| Title |
Profiling the specificity of the tnpb - transposon associated nuclease / |
| Translation of Title |
Su transpozonais susijusios nukleazės TnpB specifiškumo nustatymas. |
| Authors |
Krikščikaitė, Lina |
| Full Text |
|
| Pages |
60 |
| Keywords [eng] |
TnpB, CRISPR-Cas, gene editing, specificity, nuclease, NucleaSeq, cleavage, RNP, gRNA, reRNA |
| Abstract [eng] |
Gene editing gained significant importance due to its potential to revolutionize fields of biomedicine, biochemistry, agriculture and address many problems. By harnessing gene editing technologies, scientists can quickly and easily alter an organism’s DNA. Despite its indisputable importance, gene editing comes with several issues including delivery of the gene editor to the cell, safety and applicability. To address these problems, scientists work on improving current gene editors or looking for new ones. This study focuses on TnpB – a transposon associated nuclease that is two times smaller than class leading gene editor Cas9 and therefore easier to deliver to the target cells. Though TnpB has been known for a while, its potential as a gene editor was only recently unravelled. That means that some of its features including specificity is unknown. Here, the main research goal to determine TnpB’s specificity profile with next-generation biochemistry is outlined and divided into smaller steps. Overall, the main method used in this study is NucleaSeq - a platform that combines DNA digestion by a nuclease with deep sequencing. NucleaSeq reveals the cleavage kinetics of a nuclease and benchmarks its specificity by quantifying cleavage rates across DNA target sequences including thousands of off-targets that do not fully match the nuclease’s RNA guide. It also reveals cleavage sites within target sequences and what kind of ends (sticky or blunt) does nuclease generate after the cleavage. In conclusion, by adopting NucleaSeq strategy the main features of TnpB and how does it compare to other well-studied gene editing tools should be determined. Obtained data could help to establish new gene editing strategies based on TnpB. |
| Dissertation Institution |
Vilniaus universitetas. |
| Type |
Master thesis |
| Language |
English |
| Publication date |
2023 |
