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Biogeoinformatics for the Management of Farm Animal Genetic Resources (Fangr)

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Biogeoinformatics for the Management of Farm Animal Genetic Resources (Fangr) Thèse n° 7147 Biogeoinformatics for the management of Farm Animal Genetic Resources (FAnGR) Présentée le 16 juillet 2020 à la Faculté de l’environnement naturel, architectural et construit Laboratoire de systèmes d’information géographique Programme doctoral en génie civil et environnement pour l’obtention du grade de Docteur ès Sciences par Solange Catherine GAILLARD Acceptée sur proposition du jury Dr J. Skaloud, président du jury Dr S. Joost, Prof. F. Golay, directeurs de thèse Dr C. Flury, rapporteuse Prof. P. Ajmone-Marsan, rapporteur Prof. R. Schlaepfer, rapporteur 2020 Acknowledgements Je voudrais remercier ici toutes les personnes sans lesquelles cette thèse n’aurait pas vu le jour. D’un point de vue scientifique, je commencerai bien sûr par mes directeurs de thèse, Prof. François Golay et plus particulièrement Dr. Stéphane Joost qui m’ont supervisé pendant cette aventure. Je voudrais aussi remercier tout le laboratoire du LaSIG pour les échanges aussi bien sociaux que scientifiques; en particulier, j’aimerais mentionner les personnes avec lesquelles j’ai eu le plus d’interaction au sujet de ma thèse: Estelle Rochat, Sylvie Stucki, Elia Vajana, Oliver Selmoni, Kevin Leempoel, Matthew Parkan, Jessie Madrazo, Anaïs Ladoy et Annie Guillaume. Certaines personnes en dehors de l’EPFL m’ont également apporté un précieux soutien. La première personne à laquelle je pense est sans aucun doute Christine Flury, qui, sans avoir été officiellement co-directrice de ma thèse m’a régulièrement suivi et m’a prodigué de nombreux conseils sur les aspects liés aux animaux d’élevage. Ensuite, je pense également à toutes les personnes que j’ai pu rencontrer lors de conférences ou de projets, tels que les projets NEXTGEN, ClimGen et bien d’autres encore. Mais le support scientifique ne serait rien sans ma famille. Mes parents d’abord, Gilbert et Claire- Lise Duruz, qui m’ont donné la vie et m’ont soutenu pendant mes études. Mes frères et sœurs, Christelle, Cyril, Myriam et Priscille, qui m’ont toujours soutenu dans les moments difficiles. Finalement mon mari et mes enfants, Jérémie, Judith and Simon Gaillard qui réchauffent mon foyer quand je rentre fatiguée le soir à la maison. 3 Summary 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. 4 Keywords Biogeoinformatics, Farm Animal Genetic Resources (FAnGR), livestock, local adaptation, local breeds, erosion of genetic diversity, climate change, transhumance, GIS, landscape genomics, integrated tools. 5 Résumé Dans le contexte de sélection drastique des animaux d’élevage et de changements climatiques, il est devenu crucial de mettre en œuvre une gestion durable de la pratique de l'élevage, soutenue par une utilisation judicieuse des technologies de l'information géographique. Sur la base de cette observation, cette thèse préconise l'utilisation de la biogéoinformatique (l'utilisation combinée de la biologie, de l'information géographique et de l'informatique) pour faire face aux défis rencontrés dans le secteur de l'élevage. En effet, si la biogéoinformatique peut fournir des informations capitales pour la gestion des ressources génétiques des animaux d’élevage, la variété et la complexité des tâches à accomplir empêchent une utilisation plus large de ces analyses. Cette thèse montre donc comment de nouveaux outils spécialisés sont susceptibles de faciliter l'adoption de cette approche par les biologistes et les acteurs du secteur de l'élevage, tout en étudiant trois grands défis des animaux d’élevage : i) l'érosion de la diversité génétique, ii) les effets du changement climatique sur l'élevage, et iii) la pression sur les pratiques d’élevage traditionnelles. La thèse s’agence selon trois axes : 1) Préserver les races adaptées localement Afin de prévenir l'érosion de la diversité génétique, les races adaptées localement devraient être surveillées pour éviter leur extinction. Nous avons donc développé une plateforme open source Web SIG appelée GENMON, capable de d'évaluer le degré de menace des races d'animaux d'élevage. Le système intègre plusieurs informations, liées entre elles grâce à l’information géographique : pedigree et introgression, concentration géographique, cryoconservation et durabilité des activités d'élevage. Le score peut être visualisé sur une carte et permet une identification rapide et régionale des races en danger. 2) Préserver les variations génétiques adaptées localement Compte tenu du rythme auquel la diversité génétique s'érode, il est crucial d'identifier pour ensuite préserver les variations génétiques liées à un phénotype adapté localement. Dans ce contexte, le logiciel Samβada avait été conçu pour rechercher des signatures d'adaptation locale via l'étude de l'association génome–environnement. Cependant, le pré- et le post-traitement peuvent être laborieux, et nous avons donc développé un package R nommé R.SamBada, qui fournit une chaîne de traitement pour la génomique environnementale. Basé sur Samβada, il va de la recherche des conditions environnementales jusqu’à l'annotation des gènes. Ainsi, R.SamBada facilite l’accès à des analyses biogéoinformatiques pour des chercheurs sans connaissance en géographie. 3) Préserver une technique d’élevage traditionnelle, adaptée aux races locales La préservation des races locales est aussi liée à la conservation de techniques d’élevage traditionnelles, qui en Suisse, comprennent la montée à l’alpage pendant l'été. L'un des principaux effets de l’alpage sur les vaches est la baisse de la production laitière. Nous avons développé un nouveau modèle mathématique pour ajuster la courbe de lactation des vaches alpées et avons testé l'influence des facteurs environnementaux, physiologiques et morphologiques en utilisant cinq millions de relevés laitiers mensuels de vaches Braunvieh. Comparées aux facteurs physiologiques, les variables environnementales montrent un impact limité sur la production de lait à l’alpage, les précipitations au printemps étant néanmoins la plus importante. 6 Mots-clés Biogéoinformatique, Ressources Génétiques des Animaux d’Elevage, adaptation locale, races locales, érosion de la diversité génétique, changements climatiques, transhumance, SIG, génomique environnementale,
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