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Articles by S.A. Farrag
Total Records ( 2 ) for S.A. Farrag
  S.A. Farrag , A.B. Tanatarov and M.E. Soltan
  Genetic fingerprinting, DNA testing or DNA profiling is a technique to distinguish between individuals of the same species using only samples of their DNA. In modern animal breeding and production, with welfare and optimum nutrition, the major health problems arise mainly from genetic background. Obviously the selection does not affect the genome, but rather changes gene frequencies in the population and modifies the range of genetic variation of selected and correlated traits. These effects can be detected at the DNA level with the use of appropriate tools. DNA fingerprinting is a powerful tool in poultry for investigating genetic diversity within stocks and establishing relationships among stocks, characterizing individuals or populations genotypically, studying the relative contribution of evolutionary forces to genetic differences between populations, for marker assisted selection, to assist in gene introgression, to predict hybrid vigor and provide useful information for the pre-selection of populations to be used in crossbreeding. This review summarizes the use of genetic fingerprinting in poultry research, especially in some genetic resources of economically important species such as chickens, quails, ducks, goose, turkey and other poultry.
  S.A. Farrag , A.B. Tanatarov , M.E. Soltan , M. Ismail and O.M. Zayed
  Three Japanese quail lines A-C were examined genetically using 13 micro-satellite markers to detect genetic diversity. The studied loci on average produced 5 alleles locus•1 (range: 2-8). The mean observed Heterozygosity (Ho) was 0.609 and ranged across loci from 0.00-0.967 whereas the mean expected Heterozygosity (He) was 0.636 and ranged between 0.139 and 0.802. The Polymorphic Information Content (PIC) values varied among loci and ranged between 0.346 for locus GUJ0010 and 0.814 for locus GUJ0087 with overall mean 0.644. Differentiation among populations was moderate but highly significant (FST = 0.10, RST = 0.17; p<0.0001) however, within populations differentiation accounted for 3.61 and -0.73% of the total nuclear microsatellite variation under Infinite Allele Model (IAM) and Stepwise Mutation model (SSM), respectively. Cluster analysis based on Nei’s genetic distance indicated that the studied populations formed two main groups. The 1st group included line A and the 2nd group harboured lines B and C. These results reflect that the set of studied markers can be used effectively to capture the magnitude of genetic variability in different Japanese quail populations.
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