Evolution of strigolactone receptors by gradual neo-functionalization of KAI2 paralogues
Bibliographic record
Abstract
BACKGROUND: Strigolactones (SLs) are a class of plant hormones that control many aspects of plant growth. The SL signalling mechanism is homologous to that of karrikins (KARs), smoke-derived compounds that stimulate seed germination. In angiosperms, the SL receptor is an α/β-hydrolase known as DWARF14 (D14); its close homologue, KARRIKIN INSENSITIVE2 (KAI2), functions as a KAR receptor and likely recognizes an uncharacterized, endogenous signal ('KL'). Previous phylogenetic analyses have suggested that the KAI2 lineage is ancestral in land plants, and that canonical D14-type SL receptors only arose in seed plants; this is paradoxical, however, as non-vascular plants synthesize and respond to SLs. RESULTS: We have used a combination of phylogenetic and structural approaches to re-assess the evolution of the D14/KAI2 family in land plants. We analysed 339 members of the D14/KAI2 family from land plants and charophyte algae. Our phylogenetic analyses show that the divergence between the eu-KAI2 lineage and the DDK (D14/DLK2/KAI2) lineage that includes D14 occurred very early in land plant evolution. We show that eu-KAI2 proteins are highly conserved, and have unique features not found in DDK proteins. Conversely, we show that DDK proteins show considerable sequence and structural variation to each other, and lack clearly definable characteristics. We use homology modelling to show that the earliest members of the DDK lineage structurally resemble KAI2 and that SL receptors in non-seed plants likely do not have D14-like structure. We also show that certain groups of DDK proteins lack the otherwise conserved MORE AXILLARY GROWTH2 (MAX2) interface, and may thus function independently of MAX2, which we show is highly conserved throughout land plant evolution. CONCLUSIONS: Our results suggest that D14-like structure is not required for SL perception, and that SL perception has relatively relaxed structural requirements compared to KAI2-mediated signalling. We suggest that SL perception gradually evolved by neo-functionalization within the DDK lineage, and that the transition from KAI2-like to D14-like protein may have been driven by interactions with protein partners, rather than being required for SL perception per se.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".