Accuracy of imputation of single nucleotide polymorphism marker genotypes from low-density panels in Japanese Black cattle

Shinichiro Ogawa, Hirokazu Matsuda, Yukio Taniguchi, Toshio Watanabe, Akiko Takasuga, Yoshikazu Sugimoto, Hiroaki Iwaisaki

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Using target and reference fattened steer populations, the performance of genotype imputation using lower-density marker panels in Japanese Black cattle was evaluated. Population imputation was performed using BEAGLE software. Genotype information for approximately 40000 single nucleotide polymorphism (SNP) markers by Illumina BovineSNP50 BeadChip was available, and imputation accuracy was assessed based on the average concordance rates of the genotypes, varying equally spaced SNP densities, and the number of individuals in the reference population. Two additional statistics were also calculated as indicators of imputation performance. The concordance rates tended to be lower for SNPs with greater minor allele frequencies, or those located near the ends of the chromosomes. Longer autosomes yielded greater imputation accuracies than shorter ones. When SNPs were selected based on linkage disequilibrium information, relative imputation accuracy was slightly improved. When 3000 and 10000 equally spaced SNPs were used, the imputation accuracies were greater than 90% and approximately 97%, respectively. These results indicate that combining genotyping using a lower-density SNP chip with genotype imputation based on a population of individuals genotyped using a higher-density SNP chip is a cost-effective and valid approach for genomic prediction.

Original languageEnglish
Pages (from-to)3-12
Number of pages10
JournalAnimal Science Journal
Volume87
Issue number1
DOIs
Publication statusPublished - 2016 Jan 1
Externally publishedYes

Keywords

  • Imputation accuracy
  • Japanese Black cattle
  • Low-density panel
  • Single nucleotide polymorphism

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)

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