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Record W4400412326 · doi:10.1093/gbe/evae095

Genome-Wide Gene Birth–Death Dynamics Are Associated with Diet Breadth Variation in Lepidoptera

2024· article· en· W4400412326 on OpenAlexaff
Hanna Dort, Wouter van der Bijl, Niklas Wahlberg, Sören Nylin, Christopher W. Wheat

Bibliographic record

VenueGenome Biology and Evolution · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
FundersVetenskapsrådetStockholms UniversitetMatemaattis-luonnontieteellinen tiedekunta, Helsingin Yliopisto
KeywordsBiologyGene familyGeneLepidoptera genitaliaGenomeEvolutionary biologyGeneticsPhylogeneticsPhylogenetic treeGeneralist and specialist speciesEcology

Abstract

fetched live from OpenAlex

Comparative analyses of gene birth-death dynamics have the potential to reveal gene families that played an important role in the evolution of morphological, behavioral, or physiological variation. Here, we used whole genomes of 30 species of butterflies and moths to identify gene birth-death dynamics among the Lepidoptera that are associated with specialist or generalist feeding strategies. Our work advances this field using a uniform set of annotated proteins for all genomes, investigating associations while correcting for phylogeny, and assessing all gene families rather than a priori subsets. We discovered that the sizes of several important gene families (e.g. those associated with pesticide resistance, xenobiotic detoxification, and/or protein digestion) are significantly correlated with diet breadth. We also found 22 gene families showing significant shifts in gene birth-death dynamics at the butterfly (Papilionoidea) crown node, the most notable of which was a family of pheromone receptors that underwent a contraction potentially linked with a shift to visual-based mate recognition. Our findings highlight the importance of uniform annotations, phylogenetic corrections, and unbiased gene family analyses in generating a list of candidate genes that warrant further exploration.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.504

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 head0.018
GPT teacher head0.194
Teacher spread0.176 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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