Find in Library

<strong>Objective</strong> <br />So far, various methods have been used to investigate the structure of the population using the markers available in the whole genome (single-nucleotide polymorphism (SNP)), each of which has Weakness and strength. In the present study, an unsupervised network clustering (SPC), a data-mining method, was used to survey the population structure of the Sarabi and Najdi cows. <br /><strong>Materials and methods </strong> <br />The study population 424 cattle consisted of 213sarabi cattle and 211 Najdi cattle, sequenced with Illumina Bead Chip 40 K v 2 for single nucleotide markers. SORTING POINTS INTO NEIGHBORHOOD(SPIN) was used to analyze population structure. After editing data, 27859 autosomal markers were analyzed. <br /><strong>Results</strong> <br />Clustering results based on the similarities and differences between nucleotides led to the classification of two base populations and nine clusters<strong>. </strong> <br /><strong>Conclusions</strong> <br />Comparison the number of samples and other existing methods for population layering, the use of the SPIN method with high computational efficiency and the needn`t for prior assumptions makes it possible to analyze the structure of populations.   <strong>Citation</strong>: Khasaliaghtaei A, Vafaye Valleh M, Dashab GR, Moradi Shahrbabak H (2019) Comparison of the Different Clustering Methods for Population Structure of Sarabi and Nadjdi Cows by Using Dense Genetic Markers. Agricultural Biotechnology Journal 11 (1), 25-54.    Agricultural Biotechnology Journal 11 (1), 25-54. DOI: 10.22103/jab.2019.13193.1098 Received:  January 16, 2019; Accepted: April 28, 2019 © Faculty of Agriculture, Shahid Bahonar University of Kerman-Iranian Biotechnology Society