Chris Ellison

Chris Ellison is an Associate Professor in the Department of Genetics at the School of Arts and Sciences, Rutgers University. His research integrates computational and experimental approaches in evolutionary genomics, primarily using Drosophila as a model system. He investigates how gene regulatory networks evolve and how transposable elements interact with host genomes.

His research focuses on two major areas: host-transposable element (TE) conflicts and the evolution of 3D genome architecture. In the context of TE dynamics, his lab explores the evolutionary arms race between TEs and host silencing mechanisms, particularly involving piwi-interacting RNAs (piRNAs). He seeks to identify TE strategies for evading host suppression, which has implications for understanding mutagenesis and disease. In 3D genome evolution, his team uses Hi-C to study topologically associating domains (TADs) across Drosophila species, finding that TAD evolution is rapid and varies by chromatin state, with developmental gene-enriched TADs being more conserved than those enriched for housekeeping genes.

Dr. Ellison’s work bridges evolutionary biology, molecular biology, and bioinformatics, contributing to fundamental questions about genome organization and regulation. His lab generates evolutionary hypotheses computationally and tests them through genetic engineering.

Scientific Awards:

• Award recognized on April 26, 2022 (jointly with Dr. Michael Verzi)

Dr. Ellison advises students and leads a research lab focused on genomic evolution, though specific advisees are not listed. He utilizes advanced genomic technologies and computational modeling to explore the dynamics of genome architecture and regulatory evolution. His lab contributes to understanding how structural and functional elements of genomes evolve under selective pressures.

Laboratory and Research Team:
The Ellison Lab conducts interdisciplinary research combining functional genomics, population genomics, and bioinformatics. The team employs Hi-C chromosome conformation capture and computational modeling to study chromatin organization and gene regulation across Drosophila species.