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Record W3154743912 · doi:10.3390/genes12050625

Variation in a Newly Identified Caprine KRTAP Gene Is Associated with Raw Cashmere Fiber Weight in Longdong Cashmere Goats

2021· article· en· W3154743912 on OpenAlexaff
Mengli Zhao, Huitong Zhou, Yuzhu Luo, Jiqing Wang, Jiang Hu, Xiu Liu, Shaobin Li, Kaiwen Zhang, Huimin Zhen, Jon G. H. Hickford

Bibliographic record

VenueGenes · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBiologySingle-nucleotide polymorphismCashmere goatGeneKeratinGeneticsAnatomyMolecular biologyGenotype

Abstract

fetched live from OpenAlex

Keratin-associated proteins (KAPs) and keratins determine the physical and chemical properties of cashmere fibers as they are the main components of the fibers. It has been reported that ovine KRTAP1-2 affects clean fleece weight, greasy fleece weight and yield in sheep, but the gene has not been described in goats and its effects on fiber traits are unknown. In this study, we identify the keratin-associated protein 1-2 gene (KRTAP1-2) in the goat genome and describe its effect on cashmere fiber traits in 359 Longdong cashmere goats. Six sequence variants (named CAPHI-KRTAP1-2*A to CAPHI-KRTAP1-2*F) were revealed using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) analysis. These sequences have the highest homology with ovine KRTAP1-2 sequences. There were a 60-bp deletion, a 15-bp insertion and five single nucleotide polymorphisms (SNPs) including two non-synonymous SNPs in the coding sequence. The caprine KRTAP1-2 gene was expressed in the skin tissue, but a signal was not observed for the kidneys, liver, lungs, spleen, heart and longissimus dorsi muscle. Variation in caprine KRTAP1-2 was found to be associated with raw cashmere fiber weight, but not with fiber diameter and length.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.683

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 head0.253
Teacher spread0.241 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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