A WebGIS platform for the monitoring of Farm Animal Genetic Resources (GENMON)

Background In 2007, the Food and Agriculture Organization of the United Nations (FAO) initiated the Global plan of action for Farm Animal Genetic Resources (FAnGR). The main goal of this plan is to reduce further loss of genetic diversity in farm animals, so as to protect and promote the diversity of farm animal resources. An important step to reach this goal is to monitor and prioritize endangered breeds in the context of conservation programs. Methodology/Web portal implementation The GENMON WebGIS platform is able to monitor FAnGR and to evaluate the degree of endangerment of livestock breeds. The system takes into account pedigree and introgression information, the geographical concentration of animals, the cryo-conservation plan and the sustainability of breeding activities based on socio-economic data as well as present and future land use conditions. A multi-criteria decision tool supports the aggregation of the multi-thematic indices mentioned above using the MACBETH method, which is based on a weighted average using satisfaction thresholds. GENMON is a monitoring tool to reach subjective decisions made by a government agency. It relies on open source software and is available at http://lasigsrv2.epfl.ch/genmon-ch. Results/Significance GENMON allows users to upload pedigree-information (animal ID, parents, birthdate, sex, location and introgression) from a specific livestock breed and to define species and/or region-specific weighting parameters and thresholds. The program then completes a pedigree analysis and derives several indices that are used to calculate an integrated score of conservation prioritization for the breeds under investigation. The score can be visualized on a geographic map and allows a fast, intuitive and regional identification of breeds in danger. Appropriate conservation actions and breeding programs can thus be undertaken in order to promote the recovery of the genetic diversity in livestock breeds in need. The use of the platform is illustrated by means of an example based on three local livestock breeds from different species in Switzerland.

Advances in farm animal genomic resources

Stéphane Joost

The history of livestock started with the domestication of their wild ancestors: a restricted number of species allowed to be tamed and entered a symbiotic relationship with humans. In exchange for food, shelter and protection, they provided us with meat, eggs, hides, wool and draught power, thus contributing considerably to our economic and cultural development. Depending on the species, domestication took place in different areas and periods. After domestication, livestock spread over all inhabited regions of the earth, accompanying human migrations and becoming also trade objects. This required an adaptation to different climates and varying styles of husbandry and resulted in an enormous phenotypic diversity. Approximately 200 years ago, the situation started to change with the rise of the concept of breed. Animals were selected for the same visible characteristics, and crossing with different phenotypes was reduced. This resulted in the formation of different breeds, mostly genetically isolated from other populations. A few decades ago, selection pressure was increased again with intensive production focusing on a limited range of types and a subsequent loss of genetic diversity. For short-term economic reasons, farmers have abandoned traditional breeds. As a consequence, during the 20th century, at least 28% of farm animal breeds became extinct, rare or endangered. The situation is alarming in developing countries, where native breeds adapted to local environments and diseases are being replaced by industrial breeds. In the most marginal areas, farm animals are considered to be essential for viable land use and, in the developing world, a major pathway out of poverty. Historic documentation from the period before the breed formation is scarce. Thus, reconstruction of the history of livestock populations depends on archaeological, archeo-zoological and DNA analysis of extant populations. Scientific research into genetic diversity takes advantage of the rapid advances in molecular genetics. Studies of mitochondrial DNA, microsatellite DNA profiling and Y-chromosomes have revealed details on the process of domestication, on the diversity retained by breeds and on relationships between breeds. However, we only see a small part of the genetic information and the advent of new technologies is most timely in order to answer many essential questions. High-throughput single-nucleotide polymorphism genotyping is about to be available for all major farm animal species. The recent development of sequencing techniques calls for new methods of data management and analysis and for new ideas for the extraction of information. To make sense of this information in practical conditions, integration of geo-environmental and socio-economic data are key elements. The study and management of farm animal genomic resources (FAnGR) is indeed a major multidisciplinary issue. The goal of the present Research Topic was to collect contributions of high scientific quality relevant to biodiversity management, and applying new methods to either new genomic and bioinformatics approaches for characterization of FAnGR, to the development of FAnGR conservation methods applied ex-situ and in-situ, to socio-economic aspects of FAnGR conservation, to transfer of lessons between wildlife and livestock biodiversity conservation, and to the contribution of FAnGR to a transition in agriculture (FAnGR and agro-ecology).

Frontiers2016

Species conservation in the face of global environmental changes: surface-based modelling of geo-environmental data to identify vulnerable populations

Estelle Rochat

Human activities are resulting in many land-use changes, particularly due to urbanisation and intensification of agricultural practices. Because of these changes, in addition to climate change, many species are facing habitat degradation. In order to avoid extinction under these conditions, they can either move to more favourable areas or adapt to their new environment. To develop appropriate conservation measures, it is essential to identify vulnerable populations that may not be able to disperse or adapt. In this context, modelling tools can be used to predict the potential impact of environmental changes on species and populations. However, to date, few approaches take into account the degree of exposure, the possibility of dispersal and the potential for adaptation. In this thesis, we present modelling approaches based on geo-environmental data to integrate these three elements. First, we use ecological niche models to estimate the distribution of suitable habitats for a given species as a function of environmental conditions. We propose an improvement of commonly used models by developing an approach to integrate spatio-temporal variability of environmental predictors. In addition, we develop a nested model to predict the distribution of vector-borne pathogens. This model can be used to identify populations that may be threatened by an increasing presence of pathogens in their habitat. We use it to model the evolution of the distribution of Ixodes ricinus ticks and their Chlamydiales bacterial pathogen. We then use landscape graphs to analyse the connectivity between habitats and estimate the possibilities for threatened species to move to more favourable areas. Connectivity is also essential for maintaining gene flow and genetic diversity, which is necessary for greater adaptive capacity. We propose here an approach combining landscape graphs, simulations and empirical genetic data to identify the impact of reduced connectivity on population persistence and genetic diversity. We use it to identify butterfly populations that are threatened by increasing fragmentation in an urban landscape. Finally, we develop the concept of "Spatial Areas of Genotypes Probability" (SPAG) to better analyse the adaptive potential of populations. SPAGs make it possible to model the probability of finding locally adapted genetic variants in a given territory, as well as to identify vulnerable populations lacking in genetic variants that would favour adaptation to future climate conditions. We use it to highlight populations of Moroccan and European goats that are poorly adapted to the climatic conditions predicted under a climate change scenario for 2070 (strong variations in precipitation or increased drought). To conclude, we show how the three modelling approaches presented can be combined and integrated into a more general conservation framework to identify vulnerable populations facing high exposure to environmental changes, low dispersal possibilities and reduced adaptive capacity.

EPFL2020

Species conservation in the face of global environmental changes: surface-based modelling of geo-environmental data to identify vulnerable populations

Estelle Rochat

EPFL2020

Advances in farm animal genomic resources

Stéphane Joost

Frontiers2016