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Indian J Exp Biol ; 2002 Feb; 40(2): 144-50
Article in English | IMSEAR | ID: sea-61562

ABSTRACT

The conventional chorioallantoic membrane (CAM) phenotype assay was conducted using 11-day-old embryonatic eggs of white Leghorn strains, each inoculated with 0.2 ml of subgroup A Rous sarcoma virus (RSV) and subgroup C RSV separately containing 10(3)pfu ml(-1). Eggs were further incubated for hatching. Harvesting of CAMs for counting of pocks and monitoring chicks for liver tumour (LT) mortality during 4 weeks of post-hatching period were followed. The conversely associated phenotype (CAP) incidence i.e. CAM(+) LT(-) and CAM(-) LT(+) was observed in all three lines for both subgroup A and C virus infection. The LT deaths of chicks in all strains occurred within 21 days post-hatch irrespective of virus subgroups. The regression analysis of %LT death (transformed data) distributed within pock count range (PCR) basis was performed. The regression coefficients (b(i)'s) were found to be non-significant, indicating that %LT death did not correlate with number of particles that entered the cells because the chicks that had at least 25 pock counts in CAMs died with few exceptions. This study upheld the view that the CAM phenotypes (S and R) under the control of a pair of alleles, a(s) and a(r) at the tva locus and c(s) and c(r) at the tvc locus as reported extensively. Because of a high correlation coefficients between CAM and LT phenotypes [S and LT(+)] in respect of subgroup A (r = 0.72) and subgroup C (r = 0.81) infection, it is obvious that one could postulate a pleiotropic control of the two traits by the tva and tvc genes, respectively. Indeed fitting a 4-allele model in both tva and tvc locus, suggesting that CAPs are the indicator for nullifying the conventional 2-allele model proposed for the induced tumour expression phenotypes by leukosis sarcoma viruses.


Subject(s)
Alleles , Alpharetrovirus/genetics , Animals , Avian Sarcoma Viruses/metabolism , Chickens , Chorion/metabolism , Genetic Markers , Liver Neoplasms/genetics , Models, Genetic , Models, Statistical , Neoplasms, Experimental/genetics , Phenotype , Polymerase Chain Reaction , Regression Analysis
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