Deciphering how complex programs of gene expression and regulation contribute to human disease is one of the major challenges facing the field of genomics. Over the past decade, a wealth of new high-throughput genomics tools have revolutionized how we identify active genomic regions and appear poised to make great strides in understanding the mechanisms of disease. Yet the application of most of these technologies has been limited to established cell lines. Currently, approaches being developed to comprehensively map functional elements across the genome involve combining data from several different genome-wide experimental assays, making them expensive and impractical to use in clinical isolates of limited quantity or even to analyze new cell lines. Compounding these technical difficulties, gene expression is a complex and highly tissue dependent biological process, and many important applications will require the direct interrogation of clinical isolates or other similarly limited sources of sample. Thus, efficient new tools that map the repertoire of functional elements across the genome are likely to transform the biomedical and clinical sciences. We propose to develop Chromatin Run-On and Sequencing (ChRO-seq) and a suite of computational tools for mapping transcription directly in limited tissue samples. Our approach uses a single genome-wide molecular assay to efficiently identify the location of promoters and enhancers, transcription factor binding sites, gene and lincRNA boundaries, transcription levels, and impute certain histone modifications. Preliminary ChRO-seq data reveals patterns of transcription that are virtually identical to those using Precision Run on and Sequencing in cultured cells, but can easily be applied in solid tissue samples. We applied our preliminary ChRO-seq technology to several primary tumors, revealing new insights into how transcriptional regulation underlies cancer development and progression, and providing a key proof-of-concept motivating further technology development. We anticipate that ChRO-seq and the computational methods proposed will enable the efficient discovery of functional elements in virtually any cell sample. In addition, ChRO-seq has the unique advantage that it can be applied in limited tissue samples and clinical isolates even after the degradation of mRNA.

Public Health Relevance

We propose to develop a suite of molecular and computational technologies that allow researchers to directly measure transcriptional regulation of genes, enhancers, and lincRNAs in limited clinical isolates. These technologies are anticipated to have a major impact on the biomedical sciences, enabling the genome-wide interrogation of transcription during virtually any disease process for the first time.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
1R01HG009309-01
Application #
9218028
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Pazin, Michael J
Project Start
2017-02-01
Project End
2022-01-31
Budget Start
2017-02-01
Budget End
2018-01-31
Support Year
1
Fiscal Year
2017
Total Cost
$341,325
Indirect Cost
$116,325
Name
Cornell University
Department
Veterinary Sciences
Type
Schools of Veterinary Medicine
DUNS #
872612445
City
Ithaca
State
NY
Country
United States
Zip Code
14850
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Danko, Charles G; Choate, Lauren A; Marks, Brooke A et al. (2018) Dynamic evolution of regulatory element ensembles in primate CD4+ T cells. Nat Ecol Evol 2:537-548
Horibata, Sachi; Rice, Edward J; Mukai, Chinatsu et al. (2018) ER-positive breast cancer cells are poised for RET-mediated endocrine resistance. PLoS One 13:e0194023
Chu, Tinyi; Wang, Zhong; Chou, Shao-Pei et al. (2018) Discovering Transcriptional Regulatory Elements From Run-On and Sequencing Data Using the Web-Based dREG Gateway. Curr Protoc Bioinformatics :e70
Birkenheuer, Claire H; Danko, Charles G; Baines, Joel D (2018) Herpes Simplex Virus 1 Dramatically Alters Loading and Positioning of RNA Polymerase II on Host Genes Early in Infection. J Virol :
Horibata, Sachi; Rice, Edward J; Zheng, Hui et al. (2018) A bi-stable feedback loop between GDNF, EGR1, and ER? contribute to endocrine resistant breast cancer. PLoS One 13:e0194522
Dukler, Noah; Booth, Gregory T; Huang, Yi-Fei et al. (2017) Nascent RNA sequencing reveals a dynamic global transcriptional response at genes and enhancers to the natural medicinal compound celastrol. Genome Res 27:1816-1829