Genomic relationships based on X chromosome markers and accuracy of genomic predictions with and without X chromosome markers.

Guosheng Su,Gert P Aamand,Ismo Strandén,Mogens S Lund,Bernt Guldbrandtsen

doi:10.1186/1297-9686-46-47

Guosheng Su, Gert P Aamand + Show 3 more

Open Access

https://doi.org/10.1186/1297-9686-46-47

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Abstract

BackgroundAlthough the X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations. In this study, we presented a method for computing genomic relationships using X chromosome markers, investigated the accuracy of imputation from a low density (7K) to the 54K SNP (single nucleotide polymorphism) panel, and compared the accuracy of genomic prediction with and without using X chromosome markers.MethodsThe impact of considering X chromosome markers on prediction accuracy was assessed using data from Nordic Holstein bulls and different sets of SNPs: (a) the 54K SNPs for reference and test animals, (b) SNPs imputed from the 7K to the 54K SNP panel for test animals, (c) SNPs imputed from the 7K to the 54K panel for half of the reference animals, and (d) the 7K SNP panel for all animals. Beagle and Findhap were used for imputation. GBLUP (genomic best linear unbiased prediction) models with or without X chromosome markers and with or without a residual polygenic effect were used to predict genomic breeding values for 15 traits.ResultsAveraged over the two imputation datasets, correlation coefficients between imputed and true genotypes for autosomal markers, pseudo-autosomal markers, and X-specific markers were 0.971, 0.831 and 0.935 when using Findhap, and 0.983, 0.856 and 0.937 when using Beagle. Estimated reliabilities of genomic predictions based on the imputed datasets using Findhap or Beagle were very close to those using the real 54K data. Genomic prediction using all markers gave slightly higher reliabilities than predictions without X chromosome markers. Based on our data which included only bulls, using a G matrix that accounted for sex-linked relationships did not improve prediction, compared with a G matrix that did not account for sex-linked relationships. A model that included a polygenic effect did not recover the loss of prediction accuracy from exclusion of X chromosome markers.ConclusionsThe results from this study suggest that markers on the X chromosome contribute to accuracy of genomic predictions and should be used for routine genomic evaluation.

Highlights

The X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations
This study investigated the accuracy of genotype imputation for markers on the X chromosome and the impact of including X chromosome markers on reliability of genomic predictions
The results showed that averaged over the 15 traits evaluated, including X chromosome markers improved the reliability of genomic prediction slightly, ranging from 0.3 to 0.5% points in various datasets and using different models

Summary

Introduction

The X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations. According to the UMD 3.1 assembly, chromosome X is the second largest chromosome in the bovine genome [1]. Markers on the X chromosome are not used for genomic prediction in some countries and populations. Inheritance of chromosome X differs from inheritance of autosomes. A male inherits a copy of the X chromosome from its mother only, while a female inherits one copy of the X chromosome from its father and one copy from its mother. The relationships caused by the X chromosome are different for males and females. A small region of the X chromosome, called the pseudo-autosomal region (PAR) is homologous to the

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