Do genetic drift and accumulation of deleterious mutations preclude adaptation? Empirical investigation using <scp>RAD</scp>seq in a northern lacustrine fish
Bibliographic record
Abstract
Understanding genomic signatures of divergent selection underlying long-term adaptation in populations located in heterogeneous environments is a key goal in evolutionary biology. In this study, we investigated neutral, adaptive and deleterious genetic variation using 7,192 SNPs in 31 Lake Trout (Salvelinus namaycush) populations (n = 673) from Québec, Canada. Average genetic diversity was low, weakly shared among lakes, and positively correlated with lake size, indicating a major role for genetic drift subsequent to lake isolation. Putatively deleterious mutations were on average at lower frequencies than the other SNPs, and their abundance relative to the entire polymorphism in each population was positively correlated with inbreeding, suggesting that the effectiveness of purifying selection was negatively correlated with inbreeding, as predicted from theory. Despite evidence for pronounced genetic drift and inbreeding, several outlier loci were associated with temperature and found in or close to genes with biologically relevant functions notably related to heat stress and immune responses. Outcomes of gene-temperature associations were influenced by the inclusion of the most inbred populations, in which allele frequencies deviated the most from model predictions. This result illustrates challenge in identifying gene-environment associations in cases of high genetic drift and restricted gene flow and suggests limited adaptation in populations experiencing higher inbreeding. We discuss the relevance of these findings for the conservation and management, notably regarding stocking and genetic rescue, of Lake Trout populations and other species inhabiting highly fragmented habitats.
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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".