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Record W3205465507 · doi:10.1038/s41467-021-26272-1

Three chromosome-level duck genome assemblies provide insights into genomic variation during domestication

2021· article· en· W3205465507 on OpenAlexafffund
Feng Zhu, Zhongtao Yin, Zheng Wang, Jacqueline Smith, Fan Zhang, Fergal J. Martin, Denye Ogeh, Maxwell T. Hincke, Fangbing Lin, David W. Burt, Zhengkui Zhou, Shuisheng Hou, Qiangsen Zhao, Xiaoqin Li, Si-Ran Ding, Guan-Sheng Li, Fang‐Xi Yang, Jing-Pin Hao, Ziding Zhang, Lizhi Lu, Ning Yang, Zhuocheng Hou

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of Ottawa
FundersBiotechnology and Biological Sciences Research CouncilNortheast Agricultural UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaWellcome Trust
KeywordsBiologyDomesticationGeneticsGenomeGenomicsPopulationGeneEvolutionary biology

Abstract

fetched live from OpenAlex

Domestic ducks are raised for meat, eggs and feather down, and almost all varieties are descended from the Mallard (Anas platyrhynchos). Here, we report chromosome-level high-quality genome assemblies for meat and laying duck breeds, and the Mallard. Our new genomic databases contain annotations for thousands of new protein-coding genes and recover a major percentage of the presumed "missing genes" in birds. We obtain the entire genomic sequences for the C-type lectin (CTL) family members that regulate eggshell biomineralization. Our population and comparative genomics analyses provide more than 36 million sequence variants between duck populations. Furthermore, a mutant cell line allows confirmation of the predicted anti-adipogenic function of NR2F2 in the duck, and uncovered mutations specific to Pekin duck that potentially affect adipose deposition. Our study provides insights into avian evolution and the genetics of oviparity, and will be a rich resource for the future genetic improvement of commercial traits in the duck.

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 score0.915
Threshold uncertainty score0.736

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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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

Citations94
Published2021
Admission routes2
Has abstractyes

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