Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Genetic characterization and population structure of six brown layer pure lines using microsatellite markers

  • Karsli, Taki (Faculty of Agriculture, Department of Animal Science, Akdeniz University) ;
  • Balcioglu, Murat Soner (Faculty of Agriculture, Department of Animal Science, Akdeniz University)
  • Received : 2017.11.27
  • Accepted : 2018.04.06
  • Published : 2019.01.01
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Abstract

Objective: The first stage in both breeding and programs for the conservation of genetic resources are the identification of genetic diversity in the relevant population. The aim of the present study is to identify genetic diversity of six brown layer pure chicken lines (Rhode Island Red [RIRI, RIRII], Barred Rock [BARI, BARII], Columbian Rock [COL], and line 54 [L-54]) with microsatellite markers. Furthermore, the study aims to employ its findings to discuss the possibilities for the conservation and sustainable use of these lines that have been bred as closed populations for a long time. Methods: In the present study, a total number of 180 samples belonging to RIRI (n = 30), RIRII (n = 30), BARI (n = 30), BARII (n = 30), L-54 (n = 30), and COL (n = 30) lines were genotyped using 22 microsatellite loci. Microsatellite markers are extremely useful tools in the identification of genetic diversity since they are distributed throughout the eukaryotic genome in multitudes, demonstrate co-dominant inheritance and they feature a high rate of polymorphism and repeatability. Results: In this study, we found all loci to be polymorphic and identified the average number of alleles per locus to be in the range between 4.41 (BARI) and 5.45 (RIRI); the observed heterozygosity to be in the range between 0.31 (RIRII) and 0.50 (BARII); and $F_{IS}$ (inbreeding coefficient) values in the range between 0.16 (L-54) and 0.46 (RIRII). The $F_{IS}$ values obtained in this context points out to a deviation from Hardy-Weinberg equilibrium due to heterozygote deficiency in six different populations. The Neighbour-Joining tree, Factorial Correspondence Analysis and STRUCTURE clustering analyzes showed that six brown layer lines were separated according to their genetic origins. Conclusion: The results obtained from the study indicate a medium level of genetic diversity, high level inbreeding in chicken lines and high level genetic differentiation between chicken lines.

