Molecular evolution in the presence of limited recombination

In recent years, sequencing technologies have made it possible
to observe the outcomes and, in some cases, the process, of molecular
evolution at a remarkable level detail. We are now able to sequence the
genomes of enormous numbers of individuals from a wide range of
populations, and to observe the evolution of rapidly evolving microbes
and viruses in real time. Yet our ability to interpret this data is
limited by our ability to solve even the simplest generative models of
molecular evolution. In this talk, I will describe a solution to a
simple `null' model of molecular evolution, in which individuals in the
population are in a well-adapted state in which all new mutations have
either neutral effects or strong costs, in which case they are purged
from the population. I will show that even in this simple case, the
time-dependent dynamics of individual genotypes can be remarkably
complex. In some cases the genetic diversity generated under this null
model can be indistinguishable from those generated by more unusual
evolutionary processes, even though the time-dependent dynamics may be
different. Thus, model distinguishability may be an important limitation
when interpreting sequence data. On the other hand, experimental
measurements that can could be used to directly test theoretical
predictions and guide model choice are remarkably sparse. A major reason
for this gap is that evolution is fundamentally driven by rare events,
and resolution limits of current methods make it impossible to directly
observe the majority of these events. I will describe a new
high-resolution experimental approach that overcomes this limitation in
evolving yeast populations by continuously re-barcoding the population
with a diverse library of DNA barcodes. I will explain how the barcode
sequence data can be used to identify beneficial mutations in the
evolving population while they are at remarkably low frequencies, which
paints a complex picture of adaptation in a simple laboratory
environment. These data demonstrate both the successes of previous
theoretical work in describing the qualitative features of molecular
evolution, and the quantitative limitations that suggest opportunities
for future work.

If you are interested in participating, please write an e-mail to Britta Baron, baron@evolbio.mpg.de