Transcriptomic Changes in Fontan Surgery Sheep Models and a Novel miRNA-mRNA Interaction Analysis Public

Abstract

Patients with congenital heart defects require a series of three surgeries known as Fontan surgery. While it is lifesaving, both cardiac and system complications can arise because multiple open-heart surgeries are needed. The underlying mechanisms and causes of these complications are not understood.

Extracellular vesicles are miniscule vesicles secreted by cells, and they play an important role in cell-to-cell communication. Circulating RNA in blood and in extracellular vesicles have been shown to have biological significance, such as mediating biological processes. Transcriptomics, or the study of RNA molecules, can reveal the causative role of RNA molecules and identify potential biomarkers for these complications.

To further understand single ventricular flow, researchers at Nationwide Children’s Hospital have been working to establish a sheep model of Fontan palliation, as the sheep’s cardiovascular system strongly mimics a human’s cardiovascular system. Here, they have successfully established a single ventricular flow in a pair of cloned sheep, Justin and Julian. Justin is the sheep that underwent Fontan surgery, and Julian serves as a control model.

To investigate the impact of Fontan surgery, this thesis will investigate the transcriptomic changes in serum and extracellular vesicles within Justin and Julian. Serum samples have been taken from preoperative and postoperative time points. From these serum samples, extracellular vesicles were isolated. Both serum and extracellular vesicle samples underwent RNA sequencing.

Three bioinformatic pipelines have been established that analyze mRNA profiles and miRNA profiles. The first mRNA pipeline analyzes clustering and differential gene expression within RNA data. The second miRNA pipeline analyzes clustering and differential gene expression within miRNA data. The third miRNA-mRNA correlation analysis uses a Pearson correlation to correlate miRNA and mRNA expression levels.

The mRNA bioinformatic pipeline uncovered transcriptomic changes in response to Fontan surgery. The miRNA bioinformatic pipeline demonstrated the potential of integrating predicted miRNA data for new clustering patterns. The miRNA-mRNA pipeline proposes a novel method to discover miRNA and mRNA interactions within serum. MiRNAs play an inhibitory role in mRNA expression. The miRNA-mRNA pipeline offers a high-throughput way to investigate the mRNA targets of miRNAs in any biological system, with an applicability towards extracellular vesicles.

Table of Contents

1. Abstract

2. Introduction

a. Extracellular Vesicles and Serum

b. Computational Theory of miRNA-mRNA Correlation Analysis

c. Sheep Models of Fontan Surgery

3. Materials And Methods

a. Experimental Procedures

i. Study Design

ii. Serum Total RNA Extraction

iii. EV Isolation and Serum Extraction

b. Computational Procedures

i. mRNA Workflow

1. mRNA Data Alignment using STAR

2. mRNA Principal Component Analysis

3. mRNA Heat Maps

4. mRNA Differential Gene Expression Analysis using limma/voom with dream

ii. miRNA Workflow

1. miRNA Data Alignment and Novel miRNA Prediction using miRDeep2

2. Principal Component Analysis with Mature and Predicted miRNA

3. miRNA Heat Maps

4. miRNA Differential Gene Expression Analysis using limma/voom along with dream

iii. miRNA-mRNA Workflow

1. miRNA-mRNA Correlation Analysis

4. Results and Discussion

a. mRNA Workflow Results

i. Unsupervised Analysis: Principal Component Analysis and Heat Maps

ii. Supervised Analysis: Differential Gene Expression Analysis

b. miRNA Workflow Results

i. Unsupervised Analysis: Principal Component Analysis and Heat Maps

ii. Supervised Analysis: Differential Gene Expression Analysis

c. miRNA-mRNA Correlation Workflow Results

5. Future Directions: miRNA/mRNA Correlation Analysis

About this Honors Thesis

Rights statement

• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Emory College
Department	Quantitative Science
Degree	B.S.
Submission	Honors Thesis
Language	English
Research Field	Biology, Biostatistics Computer Science Biology, Bioinformatics
Mot-clé	Fontan Surgery Transcriptomics Sheep Models Bioinformatics
Committee Chair / Thesis Advisor	Michael Davis, Emory University Kevin McAlister, Emory University
Committee Members	Adam Glynn, Emory University

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