Genotype imputation for the prediction of genomic breeding values in non-genotyped and low-density genotyped individuals
2011

Genotype Imputation for Predicting Genomic Breeding Values

Sample size: 3226 publication Evidence: moderate

Author Information

Author(s): Cleveland Matthew A, Hickey John M, Kinghorn Brian P

Primary Institution: Genus plc.

Hypothesis

Can genotype imputation improve the accuracy of genomic breeding values in non-genotyped and low-density genotyped individuals?

Conclusion

Genotype imputation using a long haplotype library can improve genomic breeding value accuracy, although some accuracy is lost compared to high-density genotyping.

Supporting Evidence

  • The study created a haplotype library to improve genotype imputation accuracy.
  • Imputation accuracy increased with the addition of low-density genotypes.
  • The maximum accuracy for imputed genotypes was 0.66, compared to 0.86 for high-density genotyping.

Takeaway

This study shows that we can guess the genetic information of animals that haven't been fully tested, which helps us make better breeding choices.

Methodology

A long haplotype library was created using a long range phasing algorithm and segregation analysis to impute dense genotypes for non-genotyped individuals.

Limitations

The accuracy of genomic breeding values was lower when using imputed genotypes compared to high-density genotyping.

Participant Demographics

The study involved 3226 individuals across five generations, with a mix of genotyped and non-genotyped individuals.

Digital Object Identifier (DOI)

10.1186/1753-6561-5-S3-S6

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