Barjasteh et al. Iranian Journal of Applied Animal Science (2020) 10(2), 231-239 231 Comparing Different Marker Densities and Various Reference Populations Using Pedigree‐Marker Best Linear Unbiased Prediction (BLUP) Model INTRODUCTION Using genomic selection is rapidly growing in the breeding programs of many livestock species, especially dairy cattle, with a large population size (Boison et al. 2017). The po- tential factors, which have influences on the genetic re- sponse, would also affect the genomic selection efficiency. Selecting animals with superior quality to serve as the next generation parents can be conducted in their early life or even in the embryogenesis throughout the genomic in- formation, which could largely reduce the generation inter- val in comparison with the traditional methods. In addition, many young animals can be evaluated theoretically and consequently could introduce a larger number of potential In order to have successful application of genomic selection, reference population and marker density should be chosen properly. This study purpose was to investigate the accuracy of genomic estimated breed- ing values in terms of low (5K), intermediate (50K) and high (777K) densities in the simulated populations, when different scenarios were applied about the reference populations selecting. After simulating the his- torical (undergoing drift and mutation) and recent (undergoing selection) population structures, 800 indi- viduals were remained in reference population. Three scenarios were considered for reducing the reference population number including: 1) 400 individuals which had the highest relationships with the validation set, 2) 400 individuals which had the highest inbreeding, and 3) 400 selected individuals by random. The ge- nomic breeding values were predicted for traits with two heritability levels (0.25 and 0.5) using best linear unbiased prediction (BLUP) with different markers and pedigree information combinations of included pedigree-based BLUP (ABLUP), which was used a numerator relationships matrix (A) only, genomic best linear unbiased prediction (GBLUP) which was used a genomic relationship matrix (G) only, and BLUP|GA, which combined both A and G by using a weight parameter (). By increasing , the prediction model was changed from GBLUP (=0) to ABLUP (=1). The results indicated that without considering the panel density effects, G matrix (=0) and A matrix (=1) usages had the highest and lowest prediction accuracy, respectively. Comparative analyses of different scenarios of reference population selection re- vealed that all individuals’ inclusion in reference population yielded the highest estimation accuracy for breeding values (P<0.05). On the contrary, using reduced single nucleotide polymorphism (SNP) panels considerably decreased the accuracy of breeding value prediction. Individuals selecting in the reference set with a high genetic relationship to target animals, considerably improved the reduction in genomic predic- tion accuracy because of small reference population size. KEY WORDS accuracy, genomic selection, marker density, simulation. S. Barjasteh 1 , G.R. Dashab 1* , M. Rokouei 1 , M.M. Shariati 2 and M. Vafaye Valleh 1 1 Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Iran 2 Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran Received on: 6 Jun 2019 Revised on: 10 Aug 2019 Accepted on: 31 Aug 2019 Online Published on: Jun 2020 *Correspondence E‐mail: dashab@uoz.ac.ir © 2010 Copyright by Islamic Azad University, Rasht Branch, Rasht, Iran Online version is available on: www.ijas.ir Research Article