The human genome encodes tens of thousands of circRNAs, of which the translation is essential for regulating important biological functions, such as cell proliferation, differentiation, and migration. Interference with circRNA translation can lead to tumorigenesis and metastasis of cancers. It is unclear, however, how disrupting circRNA translation can cause the diseases. Identifying the regulatory components of circRNA translation can provide valuable clinical insights. However, current technologies cannot distinguish circRNAs from linear RNAs efficiently, such that the mechanism and molecular components regulating circRNA translation remain unclear. Thus, it is imperative to develop a technology that can identify the components regulating circRNA translation with higher sensitivity and specificity. I have developed a high-throughput reporter screening assay that can systematically screen and identify the RNA sequences that initiate circRNA translation specifically. Utilizing the technology, I discovered two groups of the RNA sequences that specifically drive translation on either circRNA or linear RNA, respectively, indicating that the regulatory components between linear RNA and circRNA translation are different (Chen et al., resubmitted to Science). In this proposed research, I will further adapt and apply this novel technology to (i) identify and characterize the sequence and protein components that regulate circRNA translation specifically, (ii) identify the association between genetic variation, circRNA translation, and disease, (iii) characterize circRNA translation in a tissue-dependent manner systematically, and (iv) build a non-integrative and stable gene expression platform with tunable expression level and tissue specificity. This proposed research will build the foundation of my future research as an independent researcher to investigate the regulation and the coordination between different translation machinery (cap-dependent vs. independent translation) among different RNA species (linear vs. circular RNAs). This work will be performed under the mentorship of Dr. Howard Chang at the Stanford University School of Medicine, an expert in technology development and RNA biology who has highly-successful track records of placing postdoctoral fellows into independent academic positions at leading institutions. Further training in scientific and professional skills will be achieved by utilizing the resources available through the Stanford University School of Medicine and the Office of Postdoctoral Affairs, which provide an outstanding intellectually- stimulating environment with all facilities and resources necessary for success. All proposed training will complement my previous training in RNA biology, technology development, and computer programming and facilitate my transition to an independent researcher, investigating the functions, regulations and clinical implications of circRNA.

Public Health Relevance

The human genome encodes tens of thousands of circular RNAs (circRNAs), of which the translation is essential for regulating important biological functions, such as cell proliferation, differentiation, and migration. Current technologies cannot distinguish circRNAs from linear RNAs efficiently, such that the mechanism and molecular components regulating circRNA translation remain unclear. The proposed research will utilize my newly developed technology, which can identify the RNA sequences that initiate circRNA translation specifically, to (i) characterize the sequence and protein components regulating circRNA translation, (ii) elucidate the association between genetic variation, circRNA translation and disease, and (iii) build a gene expression platform with tunable expression level and tissue specificity.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Career Transition Award (K99)
Project #
1K99HG011475-01
Application #
10104839
Study Section
National Human Genome Research Institute Initial Review Group (GNOM)
Program Officer
Sen, Shurjo Kumar
Project Start
2021-02-15
Project End
2023-01-31
Budget Start
2021-02-15
Budget End
2022-01-31
Support Year
1
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305