Decoding non-random mutational signatures at Cas9 targeted sites. Issue 16 (19th July 2018)

• Record Type: Journal Article
• Authors: Taheri-Ghahfarokhi, Amir; Taylor, Benjamin J M; Nitsch, Roberto; Lundin, Anders; Cavallo, Anna-Lina; Madeyski-Bengtson, Katja; Karlsson, Fredrik; Clausen, Maryam; Hicks, Ryan; Mayr, Lorenz M; Bohlooly-Y, Mohammad; Maresca, Marcello
• Is Part Of: Nucleic acids research. Volume 46:Issue 16(2018)
• Page Start: 8417
• Page End: 8434
• Publication Date: 2018-07-19
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gky653
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: The mutation patterns at Cas9 targeted sites contain unique information regarding the nuclease activity and repair mechanisms in mammalian cells. However, analytical framework for extracting such information are lacking. Here, we present a novel computational platform called Rational InDel Meta-Analysis (RIMA) that enables an in-depth comprehensive analysis of Cas9-induced genetic alterations, especially InDels mutations. RIMA can be used to quantitate the contribution of classical microhomology-mediated end joining (c-MMEJ) pathway in the formation of mutations at Cas9 target sites. We used RIMA to compare mutational signatures at 15 independent Cas9 target sites in human A549 wildtype and A549-POLQ knockout cells to elucidate the role of DNA polymerase θ in c-MMEJ. Moreover, the single nucleotide insertions at the Cas9 target sites represent duplications of preceding nucleotides, suggesting that the flexibility of the Cas9 nuclease domains results in both blunt- and staggered-end cuts. Thymine at the fourth nucleotide before protospacer adjacent motif (PAM) results in a two-fold higher occurrence of single nucleotide InDels compared to guanine at the same position. This study provides a novel approach for the characterization of the Cas9 nucleases with improved accuracy in predicting genome editing outcomes and a potential strategy for homology-independent targeted genomic integration.