# Core C:  Genomics Core

> **NIH NIH U19** · UNIVERSITY OF WYOMING · 2021 · $185,477

## Abstract

ABSTRACT 
The Genomics Core of the U19 will provide state-of-the-art transcriptomics, small transcriptomics and exosome 
transcriptomics analysis support for organ and cell systems investigated in the three projects: brain (Project 1); 
heart (Project 2); and liver and skeletal muscle (Project 3). All methodologies and analysis tools proposed for 
the Core are routinely used and well-established. Specifically, the Genomics Core will provide the following 
analyses: 
RNA Analysis: Transcriptomic studies and analyses of coding RNAs and long noncoding RNAs (lncRNA) will 
be performed on tissues and cells specific to each project. 
microRNA Analysis: microRNAs (miRNAs) and other small regulatory RNAs will be isolated from tissues and 
cells from the three projects. In addition, exosome analysis will be used to determine whether circulating 
exosome microRNAs (miRNAs) correlate with changes observed in target tissues and cells in the three 
Projects. 
The Genomics Core will also provide integrated analysis of results to establish the role of transcript variation, 
including coding and non-coding RNAs, in normal aging (normal life course, NLC), aging in intrauterine growth 
restricted offspring (IUGR) and offspring of maternal obesity during pregnancy (MO) in baboon tissues or cells 
for each Project, as well as for tissues and cells in corticol replacement intervention (CRI) baboons. The Core 
will also assist the Projects in identifying coordinated molecular networks responsive to aging in these four 
animal cohorts, and identify central hubs regulating these networks. Network tools will be used to integrate 
multiple datasets (e.g., miRNA and mRNA) into high-dimensional networks as a first step to develop a systems 
analysis of the aging nonhuman primate (NHP). 
All three projects will use the services of the Genomics Core. Our synergistic approach analyzing samples 
using the same method for all three projects allows multiplexing of samples for analysis, minimizing reagent 
costs and reducing analysis artifacts. In addition, this approach allows for integration of “omics” data for the all 
tissues analyzed, which will provide a first look at the “systems” response to aging in the five baboon cohorts.

## Key facts

- **NIH application ID:** 10201484
- **Project number:** 5U19AG057758-04
- **Recipient organization:** UNIVERSITY OF WYOMING
- **Principal Investigator:** Laura A Cox
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $185,477
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10201484

## Citation

> US National Institutes of Health, RePORTER application 10201484, Core C:  Genomics Core (5U19AG057758-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10201484. Licensed CC0.

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