A species-wide inventory of receptor-like kinases in Arabidopsis thaliana
Bibliographic record
Abstract
BACKGROUND: The receptor-like kinases (RLKs) are the largest family of proteins in plants. Characterized members play critical roles in diverse processes from growth to immunity, and yet the majority do not have a known function. Assigning function to RLKs poses a significant challenge due to the specificity of ligand recognition and because of the often pleiotropic or redundant functions RLKs possess. These problems inhibit the important work of identifying stress-related receptors that may be targets for crop improvement. Identification of stress-related evolutionary signatures can provide a way to expedite the discovery of candidate receptors. Pan-genome analysis can be used to compare naturally occurring variants within a species to identify evolutionary signatures that may otherwise be hidden by using only a single ecotype. RESULTS: Using 146 ecotypes of Arabidopsis, we generated a pan-RLKome to investigate species-wide natural diversity and identify structural variation and other patterns indicative of stress adaptation. We discovered significant presence/absence variation across a subset of RLKs, most of which occurred in specific subclades nested within receptor subfamilies. These same subclades tended to have arisen through proximal or tandem duplication, both of which are common mechanisms during the expansion of stress-related genes. We also identified strong positive selection across many gene subfamilies and a bias of positive selection in the extracellular domains of receptors. This suggests escape from adaptive conflict within the extracellular domain may have played a large role in the evolution and adaptation of the RLKs. CONCLUSION: Taken together, this work represents an excellent tool for the comparative study of RLKs and has identified lineages and subclades within RLK subfamilies with the hallmarks of involvement in stress adaptation.
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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) | 0.001 | 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".