There is a fundamental gap in understanding how the millions of known regulatory elements functionally contribute to gene regulation and phenotypes. Continued existence of that gap is an important problem because, until it is filled, it will remain extremely difficult to identify the genetic mechanisms underlying the thousands of observed genetic associations with disease phenotypes. Our long-term goal is to understand how and to what extent gene regulatory elements alter target gene expression and impact phenotypes. The objectives of this particular proposal are to functionally characterize all regulatory elements contributing to the differentiation of CD4+ T cells. In doing so, we will identify the causal regulatory mechanisms that modulate the immune system. The rationale for this work is that understanding those mechanisms will be the foundation for future efforts to therapeutically modulate the immune system, and will establish a discovery platform for determining the mechanisms underlying countless other model systems. Specifically, we will characterize three complementary components of regulatory element activity: (i) the capacity of regulatory elements to drive expression of a reporter gene, (ii) the effect of each regulatory element on the expression of one or more target genes, and (iii) the contributions of regulatory elements to phenotypic function, namely differentiation. We will accomplish those goals across three specific aims.
In Aim 1, we will quantify the activity of all regulatory elements that have evidence of differential activity between subtypes of mouse CD4 T cells. We will do so using a capture-based high-throughput reporter assay that allows us to assay larger (>500 bp) fragments from specific genomic regions of interest.
In Aim 2, we will quantify the effects of regulatory elements on target genes using a novel strategy that combines high-throughput CRISPR/ Cas9-based epigenome editing screens and targeted high-throughput single-cell RNA-sequencing.
In Aim 3, we will determine which regulatory elements are necessary or sufficient for CD4 T cell differentiation using high-throughput CRISPR/Cas9-based epigenome-editing screens combined differentiation into particular CD4 T cell subtypes.
Each aim will provide functional characterization of all of the regulatory elements implicated in CD4 T cell differentiation. Together, the aims will provide a comprehensive, multi-layered, and systematic understanding of the ways that gene regulatory elements modulate the immune system. The result will be an actionable set of targets for designing strategies to modulate immune system activity for therapeutic benefit. Because the approach is general to any model system, the same strategy can be readily transferred to diverse systems including differentiation and disease models. Therefore, we expect that this project will have both immediate and long-term benefit for determining the ways that regulatory elements contribute to health and disease.

Public Health Relevance

(Relevance) Increases and decreases in the activity of the immune system contribute to myriad diseases including autoimmune disease and cancer. In this project, we will characterize the activity of regulatory elements that contribute to tuning the immune system. In doing so, we will identify novel therapeutic targets for modulating immune system activity in patients.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project with Complex Structure Cooperative Agreement (UM1)
Project #
1UM1HG009428-01
Application #
9247591
Study Section
Special Emphasis Panel (ZHG1)
Program Officer
Pazin, Michael J
Project Start
2017-08-21
Project End
2021-06-30
Budget Start
2017-08-21
Budget End
2018-06-30
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Duke University
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
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Gersbach, Charles A; Barrangou, Rodolphe (2018) Pulling the genome in opposite directions to dissect gene networks. Genome Biol 19:42