Speaker
Sergey Kryazhimzkiy
Description
The effect of a mutation on a phenotype of interest often depends on
the presence of other mutations in the genome. Such dependencies are
known as epistasis or genetic interactions. The evolutionary process
fundamentally depends on the structure and type of these interactions.
Certain types of epistasis are involved in explaining the evolution of
sexual reproduction, historical contingency, robustness to deleterious
mutations, etc. Epistasis is also extensively used in genetics to identify
genes involved in various biological processes. Despite its prominent
role in biology, our current understanding of the mechanistic origins of
epistasis is poor, especially for mutations affecting different genes. In
particular, we lack a null expectation for what types of epistasis (if any)
should be common to many or even all biological systems and what
types of epistasis may be signatures of potentially interesting
idiosyncratic interactions between specific gene products.
Here, I develop a mathematical theory for understanding what types of
epistasis we might expect to observe between mutations affecting
microbial metabolism. I consider a hierarchy of increasingly coarse-
grained descriptions of a metabolic network, such that more coarse-
grained (“higher-level”) descriptions typically have fewer effective
parameters than more detailed (“lower-level”) descriptions, with the
growth rate being the single top-level parameter. I find that mutations
that exhibit no epistasis for lower-level parameters (e.g., mutations
affecting different enzymes) almost certainly exhibit epistasis for
higher-level parameters, and that epistasis for lower-level parameters
generically implies epistasis for higher-level parameters. This suggests
that any metabolic mutations that have effects on growth rate are
generically expected to exhibit epistasis. Moreover, I show that, for
networks with first-order reaction kinetics, negative epistasis at a lower
level remains negative at all higher levels, and strong positive epistasis
at a lower level remains strongly positive at all higher levels. Finally, I
show that certain topological relationships between reactions within the
network impose constraints on the sign of epistasis for growth rate that
mutations affecting these reactions can exhibit.
This theory provides a foundation for interpreting epistasis observed in
experiments and for constructing more realistic models of genome-wide
fitness landscapes.
Primary author
Sergey Kryazhimzkiy
