Browse > Article
http://dx.doi.org/10.1186/s40781-015-0044-6

Discrimination of the commercial Korean native chicken population using microsatellite markers  

Choi, Nu Ri (Department of Animal Science and Biotechnology, College of Agriculture and Life Sciences, Chungnam National University)
Seo, Dong Won (Department of Animal Science and Biotechnology, College of Agriculture and Life Sciences, Chungnam National University)
Jemaa, Slim Ben (Department of Animal Science and Biotechnology, College of Agriculture and Life Sciences, Chungnam National University)
Sultana, Hasina (Department of Animal Science and Biotechnology, College of Agriculture and Life Sciences, Chungnam National University)
Heo, Kang Nyeong (Poultry Science Division, National Institute of Animal Science, RDA)
Jo, Cheorun (Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute for Agriculture and Life Science, Seoul National University)
Lee, Jun Heon (Department of Animal Science and Biotechnology, College of Agriculture and Life Sciences, Chungnam National University)
Publication Information
Journal of Animal Science and Technology / v.57, no.2, 2015 , pp. 5.1-5.8 More about this Journal
Abstract
Background: Korean native chicken (KNC) is a well-known breed due to its superior meat taste. This breed, however, owing to a low growth rate, has a high market price. In order to overcome this disadvantage, the National Institute of Animal Science (NIAS) in Korea developed a commercial KNC breed, named Woorimatdag version 2 (WM2), an upgraded version of the Woorimatdag (WM1) breed and the WM2 was created by crossing the KNC with meat type breeds. This study aims to discriminate between WM2 and other chicken breeds using microsatellite (MS) markers. Methods: A total of 302 individuals from eight Korean chicken populations were examined. The genetic diversity and population structure analysis were investigated using Cervus, API-CALC, STRUCTURE, PowerMarker programs. Results: Based on heterozygosity and polymorphic information content (PIC) values, 30 MS markers were initially selected from 150 markers. The identified average number of alleles (Na), expected heterozygosity, and PIC values for the WM2 samples were 7.17, 0.741, and 0.682, respectively. Additionally, the paternity of individuals was assigned with a success rate of greater than 99% using 12 markers, the best minimum number of markers. The 12 selected markers contained heterozygosity and PIC values above 0.7 and probability of identity values around zero. Using these markers, the determined probability of identity (PI), $PI_{half-sibs}$, and $PI_{sibs}$ values were 3.23E-33, 5.03E-22, and 8.61E-08, respectively. Conclusions: WM2 is well differentiated with respect to other chicken breeds based on estimated genetic distances. The results presented here will contribute to the identification of commercial WM2 chicken in the market.
Keywords
Discrimination; Diversity; Microsatellite; Korean native chicken; Woorimatdag;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
연도 인용수 순위
1 Ministry of Agriculture, Food and Rural Affairs. Primary statistics of Ministry of Agriculture, Food and Rural Affairs. 2014, Korea
2 Jaturasitha S, Srikanchai T, Kreuzer M, Wicke M. Differences in carcass and meat characteristics between chicken indigenous to northern Thailand (Black-boned and Thai native) and imported extensive breeds (Bresse and Rhode Island Red). Poult Sci. 2008;87:160-9.   DOI
3 Heo KN, Choo HJ, Seo BY, Park MN, Jung KC, Hwangbo J, et al. Investigation of TYR and MC1R polymorphisms in Korean native chickens and the commercial chickens. CNU J Agric Sci. 2011;38:465-71.
4 Park MN, Hong EC, Kang BS, Kim HK, Kim JH, Na SH, et al. Chemical composition and meat quality of crossbred Korean native chickens (KNC). Korean J Poult Sci. 2010;37:415-21.   DOI
5 Jung YK, Jeon HJ, Jung S, Choe JH, Lee HJ, Heo KN, et al. Comparison of quality traits of thigh meat from Korean native chickens and broilers. Korean J Food Sci Ani resour. 2011;31:684-92.   DOI
6 Park MN, Kim TH, Lee HJ, Choi JA, Heo KN, Kim CD, et al. Genetic variatiion of chicken MC1R gene and associations with feather color of Korean native chicken (KNC) 'Woorimatdag'. Korean J Poult Sci. 2013;40:139-45.   DOI
7 Hillel J, Groenen MA, Tixier-Boichard M, Korol AB, David L, Kirzhner VM, et al. Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools. Genet Sel Evo. 2003;35:533-58.   DOI
8 Lim HT, Seo BY, Jung EJ, Yoo CK, Yoon DH, Jeon JT. A comparison of discriminating powers between 14 microsatellite markers and 60 SNP markers applicable to the cattle identification test. J Anim Sci Technol. 2009;51:353-60.   DOI
9 Lim HT, Seo BY, Jung EJ, Yoo CK, Zhong T, Cho IC, et al. Estabilishment of a microsatellite marker set for individual, pork brand and product origin identification in pigs. J Anim Sci Technol. 2009;51:201-6.   DOI
10 Cheng HH, Crittenden LB. Microsatellite markers for genetic mapping in the chicken. Poult Sci. 1994;73:539-46.   DOI
11 Crooijmans RP, Groen AF, Van Kampen AJ, Van der Beek S, Van der Poel JJ, Groenen MA. Microsatellite polymorphism in commercial broiler and layer lines estimated using pooled blood samples. Poult Sci. 1996;75:904-9.   DOI
12 Abasht B, Dekkers JCM, Lamont SJ. Review of quantitative trait loci identified in the chicken. Poult Sci. 2006;85:2079-96.   DOI
13 Food and Agriculture Organization of the United Nations. Molecular genetic characterization of animal genetic resources. Rome: FAO Animal production and Health Guidelines; 2011. No. 9: 84-85.
14 Seo DW, Hoque MR, Choi NR, Sultana H, Park HB, Heo KN, et al. Discrimination of Korean native chicken lines using fifteen selected Microsatellite markers. Asian-Aust J Anim Sci. 2013;26:316-22.   DOI
15 Marshall T, Slate J, Kruuk L, Pemberton J. Statistical confidence for likelihood‐based paternity inference in natural populations. Mol Ecol. 1998;7:639-55.   DOI
16 Ayres KL, Overall AD. api‐calc 1.0: a computer program for calculating the average probability of identity allowing for substructure, inbreeding and the presence of close relatives. Mol Ecol Notes. 2004;4:315-8.   DOI
17 Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000;155:945-59.
18 Jombart T, Collins C, Solymos P, Ahmed I, Calboli F, Cori A. Package 'adegenet'. ftp://mint.c3sl.ufpr.br/CRAN/web/packages/adegenet/adegenet.pdf. Accessed June 7, 2014.
19 Jombart T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics. 2008;24:1403-5.   DOI
20 Jombart T, Devillard S, Balloux F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics. 2010;11:94.
21 Nei M, Tajima F, Tateno Y. Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol. 1983;19:153-70.   DOI
22 Liu K, Muse SV. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics. 2005;21:2128-9.   DOI
23 Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics. 2004;20:289-90.   DOI
24 Huson DH, Bryant D. Application of phylogenetic networks in evolutionary studies. Mol Biol Evol. 2006;23:254-67.   DOI
25 Suh S, Cho CY, Kim JH, Choi SB, Kim YS, Kim H, et al. Analysis of genetic characteristics and probability of individual discrimination in Korean indigenous chicken brands by microsatellite marker. J Anim Sci Technol. 2013;55:185-94.   DOI
26 Botstein D, White RL, Skolnik M, Davis RW. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet. 1980;32:314-31.
27 Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol. 2005;14:2611-20.   DOI