PhD Candidate
Massachusetts Institute of Technology
Areas of Interest
- Biosystems and Computational Biology
Poster
Identification of determinants of differential chromatin accessibility through a massively parallel genome-integrated reporter assay
Abstract
A key mechanism in cellular regulation is the ability of the transcriptional machinery to physically access DNA. Pioneer transcription factors interact with DNA to open chromatin, which subsequently enables changes to gene expression during development, disease, or as a response to environmental stimuli. However, the regulation of DNA accessibility via the recruitment of transcription factors is difficult to understand in the context of the native genome because every genomic site is distinct in multiple ways. Here we introduce the Multiplexed Integrated Accessibility Assay (MIAA), a multiplexed parallel reporter assay which measures changes to genome accessibility as a result of the integration of synthetic oligonucleotide phrase libraries into a controlled, natively inaccessible genomic context. We apply MIAA to measure the effects of sequence motifs on cell type-specific DNA accessibility between mouse embryonic stem cells and embryonic stem cell-derived definitive endoderm cells, screening a total of 7,905 distinct phrases. MIAA is able to recapitulate differential accessibility patterns of 100-nt sequences derived from natively differential genomic regions, identifying the presence of E-box motifs common to epithelial-mesenchymal transition driver transcription factors in stem cell-specific accessible regions that become repressed during differentiation to endoderm. We further present causal evidence that a single binding motif for a key regulatory transcription factor is sufficient to open chromatin, and classify sets of stem cell-specific, endoderm-specific, and shared pioneer factor motifs. We also demonstrate that over-expression of two definitive endoderm transcription factors, Brachyury and FoxA2, results in changes to accessibility in phrases containing their respective DNA-binding motifs. Finally, we use MIAA results to explore the order of motif interactions and identify preferential motif ordering arrangements that appear to have an effect on accessibility.
Bio
Jennifer Hammelman (she/her) is a PhD student at MIT in the Computational and Systems Biology program. As a member of Dr. David Gifford's laboratory in CSAIL and a NSF graduate research fellow, she develops computational methods for functional genomics. She received her B.S. from Tufts University in Computer Science and Biology in 2016 where she performed research in biologically-inspired computing under Dr. Michael Levin. She is the program chair for the Graduate Women at MIT Mentoring Program, a Project Short Consultant, and has served as an HSSP Instructor.
