MétaCan
Menu
Back to cohort
Record W2806690444 · doi:10.1093/jhered/esy027

Purifying Selection in the Toll-Like Receptors of Song Sparrows Melospiza melodia

2018· article· en· W2806690444 on OpenAlexaff
Martha J. Nelson‐Flower, Ryan R. Germain, Elizabeth A. MacDougall‐Shackleton, Sabrina S. Taylor, Peter Arcese

Bibliographic record

VenueJournal of Heredity · 2018
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsWestern UniversityUniversity of British Columbia
Fundersnot available
KeywordsBiologyGeneticsLoss of heterozygosityInbreedingGeneGenetic variationInnate immune systemNegative selectionEvolutionary biologyNatural selectionSelection (genetic algorithm)Immune systemGenomeAllelePopulation

Abstract

fetched live from OpenAlex

Variation in immune gene sequences is known to influence resistance to infectious diseases and parasites, and hence survival and mate choice, across animal taxa. Toll-like receptors (TLRs) comprise one essential gene family in the vertebrate innate immune system and recognize evolutionarily conserved structures from all major microorganism classes. However, the causes and consequences of TLR variation in passerine birds remain largely unexplored. We examined 7 TLR genes in song sparrows (Melospiza melodia), a species that is studied across North America. We then examined sequences from 4 unduplicated TLRs (TLR1LB, TLR3, TLR4, and TLR15) from birds in 2 parts of the species' range (N = 27, N = 6), tested for evidence of selection, and conducted pilot analyses of the role of TLR heterozygosity in survival. We identified 45 SNPs: 19 caused changes in amino acid sequences and 2 of these were likely deleterious. We found no evidence of codon-level episodic positive selection but detected purifying selection at codons in all TLRs. Contrary to expectations we found no strong correlation between heterozygosity at TLRs and inbreeding coefficient f (estimate ± standard error [SE] = -0.68 ± 0.37, Radj2 = 0.08, F1,25 = 3.38, P = 0.08). In addition, pilot analyses revealed no relationship between TLR heterozygosity and survival (β ± SE: 0.09 ± 2.00, P = 0.96), possibly due to small sample size. Further analyses of genetic diversity in TLRs are likely to advance understanding of the effects of innate immune gene diversity on the fitness and persistence of wild populations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.344

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 head0.031
GPT teacher head0.315
Teacher spread0.283 · 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 designObservational
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

Citations20
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of HereditySame topicViral Infections and VectorsFrench-language works237,207