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Assessment of Population Structure and Genetic Diversity of 15 Chinese Indigenous Chicken Breeds Using Microsatellite Markers

  • Chen, Guohong (Animal Science and Technology College, Yangzhou University) ;
  • Bao, Wenbin (Animal Science and Technology College, Yangzhou University) ;
  • Shu, Jingting (Animal Science and Technology College, Yangzhou University) ;
  • Ji, Congliang (Guangdong Wen's Group) ;
  • Wang, Minqiang (Chemical Biology and Physics College, Yantai University) ;
  • Eding, Herwin (Institute for Animal Breeding, Federal Agricultural Research Centre) ;
  • Muchadeyi, Farai (Institute for Animal Breeding, Federal Agricultural Research Centre) ;
  • Weigend, Steffen (Institute for Animal Breeding, Federal Agricultural Research Centre)
  • Received : 2007.02.21
  • Accepted : 2007.10.12
  • Published : 2008.03.01

Abstract

The genetic structure and diversity of 15 Chinese indigenous chicken breeds was investigated using 29 microsatellite markers. The total number of birds examined was 542, on average 36 birds per breed. A total of 277 alleles (mean number 9.55 alleles per locus, ranging from 2 to 25) was observed. All populations showed high levels of heterozygosity with the lowest estimate of 0.440 for the Gushi chickens, and the highest one of 0.644 observed for Wannan Three-yellow chickens. The global heterozygote deficit across all populations (FIT) amounted to 0.180 (p<0.001). About 16% of the total genetic variability originated from differences between breeds, with all loci contributing significantly to this differentiation. An unrooted consensus tree was constructed using the Neighbour-Joining method and pair-wise distances based on marker estimated kinships. Two main groups were found. The heavy-body type populations grouped together in one cluster while the light-body type populations formed the second cluster. The STRUCTURE software was used to assess genetic clustering of these chicken breeds. Similar to the phylogenetic analysis, the heavy-body type and light-body type populations separated first. Clustering analysis provided an accurate representation of the current genetic relations among the breeds. Remarkably similar breed rankings were obtained with all methods.

Keywords

References

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