Evidence of recombination producing allelic diversity in MHC class I <i>Mafa‐B</i> and <i>‐A</i> alleles in cynomolgus macaques
Bibliographic record
Abstract
The MHC class I-A and -B genes of cynomolgus macaques are highly polymorphic. These genes encode proteins presenting peptides to CD8+ T cells to initiate adaptive immune response. Recombination events are one way the diversity of these alleles can be increased. Such events have been well characterized in humans, but have not been as well characterized in macaques. In order to identify and examine recombinations that create new alleles, it is important to analyze intron sequences. Intron sequences have been shown to be important to understand the evolutionary mechanisms involved in the generation of major histocompatibility complex (MHC) alleles and loci. Thus far, there have been relatively few intron sequences reported for MHC class I alleles in macaques, and this has hampered the understanding of MHC organization and evolution in macaques. In this study, we present evidence of a gene conversion event generating the Mafa-B*099 allele lineage by the combination of Mafa-B*054 and Mafa-B*095 allele lineages. A potential recombination between the Mafa-A3*13 and Mafa-A4:14 lineages was also observed, but it is less clear due to lack of intron 2 sequence. This report stresses the role that recombination can play in MHC class I diversity in cynomologus macaques, and the importance of introns in identifying and analyzing such events.
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 | 0.000 |
| 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".