Comparative genomics of the chitinase gene family in lodgepole and jack pines: contrasting responses to biotic threats and landscape level investigation of genetic differentiation
Bibliographic record
Abstract
The sister species, lodgepole pine (Pinus contorta var. latifolia Engelm.) and jack pine (Pinus banksiana Lamb), face pressures from a multitude of biotic agents, including mountain pine beetle (Dendroctonus ponderosae Hopkins, 1902) and their pathogenic fungal associates (e.g., Grosmannia clavigera (Rob.-Jeffr. & R.W. Davidson) Zipfel, Z.W. de Beer & M.J. Wingf.), mistletoe (Arceuthobium americanum Nutt. ex A.Gray), and the pathogen causing western gall rust (Cronartium harknessii E. Meinecke). Here, we report new stem tissue transcriptome resources developed for lodgepole and jack pines subjected to these biotic stresses. The annotated transcriptomes were compared to determine species-specific responses to the necrotrophic G. clavigera and the biotrophic Cronartium harknessii. We focused on chitinases, a family that includes members with well-documented roles in defense. Putative chitinase family members were identified via annotation, sequence similarity to reference chitinase genes, phylogenetic analyses, and in silico motif characterization. RNA-Seq revealed marked differences in the responses of lodgepole and jack pine chitinases to G. clavigera and Cronartium harknessii. The potential for adaptive variation in chitinases was investigated by assessing the level of genetic differentiation between and within lodgepole and jack pines using single nucleotide polymorphisms within chitinases. These analyses illustrate the potential of combining transcriptomic and genotyping resources to investigate genotype–phenotype correlations for non-model species.
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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 | 0.000 | 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 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".