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Genomic Heterogeneity of Chicken Populations in India

  • Rajkumar, Ullengala (College of Veterinary Science, Sri Venkateswara Veterinary University) ;
  • Gupta, B. Ramesh (College of Veterinary Science, Sri Venkateswara Veterinary University) ;
  • Reddy, A. Rajasekhara (College of Veterinary Science, Sri Venkateswara Veterinary University)
  • Received : 2008.05.22
  • Accepted : 2008.08.25
  • Published : 2008.12.01

Abstract

A comprehensive genome profiling study was undertaken based on automated genotyping and analysis of 20 microsatellite markers that involved 155 birds representing eight different populations. The distribution of microsatellite markers in each of these breeds helped us to decipher genetic heterogeneity, population genetic structure and evolutionary relationships of the present day chicken populations in India. All the microsatellite loci utilized for the analysis were polymorphic and reasonably informative. A total of 285 alleles were documented at 20 loci with a mean of 14.25 alleles/locus. A total of 103 alleles were found to be population/strain specific of which, only 30 per cent had a frequency of more than 10. The mean PIC values ranged from 0.39 for the locus ADL158 to 0.71 for loci MCW005 or ADL267 across the genomes and 0.55 in Dahlem Red to 0.71 in Desi (non-descript), among the populations. The overall mean expected and observed heterozygosity estimates for our populations were 0.68 and 0.64, respectively. The overall mean inbreeding coefficients (FIS) varied between -0.05 (Babcock) and 0.16 (Rhode Island Red). The pairwise FST estimates ranged from 0.06 between Aseel and Desi (non-descript) to 0.14 between Dahlem Red and Babcock. The Nei's genetic distance varied from 0.30 (WLH-IWD and WLH-IWF) to 0.80 (Dahlem Red and Babcock. Phylogenetic analysis grouped all the populations into two main clusters, representing i) the pure breeds, Dahlem Red and Rhode Island Red, and ii) the remaining six populations/strains. All the chicken populations studied were in the state of mild to moderate inbreeding except for commercial birds. A planned breeding is advised for purebreds to revive their genetic potential. High genetic diversity exists in Desi (non-descript), local birds, which can be exploited to genetically improve the birds suitable for backyard poultry.

