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      In vivo genome editing using Staphylococcus aureus Cas9

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          Abstract

          The RNA-guided endonuclease Cas9 has emerged as a versatile genome-editing platform. However, the size of the commonly used Cas9 from Streptococcus pyogenes (SpCas9) limits its utility for basic research and therapeutic applications that employ the highly versatile adeno-associated virus (AAV) delivery vehicle. Here, we characterize six smaller Cas9 orthologs and show that Cas9 from Staphylococcus aureus (SaCas9) can edit the genome with efficiencies similar to those of SpCas9, while being >1kb shorter. We packaged SaCas9 and its sgRNA expression cassette into a single AAV vector and targeted the cholesterol regulatory gene Pcsk9 in the mouse liver. Within one week of injection, we observed >40% gene modification, accompanied by significant reductions in serum Pcsk9 and total cholesterol levels. We further demonstrate the power of using BLESS to assess the genome-wide targeting specificity of SaCas9 and SpCas9, and show that SaCas9 can mediate genome editing in vivo with high specificity.

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          Most cited references20

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          Identifying ChIP-seq enrichment using MACS.

          Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.
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            Clustered regularly interspaced short palindrome repeats (CRISPRs) have spacers of extrachromosomal origin.

            Numerous prokaryote genomes contain structures known as clustered regularly interspaced short palindromic repeats (CRISPRs), composed of 25-50 bp repeats separated by unique sequence spacers of similar length. CRISPR structures are found in the vicinity of four genes named cas1 to cas4. In silico analysis revealed another cluster of three genes associated with CRISPR structures in many bacterial species, named here as cas1B, cas5 and cas6, and also revealed a certain number of spacers that have homology with extant genes, most frequently derived from phages, but also derived from other extrachromosomal elements. Sequence analysis of CRISPR structures from 24 strains of Streptococcus thermophilus and Streptococcus vestibularis confirmed the homology of spacers with extrachromosomal elements. Phage sensitivity of S. thermophilus strains appears to be correlated with the number of spacers in the CRISPR locus the strain carries. The authors suggest that the spacer elements are the traces of past invasions by extrachromosomal elements, and hypothesize that they provide the cell immunity against phage infection, and more generally foreign DNA expression, by coding an anti-sense RNA. The presence of gene fragments in CRISPR structures and the nuclease motifs in cas genes of both cluster types suggests that CRISPR formation involves a DNA degradation step.
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              Interference by clustered regularly interspaced short palindromic repeat (CRISPR) RNA is governed by a seed sequence.

              Prokaryotic clustered regularly interspaced short palindromic repeat (CRISPR)/Cas (CRISPR-associated sequences) systems provide adaptive immunity against viruses when a spacer sequence of small CRISPR RNA (crRNA) matches a protospacer sequence in the viral genome. Viruses that escape CRISPR/Cas resistance carry point mutations in protospacers, though not all protospacer mutations lead to escape. Here, we show that in the case of Escherichia coli subtype CRISPR/Cas system, the requirements for crRNA matching are strict only for a seven-nucleotide seed region of a protospacer immediately following the essential protospacer-adjacent motif. Mutations in the seed region abolish CRISPR/Cas mediated immunity by reducing the binding affinity of the crRNA-guided Cascade complex to protospacer DNA. We propose that the crRNA seed sequence plays a role in the initial scanning of invader DNA for a match, before base pairing of the full-length spacer occurs, which may enhance the protospacer locating efficiency of the E. coli Cascade complex. In agreement with this proposal, single or multiple mutations within the protospacer but outside the seed region do not lead to escape. The relaxed specificity of the CRISPR/Cas system limits escape possibilities and allows a single crRNA to effectively target numerous related viruses.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                11 March 2015
                01 April 2015
                9 April 2015
                09 October 2015
                : 520
                : 7546
                : 186-191
                Affiliations
                [1 ]Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
                [2 ]Society of Fellows, Harvard University, Cambridge, MA 02138, USA
                [3 ]Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                [4 ]Graduate Program in Biophysics, Harvard Medical School, Boston, MA 02115, USA
                [5 ]Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA
                [6 ]McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                [7 ]Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                [8 ]Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
                [9 ]David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                [10 ]National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
                [11 ]Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                Author notes
                []Correspondence and requests for materials should be addressed to: F.Z. ( zhang@ 123456broadinstitute.org )
                [*]

                These authors contributed equally to this work.

                Article
                NIHMS661947
                10.1038/nature14299
                4393360
                25830891
                accaf656-edc4-4359-9029-d1a6ebbcdbf8

                Reprints and permissions information is available at www.nature.com/reprints

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