Conservation genomics of Atlantic salmon: variation in gene expression between and within regions of the Bay of Fundy
Bibliographic record
Abstract
Due to difficulties in identifying important within-species biodiversity for effective species management and conservation, the use of multiple complementary sources of information is required to identify and assess the designation of conservation units based on the degree of variation among populations within a species. In this study, we combined estimates of microsatellite and transcriptomic variation to assess the population structure and potential for adaptive variation of threatened Atlantic salmon, Salmo salar, among rivers in the Bay of Fundy. In general, population structure identified by genetic differentiation was consistent with the patterns of variation in gene expression, although there was not a strong correlation between neutral genetic variation and variation in gene expression. Both data sets provided clear indication of strong regional differentiation between rivers located within the inner Bay of Fundy relative to rivers located within the outer Bay of Fundy or the Southern Upland region, and there was also support for more refined population structure. Both data sets indicated that Atlantic salmon populations from the inner and outer Bay of Fundy reflect unique genetic lineages, with some evidence of population differentiation between regions of the inner Bay of Fundy, and between individual rivers within a region. Consistency of the microarray data across 2 years helped to validate the use of this technique as a useful tool in assessment of variation among wild populations for species conservation.
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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 | 0.001 |
| 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".