Determination of the impact of some factors on genotype imputation error rates for genome wide association studies in dairy cattle

Sahebhonar, Mohammad; Moradi Shahrbabak, Mohammad; Miraei Ashtiani, Seyed Reza; Pakdel, Abbas; J. Garrick, Dorian

doi:10.22059/ijas.2014.51744

Determination of the impact of some factors on genotype imputation error rates for genome wide association studies in dairy cattle

Document Type : Research Paper

Authors

Mohammad Sahebhonar ¹

Mohammad Moradi Shahrbabak ²

Seyed Reza Miraei Ashtiani ²

Abbas Pakdel ³

Dorian J. Garrick ⁴

¹ PhD Candidate, University College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

² Professor, University College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

³ Associate Professor, University College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

⁴ Professor, Department of Animal Science, Iowa State University, Ames, USA.

10.22059/ijas.2014.51744

Abstract

In this study, effect of two genotype imputation strategies, relatedness between reference panel and test populations and minor allele frequency on imputation error rate were examined with using a stochastic simulated population. Reference panel and test populations were composed of 1,000 and 500 individuals, respectively. Individuals in the reference panel were genotyped with using a high and a medium density chips. The high density chip contained 75,000 SNPs plus QTLs. The medium density chip contained 7,500 SNPs. Individuals in the test populations were genotyped with using a low density chip with 500 SNPs. Two strategies were applied for genotype imputation. In 2-tiered strategy, genotypes of low density chip were directly imputed from high density chip. In 3-tiered strategy, genotypes of low density chip were imputed from high density chip with using a medium density chip. In order to impute genotypes, BEAGLE method was used. Correlation between imputation error rate and minor allele frequency showed that imputation error rate was affected by minor allele frequency in both strategies. Imputation error rates were decreased when using a medium density chip to predict genotypes of low density chip. Closer relationship between reference panel and test populations led to a higher accuracy.

Keywords

genotype imputation

high density chip

minor allele frequency

simulation