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Genome-wide detection and analysis of CRISPR-Cas off-targets.
Rodríguez, Tomás C; Dadafarin, Sina; Pratt, Henry E; Liu, PengPeng; Amrani, Nadia; Zhu, Lihua Julie.
Afiliación
  • Rodríguez TC; University of Massachusetts Medical School Medical Scientist Training Program, Worcester, MA, United States; RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA, United States. Electronic address: tomas.rodriguez@umassmed.edu.
  • Dadafarin S; RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA, United States; Department of Microbiology and Immunology, New York Medical College, Valhalla, NY, United States.
  • Pratt HE; University of Massachusetts Medical School Medical Scientist Training Program, Worcester, MA, United States; Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, United States.
  • Liu P; Department of Molecular, Cell and Cancer Biology, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, United States.
  • Amrani N; RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA, United States.
  • Zhu LJ; Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, United States; Department of Molecular, Cell and Cancer Biology, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, United States. Electronic address:
Prog Mol Biol Transl Sci ; 181: 31-43, 2021.
Article en En | MEDLINE | ID: mdl-34127199
The clustered, regularly interspersed, short palindromic repeats (CRISPR) technology is revolutionizing biological studies and holds tremendous promise for treating human diseases. However, a significant limitation of this technology is that modifications can occur on off-target sites lacking perfect complementarity to the single guide RNA (sgRNA) or canonical protospacer-adjacent motif (PAM) sequence. Several in vivo and in vitro genome-wide off-target profiling approaches have been developed to inform on the fidelity of gene editing. Of these, GUIDE-seq has become one of the most widely adopted and reproducible methods. To allow users to easily analyze GUIDE-seq data generated on any sequencing platform, we developed an open-source pipeline, GS-Preprocess, that takes standard base-call output in bcl format and generate all required input data for off-target identification using bioconductor package GUIDEseq for off-target identification. Furthermore, we created a Docker image with GS-Proprocess, GUIDE-seq, and all its R and system dependencies already installed. The bundled pipeline will empower end users to streamline the analysis of GUIDE-seq data and motivate their use of higher throughput sequencing with increased multiplexing for GUIDE-seq experiments.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ARN Guía de Kinetoplastida / Sistemas CRISPR-Cas Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Prog Mol Biol Transl Sci Asunto de la revista: BIOLOGIA MOLECULAR Año: 2021 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ARN Guía de Kinetoplastida / Sistemas CRISPR-Cas Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Prog Mol Biol Transl Sci Asunto de la revista: BIOLOGIA MOLECULAR Año: 2021 Tipo del documento: Article Pais de publicación: Países Bajos