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Articles by J.Y. Wang
Total Records ( 6 ) for J.Y. Wang
  O. Olowofeso , J.Y. Wang , G.J. Dai1 , Y. Yang , D.M. Mekki and H.H. Musa
  A total of 240 genomic DNAs were isolated from the four Haimen chicken populations: Rugao, Jiangchun, Wan-Nan and Cshiqishi, through a saturated salt procedure. The samples were used in a polymerase chain reaction (PCR) with 15 microsatellite markers. Amplified PCR-products with the markers were separated on a 12% polyacrylamide gel. Genetic parameters measured included allele number within locus per population, mean allele number across populations, mean allele number among loci for each population, effective allele number for each locus, mean across populations and among loci effective number of alleles (). Polymorphism information content (PIC) per locus and for all loci obtained as well as the average heterozygosity (H) among loci in the populations. The mean allele number for all loci ranged between 5.73±0.85 (Cshiqishi) to 6.00±0.74 (Rugao) and 6.00±0.84 (Jiangchun) with across populations for all loci equals 5.88±0.06; while (H) ranged from 0.6486±0.06 (Wan-Nan) to 0.7017±0.03 (Jiangchun) among loci and across populations, (H) was 0.6828±0.01. The () ranged from 3.96±0.60 (Wan-Nan) to 4.11±0.47 (Rugao); and () have values between 0.6068±0.06 (Wan-Nan) to 0.6509±0.04 (Jiangchun). The average heterozygosity among loci in each population was used further to obtained the cumulative power of discrimination (CPD) and was 99%. Angular genetic distances (DA) calculated ranged between 0.1691 (Rugao vs Wan-Nan) to 0.3372 (Rugao vs Cshiqishi). Dendrogram developed linked Rugao and Jiangchun as closely related, Wan-Nan been intermediate and Cshiqishi distantly related. It was concluded that the markers were suitable for the measurement of all genetic parameters of Haimen chicken populations.
  O. Olowofeso , J.Y. Wang , K.Z. Xie and G.Q. Liu
  To detect the genetic lineage of four ubiquitous port-city (Haimen) chicken populations in China, a genetic study involving two-marker types viz: random and microsatellite markers were used with the genomic DNAs isolated from the chicken populations. A total of two hundred and forty genomic DNAs with 60 samples from each of Rugao, Jiangchun, Wan-Nan and Cshiqishi populations were used. All samples were subjected to both 45 and 35 cycles of amplifications with five random and fifteen microsatellite markers in polymerase chain reactions (PCRs), respectively. Average band-sharing coefficient (BSC) and the Nei standard genetic distances (Dij) obtained using the data generated by the random markers with the genomic DNAs. Using the microsatellite markers with the same set of genomic DNAs, allele frequencies were obtained through direct gene counting approach. The generated allele frequencies were used to compute the (Dij) between populations. With the random markers, the (Dij) obtained ranged from 0.0083 (Jiangchun and Cshiqishi) to 0.2789 (Rugao and Wan-Nan); while that of microsatellite markers ranged from 0.2360 (Rugao and Jiangchun) to 0.5072 (Rugao and Cshiqishi), respectively. Phylogenetic trees developed using both standard (Dij`s) revealed significant variations in the level of divergence between populations. Phylogenetic linkage of these chicken populations based on the random markers showed Jiangchun and Cshiqishi to be well related, whereas Rugao and Wan-Nan distantly related. For the microsatellite markers, Rugao and Jiangchun appeared very close, while Rugao and Cshiqishi populations appeared remote between the populations. The results emanated from the application of these markers with these chicken populations suggests that Jiangchun and Cshiqishi and or Rugao and Jiangchun are likely to have originated from the same source and Wan-Nan intermediate in both cases of the phylogeny trees, might had been developed through crossbreeding activities of these populations.
