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Record W2293828693 · doi:10.1111/evo.12897

Partially repeatable genetic basis of benthic adaptation in threespine sticklebacks

2016· article· en· W2293828693 on OpenAlexaff
Priscilla A. Erickson, Andrew M. Glazer, Emily Killingbeck, Rachel M. Agoglia, Jiyeon Baek, Sara M. Carsanaro, Anthony M. Lee, Phillip A. Cleves, Dolph Schluter, Craig T. Miller

Bibliographic record

VenueEvolution · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Dental and Craniofacial ResearchNational Center for Research ResourcesNational Institute of General Medical Sciences
KeywordsBiologyAdaptation (eye)Evolutionary biologyBenthic zoneGasterosteusEcologyFish <Actinopterygii>FisheryNeuroscience

Abstract

fetched live from OpenAlex

The extent to which convergent adaptation to similar ecological niches occurs by a predictable genetic basis remains a fundamental question in biology. Threespine stickleback fish have undergone an adaptive radiation in which ancestral oceanic populations repeatedly colonized and adapted to freshwater habitats. In multiple lakes in British Columbia, two different freshwater ecotypes have evolved: a deep-bodied benthic form adapted to forage near the lake substrate, and a narrow-bodied limnetic form adapted to forage in open water. Here, we use genome-wide linkage mapping in marine × benthic F2 genetic crosses to test the extent of shared genomic regions underlying benthic adaptation in three benthic populations. We identify at least 100 Quantitative Trait Loci (QTL) harboring genes influencing skeletal morphology. The majority of QTL (57%) are unique to one cross. However, four genomic regions affecting eight craniofacial and armor phenotypes are found in all three benthic populations. We find that QTL are clustered in the genome and overlapping QTL regions are enriched for genomic signatures of natural selection. These findings suggest that benthic adaptation has occurred via both parallel and nonparallel genetic changes.

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 score0.596
Threshold uncertainty score0.225

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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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

Citations44
Published2016
Admission routes1
Has abstractyes

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