References
- Chen, G., W. Bao, J. Shu, C. Ji, M. Wang, H. Eding, F. Muchadeyi, and S. Weigend. 2008. Assessment of population structure and genetic diversity of 15 Chinese indigenous chicken breeds using microsatellite markers. Asian Australas. J. Anim. Sci. 21:331-339. https://doi.org/10.5713/ajas.2008.70125
- Crooijmans, R. P. M. A., J. V. D. Poel, and M. A. M. Groenen. 1995. Functional genes mapped on the chicken genome. Anim. Gent. 26:73-78.
- Dunnington, E. A., L. C. Stallard, J. Hillel, and P. B. Siegel. 1994. Genetic diversity among commercial chicken populations estimated from DNA fingerprints. Poult. Sci. 73:1218-1225. https://doi.org/10.3382/ps.0731218
- Earl, D. A. and B. M. von-Holdt. 2012. STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4:359-361. https://doi.org/10.1007/s12686-011-9548-7
- Evanno, G., S. Regnaut, and J. Goudet. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14:2611-2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x
- FAO/MoDAD. 2004. Secondary Guidelines. Measurement of Domestic Animal Diversity (MoDAD): Recommended Microsatellite Markers. Available at http://fao.org/dad-is
- Goudet, J. 2001. FSTAT, a program to estimate and test gene diversities and fixation indices (ver. 2.9.3.) Lausanne (Switzerland). Institute of Ecology. Available at http://www2.unil.ch/popgen/softwares/fstat.html
- Hillel, J., M. A. Groenen, M. Tixier-Boichard, A. B. Korol, L. David, V. M. Kirzhner, T. Burke, A. Barre-Dirie, R. P. M. A. Crooijmans, K. Elo, M. W. Feldman, P. J. Freidlin, A. Maki-Tanila, M. Oortwijn, P. Thomoson, 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
- Jakobsson, M. and N. A. Rosenberg. 2007. CLUMPP: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801-1806. https://doi.org/10.1093/bioinformatics/btm233
- Kalinowski, S. T., M. L. Taper, and T. C. Marshall. 2007. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 16:1099-1106. https://doi.org/10.1111/j.1365-294X.2007.03089.x
- Kaya, M. and M. A. Yıldız. 2008. Genetic diversity among Turkish native chickens, Denizli and Gerze, estimated by microsatellite markers. Biochem. Genet. 46:480-491. https://doi.org/10.1007/s10528-008-9164-8
- 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 Australas. J. Anim. Sci. 19:1546-1550. https://doi.org/10.5713/ajas.2006.1546
- Leroy, G., E. Verrier, J. C. Meriaux, and X. Rognon. 2009. Genetic diversity of dog breeds: Between.breed diversity, breed assignation and conservation approaches. Anim. Genet. 40:333-343. https://doi.org/10.1111/j.1365-2052.2008.01843.x
- MAF (Ministry of Agriculture and Forestry, Republic of Korea). 2004. National report on the state of animal genetic resources. Seoul, Rep of Korea. p. 23. Available at: ftp://ftp.fao.org/docrep/fao/010/a1250e/annexes/CountryReports/KoreanRepublic.pdf
- Muchadeyi, F. C., H. Eding, C. B. A. Wollny, E. Groeneveld, S. M. Makuza, R. Shamseldin, H. Simianer, and S. Weigend. 2007. Absence of population substructuring in Zimbabwe chicken ecotypes inferred using microsatellite analysis. Anim. Genet. 38:332-339. https://doi.org/10.1111/j.1365-2052.2007.01606.x
- Nei, M., F. Tajima, and Y. Tateno. 1983. Accuracy of estimated phylogenetic trees from molecular data. J. Mol. Evol. 19:153-170. https://doi.org/10.1007/BF02300753
- 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 chickens assessed by microsatellite DNA profiling. Asian Australas. J. Anim. Sci. 19:1369-1378. https://doi.org/10.5713/ajas.2006.1369
- Ota, T. 1993. DISPAN. Pennsylvania State University, PA, USA.
- Peakall, R. O. D. and P. E. Smouse. 2006. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6:288-295. https://doi.org/10.1111/j.1471-8286.2005.01155.x
- Pritchard, J. K., M. Stephens, and P. Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155:945-959.
- Rosenberg, N. A. 2004. DISTRUCT: A program for the graphical display of population structure. Mol. Ecol. Notes 4:137-138.
- Seo, D. W., M. R. Hoque, N. R. Choi, H. Sultana, H. B. Park, K. N. Heo, B. S. Kang, H. T. Lim, S. H. Lee, C. Jo, and J. H. Lee. 2013. Discrimination of Korean Native chicken lines using fifteen selected microsatellite markers. Asian Australas. J. Anim. Sci. 26:316-322. https://doi.org/10.5713/ajas.2012.12469
- Smith, E. J., S. A. Ray, M. R. Bakst, C. Teuscher, and T. F. Savage. 1996. Simple sequence repeat.based single primer amplification of genomic DNA in random bred populations of turkeys and chickens. Anim. Biotechnol. 7:47-58. https://doi.org/10.1080/10495399609525847
- 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
- Vanhala, T., M. Tuiskula-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
- Weir, B. S. and C. C. Cockerham. 1984. Estimating F-statistics for the analysis of population structure. Evolution 38:1358-1370. https://doi.org/10.2307/2408641
- Wilkinson, S., P. Wiener, D. Teverson, C. S. Haley, and P. M. Hocking. 2012. Characterization of the genetic diversity, structure and admixture of British chicken breeds. Anim. Genet. 43:552-563. https://doi.org/10.1111/j.1365-2052.2011.02296.x
- Wimmers, K., S. Ponsuksili, T. Hardge, A. Valle.Zarate, P. K. Mathur, and P. Horst. 2000. Genetic distinctness of African, Asian and South American local chickens. Anim. Genet. 31:159-165. https://doi.org/10.1046/j.1365-2052.2000.00605.x
Cited by
- DNA Markers for the Genetic Diversity in Korean Native Chicken Breeds: A Review vol.43, pp.2, 2016, https://doi.org/10.5536/KJPS.2016.43.2.63
- The breeding history and commercial development of the Korean native chicken vol.73, pp.01, 2017, https://doi.org/10.1017/S004393391600088X
- Assessment of the population structure and genetic diversity of Denizli chicken subpopulations using SSR markers pp.1828-051X, 2018, https://doi.org/10.1080/1828051X.2017.1384336
- MS 마커를 활용한 지역별 오계 유전자원의 다양성 및 유연관계 분석 vol.45, pp.3, 2014, https://doi.org/10.5536/kjps.2018.45.3.229
- Genetic diversity of 21 experimental chicken lines with diverse origins and genetic backgrounds vol.68, pp.2, 2014, https://doi.org/10.1538/expanim.18-0139
- 초위성체 마커를 활용한 가축다양성정보시스템(DAD-IS) 등재 재래닭 집단의 유전적 다양성 분석 vol.46, pp.2, 2019, https://doi.org/10.5536/kjps.2019.46.2.65
- Deciphering the Patterns of Genetic Admixture and Diversity in the Ecuadorian Creole Chicken vol.9, pp.9, 2014, https://doi.org/10.3390/ani9090670
- The Development of Multiplex PCR Microsatellite Marker Sets for Korean Chicken Breeds vol.18, pp.10, 2014, https://doi.org/10.3923/ijps.2019.492.498
- Estimating genetic diversity and population structure of 22 chicken breeds in Asia using microsatellite markers vol.33, pp.12, 2014, https://doi.org/10.5713/ajas.19.0958