How does naturally genetic variation modulate cell biological traits relevant to human disease? Many common diseases, ranging from autism to obesity, are influenced by multiple sequence variants. Genome-wide association (GWA) studies are yielding more and more human disease risk factors, but how these genetic variants act collectively to confer disease risk remains unclear. In many cases the identified genetic variants only explain a small fraction of the disease risk heritability. Yet, the promise of personalized medicine hinges on whether we can account for the effect of an individual's genetic makeup. Due to its genetic pliability the budding yeast S. cerevisiae is an ideal model system to investigate the genomic architecture of complex traits. Prof. Leonid Kruglyak and his lab have previously used two divergent S. cerevisiae isolates to map the genetic variation mediating various phenotypes, including differences in gene expression. However, these two strains only represent a minute fraction of the S. cerevisiae species-wide genetic and phenotypic variance. I am developing a method that will allow me to generate large mapping populations of individual segregants starting from any two divergent S. cerevisiae isolates. This approach will enable me to investigate how genetic variation modulates a core MAPK signaling cascade, the HOG high osmolarity signaling pathway. The HOG MAPK cascade is highly conserved, with its human counterpart playing a key role in various cancers and its equivalents controlling virulence in several pathogenic fungi. Yet, how genetic variation influences HOG pathway activity is unknown. I will identify sequence variants that alter HOG pathway activity and will then characterize how signaling is altered specifically. The approaches I will develop to measure HOG signaling could later be applied to the study of other MAPK signaling pathways. The virulence of the pathogenic fungus Cryptococcus neoformans is governed by several complex traits. Intriguingly, HOG pathway activity is required for full virulence of this fungus. I will idntify the genetic variations that modulate virulence attributes of C. neoformans. In particular, I will characterize the genetic contributions to melanin production, capsule size and organ-specific infectivity. These analyses could be extended to additional medically relevant properties of this pathogen and will aid the study of other pathogenic fungi.
Aim 1 : To develop methodology to rapidly extend quantitative trait loci (QTL) mapping to additional S. cerevisiae isolates.
Aim 2 : T characterize the effect of genetic variation on MAPK signaling.
Aim 3 : To identify QTL modulating virulence of C. neoformans.

Public Health Relevance

Genetic information varies among individuals. This naturally occurring genetic variation in part determines our risk of contracting many common diseases. To increase our understanding of the effect of genetic variation on disease relevant cellular processes, I will elucidate how genetic variation alters cell signaling and fungal virulence.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32GM101857-03
Application #
8634804
Study Section
Special Emphasis Panel (ZRG1-F08-K (20))
Program Officer
Reddy, Michael K
Project Start
2012-04-01
Project End
2015-03-31
Budget Start
2014-04-01
Budget End
2015-03-31
Support Year
3
Fiscal Year
2014
Total Cost
$55,094
Indirect Cost
Name
Princeton University
Department
None
Type
Organized Research Units
DUNS #
002484665
City
Princeton
State
NJ
Country
United States
Zip Code
08544
Albert, Frank W; Treusch, Sebastian; Shockley, Arthur H et al. (2014) Genetics of single-cell protein abundance variation in large yeast populations. Nature 506:494-7