Construction of microsatellite‐based linkage maps and identification of size‐related quantitative trait loci for Zhikong scallop (<i>Chlamys farreri</i>)
Bibliographic record
Abstract
We constructed the microsatellite-based linkage maps using 318 markers typed in two F(1) outbred families of Zhikong scallop (Chlamys farreri). The results showed an extremely high proportion (56.2%) of non-amplifying null alleles and a high ratio (30%) of segregation distortion. By aligning different individual-based linkage maps, 19 linkage groups were identified, which are consistent with the haploid chromosome number of Zhikong scallop. The integrated linkage map contains 154 markers covering 1561.8 cM with an average intermarker spacing of 12.3 cM and 77.0% of genome coverage. We found that the heterogeneity in recombination rate was not determined by sexes but by different individuals on 18 linkage regions. The phenotypic marker of general shell colour was placed on LG4, which was flanked by microsatellite markers CFLD064 and CFBD055. Four size-related traits including shell length (SL), shell width (SW), shell height (SH) and gross weight (GW) were analysed to identify the putative quantitative trait loci (QTL). Under the half-sib model, using dam as common parent, three, two, two and one QTL affecting SL, SW, SH and GW exceeded the genome-wide thresholds respectively. While using sir as common parent, a larger number of QTL were detected for these four traits: four, five, three and two for SL, SW, SH and GW respectively. The single QTL explained 3.7-19.2% of the phenotypic variation. The linkage map and the QTL associated with economic traits will provide useful information for marker-assisted selection of Zhikong scallop.
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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 | 0.000 |
| 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 | 0.000 |
| 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".