Project Summary/Abstract
A central goal of biology is to understand the relationship between DNA sequence (genotype) and the
characteristics of the resulting organism (phenotype). For a century or so, geneticists identified mutants with
phenotypes of interest through genetic screens, and, since the ~1970s, could isolate the mutated genes
responsible for such changes. More recently, for a handful of model organisms, systematic approaches have
been devised to interrogate the phenotypic consequences of gene knockouts or knockdowns using specialized
genome wide collections, which took years to construct. Recent technological innovations have made it possible
to systematically measure the consequences of gene knockout/knockdown in high throughput in many
organisms, yet comparative approaches, to determine gene function not only on a large scale, but in multiple,
related organisms, are lacking. Such studies are crucial to better understand the relationship between changes
in DNA sequence, and the phenotypic and fitness consequences. Furthermore, there are no studies that have
characterized genetic interaction networks in a group of related organisms, to determine how this next level of
functional organization evolves over time. To address these knowledge gaps, we propose 3 integrated aims: for
five closely related Saccharomyces species, we will 1) determine the fitness consequences of disrupting each
gene, under multiple experimental conditions, 2) generate genetic interaction networks under a subset of the
same multiple experimental conditions for an important subset of the genes, and 3) for genes and genetic
interactions that show clear differences across species, further investigate the underlying nature of those
differences. In the first Aim, we will take advantage of SATAY, a saturation transposon mutagenesis approach
that will allow us to measure the fitness of hundreds of thousands of transposon insertion events, under many
experimental conditions. Not only will this allow us to determine the essential genes in each of the 5 species, but
in some cases, it also allows the identification of gene substructure. Because we will measure the most
appropriate phenotype, Darwinian fitness, we will also be able to make quantitative comparisons between
different species as to the consequences of disrupting any given ortholog under a particular condition. In the
second Aim, we will create genetic interaction networks, by measuring for a rationally chosen set of genes, tens
of thousands of genetic interaction scores, using CRISPRiSeq, a pooled pairwise interaction fitness approach
we recently developed. These data will bridge a crucial gap in knowledge on how genetic networks change over
evolutionary time, which could result in better prediction of genetic interactions . Finally, in the third Aim, we will
further investigate the observed inter-species differences from Aims 1 and 2. Our preliminary data suggest that
there will be many genes that are essential in some species, but not others, and we predict that we will also
observe changes (both qualitative and quantitative) in genetic interaction networks; we will investigate the
underlying causes of these differences.