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Dernière mise à jour : Mai 2018

Menu Logo Principal AgroParisTech Université Paris-Saclay

INRA GABI Unit

GABI : Génétique Animale et Biologie IntégrativeUnité Mixte de Recherche INRA - AgroParisTech

Use of complete genome sequencing data in genomic selection

Use of complete genome sequencing data in genomic selection
Big reference populations used in genomic selection, combined with the availability of the numerous sequences of the complete genome make up efficient schemes when searching for the polymorphisms responsible for genetic variability of selected traits, which can be considered in the genomic evaluation of reproducing animals. This approach provides genomic predictions with an improved precision and robustness, especially for multiple-breed evaluations.

Context and stakes

The availability of numerous complete sequences of the genome, in particular within the “1000 bovine genome” project, allows the search for polymorphisms responsible for genetic variability of selected traits and to consider taking them into account in genomic evaluation of breeding animals.

Results

The potential of complete genome sequence data was analyzed as part of a partnership with the Aarhus University and during the EGS-ABG Marie Curie doctoral studies of Irene Van Den Berg. The main causal variants may be precisely mapped, using a system made up of genotyped individuals for whom we have the whole sequences. Studies using simulations and real data, show that causal mutations provide a gain in precision and robustness of predictions under the following conditions. The high number of variants in a sequence induces a lot of background noise; the gain therefore comes from the capacity of not considering causal variants or variants that are very similar and the ability to eliminate most of the others. The gain is more important with multiple-breed evaluations whereas it is limited amongst the same population due to long distance linkage disequilibrium.

Perspectives

Studies are underway to validate numerous candidate mutations by large scale genotyping, before they are probably considered in genomic evaluation by the end of 2017.

Valorisation

Several publications, while waiting for the first applications in a few months.

References

Van Den Berg  I., Boichard D., Guldbrandtsen B., Lund M.S. 2016. Use of sequence variants to improve accuracy of genomic prediction in dairy cattle breeds. G3, 6, 2553-2561.

Van Den Berg I., Boichard D., Lund M.S. 2016. Comparing power and precision of within and multi breed genome wide association studies of production traits using whole genome sequence data for five French and Danish dairy cattle breeds. Journal of Dairy Science, 99, 8932–8945.

Van Den Berg I., Boichard D., Lund M.S. 2016. Sequence variants selected from a multi breed GWAS can improve the reliability of genomic prediction in dairy cattle. Genetics Selection Evolution, 48, 83.