Fine‐scale population structure of the northern hard clam (<i>Mercenaria mercenaria</i>) revealed by genome‐wide SNP markers
Bibliographic record
Abstract
Abstract Aquaculture is growing rapidly worldwide, and sustainability is dependent on an understanding of current genetic variation and levels of connectivity among populations. Genetic data are essential to mitigate the genetic and ecological impacts of aquaculture on wild populations and guard against unintended human‐induced loss of intraspecific diversity in aquacultured lines. Impacts of disregarding genetics can include loss of diversity within and between populations and disruption of local adaptation patterns, which can lead to a decrease in fitness. The northern hard clam, Mercenaria mercenaria (Linnaeus, 1758), is an economically valuable aquaculture species along the North American Atlantic and Gulf coasts. Hard clams have a pelagic larval phase that allows for dispersal, but the level of genetic connectivity among geographic areas is not well understood. To better inform the establishment of site‐appropriate aquaculture brood stocks, this study used DArTseq™ genotyping by sequencing to characterize the genetic stock structure of wild clams sampled along the east coast of North America and document genetic diversity within populations. Samples were collected from 15 locations from Prince Edward Island, Canada, to South Carolina, USA. Stringent data filtering resulted in 4960 single nucleotide polymorphisms from 448 individuals. Five genetic breaks separating six genetically distinct populations were identified: Canada, Maine, Massachusetts, Mid‐Atlantic, Chesapeake Bay, and the Carolinas ( F ST 0.003–0.046; p < 0.0001). This is the first study to assess population genetic structure of this economically important hard clam along a large portion of its native range with high‐resolution genomic markers, enabling identification of previously unrecognized population structure. Results of this study not only broaden insight into the factors shaping the current distribution of M. mercenaria but also reveal the genetic population dynamics of a species with a long pelagic larval dispersal period along the North American Atlantic and Gulf coasts.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".