MICROSATELLITE-BASED SIBSHIP RECONSTRUCTION AND ESTIMATION OF GENETIC RELATEDNESS IN THE ENDANGERED LABEOCALBASU (HAMILTON
1822) (CYPRINIDAE:CYPRINIFORMES)

M. Nahiduzzaman1, S. Akter2, M.RobiulHasan3, M. A. R. Hossain2 and M. S. Alam2*

Department of Fisheries Biology and Genetics, Bangladesh Agricultural University, Mymensingh 2202 Bangladesh
1 World Fish Center, Dhaka, Bangladesh
2Department of Fisheries Biology and Genetics, Bangladesh Agricultural University, Mymensingh 2202
3Department of Fisheries and Marine Science, Noakhali Science and Technology University, Noakhali 3814.
* Corresponding author Email: samsul.alam@bau.edu.bd

ABSTRACT

The microsatellite genotyping technique was used to reconstruct sibship and estimate pairwise relatedness among individuals of Labeocalbasu collected from four natural and one hatchery stocks. The mean values for the number of alleles, observed and expected heterozygosity and polymorphic information content of the five microsatellite markers used for genotyping 165 individuals were 6.00, 0.622, 0.743 and 0.699 respectively. Deviation from Hardy-Weinberg expectation was detected at four of the five loci. The numberof reconstructed half-sib family was lowest in the Hatchery sample. The number of full-sib family was lowest in the Jamuna river sample and highest in the Haor sample. The numbers of reconstructed families were fewer in the real sample compared to the simulated sample of the same number of unrelated individuals.  The mean relatedness coefficients rxyW was found to be highest in the Jamuna river sample and lowest in the Hatchery sample, though no difference was observed in mean rxyLR values of the five samples. The misclassification rates estimated based on the relatedness coefficients were found to be quite high, ranging from 11.17 (Unrelated-Fullsib) to 32.02% (Halfsib-Fullsib) and more loci need to be analyzed for accurate separation of related individuals from unrelated ones.
Key words: Polymorphism, Microsatellite, Relatedness, Family Reconstruction,Labeocalbasu