Smg1 is required for embryogenesis and regulates diverse genes via alternative splicing coupled to nonsense-mediated mRNA decay
Bibliographic record
Abstract
Smg1 is a PI3K-related kinase (PIKK) associated with multiple cellular functions, including DNA damage responses, telomere maintenance, and nonsense-mediated mRNA decay (NMD). NMD degrades transcripts that harbor premature termination codons (PTCs) as a result of events such as mutation or alternative splicing (AS). Recognition of PTCs during NMD requires the action of the Upstream frameshift protein Upf1, which must first be phosphorylated by Smg1. However, the physiological function of mammalian Smg1 is not known. By using a gene-trap model of Smg1 deficiency, we show that this kinase is essential for mouse embryogenesis such that Smg1 loss is lethal at embryonic day 8.5. High-throughput RNA sequencing (RNA-Seq) of RNA from cells of Smg1-deficient embryos revealed that Smg1 depletion led to pronounced accumulation of PTC-containing splice variant transcripts from approximately 9% of genes predicted to contain AS events capable of eliciting NMD. Among these genes are those involved in splicing itself, as well as genes not previously known to be subject to AS-coupled NMD, including several involved in transcription, intracellular signaling, membrane dynamics, cell death, and metabolism. Our results demonstrate a critical role for Smg1 in early mouse development and link the loss of this NMD factor to major and widespread changes in the mammalian transcriptome.
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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) | 0.001 | 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".