Keywords

References

  1. Botstein, D., R. L. White, M. Skolnik and R. W. Davis. 1980. Construction of genetic linkage map in manusing restriction fragment length polymorphisms. Am. J. Hum. Genet. 32:314-331.
  2. Chen, G. H., X. S. Wu, D. Q. Wang, J. Qin, S. L. Wu, Q. L. Zhou, F. Xie, R. Cheng, Q. Xu, B. Liu, X. Y. Zhang and O. Olowofeso. 2004. Cluster analysis of 12 Chinese native chicken populations using microsatellite markers. Asian-Aust. J. Anim. Sci. 17:1047-1052. https://doi.org/10.5713/ajas.2004.1047
  3. Cheng, H. H., I. Levi, R. L. Vallejo, H. Khatib, J. B. Dodgson, L. B. Crittenden and J. Hillel. 1995. Development of genetic map of the chicken with markers of high utility. Poult. Sci. 74:1874-1885.
  4. Crooijmans, R. P. M. A., A. F. Groen, A. J. A. Van Kampen, S. Van der Beek, J. J. Van der Poel and M. A. M. Groenen. 1996a. Microsatellite polymorphism commercial broiler and layer lines estimated using pooled blood samples. Poult. Sci. 75:904-909. https://doi.org/10.3382/ps.0750904
  5. Crooijmans, R. P. M. A., P. A. M. van Ders, J. A. Strijk, J. J. Van der Poel and M. A. M. Groenen.1996b. Priliminary linkage map of the chicken (Gallus domesticus) genome based on microsatellite markers: 77 new markers mapped. Poult. Sci. 75:746-754. https://doi.org/10.3382/ps.0750746
  6. Emara, M. G., H. Kim, J. Zhu, R. R. Lapierre, N. Lakshmanan and H. S. Lillehoj. 2002. Genetic diversity at the major histocompatibility complex (B) and microsatellite loci in three commercial broiler pure lines. Poult. Sci. 81:1609-1617. https://doi.org/10.1093/ps/81.11.1609
  7. Fan, B., Y. Chen, C. Moran, S. H. Zhao, B. Liu, M. J. Zhu, T. A. Xiang and K. Li. 2005. Individual breed assignment analysis in swine production by using microsatellite markers. Asian-Aust. J. Anim. Sci. 18:1529-1534. https://doi.org/10.5713/ajas.2005.1529
  8. Flock, D. and R. Preisinger. 2002. Breeding plan for poultry with emphasis on sustainability. 7th World Conference on Genetic Applications for Livestock Production, 19-23 August, Montpelliers, France.
  9. Goudet, J. 1995. FSTAT (Version 1.2): A computer program to calculate F-statistics. J. Hered. 86:485-486. https://doi.org/10.1093/oxfordjournals.jhered.a111627
  10. Freimer, N. B. and M. Slatkin. 1996. Microsatellites: Evolution and mutation processes. Ciba Found. Symp. 197:51-72.
  11. Hillel, J., A. M. Groenen, M. T. Biochard, A. B. Korol, L. David, V. M. Kirzhner, T. Burke, A. B. Dirie, R. P. M. A. Crooijmans, K. Elo, M. W. Feldman, P. J. Freidlin, A. M. Tanila, M. Oortwijn, P. Thomson, A. Vignal, K. Wimmers and S. Weigend. 2003. Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools. Genet. Sel. Evol. 35:533-557. https://doi.org/10.1186/1297-9686-35-6-533
  12. Ji, C. L., G. H. Chen, M. Q. Wang and S. Weigend. 2005. Genetic structure and diversity of 12 Chinese indigenous chicken breeds. The role of Biotech. 5-7 March 2005, Villa Gualino, Turin, Italy.
  13. Lee, Y. J., M. S. A. Bhuiyan, H. J. Chung, W. Y. Jung, K. D. Choi, B. G. Jang, W. K. Paek, J. T. Jeon, C. S. Park and J. H. Lee. 2007. Mitochondreal DNA delivary of Korean Ogol chicken. Asian-Aust. J. Anim. Sci. 20:477-482. https://doi.org/10.5713/ajas.2007.477
  14. Kaya, M. and M. A. Yildizi. 2008. Genetic diversity among Turkish native chickens, Denzil and Gerze, estimated by microsatellite markers. Biochem. Genet. 46:480-491. https://doi.org/10.1007/s10528-008-9164-8
  15. Kong, H. S., J. D. Oh, J. H. Lee, K. J. Jo, B. D. Sang, C. H. Choi, S. D. Kim, S. J. Lee, S. H. Yeon, G. J. Jeon and H. K. Lee. 2006. Genetic variation and relationships of Korean native chickens and foreign breeds using 15 microsatellite markers Asian-Aust. J. Anim. Sci. 19:1546-1550. https://doi.org/10.5713/ajas.2006.1546
  16. Kumar, S., K. Tamura and M. Nei. 2004. MEGA 3.1: Integrated software for molecular evolutionary genetics analysis and sequence alignment. Bioinform. 5:150-163. https://doi.org/10.1186/1471-2105-5-150
  17. Muir, W. M., G. K. Wong, Y. Zhang, J. Wang, M. A. M. Groenen, R. P. M. A. Crooijmans, H.-J. Megens, H. M. Zhang, J. C. Mckay, S. Mcleod, R. Okimoto, J. E. Fulton, P. Settar, N. P. O'Sullivan, A. Vereijken, A. Jungerius-Rattink, G. A. A. Albers, C. Taylor Lawley, M. E. Delany and H. H. Cheng. 2008. Review of the initial validation and characterization of a 3K chicken SNP array. Wor Poult. Sci. J. 64:219-226. https://doi.org/10.1017/S0043933908000019
  18. Nei, M. 1972. Genetic distance between populations. Am. Natur. 106:283-292. https://doi.org/10.1086/282771
  19. Nei, M. 1987. Molecular evolutionary genetics.Columbia Press, NY.
  20. Oh, J. D., H. S. Kong, J. H. lee, I. S. Choi, S. J. Lee, S. G. Lee, B. D. Sang, C. H. Choi, B. W. Cho, G. J. Jeon and H. K. Lee. 2006. Identification of novel SNPs with effect on economic traits in uncoupling protein gene of Korean native chicken. Asian-Aust. J. Anim. Sci. 19:1065-1070. https://doi.org/10.5713/ajas.2006.1065
