Genome-wide RNA structure changes during human neurogenesis drive gene regulatory networks
Bibliographic record
Abstract
Abstract The distribution, dynamics and function of RNA structures in human development is under- explored. Here, we systematically assayed RNA structural dynamics and its relationship with gene expression, translation and decay during human neurogenesis. We observed that the human ESC transcriptome is globally more structurally accessible than that of differentiated cells; and undergo extensive RNA structure changes, particularly in the 3’UTR. Additionally, RNA structure changes during differentiation is associated with translation and decay. We also identified stage-specific regulation as RBP and miRNA binding, as well as splicing is associated with structure changes during early and late differentiation, respectively. Further, RBPs serve as a major factor in structure remodelling and co-regulates additional RBPs and miRNAs through structure. We demonstrated an example of this by showing that PUM2-induced structure changes on LIN28A enable miR-30 binding. This study deepens our understanding of the wide-spread and complex role of RNA-based gene regulation during human development.
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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 | 0.000 |
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".