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Record W4320515760 · doi:10.5281/zenodo.7357245

Polymorphism of Keratin - associated protein (KAP) 3.2 gene in Sandyno and Nilagiri breeds of sheep

2022· article· en· W4320515760 on OpenAlexaboutno aff
R Bharathesree, N. Murali, R. Saravanan, R Anilkumar

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsnot available
Fundersnot available
KeywordsKeratinGeneBiologyGeneticsPolymorphism (computer science)Genotype

Abstract

fetched live from OpenAlex

ABSTRACT ABSTRACT Polymorphic variants of keratin-associated protein (KAP) 3.2 gene in Sandyno and Nilagiri breeds of sheep were investigated. Genomic DNA was isolated from blood samples of 125 Sandyno, Nilagiri and Dorset x Nilagiri breeds and 76 numbers of wool samples were collected and processed. A 393 bp segment was amplified by PCR using ovine specific primers for KAP 3.2 gene. The genotyping was done by using PCR-SSCP. KAP 3.2 gene locus revealed 3 genotypes, viz. AA, AB and BB with a frequency of 0.84, 0.16 and 0; 0.86, 0.12 and 0.02 in Sandyno and Nilagiri breeds respectively with allele frequencies of A(0.92) and B(0.08) in both the breeds revealing monomorphic nature of this in this population. The result showed that the population was in Hardy-Weinberg equilibrium for KAP 3.2 with no significant difference. KAP 3.2 gene was found to have high degree of homozygosity (0.8824) in Nilagiri sheep. The effective number of alleles (Ne) for KAP 3.2 was 1.1716 and 1.1690 respectively in Sandyno and Nilagiri breeds of sheep. The PIC values for KAP 3.2 was 0.1356 and 0.1341 in Sandyno and Nilagiri breeds of sheep respectively. FIS values for KAP 3.2 was positive (0.1862) in Nilagiri breed and it was negative (– 0.0864) in Sandyno breed. The result revealed that presence of few alleles at the KAP 3.2 loci in Sandyno and Nilagiri breeds of sheep indicates monomorphic situation. Keywords: Keratin Associated Protein (KAP) 3.2 , PCR-SSCP, Polymorphism, Sheep, Wool traits REFERENCES Barba, C., Mendez, S., Martí, M., Parra, J.L. and Coderch, L. (2009). Water content of hair and nails. Thermochim Acta., 494: 136–40. Bassam, B.J., Caetano-Anolles, G. and Gresshoff, P.M. (1991). Fast and sensitive silver staining of DNA in polyacrylamide gels. Anal Biochem., 196: 80-83. Feughelman, M. (1996). Mechanical properties and structure of alpha-keratin fibres: wool, human hair and related fibres. UNSW Press Sydney, Australia. Ganesakale, D. and Rathnasabapathy, V. (1973). Sheep breeds of Tamil Nadu. Cheiron 2: 146–155. Itenge-Mweza, T.O. (2012). Identification of Polymorphism in the Keratin Genes (KAP3.2, KAP6.1, KAP7, KAP8) and Microsatellite BfMS in Merino Sheep Using Polymerase Chain Reaction-Single Strand Conformational Polymorphism(PCR-SSCP)analysis. (http://dx.doi.org/10.5772/45732 Mahajan.V., Das, A.K., Taggar, R.K., Kumar, D. and Kumar, N. (2015). Polymorphism of keratin-associated protein KAP) 3.2 gene and its association with wool traits in Rambouillet sheep. Indian J Anim Sci., 85 (3): 262–265. McLaren,R.J., Geraldine R. Rogers., Kizanne P. Davies., Jill F. Maddox. and Grant W. Montgomery. (1997). Linkage mapping of wool keratin and keratin-associated protein genes in sheep. Mamm Genome., 8: 938-940. Montgomery, G.W. and Sise, J.A. (1990). Extraction of DNA from sheep white blood cells. New Zeal J Agr Res., 33(3): 437-441. Plowman, J.E. (2003). Proteomic database of wool components. J. Chromatogr. B., 787: 63–76. Powell, B.C. (1996). The keratin proteins and genes of wool and hair. Wool Tech Sheep Bree., 44: 100–118. Rogers, M.A., Langbein, L., Praetzel, W.S., Winter, H. and Schweizer, J. (2006). Human hair keratin associated proteins (KAPs). Int Rev Cytol., 251: 209–263 Schweizer, J., Bowden, P.E., Coulombe, P.A., Langbein, L., Lane, E.B., Magin, T.M., Maltais, L., Omary, M.B., Parry, D.A., Rogers, M.A. and Wright, M.W. (2006). New consensus nomenclature for mammalian keratins. J. Cell Biol., 174: 169–174. Wang, Z.Y. and QI, Q.Q. (2010). Analysis on single nucleotide polymorphisms of Keratin-associated Proteins gene in Plateau Tibetan sheep. China Animal Husbandry & Veterinary Medicine., 37(10): 120-124. Sateesh Pujari and Estari Mamidala (2015). Anti-diabetic activity of Physagulin-F isolated from Physalis angulata fruits. The Ame J Sci & Med Res, 2015,1(1):53-60 Wang, Z.Y., Chen, Y.L., Xu, Q.L., Ma, Z.R. and Qi, Q.Q. (2011). Polymorphism of KAP 3.2 gene and its effect on partial economic traits in Tibetan sheep. Acta Veterinaria et Zootechnica Sinica., 42 (2): 284–288. Yeh, F.C., Yang, R.C., Boyle, B.J.T., Ye, Z.H. and Mao, X.J. (1999). POPGENE 32 version 1.32, the user-friendly shareware for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta,Canada.(http://www.ualberta.ca/~fyeh/ fyeh).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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".

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Published2022
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