The H2020 RUMIGEN Project kick-off was held from June 30th to July 2nd.

More sustainable selection programmes and the technologies involved should be in phase with societal demands; they should include genetic diversity and the adaptation necessary for climate change.

To reach these objectives, RUMIGEN will engage a variety of stakeholders to assess the social perception of breeding objectives and related technologies in ruminants. It will define "acceptance rooms" that will be implemented in sustainable breeding scenarios that will then be evaluated by multi-stakeholder panels.

To define new breeding programmes, RUMIGEN, which includes partners representing paneuropean leaders in ruminant breeding, questions the compromises and pleiotropic effects of adaptation to environmental stress factors such as heat stress.

Cosmopolitan and local bovine dairy breeds will be analyzed to evaluate middle- and long-term effects as well as the impact on the next generation (fetal progamming). This work will be based on large-scale data coming from commercial farms combined with climate data, using a large panel of situations throughout Europe and a unique conception implicating half-sibling cows raised in contrasted conditions in Denmark and India. Diversity will also be studied using new breed genome assemblies. Methods will be developed to consider rare alleles and to maintain diversity. An epigenotyping platform will be conceived for the following: (i) to explore the influence of the epigenome of sperm on fertility of bulls and their progeny, (ii) to decipher the underlying mechanisms of epigenetic inheritance and (iii) to evaluate how epigenetic biomarkers improve phenotype prediction. RUMIGEN will answer questions on the specificity of genome editing and security problems by evaluating its potential for preserving genetic diversity and increasing genetic gains.

Globally, RUMIGEN will develop models combining genomics, epigenomics, and biotechnologies to improve genomic selection, preserve genetic biodiversity and avoid genetic charge.The improvement of phenotype prediction will lead to new management indexes for precision agriculture.

Contact :

• Eric Pailhoux, Coordinator