Genome-wide allele frequency studies in Pacific oyster families identify candidate genes for tolerance to ostreid herpesvirus 1 (OsHV-1)
Bibliographic record
Abstract
BACKGROUND: Host genetics influences the development of infectious diseases in many agricultural animal species. Identifying genes associated with disease development has the potential to make selective breeding for disease tolerance more likely to succeed through the selection of different genes in diverse signaling pathways. In this study, four families of Pacific oysters (Crassostrea gigas) were identified to be segregating for a quantitative trait locus (QTL) on chromosome 8. This QTL was previously found to be associated with basal antiviral gene expression and survival to ostreid herpesvirus 1 (OsHV-1) mortality events in Tomales Bay, California. Individuals from these four families were phenotyped and genotyped in an attempt to find candidate genes associated with the QTL on chromosome 8. RESULTS: Genome-wide allele frequencies of oysters from each family prior to being planting in Tomales Bay were compared with the allele frequencies of oysters from respective families that survived an OsHV-1 mortality event. Six significant unique QTL were identified in two families in these genome-wide allele frequency studies, all of which were located on chromosome 8. Three QTL were assigned to candidate genes (ABCA1, PIK3R1, and WBP2) that have been previously associated with antiviral innate immunity in vertebrates. CONCLUSION: The identification of vertebrate antiviral innate immunity genes as candidate genes involved in molluscan antiviral innate immunity reinforces the similarities between the innate immune systems of these two groups. Causal variant identification in these candidate genes will enable future functional studies of these genes in an effort to better understand their antiviral modes of action.
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".