Assessment of Imputation from Low-Pass Sequencing to Predict Merit of Beef Steers.

Warren M Snelling,Larry A Kuehn,Joseph K Pickrell,Brittney N Keel,Jeremiah H Li,Jesse L Hoff,Amanda K Lindholm-Perry

doi:10.3390/genes11111312

Warren M Snelling, Larry A Kuehn + Show 5 more

Open Access

https://doi.org/10.3390/genes11111312

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Abstract

Decreasing costs are making low coverage sequencing with imputation to a comprehensive reference panel an attractive alternative to obtain functional variant genotypes that can increase the accuracy of genomic prediction. To assess the potential of low-pass sequencing, genomic sequence of 77 steers sequenced to >10X coverage was downsampled to 1X and imputed to a reference of 946 cattle representing multiple Bos taurus and Bos indicus-influenced breeds. Genotypes for nearly 60 million variants detected in the reference were imputed from the downsampled sequence. The imputed genotypes strongly agreed with the SNP array genotypes () and the genotypes called from the transcript sequence (). Effects of BovineSNP50 and GGP-F250 variants on birth weight, postweaning gain, and marbling were solved without the steers’ phenotypes and genotypes, then applied to their genotypes, to predict the molecular breeding values (MBV). The steers’ MBV were similar when using imputed and array genotypes. Replacing array variants with functional sequence variants might allow more robust MBV. Imputation from low coverage sequence offers a viable, low-cost approach to obtain functional variant genotypes that could improve genomic prediction.

Highlights

Current genomic evaluations of beef cattle use genotypes from commercial SNP arrays to predict breeding values with greater accuracy than breeding values predicted using only pedigree and performance records
Sequence contributing to the imputation reference was generated in different projects, using SOLiD
Downsampling mimicked low-pass sequencing, and genotypes for nearly 60 million variants detected in a broad haplotype reference panel were imputed

Summary

Introduction

Current genomic evaluations of beef cattle use genotypes from commercial SNP arrays to predict breeding values with greater accuracy than breeding values predicted using only pedigree and performance records. For multi-breed populations, can be achieved by including functional sequence variants [1,2,3]. Obtaining the functional variant genotypes needed to increase accuracy, is a challenge. One array to genotype potentially functional variants is available [4], but it is missing much of the functional variation detected in the sequence of beef cattle [5], and many alleles probed by that array are too rare to be informative. One intent of sequencing efforts is to provide a reference for imputation from array genotypes to sequence variants, but the disparity in allele frequency distributions of array and sequence variants [4,6] limits imputation accuracy, especially for the rare variants. Low-pass (

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