In animal breeding, there has been an increasing interest in investigating the added value of intermediate omics traits such as transcriptomes, metabolites and methylation patterns in genomic predictions. Such data are available only for small number of animals. The ‘single-step genomic prediction’ machinery, which was first proposed to combine pedigree information of a large number of individuals, and genomic information of a fraction of the population, can be useful to handle incomplete omics data. Such an approach, when applied to incomplete omics data scenarios, imply a simple linear relationship from genotypes to different omics traits, which in reality may be very complex. Little is known about the accuracy of genetic evaluations when the omics traits are generated for the whole population. Here, we present two different approaches to handle incomplete omics data, and investigate their impact on genomic predictions, using simulations.
Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP)
Technical and species orientated innovations in animal breeding, and contribution of genetics to solving societal challenges
EditorsR.F. Veerkamp and Y. de Haas
Published: 2022 Pages: 3364
eISBN: 978-90-8686-940-4
Book Type: Conference Proceedings
306. Genomic prediction with incomplete omics data
E. Karaman Related information
1Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830 Tjele, Denmark.
*Corresponding author: emre@qgg. au. dk
, V. Milkeviych Related information*Corresponding author: emre@qgg.
1Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830 Tjele, Denmark.
, Z. Cai Related information1Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830 Tjele, Denmark.
, L. Janss Related information1Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830 Tjele, Denmark.
, G. Sahana Related information1Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830 Tjele, Denmark.
, M.S. Lund Related information1Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830 Tjele, Denmark.
Pages: 1286 - 1289
Published Online: February 09, 2023
Abstract: