Involvement of Arabidopsis RACK1 in Protein Translation and Its Regulation by Abscisic Acid
Bibliographic record
Abstract
Earlier studies have shown that RACK1 functions as a negative regulator of abscisic acid (ABA) responses in Arabidopsis (Arabidopsis thaliana), but the molecular mechanism of the action of RACK1 in these processes remains elusive. Global gene expression profiling revealed that approximately 40% of the genes affected by ABA treatment were affected in a similar manner by the rack1 mutation, supporting the view that RACK1 is an important regulator of ABA responses. On the other hand, coexpression analysis revealed that more than 80% of the genes coexpressed with RACK1 encode ribosome proteins, implying a close relationship between RACK1's function and the ribosome complex. These results implied that the regulatory role for RACK1 in ABA responses may be partially due to its putative function in protein translation, which is one of the major cellular processes that mammalian and Saccharomyces cerevisiae RACK1 is involved in. Consistently, all three Arabidopsis RACK1 homologous genes, namely RACK1A, RACK1B, and RACK1C, complemented the growth defects of the S. cerevisiae cross pathway control2/rack1 mutant. In addition, RACK1 physically interacts with Arabidopsis Eukaryotic Initiation Factor6 (eIF6), whose mammalian homolog is a key regulator of 80S ribosome assembly. Moreover, rack1 mutants displayed hypersensitivity to anisomycin, an inhibitor of protein translation, and displayed characteristics of impaired 80S functional ribosome assembly and 60S ribosomal subunit biogenesis in a ribosome profiling assay. Gene expression analysis revealed that ABA inhibits the expression of both RACK1 and eIF6. Taken together, these results suggest that RACK1 may be required for normal production of 60S and 80S ribosomes and that its action in these processes may be regulated by ABA.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".