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

Genes (Basel). 2020 Nov 5;11(11):1312. doi: 10.3390/genes11111312.

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 (r¯=0.99) and the genotypes called from the transcript sequence (r¯=0.97). 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.

Keywords: beef cattle; genomic prediction; imputation; sequence.

MeSH terms

  • Animal Husbandry / methods*
  • Animals
  • Breeding / methods
  • Cattle / genetics*
  • Genomics / methods
  • Genotype
  • Male
  • Phenotype
  • Polymorphism, Single Nucleotide / genetics
  • Red Meat
  • Sequence Analysis, DNA / methods*
  • United States