Single nucleotide polymorphisms shed light on correlations between environmental vairalbe and adaptive genetic divergence in Chum salmon ( <i>Oncorhynchus keta</i> )
Bibliographic record
Abstract
Abstract Identifying the genetic and ecological basis of adaptation is of immense importance in evolutionary biology. In our study, we applied a panel of 58 biallelic single nucleotide polymorphisms (SNPs) for the economically and culturally important salmonid Oncorhynchus keta. Samples included 4164 individuals from 43 populations ranging from Coastal Western Alaska to southern British Colombia and northern Washington. Signatures of natural selection were detected by identifying seven outlier loci using two independent approaches: one based on outlier detection and another based on environmental correlations. Evidence of divergent selection at two candidate SNP loci, Oke_RFC2-168 and Oke_MARCKS-362 , indicates significant environmental correlations, particularly with the number of frost-free days (NFFD). Important associations found between environmental variables and outlier loci indicate that those environmental variables could be the major driving forces of allele frequency divergence at the candidate loci. NFFD, in particular, may play an important adaptive role in shaping genetic variation in O. keta. Correlations between divergent selection and local environmental variables will help shed light on processes of natural selection and molecular adaptation to local environmental conditions.
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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 | 0.001 |
| 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) | 0.001 | 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".