  21. Ohta, T. and M. Kimura. 1973. The model of mutation appropriate to estimate the number of electrophoretically detectable alleles in a genetic population. Genet. Res. 22:201-204. https://doi.org/10.1017/S0016672300012994
  22. Olowofeso, O., J. Y. Wang, G. J. Dail, Y. Yang, D. M. Mekki and H. H. Musa. 2005a. Measurement of genetic parameters within and between Haimen chicken populations using microsatellite markers. Int. J. Poult. Sci. 4:143-148. https://doi.org/10.3923/ijps.2005.143.148
  23. Olowofeso, O., J. Y. Wang, K. Z. Xie and G. Q. Liu. 2005b. Phylogenetic scenario of port-city chickens in China based on two-marker types. Int. J. Poult. Sci. 4:206-212. https://doi.org/10.3923/ijps.2005.206.212
  24. Osman, S. A. M., M. Sekino, A. Nishihata, Y. Kobayashi, W. Takenaka, K. Kinoshita, T. Kuwayama, M. Nishibori, Y. Yamamoto and M. Tsudzuki. 2006. The genetic variability and relationships of Japanese and foreign chicken assessed by microsatellite DNA profiling. Asian-Aust. J. Anim. Sci. 19:1369-1378. https://doi.org/10.5713/ajas.2006.1369
  25. Park, S. D. E. 2001. The excel microsatellite toolkit: Trypanotolerance in west African cattle and the population genetic effects of selection (Ph.D. thesis), University of Dublin. Available at http://oscar.gen.tcd.ie/-sdepark/ms-toolkit/
  26. Pandey, A. K., Bina Misra, Preeti Chaudhary, M. S. Tantia and R. K. Vijh. 2003. Microsatellite analysis in three breeds of Indian poultry. Indian J. Anim. Sci. 73:788-792.
  27. Pandey, A. K., Dinesh Kumar, Rekha Sharma, Uma Sharma, R. K. Vijh and P. S. Ahlawat. 2005. Population structure and genetic bottleneck analysis of Ankleshwar poultry breed by microsatellite markers. Asian-Aust. J. Anim. Sci. 18:915-921. https://doi.org/10.5713/ajas.2005.915
  28. Pandey, A. K., M. S. Tantia, Dinesh Kumar, Bina Mishra, Preeti Chaudhary and R. K. Vijh. 2002. Microsatellite analysis of three poultry breeds of India. Asian-Aust. J. Anim. Sci. 15:1536-1542. https://doi.org/10.5713/ajas.2002.1536
  29. Peakall, R. and P. E. Smouse. 2005. GenAlEx 6: Genetic analysis in excel. Population genetic software for teaching and research. Mol. Ecol. Notes, Available at http://www.anu.edu.au/BoZo/GenAlEx/
  30. Pirany, N., M. N. Romanov, S. P. Ganpule, G. Devegowda and D. T. Prasad. 2007. Microsatellite analysis of genetic diversity in Indian chicken populations. J. Poult. Sci. 44:19-28. https://doi.org/10.2141/jpsa.44.19
  31. Qu, L., X. Li, G. Xu, K. Chen, H. Yang, L. Zhang, G. Wu, Z. Hou, G. Xu and N. Yang. 2006. Evaluation of genetic diversity in Chinese indigenous chicken breeds using microsatellite markers. Sci. China C. Life Sci. 49:332-341. https://doi.org/10.1007/s11427-006-2001-6
  32. Romanov, M. N. and S. Weigend. 2001. Analysis of genetic relationships between various populations of domestic and red jungle fowl using microsatellite markers. Poult. Sci. 80:1057-1063. https://doi.org/10.1093/ps/80.8.1057
  33. Shahabazi, S., S. Z. Mirhossini and M. N. Romanov. 2007. Genetic diversity in five Iranian native chicken populations estimated by microsatellite markers. Biochem. Genet. 45:63-75. https://doi.org/10.1007/s10528-006-9058-6
  34. Tadano, R., M. Sekino, M. Nishibori and M. Tsudzuki. 2007. Microsatellite marker analysis for the genetic relationships among Japanese long tailed Chicken breeds. Poult. Sci. 86:460-469. https://doi.org/10.1093/ps/86.3.460
  35. Vanhala, T., M.Tuiskala-Haavisto, K. Elo, J. Vilkki and A. Maki Tanila. 1998. Evaluation of genetic variability and genetic distances between eight chicken lines using microsatellite markers. Poult. Sci. 77:783-790. https://doi.org/10.1093/ps/77.6.783
  36. Vijh, R. K., Bina Misra, A. K. Pandey, Preeti Chaudhary and M. S. Tantia. 2004. Phylogenetic reconstruction of four poultry populations using stepwise-mutation model. Indian J. Anim. Sci. 74:647-652.
  37. Wandelt, R. and J. Wolters. 1996. Handbuch der Huhnerrassendie Huhnerrassen der Welt. Verlag Wolters, Bottrop, Germany.
  38. Wimmers, K., S. Ponsuksili, T. Hardge, A. Valle-Zarate, P. K. Mathur and Horst. 2000. Genetic distances of African, Asian and South American local chickens. Anim. Genet. 31:159-165. https://doi.org/10.1046/j.1365-2052.2000.00605.x
  39. Wright, S. 1978. Variability within and among natural populations. Evolution and the Genetics of Populations. Vol. 4, University of Chicago Press, Chicago.
  40. Yoon, D. H., J. D. Oh, J. H. Lee, K. J. Jo, K. S. Kong, B. W. Chow, J. D. Kim, K. J. Jeon C. Y. Joe, G. J. Jeon and H. K. Lee. 2005. Establishment of individual identification system based on the microsatellite polymorphism in Hanwoo. Asian-Aust. J. Anim. Sci. 18:762-766. https://doi.org/10.5713/ajas.2005.762
  41. Zhou, H. and S. J. Lamont. 1999. Genetic characterization of biodiversity in highly inbred chicken lines by microsatellite markers. Anim. Genet. 30:256-264. https://doi.org/10.1046/j.1365-2052.1999.00505.x

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