MétaCan
Menu
Back to cohort

MHC studies in nonmodel vertebrates: what have we learned about natural selection in 15 years?

2003· review· en· W1652383174 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Evolutionary Biology · 2003
Typereview
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyNatural selectionMajor histocompatibility complexEvolutionary biologyBalancing selectionSelection (genetic algorithm)Local adaptationPopulationGeneticsAdaptation (eye)Negative selectionGenetic diversitySexual selectionGenetic driftGenetic variationGene

Abstract

fetched live from OpenAlex

Elucidating how natural selection promotes local adaptation in interaction with migration, genetic drift and mutation is a central aim of evolutionary biology. While several conceptual and practical limitations are still restraining our ability to study these processes at the DNA level, genes of the major histocompatibility complex (MHC) offer several assets that make them unique candidates for this purpose. Yet, it is unclear what general conclusions can be drawn after 15 years of empirical research that documented MHC diversity in the wild. The general objective of this review is to complement earlier literature syntheses on this topic by focusing on MHC studies other than humans and mice. This review first revealed a strong taxonomic bias, whereby many more studies of MHC diversity in natural populations have dealt with mammals than all other vertebrate classes combined. Secondly, it confirmed that positive selection has a determinant role in shaping patterns of nucleotide diversity in MHC genes in all vertebrates studied. Yet, future tests of positive selection would greatly benefit from making better use of the increasing number of models potentially offering more statistical rigour and higher resolution in detecting the effect and form of selection. Thirdly, studies that compared patterns of MHC diversity within and among natural populations with neutral expectations have reported higher population differentiation at MHC than expected either under neutrality or simple models of balancing selection. Fourthly, several studies showed that MHC-dependent mate preference and kin recognition may provide selective factors maintaining polymorphism in wild outbred populations. However, they also showed that such reproductive mechanisms are complex and context-based. Fifthly, several studies provided evidence that MHC may significantly influence fitness, either by affecting reproductive success or progeny survival to pathogens infections. Overall, the evidence is compelling that the MHC currently represents the best system available in vertebrates to investigate how natural selection can promote local adaptation at the gene level despite the counteracting actions of migration and genetic drift. We conclude this review by proposing several directions where future research is needed.

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.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.003
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 head0.061
GPT teacher head0.339
Teacher spread0.278 · 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