Genome-Wide Insights into the Efficiency of Cellular Reprogramming

Seminar Series

Thursday, September 7, 2017 - 12:00
CIEMAS Schiciano B
Dr. Raluca Gordan

Cellular transdifferentiation systems are increasingly being used in basic and translational research studies. Still, our understanding of transdifferentiation processes is limited. It is oftentimes unknown, at a genome-wide scale, how much transdifferentiated cells differ quantitatively from both the starting cells and the target cells. Focusing on transdifferentiation of primary human skin fibroblasts by forced expression of myogenic transcription factor MyoD, we performed quantitative analyses of gene expression and chromatin accessibility profiles of transdifferentiated cells compared to fibroblasts and myoblasts. In this system, we find that while many of the early muscle marker genes are reprogrammed, global gene expression and accessibility changes are still incomplete when compared to myoblasts. In addition, we find evidence of epigenetic memory in the transdifferentiated cells, with reminiscent features of fibroblasts being visible both in chromatin accessibility and gene expression. Quantitative analyses revealed a continuum of changes in chromatin accessibility induced by MyoD, and a strong correlation between chromatin-remodeling deficiencies and incomplete gene expression reprogramming. We identify potential explanations for the incomplete reprogramming at the chromatin level, and suggest ways to improve the process through additional regulatory factors and induced epigenetic changes. Our approach for analyzing, on a genome-wide scale, the efficiency of cellular transdifferentiation driven by a transcription factor master regulator can be applied to any transdifferentiation system, and we expect it to be particularly useful for studying systems with low conversion efficiency.

Raluca Gordan, PhDRaluca Gordan, PhD
Assistant Professor
Department of Biostatistics and Bioinformatics and Computer Science 
Duke University   

Biography: Raluca Gordan is an assistant professor at Duke University, with primary appointments in Biostatistics & Bioinformatics and Computer Science. Her primary research interests are in regulatory genomics. Her laboratory, located in the Duke Center for Genomic and Computational Biology, develops computational methods and high-throughput experimental techniques to quantitatively characterize protein-DNA interactions and their role in gene regulation. Raluca began her career as a computer scientist and received her B.S. in computer science from University of Iasi, Romania. Her Ph.D. work, in the Computer Science department at Duke, focused on applications of machine learning techniques to problems in computational regulatory genomics. In 2009, Raluca started a postdoctoral fellowship at the Harvard Medical School, where she gained experimental skills as she continued her work on deciphering protein-DNA recognition mechanisms. Raluca joined Duke as an assistant professor in 2011.