The development of innovative high throughput genome-wide methodologies and technologies such as RNA-Seq and ChIP-Seq have made it possible to identify and analyze all coding and non-coding RNAs as well as map epigenetic marks and transcription factor binding sites. However, RNA-Seq is typically performed using total RNA isolated from cells or tissues and such analysis will generate signatures of steady-state levels of RNA but will not inform on whether particular gene expression alterations are due to altered transcription and/or altered RNA stability. Recently, a number of different approaches have been developed to estimate nascent transcription of genomic sequences such as GRO-Seq, NET-Seq and by metabolic labeling and isolated of nascent RNA. We will in this R01 application further develop and validate two approaches that we believe add important new capabilities to existing techniques for the comprehensive and high throughput exploration of gene expression signatures in human cells. BruChase-Seq is based on bromouridine pulse-chase labeling coupled to deep sequencing directly measuring the kinetics of synthesis and degradation of all primary and mature mRNAs and non-coding RNAs as well as determines splicing kinetics of all intron sequences. BrUV-Seq introduces random transcription-blocking lesions by UV light prior to BrU-labeling, identifying transcription start sites (TSS), putative enhancer elements and by stabilizing transcripts that might be labile if completely transcribed allowing their more sensitive detection. Each of these advances has the potential to greatly expand current genomic annotations by assigning additional functional assessments to known genes, showing how the parts of genes act independently, and identifying cryptic intergenic elements.

Public Health Relevance

We have initiated the development of two new approaches, named BruChase-Seq and BrUV-Seq, for the comprehensively analysis of gene expression signatures. In this R01 proposal, we will attempt to validate these approaches as well as determining their predictive power of determining RNA stability and identifying specific transcription regulatory elements.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Research Project (R01)
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Special Emphasis Panel (ZHG1-HGR-M (J2))
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Pazin, Michael J
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University of Michigan Ann Arbor
Schools of Medicine
Ann Arbor
United States
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