The regulation of eukaryotic genes involves many hundreds of proteins. How they work together at the many thousands of genes that comprise a genome is not known. In order to obtain a comprehensive understanding of how all genes are regulated, we need to know the precise spatial organization, structure, and occupancy levels of all involved proteins. We have developed a genome-wide assay, called ChIP-exo, to measure these aspects of genome regulation, and now propose to develop a higher-throughput version of the assay, and apply it to the mapping of hundreds of genome-binding proteins (aim 1). From this we expect to gain a comprehensive understanding of the structural organization of chromatin and its regulation. The structural information about genomic binding events is woven into the complex patterning of exonuclease stop sites that probe specific DNA contact points. These patterns and their relationships with patterns generated by other proteins often require substantial bioinformatic analyses, which is often out of reach of typical wet-bench scientists. The root of the problem lies at steep learning curve for command-line operations, scripting and proper script application, and keeping data analyses organized. This creates an inherently slow trial-and-error process in biological discovery. Therefore, to alleviate the bottleneck in distillig ChIP-exo data into biological discovery which is so essential to aim 1, we will develop a dedicated and specialized bioinformatic pipeline designed to conduct rapid, easy, and efficient ChIP-exo analyses. Relationships among binding events will provide new insights into transcription complex assembly and regulation. The goal of aim 1 will be to collect ChIP-exo data on 200 yeast potential genome-binding proteins, and their interacting partners or complexes, under multiple cellular states (growth conditions, cell cycle). Tangible outcomes include a precise near-bp map of genomic locations and sub-complex organization, with minimal false positives and negatives. We envision achieving a snapshot of the detailed spatial organization genome- binding proteins at promoters. The goal of aim 2 will be to create a user-friendly, quickly-navigable, platform to execute scripts on ChIP-exo and related data, using our established pipeline. Public use utility of the ChIP-exo datasets will be enhanced with a dedicated platform.

Public Health Relevance

Mis-expression of genes leads to disease states that may be correctable if we have knowledge of the inner workings of gene regulatory machinery. For this, we need to understand the precise organization of the machinery at all genes across a genome. This work aims to precisely define the genome-wide organization of DNA binding proteins that associate with the genome.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
3R01ES013768-12S2
Application #
9999164
Study Section
Molecular Genetics B Study Section (MGB)
Program Officer
Tyson, Frederick L
Project Start
2007-01-01
Project End
2020-02-29
Budget Start
2019-08-15
Budget End
2020-02-29
Support Year
12
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Pennsylvania State University
Department
Biochemistry
Type
Schools of Arts and Sciences
DUNS #
003403953
City
University Park
State
PA
Country
United States
Zip Code
16802
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Yamada, Naomi; Lai, William K M; Farrell, Nina et al. (2018) Characterizing protein-DNA binding event subtypes in ChIP-exo data. Bioinformatics :
Rossi, Matthew J; Lai, William K M; Pugh, B Franklin (2018) Simplified ChIP-exo assays. Nat Commun 9:2842
Niu, Ben; Coslo, Denise M; Bataille, Alain R et al. (2018) In vivo genome-wide binding interactions of mouse and human constitutive androstane receptors reveal novel gene targets. Nucleic Acids Res 46:8385-8403
Rossi, Matthew J; Lai, William K M; Pugh, B Franklin (2018) Genome-wide determinants of sequence-specific DNA binding of general regulatory factors. Genome Res 28:497-508
Miller, Jason E; Zhang, Liye; Jiang, Haoyang et al. (2018) Genome-Wide Mapping of Decay Factor-mRNA Interactions in Yeast Identifies Nutrient-Responsive Transcripts as Targets of the Deadenylase Ccr4. G3 (Bethesda) 8:315-330
Mahony, Shaun; Pugh, B Franklin (2015) Protein-DNA binding in high-resolution. Crit Rev Biochem Mol Biol 50:269-83
Chang, Gue Su; Chen, Xiangyun Amy; Park, Bongsoo et al. (2014) A comprehensive and high-resolution genome-wide response of p53 to stress. Cell Rep 8:514-27
Nakahashi, Hirotaka; Kieffer Kwon, Kyong-Rim; Resch, Wolfgang et al. (2013) A genome-wide map of CTCF multivalency redefines the CTCF code. Cell Rep 3:1678-1689
Li, Jian; Liu, Yingyun; Rhee, Ho Sung et al. (2013) Kinetic competition between elongation rate and binding of NELF controls promoter-proximal pausing. Mol Cell 50:711-22

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