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Effective management of genetic resources in the domestic animals is based on characterization of genetic structure and diversity among populations. Strategies reducing complexity and dimensions of data are required to analyze the genetic relationships between populations based on dense genomic data. The objective of this study was to use the discriminant analysis of principal components (DAPC) for investigating the genetic structure of the Iranian native cattle based on a high-density single nucleotide polymorphism data. Samples were genotyped using Illumina BovineHD SNP chip containing 777962 SNPs. Genetic distances among different breeds were determined based on allele frequencies of populations. Discriminant analysis of principal components was performed using "adegenet" package in the R software. Pars and Kermani breeds had the lowest genetic distances among studied breeds and the highest genetic distances were observed between Kurdi and Sistani breeds. Three numbers of genetic clusters were selected as the best number of inferred groups to perform discriminant analysis of principal components. Results from this study confirmed that there were three main genetic groups among Iranian native cattle. In accordance with geographical distribution, Mazandarani and Taleshi breeds were classified as the same cluster. In addition, other two distinct genetic groups included breeds distributed on the North West mountainous area of the country (Sarabi and Kurdi) and those can be found in the Southern area (Sistani, Kermani, Najdi and Pars). Discriminant analysis of principal components could well distinguish individuals from different genetic groups. Genetic structure identified in the current study can be applied to design the genetic conservation programs for Iranian native cattle.

Investigation of the Population Structure in Iranian Native Cattle using Discriminant Analysis of Principal Components