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Record W4406838870 · doi:10.1038/s41597-025-04498-8

Chromosome-level genome assembly and annotation of the gynogenetic large-scale loach (Paramisgurnus dabryanus)

2025· article· en· W4406838870 on OpenAlexaff
Lei Zhang, Wanting Zhang, Yingyin Cheng, Yutong Fang, Xin Guan, Ao Gong, Yanxin Jiang, You Duan, Lei Huang, Waqar Younas, Yaping Wang, Mijuan Shi, Xiao-Qin Xia

Bibliographic record

VenueScientific Data · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsMinistry of Agriculture
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsBiologyGenomeCypriniformesCobitidaeGeneticsSequence assemblyGeneReference genomeChromosomeEvolutionary biologyGenome projectComputational biologyFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

The large-scale loach (Paramisgurnus dabryanus; Cypriniformes: Cobitidae) is primarily distributed in East Asia. It is an important economic fish species characterized by fast growth, temperature-dependent sex determination and the ability to breathe air. Currently, molecular mechanism studies related to some aspects such as sex determination, toxicology, feed nutrition, growth and genetic evolution have been conducted. However, the lack of a high-quality reference genome has hindered further research. In this study, we performed PacBio HiFi and Hi-C sequencing on a female (ZW) specimen and assembled the first high-quality chromosome-level genome of the large-scale loach. The assembled genome comprises 24 chromosomes, with a total length of 1.04 Gb, a scaffold N50 of 41.7 Mb, and a BUSCO completeness of 95.8%, including 28,311 protein-coding genes. These findings not only provide new insights into the genome structure of the large-scale loach but also establish a crucial reference point for omics studies and serve as an essential genomic resource for breeding programs in this species.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
gptno category
Domain: not available · Genre: Dataset
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models splitAgreement compares identical category sets and study designs across arms.

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 score0.687
Threshold uncertainty score0.363

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 science0.0010.001
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 head0.029
GPT teacher head0.269
Teacher spread0.240 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designBench or experimental · Not applicable
Domainnot available
GenreEmpirical · Dataset

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
Published2025
Admission routes1
Has abstractyes

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