Clustered regularly interspaced short palindromic repeats (CRISPR) technologies allow for facile genomic modification in a site-specific manner. A key step in this process is the in-silico design of single guide RNAs (sgRNAs) to efficiently and specifically target a site of interest. To this end, it is necessary to enumerate all potential off-target sites within a given genome that could be inadvertently altered by nuclease-mediated cleavage. Off-target sites are quasi-complementary regions of the genome in which the specified sgRNA can bind, even without a perfect complementary nucleotides sequence. This problem is known as, off-target sites enumeration, and became common after discovery of CRISPR technology. To solve this problem, many in-silico solutions were proposed in the last years but, currently available software for this task are limited by computational efficiency, variant support, genetic annotation, assessment of the functional impact of potential off-target effects at population and individual level, and a user-friendly graphical interface designed to be usable by non-informatician without any programming knowledge. This thesis addresses all these topics by proposing two software to directly answer the off-target enumeration problem and perform all the related analysis. In details, the thesis proposes CRISPRitz, a tool designed and developed to compute fast and exhaustive searches on reference and alternative genome to enumerate all the possible off-target for a user-defined set of sgRNAs with specific thresholds of mismatches (non-complementary bps in RNA-DNA binding) and bulges (bubbles that alters the physical structure of RNA and DNA limiting the binding activity). The thesis also proposes CRISPRme, a tool developed starting from CRISPRitz, which answers the requests of professionals and technicians to implement a comprehensive and easy to use interface to perform off-target enumeration, analysis and assessment, with graphical reports, a graphical interface and the capability of performing real-time query on the resulting data to extract desired targets, with a focus on individual and personalized genome analysis.
|Titolo:||Personal genome editing algorithms to identify increased variant-induced off-target potential|
CANCELLIERI, SAMUELE [Writing – Original Draft Preparation] (Corresponding)
|Data di pubblicazione:||Being printed|
|Appare nelle tipologie:||07.13 Doctoral Thesis|