A Nucleolar PUF RNA-binding Protein with Specificity for a Unique RNA Sequence
Bibliographic record
Abstract
PUF proteins are a conserved group of sequence specific RNA-binding proteins that bind to RNA in a modular fashion. The RNA-binding domain of PUF proteins typically consists of eight clustered Puf repeats. Plant genomes code for large families of PUF proteins that show significant variability in their predicted Puf repeat number, organization, and amino acid sequence. Here we sought to determine whether the observed variability in the RNA-binding domains of four plant PUFs results in a preference for nonclassical PUF RNA target sequences. We report the identification of a novel RNA binding sequence for a nucleolar Arabidopsis PUF protein that contains an atypical RNA-binding domain. The Arabidopsis PUM23 (APUM23) binding sequence was 10 nucleotides in length, contained a centrally located UUGA core element, and had a preferred cytosine at nucleotide position 8. These RNA sequence characteristics differ from those of other PUF proteins, because all natural PUFs studied to date bind to RNAs that contain a conserved UGU sequence at their 5' end and lack specificity for cytosine. Gel mobility shift assays validated the identity of the APUM23 binding sequence and supported the location of 3 of the 10 predicted Puf repeats in APUM23, including the cytosine-binding repeat. The preferred 10-nucleotide sequence bound by APUM23 is present within the 18S rRNA sequence, supporting the known role of APUM23 in 18S rRNA maturation. This work also reveals that APUM23, an ortholog of yeast Nop9, could provide an advanced structural backbone for Puf repeat engineering and target-specific regulation of cellular RNAs.
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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) | 0.002 | 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".