How does transcription of a gene change when the gene receives multiple input signals? A wide variety of outcomes are possible, ranging from sub-additive to super-multiplicative integration of each signal?s effects. A common belief is that it is not possible to predict how a gene will integrate two or more signals because cellular signal responses depend on ?context?. Nevertheless, gene regulation studies select either an additive or multiplicative null model when determining cooperativity or antagonism in transcriptional responses to pairs of signals. However, it remains unknown what the ?default? mode of integration is for multiple cell signals. Moreover, newer epigenetic profiling methods have yet to reveal the context that determines how a gene integrates two signals. We propose transcriptome-wide profiling of signal integration outcomes in human cells to map the degree to which genes use additive, multiplicative, or other modes of integration. In parallel, we will analyze changes in chromatin accessibility near these genes to reveal the nature of cis-regulatory element activities that corresponds to a gene?s signal integration mode. We will use a simple model system where we co-expose human breast carcinoma (MCF-7) cells to two potent cell signals: retinoic acid and TGF-beta. After exposing these cells to either or both signals, we will perform paired RNA-seq and ATAC-seq measurements. Our preliminary data suggest that TGF-beta and retinoic acid change the expression of 693 shared target genes. Comparing individual versus combined signal effects at these genes, we observe a variety of signal integration functions that range from sub-additive to super-multiplicative. Our preliminary findings also suggest that a gene?s signal integration function remains consistent across multiple dosages. This implies that the structure of nearby regulatory elements may determine a gene?s mode of integration. Do two signals add their effects when they act on distinct enhancers, but multiply their effects when they act on the same enhancers? Or do specific transcription factor combinations dictate a gene?s mode of integration? We will analyze our paired ATAC-seq data to distinguish between possible ?epigenetic arrangements? that enable different signal integration functions, using differential peak analysis to measure activated regulatory elements and transcription factor motif analysis to test for associations between genes and specific transcription factor pairs. We will test our predictions by silencing specific enhancers near endogenous genes with CRISPR-based approaches. Our studies in MCF-7 cells will provide a rich starting point for our question, but we will also expand the scope of our work to test the effects of cell type, relative timing of signal onset, and higher order signal combinations (up to four simultaneous signals). This work could revise leading quantitative models of how genes respond to interacting input signals, which could be then used for designing synthetic genes or predicting transcriptional responses to combinations of drugs.

Public Health Relevance

Project Summary When a gene receives multiple signals that change its expression, it combines their effects with a specific integration function. To understand how genes select signal integration functions, we will collect paired gene expression and chromatin accessibility measurements on signal-treated human cells and perform genome-wide analysis of cis-regulatory element activity at the common targets of multiple signals. Our results will have the potential to inform strategies for designing combination therapies that act on the disease-relevant cell types in specific tissues.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
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Special Emphasis Panel (ZRG1)
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Gatlin, Tina L
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University of Pennsylvania
Biomedical Engineering
Biomed Engr/Col Engr/Engr Sta
United States
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