Indian Journal of Animal Research

  • Chief EditorK.M.L. Pathak

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Indian Journal of Animal Research, volume 51 issue 3 (june 2017) : 444-448

Association between microsatellite regions and reproduction related traits in indigenous chicken ecotypes

B.H. Rudresh*, H.N.N. Murthy, A.M. Kotresh, V.B. Shettar
1<p>Department of Animal Genetics and Breeding,&nbsp;Veterinary College, Shimoga-577 204, Karnataka, India.</p>
Cite article:- Rudresh* B.H., Murthy H.N.N., Kotresh A.M., Shettar V.B. (2016). Association between microsatellite regions and reproductionrelated traits in indigenous chicken ecotypes . Indian Journal of Animal Research. 51(3): 444-448. doi: 10.18805/ijar.9556.

The present study was carried out in six indigenous ecotypes of two divisions of Karnataka to assess association of twenty microsatellite regions of thirteen chicken autosomes with age, body weight and egg weight at sexual maturity and Forty week egg production. The general molecular technique protocols were adopted wherever required in PCR, electrophoresis,    gel staining   and reading.  The analysis revealed significant difference (p<0.05) among genotypes combined across ecotypes for nineteen microsatellite loci for body weight at sexual maturity. The analysis revealed significant difference (P<0.05) among genotypes combined across ecotypes for eighteen microsatellite loci for EWSM. The posthoc dunnet’s test conducted in one of the microsatellite region ADL0020 genotypes after excluding genotypes with only one bird at 0.05 level of significance revealed that a particular genotype A was significantly different from two of the genotypes C and D, indicating the important role of the corresponding alleles of these genotypes in influencing the Body weight at sexual maturity. The validity of using thus identified markers or alleles need further authentication by research in other populations and further proof by expression studies.

  1. Abasht, B., Dekkers, J.C.M. and Lamont, S.J., (2006). Review of quantitative trait loci identified in the chicken. Poult. Sci., 85: 2079-2096.

  2. Ambady, S., Cheng, H.H. and Ponce de Leo´n, F.A., (2002). Development and mapping of microsatellite markers derived from chicken chromosome-specific libraries. J. Poult. Sci., 81: 1644-1646.

  3. Beckman, J. S. and Soller, M., (1983). Restriction fragment length polymorphisms in genetic improvement-    methodologies, mapping and costs. Theor. Appl. Genet., 67:35-43.

  4. Besbes, B., Tixierboichard, M., Hoffmann, I. and Jain, G.L., (2007). Future trends for poultry genetic resources. FAO-    bangkok: 1-8.

  5. Boschiero, C., Rosario, M.F., Ledur, M.C., Campos, R.L.R., Ambo, M., Coutinho, L.L. and Moura, A.S.A.M.T., (2009). Associations between microsatellite markers and traits related to performance, carcass and organs in chickens. Int. J. Poult. Sci., 8: 615-620.

  6. Chatterjee, R. N., Sharma, R. P., Bhattacharya, T. K., Niranjan, M. and Reddy, B. L. N., (2010). Microsatellite variability and its relationship with growth, egg production and immune competence traits in chickens. Biochem.Genet., 48: 71–82.

  7. Chatterjee, R.N., Sharma, R.P., Mishra, A., Dange, M. and Bhattacharya, T.K., (2008). Variability of microsatellites and their association with egg production traits in chicken. Int. J. Poult. Sci., 7: 77-80.

  8. Dekkers, J. C. M. and Hospital, F., (2002). The use of molecular genetics in the improvement of agricultural populations. Nature, 3:22-32.

  9. Falconer, D. S. and Mackay, T. F. C., (1996). Introduction to Quantitative Genetics. Longman: New York, pp: 42-44.

  10. FAO, (2011). Molecular Genetic Characterization of Animal Genetic Resources. Animal Production and Health Guidelines. No. 9. Rome. pp 84.

