Project Summary/Abstract
One of the core attributes of cells is their ability to grow and divide. This process is driven by a network of
proteins, commonly called the cell cycle machinery, which acts like a miniature engine driving cycles of growth
and division. How the proteins of the cell cycle machinery work together is relatively well understood. However,
the rules of their production from the corresponding genes are much less clear, and yet are equally important
to create a functional engine. Genes can differ widely in the strategy they use to produce their corresponding
protein. For example, they may produce more or less of the messenger RNA intermediate, the messenger
RNA or the protein may have a long or a short lifetime, and production can be directly linked to those of other
proteins or not. These features in turn influence the dynamic range of protein levels, the interaction between
proteins, and the robustness of the system in the face of perturbations. How expression strategies are
encoded in the DNA and how they contribute to proper protein function is poorly understood and therefore
limits our understanding of cell cycle regulation. Interestingly, different cell cycle regulators use different
expression strategies even when operating in the same pathway and it is likely that each strategy is selected
for optimal function of this protein within the cell cycle machinery. Our long-term goal is to understand how
these different expression strategies support cell cycle regulation, and how the information for a specific
expression strategy is encoded on the DNA. Our immediate goal is to understand how messenger RNA
features of select cell cycle regulators support the function of the protein that they encode. We will address
this question in fission yeast, a eukaryotic model organism that shares many features with human cells but
uses a minimal cell cycle machinery that is experimentally well-tractable. Gaining a deep understanding of
how different expression strategies are encoded in the genome will enhance our understanding of cell
physiology and will provide insight into the consequences of non-coding mutations that are observed in cancer
or other genetic diseases, thus promoting advances in precision medicine.