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Articles by G.J. Dai
Total Records ( 3 ) for G.J. Dai
  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 , 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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