  11. Gupta, P.K., (2002). Molecular markers and QTL analysis in crop plants. Curr. Sci., 83: 113-114.

  12. Haley, C. S. and Knott, S. A. (1992). A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity, 69:315-324.

  13. Halima, B., Jean-Marie, J., Jean-Pierre, B. and Guy, M., (2006). Optimization of a reliable, fast, cheap and sensitive silver staining method to detect SSR markers in polyacrylamide gels, Biotechnol.Agron. Soc. Environ., 10: 77 – 81.

  14. Hocking, P.M., (2005). Review of QTL mapping results in chickens. World’s Poult. Sci.J., 61: 215-226.

  15. Lander, E. and Kruglyak, L., (1995). Genetic dissection of complex traits: Guidelines for interpreting and reporting linkage results. Nat. Genet., 11:241-247.

  16. Liu, Z., Tan, G., LI, P. and Dunham, R.A., (1999). Transcribed dinucleotide microsatellites and their associated genes from channel catfish Ictaluruspunctatus. Biochemical and Biophysical Res. Commun., 259: 190-194.

  17. Mcelroy, J.P., Dekkers, J.C.M., Fulton, J.E., O’Sullivan, N.P., Soller, M., Lipkin, E., Zhang, W., Koehler, K.J., Lamont, S.J. and Cheng, H.H., (2005). Microsatellite markers associated with resistance to Marek’s disease in commercial layer chickens. J. Poult. Sci., 84: 1678-1688.

  18. Nassar F. S., Moghaieb,R. E. A., Abdou, A. M. and Stino, F. K. R., 2012. Afr. J. Biotech., 11: 3514-3521.

  19. Pandey, A. K., Dinesh Kumar, Sharma, R., Sharmau., VIJH, R. K. and Ahlawat, S. P. S., (2005). Population structure and genetic bottleneck analysis of Ankaleshwar poultry breed by microsatellite markers. Asian–Aust. J. Anim. Sci., 18: 915–921

  20. Pirany, N., Romanov, M. N., Ganpule, S. P., Devegowda, G. and Prasad, D.T., (2007). Microsatellite analysis of genetic diversity in Indian chicken populations. J. Poult. Sci., 44:19-28.

  21. Podisi, Baitsi, K., Sara, A., Knott, David, W., Burt and Hocking, Paul. M., (2013). Comparative analysis of quantitative trait loci for body weight, growth rate and growth curve parameters from 3 to 72 weeks of age in female chickens of a broiler–layer cross. BMC Genetics, 14:22.

  22. Rajkumar, U., Gupta, B. R. and Reddy, A. R., (2008). Genomic heterogeneity of chicken populations of India. Asian-Aust. J. Anim. Sci., 21:1710-1720.

  23. Sambrook, J., Fritsch, E.F. and Manutis, T., (1989). Molecular cloning: A Laboratory Manual., 2nd ed, vol. 1 & 2. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.

  24. Stallings, R. L., Ford, A. F., Nelson, D., Torney, D. C., Hildebrand, C. E. and Moyzis, R. K., (1991). Evolution and distribution of (GT)n repetitive sequences in mammalian genomes. Genomics, 10:807–815.

  25. Tuiskula-Haavisto, M., Honkatukia, M., Vilkki, J., De Koning, D.J., Schulman, N.F. and Ma¨Ki-Tanil, A., (2002). Mapping of quantitative trait loci affecting quality and production traits in egg layers. Poult. Sci., 81: 919- 927.

  26. Wardecka, B., Jaszczak, K., Pierzchala, M., Parada, R. and Korczak, M., (2004). Divergent selection for skeletal malformations in chickens alters polymorphism at microsatellite loci. J. Appl. Genet., 45: 61-71.

  27. Zhang, Hui., Shouzhi Wang, Hui Li, Xijiang Yu, Ning Li, Qin Zhang, Xiaofeng Liu Qigui Wang, Xiao Xiang Hu, Yuxiang Wang and Zhiquan Tang, (2008). Microsatellite Markers Linked to Quantitative Trait Loci Affecting Fatness in Divergently Selected Chicken Lines for Abdominal Fat. Asian-Aust. J. Anim. Sci., 21:1389-1394.


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