Skip Navigation

Joshua Rest, Associat Professor (CV)

Ph.D., University of Michigan, 2004

Genome evolution


Office: LS676

Phone:  (631)632-1916

Lab Website: Rest Lab Website

Research Summary:

Fitness Landscapes of Gene Expression
Related publications: Nonlinear fitness consequences of variation in expression level of a eukaryotic gene, Contribution of transcription factor binding site motif variants to condition-specific gene expression patterns in budding yeast.
We are measuring the extent that changes in the expression of genes result in changes in the fitness (reproductive capacity) of cells. We alter the expression level of a given gene using a repressible promoter, and measure the resulting fitness by competing the cells with altered expression against cells with normal expression. The result is an expression-fitness curve that indicates the precise relationship between expression level and fitness. The fitness curve for a gene predicts the amount of variation in expression among individuals in a population, where flatter functions are expected to show more variation.
We have completed measurement of the expression-fitness function for a gene, LCB2, that is essential for the production of sphingolipids in the cell. We are now using next-generation sequencing technology to scale up this analysis for a larger number of genes.

Variation in the Carbon Metabolic Network
Related publication: Coevolution trumps pleiotropy: Carbon assimilation traits are independent of metabolic network structure in budding yeast.
A goal in molecular evolution is to understand how evolution acts to integrate selective pressures from diverse and changing environmental parameters in light of constraints imposed by cellular architecture. We are taking advantage of the tremendous diversity for carbon utilization within the species Saccharomyces cerevisiae and S. paradoxus to investigate this. We are studying how sets of metabolic traits co-evolve, and what the effect of sharing of pathways of cellular systems among traits is on their co-evolution. We are taking advantage of natural variation in the number of carbon utilization traits to study whether the complexity of molecular pathways alters the effect of mutational input through canalization or mutational robustness.

Protein Interaction Stability, Degree, and Authenticity
We are investigating model-based integration among various types of protein-protein interaction data with the goal of robust inference of the degree, stability, and reality of individual interactions.

Phylogenetics and Horizontal Gene Transfer
Related publications: Massive mitochondrial gene transfer in a parasitic flowering plant clade,Horizontal transfer of expressed genes in a parasitic flowering plant, Sulfate activation enzymes: phylogeny and association with pyrophosphatase, Strong mitochondrial DNA support for a Cretaceous origin of modern avian lineages, and others listed here.
We use phylogenetic methods to detect horizontal gene transfer, to reconstruct ancestral protein and regulatory sequences, and to test biological hypotheses. We are particularly interested in statistical methods to reject or accept alternative biological hypotheses.

Interfering Interactions as a Driver of Regulatory Architecture
We are examining the extent that modularity is driven by avoidance of gain-of-function mutations, including avoidance of deleterious pairwise interactions. We artificially turn genes on at the same time to see if there is an epistatic cost for co-expression.


Login to Edit