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Removal of alleles by genome editing (RAGE) against deleterious load

Authors :
Martin Johnsson
R. Chris Gaynor
Janez Jenko
Gregor Gorjanc
Dirk-Jan de Koning
John M. Hickey
Source :
Genetics Selection Evolution, Vol 51, Iss 1, Pp 1-18 (2019)
Publication Year :
2019
Publisher :
BMC, 2019.

Abstract

Abstract Background In this paper, we simulate deleterious load in an animal breeding program, and compare the efficiency of genome editing and selection for decreasing it. Deleterious variants can be identified by bioinformatics screening methods that use sequence conservation and biological prior information about protein function. However, once deleterious variants have been identified, how can they be used in breeding? Results We simulated a closed animal breeding population that is subject to both natural selection against deleterious load and artificial selection for a quantitative trait representing the breeding goal. Deleterious load was polygenic and was due to either codominant or recessive variants. We compared strategies for removal of deleterious alleles by genome editing (RAGE) to selection against carriers. When deleterious variants were codominant, the best strategy for prioritizing variants was to prioritize low-frequency variants. When deleterious variants were recessive, the best strategy was to prioritize variants with an intermediate frequency. Selection against carriers was inefficient when variants were codominant, but comparable to editing one variant per sire when variants were recessive. Conclusions Genome editing of deleterious alleles reduces deleterious load, but requires the simultaneous editing of multiple deleterious variants in the same sire to be effective when deleterious variants are recessive. In the short term, selection against carriers is a possible alternative to genome editing when variants are recessive. Our results suggest that, in the future, there is the potential to use RAGE against deleterious load in animal breeding.

Details

Language :
German, English, French
ISSN :
12979686
Volume :
51
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genetics Selection Evolution
Publication Type :
Academic Journal
Accession number :
edsdoj.61720668d68645c2bf775e6de2b65478
Document Type :
article
Full Text :
https://doi.org/10.1186/s12711-019-0456-8