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Record W4387079232 · doi:10.1093/gbe/evad173

No Signs of Adaptations for High Flight Intensity in the Mitochondrial Genome of Birds

2023· article· en· W4387079232 on OpenAlexafffund
Santiago Claramunt, Oliver Haddrath

Bibliographic record

VenueGenome Biology and Evolution · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsRoyal Ontario MuseumUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyMitochondrial DNAGenomeGeneMitochondrionGeneticsPhylogenetic treeAmino acidEvolutionary biologyAdaptation (eye)

Abstract

fetched live from OpenAlex

Mitochondrial genomes are expected to show adaptations for optimizing aerobic respiration in birds that make intense use of flight. However, there is limited empirical evidence of such a relationship. We here examine correlates of several mitochondrial genome characteristics and flight use across a diverse sample of 597 bird species. We developed an index of flight use intensity that ranged from 0 in flightless species to 9 in migratory hummingbirds and examined its association with nucleobase composition, amino acid class composition, and amino acid site allelic variation using phylogenetic comparative methods. We found no evidence of mitochondrial genome adaptations to flight intensity. Neither nucleotide composition nor amino acid properties showed consistent patterns related to flight use. While specific sites in mitochondrial genes exhibited variation associated with flight intensity, there was limited association between specific amino acid residues and flight intensity levels. Our findings suggest a complex genetic architecture for aerobic performance traits, where multiple genes in both mitochondria and the nucleus may contribute to overall performance. Other factors, such as gene expression regulation and anatomical adaptations, may play a more significant role in influencing flight performance than changes in mitochondrial genes. These findings highlight the need for comprehensive genomic analyses to unravel the intricate relationship between genetic variants and aerobic performance in birds.

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)0.000
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 score0.993
Threshold uncertainty score0.127

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 head0.022
GPT teacher head0.235
Teacher spread0.213 · 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
Published2023
Admission routes2
Has abstractyes

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