Dynamics of introgressive hybridization assessed by SNP population genomics of coding genes in stocked brook charr (<i>Salvelinus fontinalis</i>)
Bibliographic record
Abstract
Salmonid fishes rank among species being most severely affected by introgressive hybridization as a result of a long tradition of stocking with hatchery-reared conspecifics. The objectives of this study were (i) to evaluate the genetic consequences of stocking and resulting introgression rates on the genetic integrity of natural populations of brook charr, (ii) to identify genomic regions potentially associated with adaptation to natural and artificial rearing environments, and (iii) to test the null hypothesis that introgression from domesticated brook charr into wild populations is homogeneous among loci. A total of 336 individuals were sampled from nine lakes, which were stocked at different intensities with domestic fish. Individuals were genotyped at 280 SNPs located in transcribed regions and developed by means of next-generation sequencing. As previously reported with microsatellites, we observed a positive relationship between stocking intensity and genetic diversity among stocking groups, and a decrease in population differentiation. Individual admixture proportions also increased with stocking intensity. Moreover, genomic cline analysis revealed 27 SNPs, seven of which were also identified as outliers in a genome scan, which showed an introgression rate either more restricted or enhanced relative to neutral expectations. This indicated that selection, mainly for growth-related biological processes, has favored or hampered the introgression of genomic blocks into the introgressed wild populations. Overall, this study highlights the usefulness of investigating the impact of stocking on the dynamics of introgression of potentially adaptive genetic variation to better understand the consequences of such practice on the genomic integrity of wild populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".