Toll Free Helpline (India): 1800 1234 070

Rest of World: +91-9810852116

Free Publication Certificate

Vol. 12, Special Issue 9 (2023)

Genetic structure and diversity study of indigenous cattle population of northeast India

Author(s):
G Zaman, Arundhati Phookan, Bula Das, Arpana Das, S Laskar and Farzin Akhtar
Abstract:
Genetic diversity study of three indigenous cattle population of northeast India viz. Assam local cattle (ALC), Arunachal Pradesh Local cattle (APLC) and Manipur local cattle (MLC) was carried out using 24 microsatellite markers. A total of 120 individuals were genotyped and 300 alleles were identified. The overall mean observed and expected numbers of alleles were found to be 4.917±0.069 and 1.880±0.084; 3.333±1.274 and 2.166±0.077; and 4.857±1.796 and 2.034±0.311 in ALC, APLC and MLC respectively. The overall means for observed and expected heterozygosities were 0.448±0.023 and 0.476±0.024; 0.634±0.233 and 0.690±0.165; and 0.544±0.248 and 0.578±0.187 in ALC, APLC and MLC respectively. The moderate to high mean heterozygosity suggested that the three cattle populations possess high level of genetic diversity. The mean Polymorphism information content values and Shannon’s information index were found to be 0.355±0.097 and 0.660±0.037, 0.417±0.086 and 0.775±0.034 and 0.394±0.071 and 0.732±0.139 in ALC, APLC and MLC respectively. The sign rank test for bottleneck analysis indicated that cattle populations under study has not undergone any recent bottle neck. The genetic distance revealed that ALC and APLC population formed a separate cluster indicating their closeness as compared to MLC which can be considered genetically more unique. The Analysis of Molecular Variance showed that 43% of the total variation was due to differences between genetic groups.
Pages: 2373-2379  |  172 Views  103 Downloads
How to cite this article:
G Zaman, Arundhati Phookan, Bula Das, Arpana Das, S Laskar and Farzin Akhtar. Genetic structure and diversity study of indigenous cattle population of northeast India. The Pharma Innovation Journal. 2023; 12(9S): 2373-2379.

Call for book chapter