Publication:20170303091021
From Bioinformatics Core Wiki
| Publication | |
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| URL | http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005341 |
| Title | Scalable Design of Paired CRISPR Guide RNAs for Genomic Deletion
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| Authors | Carlos Pulido-Quetglas, Estel Aparicio-Prat, Carme Arnan, Taisia Polidori, Toni Hermoso, Emilio Palumbo, Julia Ponomarenko, Roderic Guigo, Rory Johnson |
| Date | 2017-03-02
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| Publisher | PLOS Computational Biology |
| DOI | 10.1371/journal.pcbi.1005341 |
| Tag | Genomics, Invertebrate genomics, Mammalian genomics, CRISPR, MicroRNAs, Human genomics, Cloning, Zebrafish |
Abstract:
CRISPR-Cas9 technology can be used to engineer precise genomic deletions with pairs of single guide RNAs (sgRNAs). This approach has been widely adopted for diverse applications, from disease modelling of individual loci, to parallelized loss-of-function screens of thousands of regulatory elements. However, no solution has been presented for the unique bioinformatic design requirements of CRISPR deletion. We here present CRISPETa, a pipeline for flexible and scalable paired sgRNA design based on an empirical scoring model. Multiple sgRNA pairs are returned for each target, and any number of targets can be analyzed in parallel, making CRISPETa equally useful for focussed or high-throughput studies. Fast run-times are achieved using a pre-computed off-target database. sgRNA pair designs are output in a convenient format for visualisation and oligonucleotide ordering. We present pre-designed, high-coverage library designs for entire classes of protein-coding and non-coding elements in human, mouse, zebrafish, Drosophila melanogaster and Caenorhabditis elegans. In human cells, we reproducibly observe deletion efficiencies of ≥50% for CRISPETa designs targeting an enhancer and exonic fragment of the MALAT1 oncogene. In the latter case, deletion results in production of desired, truncated RNA. CRISPETa will be useful for researchers seeking to harness CRISPR for targeted genomic deletion, in a variety of model organisms, from single-target to high-throughput scales.
CRISPR-Cas9 technology can be used to engineer precise genomic deletions with pairs of single guide RNAs (sgRNAs). This approach has been widely adopted for diverse applications, from disease modelling of individual loci, to parallelized loss-of-function screens of thousands of regulatory elements. However, no solution has been presented for the unique bioinformatic design requirements of CRISPR deletion. We here present CRISPETa, a pipeline for flexible and scalable paired sgRNA design based on an empirical scoring model. Multiple sgRNA pairs are returned for each target, and any number of targets can be analyzed in parallel, making CRISPETa equally useful for focussed or high-throughput studies. Fast run-times are achieved using a pre-computed off-target database. sgRNA pair designs are output in a convenient format for visualisation and oligonucleotide ordering. We present pre-designed, high-coverage library designs for entire classes of protein-coding and non-coding elements in human, mouse, zebrafish, Drosophila melanogaster and Caenorhabditis elegans. In human cells, we reproducibly observe deletion efficiencies of ≥50% for CRISPETa designs targeting an enhancer and exonic fragment of the MALAT1 oncogene. In the latter case, deletion results in production of desired, truncated RNA. CRISPETa will be useful for researchers seeking to harness CRISPR for targeted genomic deletion, in a variety of model organisms, from single-target to high-throughput scales.
| Annotation | This paper presents CRISPETa, a web-tool for designing optimal pairs of sgRNAs for deletion of desired genomic regions; for example, lncRNAs. (Crispeta means popcorn, in Catalan.) The target regions can be supplied in the BED or UCSC format. CRISPETa can be run on any number of targets - from one to thousands. At present, designs can be performed for five species, human, mouse, zebrafish, fruitfly, and worm. The BioCore has designed and developed the website for CRISPETa. Impact factor 4,4. |
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