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Record W2098861504 · doi:10.1093/molbev/msv071

Genomic Analyses Reveal Potential Independent Adaptation to High Altitude in Tibetan Chickens

2015· article· en· W2098861504 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

VenueMolecular Biology and Evolution · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock and Poultry Management
Canadian institutionsDiabetes CanadaUniversity of Toronto
Fundersnot available
KeywordsBiologyDomesticationAdaptation (eye)GeneGenomeEvolutionary biologyCandidate geneGeneticsZoology

Abstract

fetched live from OpenAlex

Much like other indigenous domesticated animals, Tibetan chickens living at high altitudes (2,200-4,100 m) show specific physiological adaptations to the extreme environmental conditions of the Tibetan Plateau, but the genetic bases of these adaptations are not well characterized. Here, we assembled a de novo genome of a Tibetan chicken and resequenced whole genomes of 32 additional chickens, including Tibetan chickens, village chickens, game fowl, and Red Junglefowl, and found that the Tibetan chickens could broadly be placed into two groups. Further analyses revealed that several candidate genes in the calcium-signaling pathway are possibly involved in adaptation to the hypoxia experienced by these chickens, as these genes appear to have experienced directional selection in the two Tibetan chicken populations, suggesting a potential genetic mechanism underlying high altitude adaptation in Tibetan chickens. The candidate selected genes identified in this study, and their variants, may be useful targets for clarifying our understanding of the domestication of chickens in Tibet, and might be useful in current breeding efforts to develop improved breeds for the highlands.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.309

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 head0.029
GPT teacher head0.276
Teacher spread0.247 · 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