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Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain
Author(s) -
Buch L.H.,
Sørensen M.K.,
Berg P.,
Pedersen L.D.,
Sørensen A.C.
Publication year - 2012
Publication title -
journal of animal breeding and genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.689
H-Index - 51
eISSN - 1439-0388
pISSN - 0931-2668
DOI - 10.1111/j.1439-0388.2011.00947.x
Subject(s) - genetic gain , trait , selection (genetic algorithm) , genomic selection , biology , animal breeding , inbreeding , genomic information , dairy cattle , genotype , breeding program , plant breeding , genetics , microbiology and biotechnology , genetic variation , single nucleotide polymorphism , genome , agronomy , computer science , population , gene , demography , machine learning , cultivar , sociology , programming language
Summary We tested the following hypotheses: (i) breeding schemes with genomic selection are superior to breeding schemes without genomic selection regarding annual genetic gain of the aggregate genotype (Δ G AG ), annual genetic gain of the functional traits and rate of inbreeding per generation (Δ F ), (ii) a positive interaction exists between the use of genotypic information and a short generation interval on Δ G AG and (iii) the inclusion of an indicator trait in the selection index will only result in a negligible increase in Δ G AG if genotypic information about the breeding goal trait is known. We examined four breeding schemes with or without genomic selection and with or without intensive use of young bulls using pseudo‐genomic stochastic simulations. The breeding goal consisted of a milk production trait and a functional trait. The two breeding schemes with genomic selection resulted in higher Δ G AG , greater contributions of the functional trait to Δ G AG and lower Δ F than the two breeding schemes without genomic selection. Thus, the use of genotypic information may lead to more sustainable breeding schemes. In addition, a short generation interval increases the effect of using genotypic information on Δ G AG . Hence, a breeding scheme with genomic selection and with intensive use of young bulls (a turbo scheme) seems to offer the greatest potential. The third hypothesis was disproved as inclusion of genomically enhanced breeding values (GEBV) for an indicator trait in the selection index increased Δ G AG in the turbo scheme. Moreover, it increased the contribution of the functional trait to Δ G AG , and it decreased Δ F . Thus, indicator traits may still be profitable to use even when GEBV for the breeding goal traits are available.