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References

  1. Mahmoudi B, Bayat M, Sadeghi R, Babayev MS, Abdollahi H. Genetic diversity among three goat populations assessed by microsatellite DNA markers in Iran. Glob Vet 2010;4:118-24.
  2. Chatterjee RN, Bhattacharya TK, Dange M, Rajkumar U. Assessment of genetic relatedness of crossbred chicken populations using microsatellite markers. Biochem Genet 2010;48: 727-36. https://doi.org/10.1007/s10528-010-9355-y
  3. Hillel J, Groenen MAM, Tixier-Boichard M, et al. Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools. Genet Sel Evol 2003;35:533-57. https://doi.org/10.1186/1297-9686-35-6-533
  4. FAO. Molecular genetic characterization of animal genetic resources. Animal Production and Health Guidelines; 9, pp. 84-5, 2011 [cited 2017 August 30]. Available from: http://www.fao.org/docrep/014/i2413e/i2413e00.htm
  5. Rajmukar U, Gupta BR, Ahmed N, Venktramaiah A, Reddy AR. Genetic variation and genetic diversity in chicken populations using microsatellite assay. Indian J Anim Sci 2007;77: 1194-8.
  6. Miller S, Dykes D, Plesky HA. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988;16:1215. https://doi.org/10.1093/nar/16.3.1215
  7. Tadano R, Nishibori M, Nagasaka N, Tsudzuki M. Assessing genetic diversity and population structure for commercial chicken lines based on forty microsatellite analyses. Poult Sci 2007;86:2301-8. https://doi.org/10.3382/ps.2007-00233
  8. Seo DW, Hoque MR, Choi NR, et al. Discrimination of Korean native chicken lines using fifteen selected microsatellite markers. Asian-Australas J Anim Sci 2013;26:316-22. https://doi.org/10.5713/ajas.2012.12469
  9. Glaubitz JC. CONVERT: A user-friendly program to reformat diploid genotypic data for commonly used population genetic software packages. Mol Ecol Notes 2004;4:309-10. https://doi.org/10.1111/j.1471-8286.2004.00597.x
  10. Kalinowski ST, Taper ML. Maximum likelihood estimation of the frequency of null alleles at microsatellite loci. Conserv Genet 2006;7: 991-5. https://doi.org/10.1007/s10592-006-9134-9
  11. Yeh FC, Yang RC, Boyle TBJ, Ye ZH, Mao JX. POPGENE, The user-friendly shareware for population genetic analysis, Molecular Biology and Biotechnology Centre. Edmonton, AB, Canada. University of Alberta; 1997.
  12. Liu K, Muse S. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 2005;21:2128-9. https://doi.org/10.1093/bioinformatics/bti282
  13. Goudet J. FSTAT (Version 1.2), A computer program to calculate F-Statistics. J Hered 1995;86:485-6. https://doi.org/10.1093/oxfordjournals.jhered.a111627
  14. Excoffier L, Laval G, Schneider S. ARLEQUIN version 3.01: an integrated software package for population genetics data analysis. Bern, Switzerland: Institute of Zoology, University of Bern; 2006.
  15. Takezaki N, Nei M, Tamura K. POPTREE2: software for constructing population trees from allele frequency data and computing other population statistics with windows-interface. Mol Biol Evol 2010;4:747-52. https://doi.org/10.1093/molbev/msp312
  16. Belkhir K, Borsa P, Chikhi L, Raufaste N, Bonhomme F. GENETIX 4.05, logiciel sous Windows pour la genetique des populations. Montpellier, France: Universite de Montpellier II; 2004.
  17. Pritchard JK, Matthew S, Donnelly P. Inference of population structure using multilocus genotype data. Genetics 2000;155: 945-59. https://doi.org/10.1093/genetics/155.2.945
  18. Earl DA, vonHoldt BM. Structure harvester: a website and program for visualizing structure output and implementing the evanno method. Conserv Genet Resour 2012;4:359-61. https://doi.org/10.1007/s12686-011-9548-7
  19. Evanno G, Regnaut S, Goudet J. Detecting the number of cluster of individuals using the software structure: a simulation study. Mol Ecol 2005;14:2611-20. https://doi.org/10.1111/j.1365-294X.2005.02553.x
  20. Ramasamy RK, Ramasamy S, Bindroo BB, Naik VG. STRUCTURE PLOT: a program for drawing elegant STRUCTURE bar plots in user friendly interface. Springerplus 2014;3:431. https://doi.org/10.1186/2193-1801-3-431
  21. Zanetti E, Marchi DE, Abbadi M, Cassandro M. Variation of genetic diversity over time in local Italian chicken breeds undergoing in situ conservation. Poult Sci 2011;90:2195-201. https://doi.org/10.3382/ps.2011-01527
  22. Pham MH, Chang WH, Salazar CB, et al. Genetic characterization of Taiwan commercial native chickens ascertained by microsatellite markers. J Poult Sci 2013;50:290-9. https://doi.org/10.2141/jpsa.0120041
  23. Choi NR, Seo DW, Jemaa SB, et al. Discrimination of the commercial Korean native chicken population using microsatellite markers. J Anim Sci Technol 2015;57:5. https://doi.org/10.1186/s40781-015-0044-6
  24. Tadano R, Nakamura A, Kino K. Analysis of genetic divergence between closely related lines of chickens. Poult Sci 2012;9:327-33. https://doi.org/10.3382/ps.2011-01879
  25. Tadano R, Nagasaka N, Goto N, Rikimaru K, Tsudzuki M. Genetic characterization and conservation priorities of chicken lines. Poult Sci 2013;92:2860-5. https://doi.org/10.3382/ps.2013-03343
  26. Granevitze Z, Hillel J, Chen GH, et al. Genetic diversity within chicken populations from different continents and management histories. Anim Genet 2007;38:576-83. https://doi.org/10.1111/j.1365-2052.2007.01650.x
  27. Muchadeyi FC, Eding H, Wollny CBA, et al. Absence of population structuring in Zimbabwe chicken ecotypes inferred using microsatellite analysis. Anim Genet 2007;38:332-9. https://doi.org/10.1111/j.1365-2052.2007.01606.x
  28. Ramadan S, Kayang BB, Inoue E, et al. Evaluation of genetic diversity and conservation priorities for Egyptian chickens. J Anim Sci 2012;2:83-90.
  29. Simon DL, Buchenauer D. Genetic diversity of European livestock breeds. European Association for Animal Production Publication No. 66. Wageningen, The Netherlands: Wageningen Pers; 1993.
  30. Mahammi FZ, Gaouar SBS, Laloe D, et al. A molecular of patterns of genetic diversity in local chickens from western Algeria in comprasion with commercial lines and wild jungle fowls. J Anim Breed Genet 2016;133:59-70. https://doi.org/10.1111/jbg.12151