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Molecular genetic studies on Nellore and Deccani sheep using microsatellite markers

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The study was undertaken to understand the genetic architecture of Deccani and Nellore sheep breeds and to assess the genetic distance between the breeds. Allele diversity, genetic variability and population… Click to show full abstract

The study was undertaken to understand the genetic architecture of Deccani and Nellore sheep breeds and to assess the genetic distance between the breeds. Allele diversity, genetic variability and population structure in the two breeds were estimated using 30 microsatellite markers. A total of 100 sheep, 50 each from Deccani and Nellore breeds were genotyped. The total number of alleles observed was 254 and 260 in Deccani and Nellore, respectively. The mean expected heterozygosity among the breeds ranged from 0.79 (Deccani) to 0.80 (Nellore) whereas the mean observed heterozygosity levels ranged from 0.77 in Deccani to 0.78 in Nellore sheep. The overall mean inbreeding coefficient was 0.029 in Deccani and 0.031 in Nellore sheep and of the 30 loci studied, 14 loci in Deccani and 16 loci in Nellore sheep showed negative inbreeding coefficient indicating the presence of outbreeding. However, eight loci (BM1314, BM6506, BM8125, ILSTS28, MAF70, MCM140, OarCB226 and OarFCB128) showed positive, mild to moderate inbreeding ranging from 0.007 to 0.25 in Deccani and 0.066 to 0.37 in Nellore sheep studied. The FIS values ranged from -0.372 to 0.74, FST values ranged from 0.001 to 0.172 and FIT values ranged from -0.370 to 0.728 between the Deccani and Nellore sheep breeds studied. The PIC values ranged from 0.498 to 0.886 with a mean of 0.773 in Deccani and from 0.574 to 0.894 with a mean of 0.777 in Nellore breed. The information generated from the present study will be valuable for setting conservation priority of these two breeds.

Keywords: using microsatellite; deccani nellore; values ranged; nellore sheep; microsatellite markers; deccani

Journal Title: Indian Journal of Animal Research
Year Published: 2017

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