  G.J. Dai , J.Y. Wang , O. Olajide , Q.S. Li , H. Shen , K.Z. Xie , Z.Y. Wang , S.L. Wu , Y.P. Gu and G.X. Zhang
  In order to develop rapid and reliable SCAR markers linked to the QTL, to get better understood of orgin of New Yangzhou chickens, two bands of OPAY02 type marker have been cloned, sequenced and two pairs of primer were designed according to the DNA sequence of two bands of OPAY02 to amplify the SCAR-markers on 86 individuals randomly selected from New Yangzhou chickens. The results of comparing the two bands DNA sequence with red jungle fowl genomic DNA database showed that the large molecular size band is located on the 3rd chromosome, the sequence identities were 98% and 8 SNPs mutations were detected, they were at 195 (T→G), 316 (A→T), 538 (G→ A), 731 (T→A), 1147 (G→A), 1329 (T→C), 1927 (C→ T) and 2081 (C→T). On the other hand, the small molecular size band can`t be found in red jungle chicken genomic DNA database, speculated that the source of New Yangzhou Chickens may originate from not only red jungle fowl, but also other jungle fowls. SCAR -markers confirmed that the two bands of OPAY02 type marker can be applied to genetic analyses because of its stability and reliability. Genotype equilibrium test showed that New Yangzhou chickens are in equilibrium on the two bands loci, two bands of OPAY02 type marker selection will be in favor of New Yangzhou chickens body weight breeding.
  G.J. Dai , O. Olowofeso and J.Y. Wang
  Five chicken populations in Yangzhou and Haimen cities, both in Jiangsu Province, East China that have recently arose the attention of poultry researchers are the New Yangzhou (NY-1), Rugao (HR-1), Jiangchun (HJ-2), Wan-Nan (HW-3) and the Cshiqishi (HC-4) chickens, respectively. Genetic differentiation degree, genetic distances and the actual time of divergence between these chicken populations were obtained by employing a suite of marker panel containing five carefully selected Micro satellite loci with 81 genomic DNAs isolated from the chicken`s blood samples. The isolated genomic DNAs were subjected to polymerase chain reaction (PCR); with all the loci involving 35 cycles carried out in a ready-to-go-thermo cycler and amplified products analyzed. Allele frequencies data were generated in the initial analyses using Pop Gene 32 software and used to compute multi-populations expected heterozygosity (H), across population`s genetic differentiation degree (FST) for each locus and the genetic distances (Dij) between population pairs considering all loci. The FST obtained ranged from 0.0082 (MCW4) to 0.0415 (ADL 176). The Dij between population pairs computed were used to calculate the divergence time (t) in years. The estimated time of divergence between these chicken populations oscillates between 167 (Wan-Nan vs. Cshiqishi) and 1954 years (Rugao vs. Jiangchun), respectively.
  Y. Yang , D.M. Mekki , S.J. Lv , L.Y. Wang , J.H. Yu and J.Y. Wang
  The three nonlinear curves of Logistic, Gompertz and Bertalanffy model were used to fit the growth model in Jinghai Yellow chicken of different sex. The results indicated that the three growth models were well fitted the prediction of growth parameters. Females reached inflexion point at earlier age than males; however, their body weight was significantly lighter than males. Inflexion body weight were 1098.99, 1161.86 and 1392.91 g for males and 824.29, 827.99 and 918.67 for female estimated from Logistic, Gompertz and Bertalanffy models, respectively. Fitting degrees (R2) for the three models were higher than 99%. The lower X2 values estimated were 9.22 and 7.43 from Bertalanffy model for males and females respectively indicated that, Bertalanffy model was the best model fitted growth prediction parameters of Jinghai Yellow chicken.
  Y. Yang , D.M. Mekki , S.J. Lv , J.H. Yu , L.Y. Wang , J.Y. Wang , K.Z. Xie and G.J. Dai
  Canonical correlation analysis of three character sets including 23 variables of Jinghai yellow chicken was performed. Strong significant correlations were obtained between body weight and body measurement characters (0.9153), body weight and carcass characteristics (0.9618) and body measurement and carcass characteristics (0.9618). The coefficients represented 98.46, 98.96 and 92.82% of the total correlation between the two character sets, respectively. Canonical correlation analysis had been able to identify the relevant variables of the three character sets of Jinghai yellow chicken and it would be an appropriate method of analysis to find optimally correlated patterns of chicken body weight, body measurement and carcass characters.
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