Increased Serine-Arginine (SR) Protein Phosphorylation Changes Pre-mRNA Splicing in Hypoxia
Bibliographic record
Abstract
The removal of introns from mRNA precursors (pre-mRNAs) is an essential step in eukaryotic gene expression. The splicing machinery heavily contributes to biological complexity and especially to the ability of cells to adapt to altered cellular conditions. Inhibitory PAS domain protein (IPAS), a dominant negative regulator of hypoxia-inducible gene expression, is generated from hypoxia inducible transcription factor-3α (HIF-3α) pre-mRNA by an alternative splicing mechanism. Inactivation of the IPAS transcript in mice leads to the neo-vascularization of the cornea, suggesting that IPAS is an important regulator of anti-angiogenesis in this tissue. For the first time we demonstrate that serine-arginine (SR) proteins are involved in oxygen tension-dependent changes in pre-mRNA splicing. SR proteins isolated from hypoxic cells differentially interact with RNA (compared with proteins isolated from cells cultured under normoxic conditions). They possess the differential ability to activate hypoxia-dependent splice sites, and they are more phosphorylated than those isolated from normoxic HeLa cells. We also show that expression of SR protein kinases (CLK1, SRPK1, SRPK2) in hypoxic cells is elevated at mRNA and protein levels. Increased expression of CLK1 kinase is regulated by HIFs. Reduction of CLK1 cellular expression levels reduces hypoxia-dependent full-length carbonic anhydrase IX (CAIX) mRNA and CAIX protein formation and changes hypoxia-dependent cysteine-rich angiogenic inducer 61 (Cyr61) mRNA isoform formation profiles.
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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".