Role of <i>cis</i>-acting elements in the control of SERCA2b Ca2+ pump mRNA decay by nuclear proteins
Bibliographic record
Abstract
Alternative splicing at position 3495 b yields SERCA2 (sarco/endoplasmic reticulum Ca2+ pump 2) RNA species, namely SERCA2a and SERCA2b which differ in 3'-end regions. This results in SERCA2b RNA being less stable. In vitro decay experiments show that, in the presence of protein extracts from nuclei of LVMs (left ventricular myocytes), the rate of decay of both SERCA2b RNA and synthetic RNA from its 3'-region is greater than that of the corresponding SERCA2a RNA. To search for cis-acting instability elements in the 3'-region of SERCA2b, we examined the effects of LVM nuclear protein extracts on the in vitro decay of six short overlapping capped [m7G(5')ppp(5')Gm] and polyadenylated (A40) RNA fragments from the 3'-end region (3444-4472) of SERCA2b. The proximal fragment 2B1 (3444-3753) was the most unstable. 2B1 RNA without a cap or a polyadenylated tail was analysed further in electrophoretic mobility-shift assays, and was observed to bind to protein(s) in the nuclear extracts. Based on competition for binding to nuclear proteins between radiolabelled 2B1 RNA and short unlabelled RNA fragments, the cis-acting element involved in this binding was the sequence 2B1-4. 2B1-4 is a 35-base (3521-3555, CCAGUCCUGCUCGUUGUGGGCGUGCACCGAGGGGG) GC-rich region just past the splice site (3495). Nuclear extracts decreased the electrophoretic mobility of the radiolabelled 2B1-4 RNA which bound to two proteins (19 and 21 kDa) in cross-linking experiments. Excess 2B1-4 RNA decreased the decay of the 2B1 RNA by the nuclear protein extract. 2B1-del 4 RNA (2B1 with the 2B1-4 domain deleted) also decayed more slowly than the control 2B1 RNA. Thus SERCA2b contains a novel GC-rich cis-acting element involved in its decay by nuclear proteins.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".