Transcriptomics at Maize Embryo/Endosperm Interfaces Identifies a Transcriptionally Distinct Endosperm Subdomain Adjacent to the Embryo Scutellum
Bibliographic record
Abstract
Seeds are complex biological systems comprising three genetically distinct tissues nested one inside another (embryo, endosperm, and maternal tissues). However, the complexity of the kernel makes it difficult to understand intercompartment interactions without access to spatially accurate information. Here, we took advantage of the large size of the maize (Zea mays) kernel to characterize genome-wide expression profiles of tissues at different embryo/endosperm interfaces. Our analysis identifies specific transcriptomic signatures in two interface tissues compared with whole seed compartments: the scutellar aleurone layer and the newly named endosperm adjacent to scutellum (EAS). The EAS, which appears around 9 d after pollination and persists for around 11 d, is confined to one to three endosperm cell layers adjacent to the embryonic scutellum. Its transcriptome is enriched in genes encoding transporters. The absence of the embryo in an embryo specific mutant can alter the expression pattern of EAS marker genes. The detection of cell death in some EAS cells together with an accumulation of crushed cell walls suggests that the EAS is a dynamic zone from which cell layers in contact with the embryo are regularly eliminated and to which additional endosperm cells are recruited as the embryo grows.
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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 | 0.001 |
| 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".