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Record W2960223606 · doi:10.1093/gbe/evz139

The Piranha Genome Provides Molecular Insight Associated to Its Unique Feeding Behavior

2019· article· en· W2960223606 on OpenAlexafffund
Manfred Schartl, Susanne Kneitz, Hélène Volkoff, Mateus Contar Adolfi, Cornelia Schmidt, Petra Fischer, Patrick Minx, Chad Tomlinson, Axel Meyer, Wesley C. Warren

Bibliographic record

VenueGenome Biology and Evolution · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsMemorial University of Newfoundland
FundersNational Center for Research ResourcesNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthJulius-Maximilians-Universität WürzburgDeutsche Forschungsgemeinschaft
KeywordsBiologyGenomeEvolutionary biologyComputational biologyGeneticsGene

Abstract

fetched live from OpenAlex

The piranha enjoys notoriety due to its infamous predatory behavior but much is still not understood about its evolutionary origins and the underlying molecular mechanisms for its unusual feeding biology. We sequenced and assembled the red-bellied piranha (Pygocentrus nattereri) genome to aid future phenotypic and genetic investigations. The assembled draft genome is similar to other related fishes in repeat composition and gene count. Our evaluation of genes under positive selection suggests candidates for adaptations of piranhas' feeding behavior in neural functions, behavior, and regulation of energy metabolism. In the fasted brain, we find genes differentially expressed that are involved in lipid metabolism and appetite regulation as well as genes that may control the aggression/boldness behavior of hungry piranhas. Our first analysis of the piranha genome offers new insight and resources for the study of piranha biology and for feeding motivation and starvation in other organisms.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.433

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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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 designBench or experimental
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

Citations16
Published2019
Admission routes2
Has abstractyes

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