Analysis of genetic structure of Iranian indigenous cattle populations using dense single nucleotide polymorphism markers

Document Type : Research Paper

Authors

1 Ph.D. Candidate of Animal Breeding and Genetics, Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Iran

2 Young Researchers Society, Shahid Bahonar University of Kerman, Kerman, Iran

3 Professor, Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

4 Associate Professor, Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

Abstract

The objective of this study was to detect genetic structure of Iranian indigenous cattle using dense single nucleotide polymorphism (SNP) markers. In total, 90 cattle individuals comprising Sarabi (n=20), Kurdi (n=10), Mazandarani (n=10), Taleshi (n=10), Sistani (n=10), Kermani (n=10), Najdi (n=10) and Fars (n=10) breeds were sampled. Genotyping was performed using Illumina High-density Bovine BeadChip designed to genotype 777,962 SNPs. After removing sites being in linkage disequilibrium (pairwise sites having r2 greater than 0.2), 64333 SNPs remained for further analyses. STRUCTURE software was used to detect genetic structure of native cattle in this data set. Number of assumed populations per run was selected between two to eight. Results of this study indicated that in the first level of clustering (K=2), Sarabi (97.6%) and Kurdi (94.3%) populations shared the same cluster and Sistani (92%) had another separate cluster while other breeds were admixed from these two clusters. Kurdi population appeared as an independent cluster at K=3. Most suitable number of genetic groups in data set was explained by three clusters (K=3). Genetic differentiation of Iranian indigenous cattle was well detected in this study. Also, similarities of geographical distribution and production characteristics were in good accordance with founded genetic relationships in this study.

Keywords

References

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Animal Production Research
Volume 4, Issue 3 - Serial Number 3
December 2015
Pages 93-104

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