AtJAC1 Regulates Nuclear Accumulation of GRP7, Influencing RNA Processing of FLC Antisense Transcripts and Flowering Time in Arabidopsis
Bibliographic record
Abstract
Lectins selectively recognize sugars or glycans for defense in living cells, but less is known about their roles in the development process and the functional network with other factors. Here, we show that Arabidopsis (Arabidopsis thaliana) JACALIN-LECTIN LIKE1 (AtJAC1) functions in flowering time control. Loss of function of AtJAC1 leads to precocious flowering, whereas overexpression of AtJAC1 causes delayed flowering. AtJAC1 influences flowering through regulation of the key flowering repressor gene FLOWERING LOCUS C (FLC). Genetic analysis revealed that AtJAC1's function is mostly dependent on GLYCINE-RICH RNA-BINDING PROTEIN7 (GRP7), an upstream regulator of FLC. Biochemical and cell biological data indicated that AtJAC1 interacted physically with GRP7 specifically in the cytoplasm. AtJAC1 influences the nucleocytoplasmic distribution of GRP7, with predominant nuclear localization of GRP7 when AtJAC1 function is lost but retention of GRP7 in the cytoplasm when AtJAC1 is overexpressed. A temporal inducible assay suggested that AtJAC1's regulation of flowering could be compromised by the nuclear accumulation of GRP7. In addition, GRP7 binds to the antisense precursor messenger RNA of FLC through a conserved RNA motif. Loss of GRP7 function leads to the elevation of total FLC antisense transcripts and reduced proximal-distal polyadenylation ratio, as well as histone methylation changes in the FLC gene body region and increased total functional sense FLC transcript. Attenuating the direct binding of GRP7 with competing artificial RNAs leads to changes of FLC antisense precursor messenger RNA processing and flowering transition. Taken together, our study indicates that AtJAC1 coordinates with GRP7 in shaping plant development through the regulation of RNA processing in Arabidopsis.
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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".