2017 — 2021 |
Lin, Lan |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Regulation and Function of Rna Editing in Human Transcriptomes @ University of California Los Angeles
PROJECT SUMMARY The central objective of this research is to comprehensively investigate the variation, regulation, and functional consequences of RNA editing in human transcriptomes. RNA editing has emerged as an important and widespread mechanism for generating transcriptome diversity in eukaryotic cells. Aberrant RNA editing has been implicated in a variety of diseases including neurological diseases and cancer. The most abundant type of RNA editing is the A-to-I RNA editing (the deamination of adenosine to inosine) mediated by the ADAR family of RNA editing enzymes. High-throughput RNA sequencing studies have revealed millions of A-to-I RNA editing sites in the human transcriptome. Despite the explosion in the number of identified RNA editing sites, there remain significant knowledge gaps about the regulation and function of RNA editing. The landscapes of RNA editing can be dynamically regulated among different tissues or cell types or in response to stimuli, as well as become dysregulated in diseases. While previous studies on the regulation of RNA editing mainly focused on the ADAR enzymes, the roles of other trans-acting regulators such as RNA binding proteins have largely been unexplored. Moreover, the functions of most A-to-I RNA editing events are currently unknown. Previous functional studies have investigated RNA editing events in coding regions of selected genes. Recent data indicate that the vast majority of A-to-I RNA editing events occur in non-coding regions, such as 5'-UTR, intron, and 3'-UTR, suggesting widespread regulatory effects of editing on the RNA. Indeed, RNA editing may influence a variety of regulatory processes at the post-transcriptional level, such as the regulation of RNA splicing, localization, stability, and translational efficiency. Of note, work from us and others has shown that RNA editing can create or disrupt functional microRNA target sites in the 3'-UTR, suggesting that RNA editing can directly regulate mRNA translation or stability. In three complementary and tightly integrated research aims, we will investigate the regulation of RNA editing by trans-acting regulators and environmental stimuli (Aim 1), the genetic variation and phenotypic association of RNA editing in human populations (Aim 2), and the functional consequences of RNA editing on mRNA translation and stability (Aim 3). Collectively, the proposed studies will provide significant insights into the regulation, genetic variation, and function of RNA editing. Additionally, through this project we will develop innovative approaches for quantitative analyses of RNA editing using a variety of transcriptome sequencing technologies. We anticipate that these approaches will be broadly useful for studying RNA editing as well as other types of RNA variants and modifications in eukaryotic transcriptomes.
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0.94 |
2019 — 2022 |
Lin, Lan |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Framework: Software: Collaborative Research: Cyberwater-An Open and Sustainable Framework For Diverse Data and Model Integration With Provenance and Access to Hpc
This project addresses a high priority need for water research communities: interoperability among a wide variety of data sources and models, and integration of different computational models into water research communities. The project will develop an open and sustainable software framework enabling integration of hydrologic data and models for interdisciplinary teamwork and discovery. The models and datasets cover fields such as hydrology, biology, environmental engineering and climate. The project also addresses one of the key issues for extreme-scale computing: scalable file systems. The collaboration draws upon computing, modeling, and hydrology expertise at six institutions: University of Pittsburgh, University of Iowa, Ball State University, North Carolina State University, Indiana University, and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI).
The project develops CyberWater, a community-driven software framework that integrates a wide range of models and datasets across disparate temporal and spatial scales. The CyberWater framework allows scientists to bypass challenges associated with model and dataset complexity. The project designs a model agent tool enabling users to generate model agents for common model types without coding, and integrates multiple existing software codes/elements that provide for broad-scale use. To develop such a diverse modeling framework, the project brings together hydrologists, climate experts, meteorologists, computer scientists and cyberinfrastructure experts. The project builds upon an existing prototype developed by the lead investigator; basic elements for the system were developed, consisting of plugged-in models and data sources with corresponding agents and a workflow engine allowing user workflow control. The prototype was successfully demonstrated for two models, making use of datasets plugged in from NASA, USGS and CUAHSI. For the current project, new models and datasets are added to the framework; the ability to use high performance computing resources is also incorporated. The team will use the CUAHSI HydroShare System to distribute CyberWater software and its associate model agents, including instructions on how to establish a local CyberWater environment, models and model agents. The project will enable substantial scientific advances for water related issues, and the solution can be applied to other research disciplines.
This award by the Office of Advanced Cyberinfrastructure is jointly supported by the NSF Directorate for Geosciences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.979 |