Study of relationship between locus and population genetic parameters in chicken adopted by microsatellite markers

G. Devegowda 1, N. Pirany 7 , S. P. Ganpule 2, H.N.N. Murthy 3,
D.T. Prasad 4, C.S. Nagaraja 5 And S.M. Byregowda 6

1. Division of Animal Science,
3. AICRP on Poultry Breeding and Meat
4. Deptartment of Biotechnology
5 Department of Animal Breeding, Genetics and Biostatistics Veterinary College ,
University of Agricultural Sciences, Bangalore , INDIA
2 Pioneer Group, Pongalur, Tamil Nadu
6 Institiute of Animal Health & Veterinary Biologicals, Hebbal, Bangalore
7 Department of Animal Science, Agricultural College, University of Tabriz , Tabriz , IRAN
Email: [email protected]

High genomic DNA was extracted from sixteen blood samples (equal sexes) pertaining to six chicken populations, viz. Naked Neck, Giriraja (a synthetic colour bird), local chickens, Silkies and commercial broilers and layers. Population genetic studies were carried out with nine highly polymorphic microsatellite loci (ADL158, ADl278, MCW5, MCW16, MCW29, MCW37, MCW69, MCW104 and MCW114). Genotyping was done by ABI 377 (Perkin Elmer). Observed (NA), effective (NE) and number of private alleles (PA); observed (H o) and expected heterozygosities (H E), fixation index (F IS) and Shannon index (H’) were calculated for each population/locus combinations. Stepwise regression analysis was carried out to find out relations between H E, H O and F IS with others.

In the preliminary analysis, H’, F IS and H E showed normal distributions. H o had highly negative (R=-0.71, P<0.01) correlation with F IS, but not with NA and PA. Other variables showed significant ( P<0.05) and positive correlations with each other. The results of the stepwise regression analysis showed that there is a strong and highly significant ( P<0.0001) relation between H’ and NA with H E. The regression coefficient of H’ was high and positive while for NA was small and negative. Shannon index itself represents 89% prediction of H E and along with NA it enhanced to 98%. When H o was considered as independent variable, the effects of F IS, H E and NE was highly significant ( P<0.0001) and partial R 2 was 0.514, 0.462 and 0.005 respectively and model R 2 being 0.98. The results for F IS as independent variable showed that H o, H E and NE are effective on the F IS ( P<0.001) and partial R 2 was 0.514, 0.462 and 0.005 respectively (model R 2 =0.98).

The following regression models were obtained for estimation each of H E, H o and F IS variables:




Source : IPSACON-2005

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