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In silico engineering and optimization of Transcription Activator-Like Effectors and their derivatives for improved DNA binding predictions.

Transcription Activator-Like Effectors (TALEs) can be used as adaptable DNAbinding
modules to create site-specific chimeric nucleases or synthetic
transcriptional regulators. The central repeat domain mediates specific DNA binding
via hypervariable repeat di-residues (RVDs). This DNA-Binding Domain can be
engineered to bind preferentially to any user-selected DNA sequence if engineered
appropriately. Therefore, TALEs and their derivatives have become indispensable
molecular tools in site-specific manipulation of genes and genomes.
This thesis revolves around two problems: in silico design and improved binding
site prediction of TALEs. In the first part, a study is shown where TALEs are
successfully designed in silico and validated in laboratory to yield the anticipated
effects on selected genes. Software is developed to accompany the process of
designing and prediction of binding sites. I expanded the functionality of the
software to be used as a more generic set of tools for the design, target and offtarget
searching.
Part two contributes a method and associated toolkit developed to allow users to
design in silico optimized synthetic TALEs with user-defined specificities for various
experimental purposes. This method is based on a mutual relationship of three consecutive tandem repeats in the DNA-binding domain. This approach revealed
positional and compositional bias behind the binding of TALEs to DNA.
In conclusion, I developed methods, approaches, and software to enhance the
functionality of synthetic TALEs, which should improve understanding of TALEs
biology and will further advance genome-engineering applications in various
organisms and cell types.

Identiferoai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/583278
Date12 1900
CreatorsPiatek, Marek J.
ContributorsBajic, Vladimir B., Biological and Environmental Sciences and Engineering (BESE) Division, Mahfouz, Magdy M., Gojobori, Takashi, Gao, Xin, Mijakovic, Ivan
Source SetsKing Abdullah University of Science and Technology
LanguageEnglish
Detected LanguageEnglish
TypeDissertation
Rights2016-12-06, At the time of archiving, the student author of this dissertation opted to temporarily restrict access to it. The full text of this dissertation became available to the public after the expiration of the embargo on 2016-12-06.

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