Breed4Food Seminar: Benefit out of whole genome sequence data

How to use whole genome sequence data (WGS) to benefit genetic gain in animal breeding was the topic of this seminar. World leading scientists gave their update of human and animal genetics research, after which young scientist gave their vision based on results of running Breed4Food projects for an audience of about 70 persons on October 17th 2019.

Organised by Wageningen University & Research - Animal Breeding & Genomics, Cobb, B4F

Thu 17 October 2019 09:00 to 18:00

Venue ReeHorst, Ede

Currently, WGS is used for genome-wide association studies (GWAS) and genomic prediction. Using imputation, a large number of animals can contribute to the power of such studies. For within breed genomic prediction, using WGS data did not improve the prediction accuracy. For GWAS studies, WGS has resulted in many associations, however, identification of causal variants remained problematic due to high linkage disequilibrium. In human genetics, efforts focused on identification of causal variants, but for inflammatory bowel disease for instance only 10 out of 200 common causal loci are in coding regions of the causal genes. Therefore, the majority of common causal variants has to be in regulatory regions, shifting focus to eQTL studies.


Gene editing in cell-lines or organoids could be used to test the effects of individual candidate variants. Another opportunity to explain more variance, lies in the rare alleles. Alleles with large effect sizes tent to be at low frequency and in low linkage disequilibrium with surrounding SNP, they are in general poorly imputed. So with reduction in sequencing cost, WGS on large numbers will provide the opportunity to capture rare alleles to identify genes, explain more variation and improve genomic prediction, was a conclusion of the speakers.

Should we select for alleles?

A lively discussion resulted in a debate whether we should select for alleles rather than animals. How can we quickly introduce an important variant into a population, without gene editing? Which combination of alleles would make the best animal? However, will this best animal also perform well in other environments, and how to consider the epigenetic factors that play a role. This very inclusive discussion was a great way to end the inspiring day.

Download the programme: