Genome editing based medicines are a new therapeutic modality being developed. They show great promise for a spectrum of genetic diseases lacking conventional treatment strategies. A major obstacle that prevents such therapies to reach the clinic is their safety. We focus on the development and establishment of newer approaches to capture and understand these safety risks during the drug development stage, to build safe drugs that would reach the clinic. To capture potential off-target double-stranded breaks generated by CRISPR, we worked on optimizing an next generation sequencing based method, INDUCE-seq. To capture larger scale on and off-target genetic changes induced by CRISPR editing, which are difficult to capture by next-generation short-read sequencing, we employed a novel imaging-based long-read genomic technology, Optical Genome Mapping (OGM). It enabled the detection of on-target integration with allelic frequency as low as 0.001%, uncovered previously unknown on-target allelic integration heterogeneity and found several off-target structural variants genome-wide, thereby proving that OGM is highly sensitive and can detect rare and complex DNA structural variants (SV) which would have been missed otherwise. Finally, to further characterize some of the identified structural variants in-depth, we employed two new approaches, Cas9 enrichment and X-drop enrichment, to selectively enrich the genomic region of interest, followed by reading it via long-read nanopore sequencing, to get a direct readout of the small genomic region of interest, without any interpretation errors that may happen by piecing together short reads. We demonstrate the successful performance of Cas9 enriched nanopore approach. And we show our progress in evaluating the X-drop approach.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-505376 |
| Date | January 2023 |
| Creators | Sheikh Farid, Noorul Shaheen |
| Publisher | Uppsala universitet, Institutionen för biologisk grundutbildning, AstraZeneca |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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