An Edge on Gene Regulation in Health and Disease
Juan Fuxman Bass
University of Massachusetts
February 18, 2016
Foege N130A, Wallace H. Coulter Seminar Room
Gene regulatory networks (GRNs) comprising interactions between transcription factors (TFs) and regulatory elements play critical roles in development, physiology and responses to environmental cues. In recent years, chromatin immunoprecipitation (ChIP) assays have greatly expanded our view of the genomic regions occupied by individual TFs. However, only ~10% of human and C. elegans TFs have been assayed by ChIP. During my postdoc, I used gene-centered enhanced yeast one-hybrid (eY1H) assays to delineate TF-wide human and C. elegans protein-DNA interaction (PDI) networks for ~3,000 regulatory regions, providing functional annotations for ~300 uncharacterized TFs. Analyses of network connectivity identified redundancy between TFs and between different regulatory regions, as well as putative functions for uncharacterized genes and TFs. Finally, we detected PDI changes caused by 58 TF missense mutations and 109 noncoding mutations associated with a wide variety of diseases. This work establishes eY1H assays as a powerful addition to the GRN mapping toolkit and for the high-throughput characterization of genomic variants that are rapidly being identified by genome-wide association studies.
Dr. Juan Fuxman Bass received his Ph.D. at the University of Buenos Aires (Argentina), where he studied the immune responses elicited by extracellular DNA present in bacterial biofilms. In 2011, he joined the laboratory of Dr. Marian Walhout at UMass Medical School, supported by a Pew Latin American postdoctoral fellowship, to study protein-DNA interaction networks in human and C. elegans. Dr. Fuxman Bass has been awarded multiple national and international prizes in the mathematics Olympiads and was recently the recipient of a K99/R00 Pathway to Independence Award from the NIH. His research interests lie in the transcriptional regulation and misregulation of immune genes, using experimental and computational approaches to characterize protein-DNA interaction networks, with the goal of modulating gene expression in disease.