Biogeoinformatics for the management of Farm Animal Genetic Resources (FAnGR)

In the context of both severe selection in farm animals and potential effects of climate change, it is crucial to implement a sustainable management of the breeding practice, supported by a judicious use of geographic information technologies. Based on this observation, this thesis advocates the use of biogeoinformatics (the combined use of biology, geographic information and informatics) to cope with the challenges encountered by the livestock sector. Indeed, although biogeoinformatics can provide key insights for FAnGR (Farm Animal Genetic Resources) management, the variety and complexity of tasks involved hinders a wider usage of this type of analyses. The thesis shows how novel dedicated tools are likely to facilitate the adoption of biogeoinformatics by animals scientists and by stakeholders in the livestock sector, while investigating three main challenges related to FAnGR management, namely i) erosion of genetic diversity, ii) effects of climate change on the breeding activity, and iii) pressure on typical cultural breeding practices such as high alpine grazing. On this basis, the thesis is organised around three axes:

1. Preserving locally adapted breeds In order to prevent the erosion of genetic diversity, locally adapted breeds should be monitored to prevent their extinction. To this end, we developed the open source GENMON WebGIS platform, able to monitor FAnGR and to evaluate the degree of endangerment of livestock breeds. The system integrates various sources of information that are linked with the help of geographic information: pedigree and introgression, geographical concentration of animals, cryo-conservation and sustainability of breeding activities. The score can be visualised on a map and allows a fast and regional identification of breeds in danger.
2. Preserving locally adapted genetic variations Considering the pace at which genetic diversity is being eroded, it has become urgent to identify and then preserve important genetic variations linked to locally adapted phenotypes. In this context, the recent Samβada software was designed to search for signatures of local adaptation through the study of genome–environment association. However, pre‐ and postprocessing of data for this analysis can be labour‐intensive, and, we therefore developed the R.SamBada R package providing a pipeline for landscape genomic analyses. Based on Samβada, it spans from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, it grants access to biogeoinformatic analyses to researchers with no skills in geography.
3. Preserving a traditional farming technique suited for local breeds The preservation of locally adapted breeds is also strongly linked with the conservation of traditional farming techniques, which in Switzerland, include the grazing of high alpine pastures during summer. One major effect of this transhumance on cows is that milk production declines due to food shortage and climatic stress. Here, we developed a new mathematical model to fit a lactation curve for mountain-pastured cows, and tested the influence of environmental, physiological, and morphological factors on the production using five million monthly milk records from Braunvieh cows. When compared to physiological factors, environmental variables show a limited impact on milk production at alpine pastures, precipitation in spring being the most important.