+ content increased after self-pollination but decreased after cross-pollination, while K+ showed reverse trend with Ca2+. A total of 990 and 3 common differentially expressed genes (DEGs) were identified in un-pollinated vs. pollinated pistils and self- vs. cross-pollinated groups after 48 h, respectively. Function annotation indicated that three genes encoding UDP-glycosyltransferase 74B1 (UGT74B1), Mitochondrial calcium uniporter protein 2 (MCU2) and G-type lectin S-receptor-like serine/threonine-protein kinase (G-type RLK) might play important roles during SI process in tea plants. Ca2+ and K+ are important signal for SI in tea plants, and three genes including UGT74B1, MCU2 and G-type RLK play essential roles during SI signal transduction.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".