Date of Award

5-1-2022

Language

English

Document Type

Master's Thesis

Degree Name

Master of Science (MS)

College/School/Department

Department of Biological Sciences

Content Description

1 online resource (v, 37 pages) : illustrations (some color)

Dissertation/Thesis Chair

Bijan Dey

Committee Members

Melinda Larsen, Andy Berglund

Keywords

Bioinformatics, Differential Gene Expression, Duchenne Muscular Dystrophy, Gene Ontology Anal, Inflamation, Meta-Analysis, Duchenne muscular dystrophy, Gene expression

Subject Categories

Bioinformatics | Biology

Abstract

Duchenne Muscular Dystrophy (DMD) is a muscle-wasting disease that primarily affects boys characterized by loss of the dystrophin gene. Dystrophin is necessary for proper muscle growth, muscles that lack dystrophin are more prone to damage. In this thesis, a bioinformatics approach was used to evaluate the transcriptomic profiles of two datasets obtained from DMD patients. The two datasets were analyzed separately, as well as combined to identify differentially expressed genes. The first dataset, GSE6011, has 23 DMD samples and 14 controls. The second, GSE38417, consists of 16 DMD samples and six controls. Differential gene expression of both datasets combined found that GSE6011 had 1586 significant genes and GSE38417 had 7107; overall meta-analysis identified 3321 significant genes. Gene Ontology analysis showed enrichment of genes related to inflammation. Differential gene analysis of the datasets separately identified upregulation of ECM components and the developmental isoforms of heavy myosin heavy chains. The upregulation of MYH8 and downregulation of dystrophin are both considered hallmarks of Duchenne muscular dystrophy and were identified in my analysis. Gene ontology analysis also demonstrated an upregulation of immune response-related gene sets. In conclusion, my analysis showed that many genes are being differentially expressed in Duchenne muscular dystrophy, particularly those related to immune system response.

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