A maternal transcriptome bias in early <i>Arabidopsis</i> embryogenesis
Bibliographic record
Abstract
After fertilization in animals, maternal mRNAs and proteins regulate development until the onset of zygotic transcription. In plants, the extent of maternal regulation of early embryo development has been less clear: two hybrid combinations of rice zygotes have a strong maternal transcript bias, zygotes of a third rice hybrid produced by gamete fusion show a small percentage of maternally biased genes, while Arabidopsis Col/Cvi and Col/Ler hybrid embryos display symmetric and asymmetric parental genome activation, respectively. Here, we explore parent-of-origin transcriptome behavior in the Arabidopsis Col/Tsu hybrid, which was previously shown to display maternal effects for embryo defective mutants indistinguishable from those of the reference ecotype, Col. Analysis of Col/Tsu transcriptomes revealed a reciprocal maternal bias in thousands of genes in zygotes and octant stage embryos. Several lines of evidence suggest that this transient maternal bias is due to preferential transcription of maternal alleles in the zygote, rather than inheritance of transcripts from the egg. Our results extend previous observations that parent-of-origin contributions to early embryogenesis differ between hybrids of Arabidopsis, show that the maternal genome plays a predominant role in early embryos of Col/Tsu, and point to a maternal transcriptome bias in early embryos of the Arabidopsis reference ecotype Columbia.
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".