Several tools were developed to help researchers facilitate clinical translation of the use of engineered nucleases towards their disease gene of interest. Two major issues addressed were the inability to accurately predict nuclease off-target sites by user-friendly \textit{in silico} methods and the lack of a high-throughput, sensitive measurement of gene editing activity at endogenous loci. These objectives were accomplished by the completion of the following specific aims. An online search interface to allow exhaustive searching of a genome for potential nuclease off-target sites was implemented. Previously discovered off-target sites were collated and ranking algorithms developed that preferentially score validated off-target sites higher than other predictions. HEK-293T cells transfected with newly developed TALENs and ZFNs targeting the beta-globin gene were analyzed at the off-target sites predicted by the tool. Many samples of genomic DNA from cells treated with different ZFNs and TALENs were analyzed for off-target effects to generate a greatly expanded training set of bona fide off-target sites. Modifications to the off-target prediction algorithm parameters were evaluated for improvement through Precision-Recall analysis and several other metrics. An analysis pipeline was developed to process SMRT reads to simultaneously measure the rates of different DNA repair mechanisms by directly examining the DNA sequences. K562 cells were transfected with different types of nucleases and donor repair templates in order to optimize conditions for repairing the beta-globin gene. This work will have significant impact on future studies as the methods developed herein allow other laboratories to optimize nuclease-based therapies for single gene disorders.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54875 |
| Date | 27 May 2016 |
| Creators | Fine, Eli Jacob |
| Contributors | Bao, Gang |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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