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SPERM COMPETITION AND MATE HARM UNRESPONSIVE TO MALE-LIMITED SELECTION IN DROSOPHILA: AN EVOLVING GENETIC ARCHITECTURE UNDER DOMESTICATION

2011· article· en· W2107548363 on OpenAlexafffund
Panpan Jiang, Stéphanie Bedhomme, Nagaraj Guru Prasad, Adam K. Chippindale

Bibliographic record

VenueEvolution · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBiologySperm competitionDomesticationEvolutionary biologyPopulationSexual selectionGeneticsGenetic architectureSelection (genetic algorithm)Sexual conflictExperimental evolutionSpermSexual dimorphismGenetic variationZoologyQuantitative trait locusGeneDemography

Abstract

fetched live from OpenAlex

Earlier research by W.R. Rice showed that experimentally limiting gene expression to males in Drosophila melanogaster leads to the rapid evolution of higher fitness. Using a similar male-limited (ML) selection protocol, we confirmed that result and showed that eliminating intralocus sexual conflict results in a comprehensive remodeling of the sexually dimorphic phenotype. However, despite starting from laboratory-evolved descendants of the same founder population used in earlier work, we found no evidence for the increased performance in sperm competition or increased postmating harm to females previously demonstrated. We employed females with both ancestral population genotypes and those of the special "clone generator" females used in ML selection. Despite strong differences in sperm storage or usage patterns between these females, there was no detectable adaptation by males to the specific female stock used in the selection protocol. The lack of evolution of postcopulatory traits suggests either that requisite genetic variation was eliminated by long-term domestication of the base population, or that complex male-by-male-by-female interactions made these traits unavailable to selection. The different evolutionary outcomes produced by two very similar experiments done at different time points underscores the potential for cryptic adaptation in the laboratory to qualitatively affect inferences made using quantitative genetic methodologies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.239
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2011
Admission routes2
Has abstractyes

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