Complex Evolutionary Dynamics of Massively Expanded Chemosensory Receptor Families in an Extreme Generalist Chelicerate Herbivore
Bibliographic record
Abstract
While mechanisms to detoxify plant produced, anti-herbivore compounds have been associated with plant host use by herbivores, less is known about the role of chemosensory perception in their life histories. This is especially true for generalists, including chelicerate herbivores that evolved herbivory independently from the more studied insect lineages. To shed light on chemosensory perception in a generalist herbivore, we characterized the chemosensory receptors (CRs) of the chelicerate two-spotted spider mite, Tetranychus urticae, an extreme generalist. Strikingly, T. urticae has more CRs than reported in any other arthropod to date. Including pseudogenes, 689 gustatory receptors were identified, as were 136 degenerin/Epithelial Na+ Channels (ENaCs) that have also been implicated as CRs in insects. The genomic distribution of T. urticae gustatory receptors indicates recurring bursts of lineage-specific proliferations, with the extent of receptor clusters reminiscent of those observed in the CR-rich genomes of vertebrates or C. elegans Although pseudogenization of many gustatory receptors within clusters suggests relaxed selection, a subset of receptors is expressed. Consistent with functions as CRs, the genomic distribution and expression of ENaCs in lineage-specific T. urticae expansions mirrors that observed for gustatory receptors. The expansion of ENaCs in T. urticae to > 3-fold that reported in other animals was unexpected, raising the possibility that ENaCs in T. urticae have been co-opted to fulfill a major role performed by unrelated CRs in other animals. More broadly, our findings suggest an elaborate role for chemosensory perception in generalist herbivores that are of key ecological and agricultural importance.
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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 | 0.000 |
| 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 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".