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Genomic management Tools to Optimise Resilience and Efficiency

Periodic Reporting for period 1 - GenTORE (Genomic management Tools to Optimise Resilience and Efficiency)

Reporting period: 2017-06-01 to 2018-11-30

The need for resilient livestock systems is clear and urgent in the context of climate change, and such systems have at their heart resilient animals. In this context, the advances provided by the genomic revolution, and by the advent of precision agriculture technologies, together offer the opportunity to improve animal resilience and efficiency (R&E) whilst finding the right balance between them.
The overall aim of GenTORE is to develop innovative genome-enabled selection and management tools to optimise cattle R&E in widely varying and changing environments. These tools, incorporating both genetic and non-genetic variables, will be applicable across the full range of cattle systems (beef, milk and mixed; conventional and organic) for increasing system resilience, and will thereby increase the sustainability of European cattle meat and milk production. The project has the following objectives:

Scientific objectives: 1) Characterise the interrelations between animal resilience and production efficiency across different life stages for meat and milk producing cattle. 2) Quantify the relative importance of the component traits of R&E in different production environments, using new proxy measures. 3) Advance genomic selection methodology to improve the accuracy of evaluations in large and medium-size breeds (beef and milk), especially through multi-breed and cross-breed genomic evaluation for key R&E traits, taking genome x environment interactions into account. 4) Develop models capable of predicting the consequences of future selection strategies on herd- and population-level R&E under varying environments.

Technological objectives: 1) Exploit near-market technologies to allow low-cost large-scale phenotyping of key R&E traits in varied environments. 2) Develop metrics to quantify local production environments in terms of their effect on animal R&E, and the relative importance of these traits for system sustainability. 3) Quantify local production environments in terms of the producers’ innovation opportunities and incentives for improvements, using available farm- and regional-scale information.

Innovation objectives: Build and deploy via stakeholders: 1) multi-trait genomic selection indices to optimise animal R&E across a diversity of production environments and breeds, 2) management tools for on-farm assessment of animal R&E that allow improved breeding and culling decisions 3) breeding strategies that exploit the diversity of cattle breeds to improve R&E at the level of the farm system, in accordance with local production environments. 4) policy support by using project tools to compare different future incentive/risk scenarios.
In the first 18 months of the project, the major scientific activities of GenTORE focused on data acquisition and preliminary data analysis. Thus, WPs 1 and 2 (see Figure for WPs) have been building databases that will allow them to produce new metrics for describing local production environments and assessing the predominant climate change risk factors (WP1), and improved methods for quantifying animal variation in R&E (WP2). These data are derived from Europe-wide climatic and socio-economic statistics resources, targeted surveys (WP1), and existing animal studies from the partners’ research farms (WP2). WP2 has also started a multi-site trial to provide new data on R&E across a wide selection of cattle types. A significant data acquisition effort has also been directed at on-farm phenotyping (WP3) to develop widely-applicable proxy measures for R&E using high-frequency measures available from at-market precision livestock technologies. This WP has also been testing use of novel drone technology for acquiring data from cattle that are out of reach of existing technologies, i.e. suitable for use in extensive, remote, grazing situations.

The WPs devoted to genomic prediction and genomic management (WPs 4 and 5) only started in month 12 of the project and are in the phase of setting up data acquisition from the different partners. Nevertheless, they have progressed the preliminary development of methodology needed to extend genomic prediction to the multi-breed context (WP4), and to improve on-farm cow worth indexes (WP5). WP6 will only start at month 24.

During this initial project phase, GenTORE has been active in outreach, communication and dissemination (WP7). The GenTORE rationale, the key concepts involved, and the expectations of this project have been presented to relevant scientific and industry communities at meetings of Interbull, the British Society of Animal Science (Keynote plenary), and by having a highly -attended dedicated session on R&E at the EAAP conference in 2018. These events were captured on videos that are available via the website as is project information in several languages. WP7 has carried out 3 stakeholder consultation exercises to get real-world views on R&E and their worth to farmers. It has also worked to create synergy with 5 related EU projects by initiating a dissemination cluster called Fitter Livestock Farms, using the EC Common Dissemination Booster programme.
As GenTORE is only 18 months old, it is not surprising that we cannot report substantial progress beyond the state-of-the-art. However, some progress towards expected potential impact has been made relative to those identified in the project proposal.

Methodological advances in genomic evaluation in admixed populations are being made, as are a number of methods for accommodating genotype-environment interactions. These developments, together with the pooled datasets across multiple breeds and environments being created in GenTORE, should have significant impact on the extension of genomic selection from the currently limited number of major breeds to the broader diversity of other breeds across Europe.

The progress being made to develop new proxies for R&E from existing on-farm sensor data, i.e. giving them a new functionality to monitor R&E, is promising. First results suggest that such data can distinguish between high and low animals for both R&E. This opens up for wide-scale recording of R&E phenotypes on many animals in a broad range of farming systems. One example of progress beyond the state-of-the-art (WP3) is to include social network analysis (e.g. using animal GPS data) as a possible means to detect behavioural changes reflecting health status, which may well be linked with resilience.

With respect to new metrics to “phenotype” local production environments, the combined farm typology and climate database assembled in WP1 will have substantial impact, providing a unified means to describe a broad range of local production environments. It will give the environmental context against which future management strategies can be evaluated with predictive modelling tools for better decision support on farm. This unified method to describe environments will also be of high value in the genomic models that deal with genotype by environment interactions.

No on-farm management index currently exists to rank animals on their expected lifetime R&E performance, applicable across the range of production systems (meat, milk, dual purpose) and breeds. The development in GenTORE of such an index, building on work launched in Ireland, that will include genomic information updated with precision livestock performance measures, has considerable potential impact to improve farm resilience and efficiency.