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Record W2042736039 · doi:10.1186/1471-2148-9-57

RSCA genotyping of MHC for high-throughput evolutionary studies in the model organism three-spined stickleback Gasterosteus aculeatus

2009· article· en· W2042736039 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.

Bibliographic record

VenueBMC Evolutionary Biology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicvaccines and immunoinformatics approaches
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsBiologyGasterosteusGeneticsSticklebackMajor histocompatibility complexGenotypingBalancing selectionEvolutionary biologyGeneGenotype

Abstract

fetched live from OpenAlex

BACKGROUND: In all jawed vertebrates, highly polymorphic genes of the major histocompatibility complex (MHC) encode antigen presenting molecules that play a key role in the adaptive immune response. Their polymorphism is composed of multiple copies of recently duplicated genes, each possessing many alleles within populations, as well as high nucleotide divergence between alleles of the same species. Experimental evidence is accumulating that MHC polymorphism is a result of balancing selection by parasites and pathogens. In order to describe MHC diversity and analyse the underlying mechanisms that maintain it, a reliable genotyping technique is required that is suitable for such highly variable genes. RESULTS: We present a genotyping protocol that uses Reference Strand-mediated Conformation Analysis (RSCA), optimised for recently duplicated MHC class IIB genes that are typical for many fish and bird species, including the three-spined stickleback, Gasterosteus aculeatus. In addition we use a comprehensive plasmid library of MHC class IIB alleles to determine the nucleotide sequence of alleles represented by RSCA allele peaks. Verification of the RSCA typing by cloning and sequencing demonstrates high congruency between both methods and provides new insight into the polymorphism of classical stickleback MHC genes. Analysis of the plasmid library additionally reveals the high resolution and reproducibility of the RSCA technique. CONCLUSION: This new RSCA genotyping protocol offers a fast, but sensitive and reliable way to determine the MHC allele repertoire of three-spined sticklebacks. It therefore provides a valuable tool to employ this highly polymorphic and adaptive marker in future high-throughput studies of host-parasite co-evolution and ecological speciation in this emerging model organism.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.057
GPT teacher head0.305
Teacher spread0.248 · 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