Abstract:
The characterization of genomic complexity is essential for understanding diverse biological processes and advancing medical applications. This dissertation investigates the potential of long-read sequencing to overcome challenges in pathogen detection, epigenomic stability, and genomic disorder diagnosis. For pathogen detection, we developed an open-source, cost-effective platform that combines Nanopore sequencing with automated high-throughput workflows for COVID-19 diagnosis and variant monitoring. Our investigation in genome editing highlights how Cas9-induced DNA double-strand breaks can affect DNA methylation patterns, underscoring the importance of considering epigenetic alterations in genome-editing applications. Furthermore, we present NanoRanger, a novel approach for rapid, single base-pair resolution of complex genomic disorders. Collectively, these contributions illustrate the power of long-read sequencing technologies in addressing genomic challenges, advancing diagnostic tools, and providing insights into genomic regulation and instability in disease contexts.

Bio:
Yingzi Zhang is a Ph.D. candidate in Bioscience at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Mo Li. Her research leverages long-read sequencing technologies to tackle key challenges in understanding genomic complexity, including pathogen detection, epigenetic stability, and the diagnosis of genomic disorders. Yingzi holds a Master’s degree in Biochemistry and Molecular Biology from the University of the Chinese Academy of Sciences and a dual Master’s degree in Omics from the University of Southern Denmark. She earned her Bachelor’s degree in Medicine from Wuhan University.