An amplicon panel for high-throughput and low-cost genotyping of Yesso scallop <i>Mizuhopecten yessoensis</i>
Bibliographic record
Abstract
Abstract The Yesso scallop Mizuhopecten yessoensis was imported from Japan to western Canada in the late 1980s to establish an economically viable scallop aquaculture industry. Since this time, the industry in Canada has operated with existing genetic diversity within the broodstock, which is considerably limited relative to wild populations. The sector has not been able to realise its full potential in part due to idiopathic hatchery failures and farm stock collapses due to disease outbreaks associated with the intracellular bacterial pathogen Francisella halioticida . To support Yesso scallop production and breeding, here we generate a low-density, genotyping-by-sequencing amplicon panel using single nucleotide polymorphism (SNP) markers that are evenly spaced across the M. yessoensis genome and that show high heterozygosity in Canada and Japan. The panel can also exploit the high genetic polymorphism of the M. yessoensis genome, with de novo SNP calling identifying over 2,500 high quality SNPs within the 579 sequenced amplicons. We demonstrate the utility and versatility of this new genotyping tool for breeding applications including parentage assignment, low density family-based genome-wide association study, trait heritability evaluation to determine potential for genomic selection, and species differentiation (against the weathervane scallop Patinopecten caurinus ). We did not find any genomic regions significantly associated with F. halioticida resistance but did identify potential for genomic selection. We could separate the two species based on genotypes, and we did not see evidence of a past M. yessoensis x P. caurinus hybridization event within the M. yessoensis breeding population at Vancouver Island University. This low-cost genotyping panel is expected to accelerate selective breeding improvements for M. yessoensis in Canada and elsewhere.
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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 | 0.001 | 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) | 0.002 | 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; 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".