Evolution and Organisation of <scp>MHC II</scp> Genes in Harbour Porpoises: Insights From Long‐Read Cetacean Genome Assemblies, Whole Genome Re‐Sequencing and Locus‐Specific Genotyping
Bibliographic record
Abstract
The Major Histocompatibility Complex (MHC) is a central element in the vertebrate immune system. While MHC genes are a common target of conservation genomic studies, it has been challenging to reliably amplify locus-specific alleles, which is especially problematic when studying endangered lineages, like some harbour porpoise (Phocoena phocoena) populations and subspecies. Here, we manually annotated all MHC II genes in the harbour porpoise genome and genotyped every exon 2 in 47 individuals (94 individuals for DRB1 and DQB genes) spanning six geographical regions, including the endangered Black Sea porpoise subspecies (Phocoena phocoena relicta) and the critically endangered Baltic proper population of the North Atlantic subspecies (P. p. phocoena). We performed gene-wise analyses of diversity and selection and put the results into perspective with 22 available harbour porpoise genomes. Furthermore, we characterised all MHC II genes in 19 available long-read genomes of cetaceans and terrestrial outgroups to study the MHC II evolution across the cetacean diversification. From the 10 MHC II loci annotated in the harbour porpoise genome, two (DRB1 and DQB) exhibited inflated allelic diversity and signatures of positive selection. Interestingly, DRB genes followed different evolutionary trajectories in mysticetes and odontocetes. Our results have significant conservation implications since we identified reduced MHC II diversity in the endangered Black Sea subspecies and provide a case study for reliable MHC II genotyping in other species. Further, our study demonstrates the need for long-read genomes to understand the genomic architecture of MHC and to accurately assess its diversity and evolution.
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 | 0.001 |
| 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 | 0.001 | 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".