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Evidence of recombination producing allelic diversity in MHC class I <i>Mafa‐B</i> and <i>‐A</i> alleles in cynomolgus macaques

2012· article· en· W2015950025 on OpenAlexaff
D. Orysiuk, Jacob Lawrence, T. Prashar, L. P. S. Spangelo, Richard Pilon, Jocelyn Fournier, Erling W. Rud, Paul Sandstrom, Francis A. Plummer, Ma Luo

Bibliographic record

VenueTissue Antigens · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsHealth CanadaUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsBiologyGeneticsMajor histocompatibility complexAlleleIntronGene conversionMHC class IGeneLineage (genetic)

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.265
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2012
Admission routes1
Has abstractyes

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