Sequence context for transcription and translation of the Arabidopsis<i>RPL23aA</i>and<i>RPL23aB</i>paralogs
Bibliographic record
Abstract
The 80S cytoplasmic ribosome is responsible for translating the transcriptome into the proteome. Demand for ribosome production depends on growth rate, and both the ribosomal RNA (rRNA) and ribosomal protein (RP) components must respond coordinately and rapidly to positive and negative growth stimuli to prevent deleterious effects of excess or insufficient subunits. The 81 RPs of the Arabidopsis 80S ribosome are encoded by multigene families that often exhibit overlapping patterns of transcript accumulation; however, only one isoform of each RP family (with the exception of a small number of acidic RPs) assembles into a single ribosome. Here we dissected the regulatory regions (RRs) of both members of the RPL23a family (RPL23aA and RPL23aB) to identify salient cis-acting elements involved in transcriptional, posttranscriptional, and translational regulation of expression. Full length and truncated RRs of RPL23a paralogs were cloned upstream of a GUS reporter gene and expressed in Arabidopsis transgenic plants. High level expression in mitotically active tissues, driven by RPL23aA and RPL23aB RRs, required TATA-box, telo-box, and site II motif elements. First and second introns were found to play a minor role in posttranscriptional regulation of paralogs, and conserved transcript features (e.g., UTR base composition) may be involved in enhancing translational efficiency. Overall, our results indicate that RPL23a expression is governed by a complex network of multiple regulatory layers.
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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) | 0.002 | 0.002 |
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".