OL.20.006 – LifesPan – Life-size pan-genomics

Route: The origin of life - on earth and in the universe

Cluster question: 134 How did life arise and how does evolution work?

Fifteen years after finishing the human genome, we have read the genomes of many living organisms; from small, simple genomes of bacteria and fungi to large, complex ones of animals and plants. This treasure trove of genome data is indispensable for science, to study and preserve biodiversity and to learn how genomes, genes, functions and organisms evolve. It also holds great promise to discover new approaches to address a number of societal challenges, including sustainable bio-based production of foods, fuels and pharmaceuticals, improvement of plant and animal breeding to secure food supplies in times of climate change, and development of new medical treatments. Progress in these areas critically depends on our ability to compare genes, pathways and organization of genomes between species, to discover and combine the wide variety of functions and interactions nature has to offer. However, efficiently and effectively mining this data across the tree of life is impossible using today’s tools. To exploit the full potential of large genomic datasets, a transition towards pan-genome approaches is therefore currently taking place. A pan-genome offers a single representation for multiple genomes, which compresses similarities but retains all variation. LifesPan will develop a scalable computational pan-genome representation and methods for navigation and (visual) analytics, uniquely enabling tree of life-scale comparative genomics. To achieve this, an inter-disciplinary approach will be taken, combining aspects of evolutionary biology, genome biology, computational biology and bioinformatics. LifesPan brings together expertise in biological research areas where comparative genomics is most relevant, the study of bacterial, fungal, plant and animal genomes; and expertise in the development of novel computational methodology needed to efficiently store, integrate, mine and present genomic information at a tree-of-life scale.

Keywords

bioinformatics, computational biology, evolution, genomics

Other organisations

Centre for Genetic Resources, Eindhoven University of Technology (TU/e), HAN University of Applied Sciences, Leiden University (LEI), Naturalis Biodiversity Center, Netherlands escience center, Utrecht University (UU), Wageningen Universities and Research (WUR), Westerdijk Fungal Biodiversity Institute

Submitter

Organisation Wageningen University (WUR)
Name Prof.dr.ir. D. (Dick) de Ridder
E-mail dick.deridder@wur.nl
Website http://www.bif.wur.nl/