RNA-RNA interactions are important components of gene regulatory networks. There is yet no technology to map the entire RNA-RNA interactome in cells or tissues. As a result, although personal genomes are being sequenced, our capabilities to interpret genomic functions and to predict phenotypic variation from genomic sequence remain limited. We desperately need high-throughput technologies to map the molecular networks in any person or tissue. Here, we propose to develop an extremely high-throughput technology to map RNA-RNA interactomes in vivo. The central idea is to convert molecular interactions into DNA sequences and then read out the interactions by DNA sequencing. The proposed RNA Hi-C technology is capable of mapping all protein- assisted RNA-RNA interactions in one assay. This new technology is expected to be generally applicable to analyze any cell types and tissues. We will use cell fate decisions in pre-implantation development as a driven biological question. The new technology will be applied to test two competing hypotheses. We expect the results to clarify a physical principle behind the earliest cell fate decision in mammals, and therefore offer unprecedented information regarding infertility, miscarriage, and birth defects.

Public Health Relevance

We propose to develop an extremely high-throughput technology to map RNA-RNA interactomes in vivo. This technology is capable of mapping all protein-assisted RNA-RNA interactions in one assay. The results will clarify a physical principle behind the earliest cell fate decision in mammals, and therefore offer unprecedented information regarding infertility, miscarriage, and birth defects.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
NIH Director’s Pioneer Award (NDPA) (DP1)
Project #
5DP1HD087990-04
Application #
9531911
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ravindranath, Neelakanta
Project Start
2015-09-30
Project End
2020-07-31
Budget Start
2018-08-01
Budget End
2019-07-31
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Engineering (All Types)
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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