Plant phase extraction: A method for enhanced discovery of the RNA-binding proteome and its dynamics in plants
Bibliographic record
Abstract
RNA-binding proteins (RBPs) play critical roles in posttranscriptional gene regulation. Current methods of systematically profiling RBPs in plants have been predominantly limited to proteins interacting with polyadenylated (poly(A)) RNAs. We developed a method called plant phase extraction (PPE), which yielded a highly comprehensive RNA-binding proteome (RBPome), uncovering 2,517 RBPs from Arabidopsis (Arabidopsis thaliana) leaf and root samples with a highly diverse array of RNA-binding domains. We identified traditional RBPs that participate in various aspects of RNA metabolism and a plethora of nonclassical proteins moonlighting as RBPs. We uncovered constitutive and tissue-specific RBPs essential for normal development and, more importantly, revealed RBPs crucial for salinity stress responses from a RBP-RNA dynamics perspective. Remarkably, 40% of the RBPs are non-poly(A) RBPs that were not previously annotated as RBPs, signifying the advantage of PPE in unbiasedly retrieving RBPs. We propose that intrinsically disordered regions contribute to their nonclassical binding and provide evidence that enzymatic domains from metabolic enzymes have additional roles in RNA binding. Taken together, our findings demonstrate that PPE is an impactful approach for identifying RBPs from complex plant tissues and pave the way for investigating RBP functions under different physiological and stress conditions at the posttranscriptional level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".