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Genomic management Tools to Optimise Resilience and Efficiency

Periodic Reporting for period 2 - GenTORE (Genomic management Tools to Optimise Resilience and Efficiency)

Reporting period: 2018-12-01 to 2020-05-31

The European cattle sector is facing challenges: ensuring food security, managing natural resources, mitigating and adapting to climate change. In this context, the overall objective of GenTORE is to develop innovative genome-enabled selection and management tools to optimise cattle resilience and efficiency (R&E) in widely varying environments. Although general climate change challenges to agriculture are known, it is important to determine how these will vary by region and farm system. European databases provide data but further details are required to allow assessment of farm-level vulnerability to environmental challenges in different regions. The project addresses different topics, the 1st of these is to use modelling, based on farm-system metrics, climatic data, and regional stakeholder expertise to predict challenges to R&E for different production environments. A 2nd topic is to understand the biological basis, and trade-off between, R&E for meat and milk producing animals. This is needed to elucidate the relationship across life stages between R&E and weight resilience vs efficiency according to the production environment. So far, on-farm technology is focused on automated monitoring with little effort being deployed on automated phenotyping. Accordingly, another topic aims to develop phenotyping proxies for R&E from: on-farm sensor technology, big data available across farms, and novel (drone) technology, across a range of production environments and systems.
GenTORE is also extending genomic methodology to allow multi-breed prediction and account for genotype-environment interactions (GxE). It will develop multi-breed selection indexes for R&E. Extending the genomic tools for on-farm applicability is another topic that aims to: develop an index to rank beef females on their value at slaughter or as a replacement animal, evaluate the potential of genomic matings, and evaluate the gains in performance achievable from a combination of genetic gain and culling. The right breeding, genetic and herd management choices can help farmers to adapt and respond to climate change by having animals that are resilient to environmental perturbations as well as being efficient users of available resources. The objectives of the final topic are to predict animal and system performance, and optimise R&E, under different future challenge scenarios, and to assess environmental, economic and social sustainability of various beef and dairy production systems in future scenarios. GenTORE ensures stakeholder participation throughout the project duration and communicates the project results and outcomes to a wider audience.
A Europe-wide database and farm typology describing cattle farm types across all the EU was constructed. It can be resolved by farm type and region, including the climatic conditions in time. The climatic impacts on farm resilience were significant, with clear regional differences; milk production could decline in southern European regions, and the opposite in more northern regions and upland areas. Stakeholder surveys, Europe-wide and regional (Spanish mountains) showed that preference for traits in cattle breeding goals are quite similar across Europe but results of the Spanish survey showed locally a gap between the farmer’s perceptions of breeding traits for R&E and their activity to record them in breeding schemes.
A common repository of data was created, and methods developed for improved quantification of animal R&E. This focused on: a multiple trait random regression model to predict efficiency at any life stage of each individual, and individual risk factors such as production, reproduction, and health were evaluated for long-term resilience. Results are being published. Multi-site trials were carried out to test the relationship between R&E. These experiments are mostly completed. Research has shown that there is a potential for precision phenotyping of complex traits using at-market technologies, and new image analysis methods in the field. However, there is no ‘one size fits all’ algorithm for all farm systems. A herd correction factor, based on national data, was developed so that resilience scores of cows on farm A can be adjusted to compare them with farm B. A method for multi-breed genomic prediction for a mixture of purebreds, crossbreds and admixed individuals has been developed and validated on simulated data. It is currently being published and will be used on real data cases of multiple breeds and admixed individuals. Besides, we are developing approaches to allow for heterogeneous (co)variances on the individual SNP level to estimate GxE in Bavarian Fleckvieh and Montbéliarde. Two indexes were developed for valuing a beef heifer if she was slaughtered vs retained as a replacement female. Validation showed that ability to predict eventual carcass revenue was twice that of the status quo. An effective tool was developed to generate the expected distribution in genetic merit of all possible progeny from a given parental mating; this is now being used by industry. As is a tool to quantify the return on investment in genotyping. Simulations have begun on an optimised use of both sexed semen and beef semen in both purebred and crossbred herds. We are also working on biological, individual-herd, bio-economic, and life cycle assessment models capturing all three pillars of sustainability (environmental, social, economic). These will assess the impact of climatic and environmental conditions in contrasting cattle systems, using contrasting breeding decisions.
The database developed in the 1st project topic provides opportunities for analysis of farm-type, region and climatic impacts on farm R&E in a comprehensive coverage of Europe. Analyses already show the considerable potential of the database, the estimations on climate change impact provide important new information on changing conditions for cattle farming in European regions.
For phenotyping, new methods were developed to estimate residual feed intake along life stages, to quantify the main causes of variation of productive lifespan, and to apply new on-farm proxies for R&E together with a resilience rank. These results will feed into genomic evaluation of R&E. A resilience indicator based on variance in milk production could be applicable for all milk producing farms. These tools open up a great opportunity for cattle in Europe (and worldwide) so that precision phenotyping is enabled for all different farming systems.
The methods for multi-breed genomic prediction for a mixture of purebreds, crossbreds and admixed individuals, and to estimate GxE, are beyond state of the art. We expect that usage of both will lead to diversity-rich breeding, efficient and resilient cows. The 2 management indexes we developed to better inform the value of a given animal are international firsts. The genomic mating algorithms allow breeding companies to inform which mating is likely to generate elite progeny for R&E. These tools, together with models in development, will provide information to stakeholders on possible future outcomes of breeding and management choices, and reduce the negative environmental impacts of cattle farming. The progress beyond the state-of-the-art described above will be given added impact by outreach and dissemination activities. It is expected to address societal concerns of a larger, younger audience and support end-users in facing new challenges.