Standardized IMGT® Nomenclature of Salmonidae IGH Genes, the Paradigm of Atlantic Salmon and Rainbow Trout: From Genomics to Repertoires
Bibliographic record
Abstract
In teleost fish as in mammals, humoral adaptive immunity is based on B lymphocytes expressing highly diverse immunoglobulins (IG). During B cell differentiation, IG loci are subjected to genomic rearrangements of V, D, and J genes, producing a unique antigen receptor expressed on the surface of each lymphocyte. During the course of an immune response to infections or immunizations, B cell clones specific of epitopes from the immunogen are expanded and activated, leading to production of specific antibodies. Among teleost fish, salmonids comprise key species for aquaculture. Rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) are especially important from a commercial point of view and, have emerged as critical models for fish immunology. The growing interest to capture accurate and comprehensive antibody responses against common pathogens and vaccines has resulted in recent efforts to sequence the IG repertoire in these species. In this context, a unified and standardized nomenclature of salmonid IG heavy chain (IGH) genes is urgently required, to improve accuracy of annotation of adaptive immune receptor repertoire dataset generated by high-throughput sequencing (AIRRseq) and facilitate comparisons between studies and species. Interestingly, the assembly of salmonids IGH genomic sequences is challenging due to the presence of two large size duplicated IGH loci and high numbers of IG genes and pseudogenes. We used data available for Atlantic salmon to establish an IMGT standardized nomenclature of IGH genes in this species, then applied the IMGT rules to the rainbow trout IGH loci to set-up a nomenclature, which takes into account the specificities of Salmonid loci. This unique, consistent nomenclature for Salmonid IGH genes was then used to construct IMGT sequence reference directories allowing accurate annotation of AIRRseq data. The complex issues raised by the genetic diversity of salmon and trout strains are discussed in the context of IG repertoire annotation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".