Polymorphism of Keratin - associated protein (KAP) 3.2 gene in Sandyno and Nilagiri breeds of sheep
Bibliographic record
Abstract
<strong>ABSTRACT</strong> <strong>ABSTRACT</strong> Polymorphic variants of keratin-associated protein (<em>KAP</em>) 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 <em>KAP</em> 3.2 gene. The genotyping was done by using PCR-SSCP. <em>KAP</em> 3.2 gene locus revealed 3 genotypes, viz. <em>AA, AB</em> and <em>BB</em> 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 <em>KAP</em> 3.2 with no significant difference. <em>KAP</em> 3.2 gene was found to have high degree of homozygosity (0.8824) in Nilagiri sheep. The effective number of alleles (Ne) for <em>KAP</em> 3.2 was 1.1716 and 1.1690 respectively in Sandyno and Nilagiri breeds of sheep. The PIC values for <em>KAP</em> 3.2 was 0.1356 and 0.1341 in Sandyno and Nilagiri breeds of sheep respectively. FIS values for <em>KAP</em> 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 <em>KAP </em>3.2 loci in Sandyno and Nilagiri breeds of sheep indicates monomorphic situation. <strong>Keywords</strong><strong>:</strong> Keratin Associated Protein (<em>KAP</em>) 3.2 , PCR-SSCP, Polymorphism, Sheep, Wool traits <strong>REFERENCES</strong> Barba, C., Mendez, S., Martí, M., Parra, J.L. and Coderch, L. (2009). Water content of hair and nails. Thermochim Acta<em>., </em>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 (<em>KAP3.2, KAP6.1, KAP7, KAP8</em>) and Microsatellite <em>BfMS</em> 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 <em>KAP</em>) 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<em>.,</em> 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. <em>China Animal Husbandry & Veterinary Medicine</em><em>.</em><em>,</em> 37(10): 120-124. Sateesh Pujari and Estari Mamidala (2015). Anti-diabetic activity of Physagulin-F isolated<br> 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 <em>KAP 3.2 </em>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).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".