Lecturer:  Tamar Friedlander HUJI
Abstract:


Fitness landscape mapping and the prediction of evolutionary trajectories on
these landscapes are major tasks in evolutionary biology research.
Evolutionary dynamics is tightly linked to the landscape topography, but
this relation is not straightforward.
Here, we analyze a fitness landscape of a yeast tRNA gene, previously
measured under four different conditions. We find that the wild type allele
is sub-optimal, and 8%-10% of its variants are fitter. We rule out the
possibilities that the wild type is fittest on average on these four
conditions or located on a local fitness maximum. Notwithstanding, we cannot
exclude the possibility that the wild type might be fittest in some of the
many conditions in the complex ecology that yeast lives at. Instead, we find
that the wild type is mutationally robust ('flat'), while more fit variants
are typically mutationally fragile. Similar observations of mutational
robustness or flatness have been so far made in very few cases,
predominantly in viral genomes.