Evidence of microsatellite hitch‐hiking selection in Atlantic cod (<i>Gadus morhua</i> L.): implications for inferring population structure in nonmodel organisms
Bibliographic record
Abstract
Microsatellites have gained wide application for elucidating population structure in nonmodel organisms. Since they are generally noncoding, neutrality is assumed but rarely tested. In Atlantic cod (Gadus morhua L.), microsatellite studies have revealed highly heterogeneous estimates of genetic differentiation among loci. In particular one locus, Gmo 132, has demonstrated elevated genetic differentiation. We investigated possible hitch-hiking selection at this and other microsatellite loci in Atlantic cod. We employed 11 loci for analysing samples from the Baltic Sea, North Sea, Barents Sea and Newfoundland covering a large part of the species' distributional range. The 'classical' Lewontin-Krakauer test for selection based on variance in estimates of F(ST) and (standardized genetic differentiation) revealed only one significant pairwise test (North Sea-Barents Sea), and the source of the elevated variance could not be ascribed exclusively to Gmo 132. In contrast, different variants of the recently developed ln Rtheta test for selective sweeps at microsatellite loci revealed a high number of significant outcomes of pair-wise tests for Gmo 132. Further, the presence of selection was indicated in at least one other locus. The results suggest that many previous estimates of genetic differentiation in cod based on microsatellites are inflated, and in some cases relationships among populations are obscured by one or more loci being the subject to hitch-hiking selection. Likewise, temporal estimates of effective population sizes in Atlantic cod may be flawed. We recommend, generally, to use a higher number of microsatellite loci to elucidate population structure in marine fishes and other nonmodel species to allow for identification of outlier loci that are subject to selection.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".