Wang Kehua

AFLP fingerprinting analysis of genetic polymorphism of 12 indigenous chicken breeds

A total of six amplified fragment length polymorphism (AFLP) primer combinations were used to detect genetic variation of pooled DNA in a sample of 12 chicken breeds indigenous to China, and AFLP DNA fingerprinting of each chicken breed was constructed. Polymorphic bands, specific bands and genetic similarity coefficients of 12 chicken breeds were calculated from AFLP data. A total of 279 polymorphic bands were generated by the six primer combinations, giving, on average, 46.5 polymorphic markers detected per primer combination. Nine specific bands were produced in the pooled DNA of Jiuyuan black and Dongxiang black chickens. However, one specific band was produced in the pooled DNA of Wenchang and Xingyi bantam chickens. An unweighted-pair-group method using average linkages (UPGMA) cluster analysis revealed that the 12 chicken breeds could be divided into three groups. Genetic similarity coefficients and the UPGMA tree of the 12 chicken breeds were consistent with their breeding history as well as their geographical distribution. Based on AFLP DNA fingerprinting, genetic diversity, genetic relationship and identification of chicken breeds can be analysed.

Random regression analyses to model the longitudinal measurements of yolk proportions in the laying chicken

Cubic spline function was used in a genetic evaluation to model the change of yolk proportion over the lay life. A total of 19,862 yolk proportion records of 2,324 hens was used. The evaluated submodels consisted of 3 to 6 knot models. The same knots were fitted for genetic and permanent environmental splines. The residual effects were specified to be independently and normally distributed, but with heterogeneous variance for each test week. (Co)variance components were estimated by the average information restricted maximum likelihood (AIREML) method. The best fitting random regression model (RRM) was a submodel with 4 knots at 32, 36, 52, and 72 wk of age for genetic and permanent environmental effects. The estimate of genetic variance was larger than that of permanent environmental variance at the same time point. The heritability of yolk proportion ranged from 0.32 to 0.55, and the repeatability ranged between 0.45 and 0.73. The genetic correlations between test wk were from moderate to unity. To the best of our knowledge, this was the first report on the use of a RRM to evaluate yolk proportion. The results of this study showed that random regression models with the spline function could be used for improvement of yolk proportion.Cubic spline function was used in a genetic evaluation to model the change of yolk proportion over the lay life. A total of 19,862 yolk proportion records of 2,324 hens was used. The evaluated submodels consisted of 3 to 6 knot models. The same knots were fitted for genetic and permanent environmental splines. The residual effects were specified to be independently and normally distributed, but with heterogeneous variance for each test week. (Co)variance components were estimated by the average information restricted maximum likelihood (AIREML) method. The best fitting random regression model (RRM) was a submodel with 4 knots at 32, 36, 52, and 72 wk of age for genetic and permanent environmental effects. The estimate of genetic variance was larger than that of permanent environmental variance at the same time point. The heritability of yolk proportion ranged from 0.32 to 0.55, and the repeatability ranged between 0.45 and 0.73. The genetic correlations between test wk were from moderate to unity. To the best of our knowledge, this was the first report on the use of a RRM to evaluate yolk proportion. The results of this study showed that random regression models with the spline function could be used for improvement of yolk proportion.