Parallel and lineage‐specific molecular adaptation to climate in boreal black spruce
Bibliographic record
Abstract
In response to selective pressure, adaptation may follow different genetic pathways throughout the natural range of a species due to historical differentiation in standing genetic variation. Using 41 populations of black spruce (Picea mariana), the objectives of this study were to identify adaptive genetic polymorphisms related to temperature and precipitation variation across the transcontinental range of the species, and to evaluate the potential influence of historical events on their geographic distribution. Population structure was first inferred using 50 control nuclear markers. Then, 47 candidate gene SNPs identified in previous genome scans were tested for relationship with climatic factors using an F(ST) -based outlier method and regressions between allele frequencies and climatic variations. Two main intraspecific lineages related to glacial vicariance were detected at the transcontinental scale. Within-lineage analyses of allele frequencies allowed the identification of 23 candidate SNPs significantly related to precipitation and/or temperature variation, among which seven were common to both lineages, eight were specific to the eastern lineage and eight were specific to the western lineage. The implication of these candidate SNPs in adaptive processes was further supported by gene functional annotations. Multiple evidences indicated that the occurrence of lineage-specific adaptive SNPs was better explained by selection acting on historically differentiated gene pools rather than differential selection due to heterogeneity of interacting environmental factors and pleiotropic effects. Taken together, these findings suggest that standing genetic variation of potentially adaptive nature has been modified by historical events, hence affecting the outcome of recent selection and leading to different adaptive routes between intraspecific lineages.
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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".