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Access Type

Open Access Thesis

Document Type


Degree Program

Molecular & Cellular Biology

Degree Type

Master of Science (M.S.)

Year Degree Awarded


Month Degree Awarded



Background: Infertility has become a growing concern across the world as cases continue to increase each year. Research has now shifted to identifying novel biomarkers to predict male fertility. While mtDNAcn has recently been found to show promising results as potential biomarker, its regulation remains unclear.

Method: Triplex probe-based PCR was used to quantify mtDNA levels, while 850K Array was used to measure methylation levels. A-clustering algorithm followed by generalized estimating equations (GEE) lead to clustering of individual CpG sites, containing a minimum of 2 CpGs within 1000 base pairs of each other. These clusters were used for analysis of the association between mtDNAcn and DNA methylation within sperm. Metascape1 was used to annotate gene ontology terms.

Result: Generalized estimating equation model analysis produced 6,038 FDR significant (q

Conclusion: Thus, we show that sperm mtDNAcn is strongly associated with sperm DNA methylation and the associated implicates mtDNAcn as an influence on infertility.


First Advisor

Richard Pilsner

Second Advisor

Alexander Suvorov

Third Advisor

Kathleen Arcaro

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.

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