Czech J. Anim. Sci., 2020, 65(12):445-453 | DOI: 10.17221/83/2020-CJAS

The use of genomic data and imputation methods in dairy cattle breedingReview

Anita Klímová ORCID...*,1,2, Eva Kašná2, Karolína Machová1, Michaela Brzáková2, Josef Přibyl2, Luboš Vostrý1
1 Department of Genetics and Breeding, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague - Suchdol, Czech Republic
2 Department of Genetics and Breeding of Farm Animals, Institute of Animal Science, Prague - Uhříněves, Czech Republic

The inclusion of animal genotype data has contributed to the development of genomic selection. Animals are selected not only based on pedigree and phenotypic data but also on the basis of information about their genotypes. Genomic information helps to increase the accuracy of selection of young animals and thus enables a reduction of the generation interval. Obtaining information about genotypes in the form of SNPs (single nucleotide polymorphisms) has led to the development of new chips for genotyping. Several methods of genomic comparison have been developed as a result. One of the methods is data imputation, which allows the missing SNPs to be calculated using low-density chips to high-density chips. Through imputations, it is possible to combine information from diverse sets of chips and thus obtain more information about genotypes at a lower cost. Increasing the amount of data helps increase the reliability of predicting genomic breeding values. Imputation methods are increasingly used in genome-wide association studies. When classical genotyping and genome-wide sequencing data are combined, this option helps to increase the chances of identifying loci that are associated with economically significant traits.

Keywords: genomic breeding values; genomic selection; genotyping; microarray; SNP

Published: December 31, 2020  Show citation

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Klímová A, Kašná E, Machová K, Brzáková M, Přibyl J, Vostrý L. The use of genomic data and imputation methods in dairy cattle breeding. Czech J. Anim. Sci. 2020;65(12):445-453. doi: 10.17221/83/2020-CJAS.
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