1000 African Mammal Genomes: Big Data to Learn from Large Animals
Navn på bevillingshaver
Rasmus Heller
Institution
University of Copenhagen
Beløb
DKK 4,999,833
År
2021
Bevillingstype
Semper Ardens: Accelerate
Hvad?
In the ongoing biodiversity crisis, large terrestrial animals are more threatened by extinction than any other group of organisms. The African continent holds the last remaining intact large-mammal community, providing the only chance to study the biology of such communities in a natural setting - which incidentally is also the birthplace of humankind. Despite this, there is still a lot we do not know about how these species evolved, became diverse and adapted to the changing climate and habitats across Africa. Many of these questions can be addressed by investigating the genomes and genetic variation across species. This approach becomes particularly powerful when viewed across many species living in the same habitat.
Hvorfor?
The project will address several important questions, including how, when and why different species moved around in Africa, and how this movement led to adaptation and new species being formed. Understanding these dynamics will definitely lead to an improved understanding of Africa as the main theater of human evolution. The data will also allow us to address how specific selection pressures, e.g. imposed by important animal diseases, have impacted the evolutionary processes in large mammals, which will provide important new knowledge about how animals have changed genetically to cope with such diseases. Finally, the project will secure a vital resource of biodiversity information for posterity before it is lost forever.
Hvordan?
In this project we will sequence whole genomes from several large mammal species in Africa, targeting 1,000 whole genomes distributed on 10-15 species. Through decades of painstaking sampling efforts and collaboration with African and other researchers, we have secured a large collection of tissue samples that allow us to sequence large numbers of individuals from many species. At the same time we are assembling a team of experts in computational biology, bioinformatics and molecular ecology that make us uniquely equipped to analyze such a large data set to the highest possible standards. The grant will cover the generation of large amounts of sequencing data, expanding the team of experts to analyze it and some essential resources neccessary to carry out this large endeavor.