David JJ. Gresham

Assistant Professor of Biology
Ph.D., Edith Cowan University, Perth, Australia, Human Genetics, 2001; B.S., McGill University, Montreal, Canada, Biochemistry, 1997

Office Address:
New York University
Center for Genomics and Systems Biology
Department of Biology
1009 Silver Center
100 Washington Square East
New York, NY 10003-6688

Email:
Phone: (212) 998-3879
Fax: (212) 995-4015
List of Publications from Pubmed
Lab Homepage
Our aim is to understand the structure and behavior of the genetic networks that interpret the external environment of the cell. We use the budding yeast to study these networks using a combination of genetic, cell biology and genomic/ computational approaches. Our research addresses three fundamental questions:

1.) What are the pathways, dynamics and principles of adaptive evolution in response to environmental conditions? We perform evolution experiments over hundreds of generations in defined environments using chemostat (continuous) cultures. We study the multigenic basis of evolved quantitative phenotypes to understand the evolutionary trajectories of fitness landscapes and how genes interact to produce quantitative variation.

2.) How does post-transcriptional regulation of gene expression facilitate response to environmental conditions? The response of biological networks to dynamic environments requires processes that occur on very short timescales. The fastest means of altering transcriptional programs is through the degradation or stabilization of pre-existing transcripts. We study the mechanisms that regulate the fate of RNAs in response to environmental signals.

3.) What is the high-resolution structure of genetic interaction networks? To build a map of genetic interactions we employ high throughput suppressor screens using conditional lethal alleles. We use forward and reverse genetic approaches to explore a large fraction of sequence space allowing us to identify both those genes (and their products) that interact and the sequence specificity of those interactions. Our ultimate aim is to infer the rules that govern the interaction and co-evolution of genes.


Areas of Research/Interest

Genomics of adaptive evolution, growth-rate regulation and post-transcriptional gene regulation.

Publications