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Record W2033806980 · doi:10.1093/molbev/msi175

Rapidly Evolving Genes of Drosophila: Differing Levels of Selective Pressure in Testis, Ovary, and Head Tissues Between Sibling Species

2005· article· en· W2033806980 on OpenAlexaff
Santosh Jagadeeshan, Rama S. Singh

Bibliographic record

VenueMolecular Biology and Evolution · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiologyNonsynonymous substitutionOvaryGeneEvolutionary biologyGenetic algorithmGeneticsGenome

Abstract

fetched live from OpenAlex

Investigations of rapidly evolving sex- and reproduction-related genes are expected to reveal important information about the process of speciation and species divergence. We screened testis, ovary, and head tissues to identify and characterize rapidly evolving genes (REGs) between closely related species. The results show differential patterns of evolution of genes expressed in reproductive and nonreproductive tissues. (1) There is a differential distribution of REGs in the Drosophila genome, with most REGs localized in the testis, followed by ovary, and then head. (2) Sequence analysis indicates that differential selective pressures are driving the rapid evolution of genes expressed in sex and nonsex tissues. Testis REGs from our data, on average, yielded higher rates of nonsynonymous substitutions relative to transcripts in ovary and head, indicating stronger selective pressures on the male reproductive system. (3) We identified REGs in the testis, ovary, as well as in head tissue that show evidence of evolving under positive selection. Identification of rapidly evolving sex genes is important for detailed investigations of cryptic female choice, sexual conflict, and faster male evolution and is pertinent to our understanding of the process of species divergence and speciation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.447

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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

Citations112
Published2005
Admission routes1
Has abstractyes

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