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LOW RATES OF BINDIN CODON EVOLUTION IN LECITHOTROPHIC HELIOCIDARIS SEA URCHINS

2012· article· en· W1903065342 on OpenAlexafffund
Michael W. Hart, Iva Popovic, Richard B. Emlet

Bibliographic record

VenueEvolution · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsSimon Fraser University
FundersSimon Fraser UniversityNational Science Foundation
KeywordsBiologyNonsynonymous substitutionEvolutionary biologySea urchinSexual selectionEcologyZoologyGeneticsGeneGenome

Abstract

fetched live from OpenAlex

Life-history variables including egg size affect the evolutionary response to sexual selection in broadcast-spawning sea urchins and other marine animals. Such responses include high or low rates of codon evolution at gamete recognition loci that encode sperm- and egg-surface peptides. Strong positive selection on such loci affects intraspecific mating success and interspecific reproductive divergence (and may play a role in speciation). Here, we analyze adaptive codon evolution in the sperm acrosomal protein bindin from a brooding sea urchin (Heliocidaris bajulus, with large eggs and nonfeeding or lecithotrophic larval development) and compare our results to previously published data for two closely related congeners. Purifying selection and low relative rates of bindin nonsynonymous substitution in H. bajulus were significantly different from selectively neutral bindin evolution in H. erythrogramma despite similar large egg size in those two species, but were similar to the background rate of nonsynonymous bindin substitution for other closely related sea urchins (including H. tuberculata, all with small egg size and feeding planktonic larval development). Bindin evolution is not driven by egg size variation among Heliocidaris species, but may be more consistent with an alternative mechanism based on the effects of high or low spatial density of conspecific mates.

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 score0.012
Threshold uncertainty score0.979

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)0.0010.000

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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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

Citations8
Published2012
Admission routes2
Has abstractyes

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