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Record W2103555940 · doi:10.1098/rspb.2006.3707

Opsin gene duplication and diversification in the guppy, a model for sexual selection

2006· article· en· W2103555940 on OpenAlexaff
Margarete Hoffmann, Namita Tripathi, Stefan R. Henz, Anna K. Lindholm, Detlef Weigel, Felix Breden, Christine Dreyer

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBiologyGuppySexual selectionPoeciliaEvolutionary biologyGeneticsOpsinMate choicePopulationGene duplicationNatural selectionGeneMating

Abstract

fetched live from OpenAlex

Identification of genes that control variation in adaptive characters is a prerequisite for understanding the processes that drive sexual and natural selection. Male coloration and female colour perception play important roles in mate choice in the guppy (Poecilia reticulata), a model organism for studies of natural and sexual selection. We examined a potential source for the known variation in colour perception, by analysing genomic and complementary DNA sequences of genes that code for visual pigment proteins. We find high sequence variability, both within and between populations, and expanded copy number for long-wave sensitive (LWS) opsin genes. Alleles with non-synonymous changes that suggest dissimilar spectral tuning properties occur in the same population and even in the same individual, and the high frequency of non-synonymous substitutions argues for diversifying selection acting on these proteins. Therefore, variability in tuning amino acids is partitioned within individuals and populations of the guppy, in contrast to variability for LWS at higher taxonomic levels in cichlids, a second model system for differentiation owing to sexual selection. Since opsin variability parallels the extreme male colour polymorphism within guppy populations, we suggest that mate choice has been a major factor driving the coevolution of opsins and male ornaments in this species.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.400

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 studies0.0010.000
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 head0.046
GPT teacher head0.242
Teacher spread0.196 · 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

Citations82
Published2006
Admission routes1
Has abstractyes

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