Transcriptome dynamics in the Arabidopsis male germline during pollen–pistil interactions
Bibliographic record
Abstract
When pollen lands on a receptive stigma, it germinates and extends a tube inside the transmitting tissue of the pistil to deliver the sperm cells for double fertilization. The growth of the pollen tube triggers significant alterations in its gene expression. The extent to which these changes occur in the vegetative cell or extend to the sperm cells transported by the tube is unclear but important to determine since sperm cells are believed to acquire a competency for fertilization during pollen-pistil interactions. To address these questions, we compared the transcriptomes of Arabidopsis thaliana sperm cells and vegetative nuclei isolated from mature pollen grains with those isolated from in vitro-grown pollen tubes. Importantly, we also compared transcriptomes of sperm cells obtained from pollen tubes grown under semi-in vivo conditions where tubes passed through a pistil section. Our data show that extensive transcriptomic changes occur in sperm cells during pollen tube growth, some of which are elicited only as sperms are carried through the pistil. Their analysis reveals a host of previously unidentified transcripts that may facilitate sperm maturation and gamete fusion. The vegetative cell undergoes even more extensive transcriptomic reprogramming during pollen tube growth, mainly through the upregulation of genes associated with pollen tube growth and vesicle-mediated transport. Interestingly, ATAC-seq data show that the promoters of genes upregulated in sperm during pollen tube growth are already accessible in sperm chromatin of mature pollen grains, suggesting pre-configured promoter accessibility. This study's expression data can be further explored here: https://bar.utoronto.ca/eFP-Seq_Browser/.
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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".