MétaCan
Menu
Back to cohort
Record W4392465290 · doi:10.1111/dgd.12918

Genomic screening of fish‐specific genes in gnathostomes and their functions in fin development

2024· article· en· W4392465290 on OpenAlexfundno aff
Hidehiro Kudoh, Sayuri Yonei‐Tamura, Gembu Abe, Junichi Iwakiri, Masahiro Uesaka, Takashi Makino, Koji Tamura

Bibliographic record

VenueDevelopment Growth & Differentiation · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceTakeda Science Foundation
KeywordsBiologyGeneFish finZebrafishGeneticsFinFish <Actinopterygii>Evolutionary biologyComputational biologyFishery

Abstract

fetched live from OpenAlex

In this study, we comprehensively searched for fish-specific genes in gnathostomes that contribute to development of the fin, a fish-specific trait. Many previous reports suggested that animal group-specific genes are often important for group-specific traits. Clarifying the roles of fish-specific genes in fin development of gnathostomes, for example, can help elucidate the mechanisms underlying the formation of this trait. We first identified 91 fish-specific genes in gnathostomes by comparing the gene repertoire in 16 fish and 35 tetrapod species. RNA-seq analysis narrowed down the 91 candidates to 33 genes that were expressed in the developing pectoral fin. We analyzed the functions of approximately half of the candidate genes by loss-of-function analysis in zebrafish. We found that some of the fish-specific and fin development-related genes, including fgf24 and and1/and2, play roles in fin development. In particular, the newly identified fish-specific gene qkia is expressed in the developing fin muscle and contributes to muscle morphogenesis in the pectoral fin as well as body trunk. These results indicate that the strategy of identifying animal group-specific genes is functional and useful. The methods applied here could be used in future studies to identify trait-associated genes in other animal groups.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.210
Teacher spread0.199 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDevelopment Growth & DifferentiationSame topicDevelopmental Biology and Gene RegulationFrench-language works237,207