Evolution of species is recorded in the genes
Ankole cattle from Uganda, an endangered species due to cross-breeding. © Raimond Spekking / Wikimedia Commons
Climate change, population movements and natural or forced cross-breeding induce or accelerate the evolution of species. Between geographical information and genetics, a method developed by a researcher at EPFL as part of a European project enables traces of evolution due to the environement to be detected in genes.
Without doubt, one of man’s greatest mistakes is to think himself above the laws of nature. However, when livestock breeders order semen online from the other side of the world in the interests of immediate productivity, they are ignoring an important fact: it’s no accident that certain species have been able to settle and survive in certain environments for millennia. “There is an obvious example in Uganda”, explains Stéphane Joost, researcher at the Laboratory of Geographic Information Systems (LASIG) at EPFL. “The Ankole cattle breed has evolved there naturally over several hundred years, and is therefore perfectly adapted to the local climatic conditions. Yet breeders cross it with, or import, Holsteins originating from the Netherlands because they produce more milk. But these cross-breeds don’t survive for long in this environment.”
Farmers in poor regions must find a balance between adequate productivity and a sustainable option that will enable them to leave a legacy for their family. Some of the tools developed by Stéphane Joost are able to provide specific elements that might help them to make the right decisions. “Our work consists of establishing a relationship between genetic markers and environmental data,” continues the researcher.
When rain “creates” lanolin
“We have also found that certain breeds of sheep produce a wool that contains more lanolin in regions with higher rainfall”, adds Stéphane Joost by way of example. This method also makes it possible to identify which area of the genome is implicated in resistance to disease transmitted by the tsetse fly: data that is crucial in the regions of Africa where the latter is rife.
Specifically, therefore, it is a matter of tapping into the vast databases of geographical information systems or measuring environmental parameters with the help of sensors on the ground, to determine which genes may derive their function from the environment in which the studied species live, and to establish correlations – hence the term “landscape genomics” being used to describe this process.
This research is associated with a number of European projects. Last month EPFL hosted a large gathering of researchers at the final workshop of Globaldiv (www.globaldiv.eu), a three-year program focusing on methods and data relating to the conservation of genetic resources of farm animals. This project will now continue until 2014 under the name of “Genomic-Resources” (genomic-resources.epfl.ch). At the same time, Stéphane Joost and LASIG are actively involved in the NextGen project (nextgen.epfl.ch), which aims to apply landscape genomics to the whole genome of several species of farm animal sequenced in Africa (goats in Iran, goats and sheep in Morocco, and Ankole cattle in Uganda).
“We want to explore potential links between the hundreds of environmental parameters and – in due course – millions of genetic markers”, explains Stéphane Joost, who directs Genomic-Resources, a four-year project. In addition to the exploratory work and genetic analysis in the field, the preparation of this “genetic atlas” demands significant computing power, requiring the use of high-performance computing and specific functions programmed within a piece of software also developed at LASIG as part of a doctoral thesis.
The method developed in the course of these projects has already been applied by many researchers, who are thereby helping to document the links discovered between the areas of the genome and certain environmental parameters. This information will be every bit as beneficial to the preservation of species as it is to the scientific framework of the breeders.