Ilya Ruvinsky

- Associate Professor, Dept. of Ecology & Evolution, University of Chicago

Contact Information

Department of Ecology & Evolution
The University of Chicago
1103 East 57th Street, EBC 304A
Chicago, IL 60637

Phone: 773 702 1533
Fax: 773 702 1533
Email: .(JavaScript must be enabled to view this email address)


My laboratory is broadly interested in the evolution of development (Evo-Devo), evolutionary genomics, and molecular evolution. We integrate developmental, genomic, and computational approaches to understand the evolution of genes and gene functions. Students and post-docs are encouraged to develop their projects under the broad umbrella of these research interests.

Our major goal is to elucidate the “tempo and mode” of cis-regulatory evolution. Orthologous genes are often expressed in similar patterns even between distantly related species. Coupled with a high degree of functional conservation of transcription factors, this would suggest that cis-regulatory elements have also been conserved over long periods of time. However, several lines of evidence suggest that this is not always the case, and the rules are likely complicated.

We are exploring a hypothesis that promoters co-evolve with the transcription factors that bind them and this results in the conservation of gene expression patterns despite rapid sequence turnover. To this end, we have dissected the mechanisms responsible for the conservation of expression of several genes between C. elegans and a closely related species.

A growing interest in the lab is to apply systems biology approaches to understanding how C. elegans copes with stress. Recently we developed a macro-level model to describe how chronic temperature stress affects reproduction in C. elegans. We used fundamental engineering principles, together with a limited set of experimentally derived facts, to provide quantitatively accurate predictions of performance under a range of physiologically relevant conditions. Currently, we are generating detailed time-resolved experimental data to gain quantitative insight into the breakdown of a robust biological system under stress.

Research Papers