Jian Ma1, Johannes Köster2, Qian Qin1, Shengen Hu1, Wei Li3, Chenhao Chen3, Qingyi Cao4, Jinzeng Wang1, Shenglin Mei1, Qi Liu1, Han Xu3, Xiaole Shirley Liu5. 1. School of Life Science and Technology, Tongji University, Shanghai 200092, China. 2. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02115, USA Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215, USA Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. 3. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02115, USA Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215, USA. 4. State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China. 5. School of Life Science and Technology, Tongji University, Shanghai 200092, China Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02115, USA Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Abstract
MOTIVATION: Despite the growing popularity in using CRISPR/Cas9 technology for genome editing and gene knockout, its performance still relies on well-designed single guide RNAs (sgRNA). In this study, we propose a web application for the Design and Optimization (CRISPR-DO) of guide sequences that target both coding and non-coding regions in spCas9 CRISPR system across human, mouse, zebrafish, fly and worm genomes. CRISPR-DO uses a computational sequence model to predict sgRNA efficiency, and employs a specificity scoring function to evaluate the potential of off-target effect. It also provides information on functional conservation of target sequences, as well as the overlaps with exons, putative regulatory sequences and single-nucleotide polymorphisms (SNPs). The web application has a user-friendly genome-browser interface to facilitate the selection of the best target DNA sequences for experimental design. AVAILABILITY AND IMPLEMENTATION: CRISPR-DO is available at http://cistrome.org/crispr/ CONTACT: qiliu@tongji.edu.cn or hanxu@jimmy.harvard.edu or xsliu@jimmy.harvard.eduSupplementary information: Supplementary data are available at Bioinformatics online.
MOTIVATION: Despite the growing popularity in using CRISPR/Cas9 technology for genome editing and gene knockout, its performance still relies on well-designed single guide RNAs (sgRNA). In this study, we propose a web application for the Design and Optimization (CRISPR-DO) of guide sequences that target both coding and non-coding regions in spCas9 CRISPR system across human, mouse, zebrafish, fly and worm genomes. CRISPR-DO uses a computational sequence model to predict sgRNA efficiency, and employs a specificity scoring function to evaluate the potential of off-target effect. It also provides information on functional conservation of target sequences, as well as the overlaps with exons, putative regulatory sequences and single-nucleotide polymorphisms (SNPs). The web application has a user-friendly genome-browser interface to facilitate the selection of the best target DNA sequences for experimental design. AVAILABILITY AND IMPLEMENTATION: CRISPR-DO is available at http://cistrome.org/crispr/ CONTACT: qiliu@tongji.edu.cn or hanxu@jimmy.harvard.edu or xsliu@jimmy.harvard.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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