Scalable Design of Paired CRISPR Guide RNAs for Genomic Deletion
Carlos Pulido-Quetglas , Estel Aparicio-Prat , Carme Arnan , Taisia Polidori, Toni Hermoso, Emilio Palumbo, Julia Ponomarenko, Roderic Guigo, Rory Johnson
Published: March 2, 2017http://dx.doi.org/10.1371/journal.pcbi.1005341
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 is a revolutionary biological technique for precisely editing cells’ genomes. Amongst its many capabilities is the deletion of defined regions of DNA, creating a wide range of applications from modelling rare human diseases, to performing very large knock-out screens of candidate regulatory DNA. CRISPR-Cas9 requires researchers to design small RNA molecules called sgRNAs to target their region of interest. A large number of bioinformatic tools exist for this task. However, CRISPR deletion requires the design of optimised pairs of such RNA molecules. This manuscript describes the first pipeline designed to accomplish this, called CRISPETa, with a range of useful features. We use CRISPETa to design comprehensive libraries of paired sgRNA for many thousands of target regions that may be used by the scientific community. Using CRISPETa designs in human cells, we show that predicted pairs of sgRNAs produce the expected deletions at high efficiency. Finally, we show that these deletions of genomic DNA give rise to correspondingly truncated RNA molecules, supporting the power of this technology to create cells with precisely deleted DNA.
Citation: Pulido-Quetglas C, Aparicio-Prat E, Arnan C, Polidori T, Hermoso T, Palumbo E, et al. (2017) Scalable Design of Paired CRISPR Guide RNAs for Genomic Deletion. PLoS Comput Biol 13(3): e1005341. doi: 10.1371/journal.pcbi.1005341
Editor: Ilya Ioshikhes, Ottawa University, CANADA
Received: August 2, 2016; Accepted: December 30, 2016; Published: March 2, 2017
Copyright: © 2017 Pulido-Quetglas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All files are available from crispeta.crg.eu.
Funding: This work was financially supported by the following grants: CSD2007-00050 from the Spanish Ministry of Science (http://www.mineco.gob.es/portal/site/mineco/idi), grant SGR-1430 from the Catalan Government (http://web.gencat.cat/ca/temes/tecnologia/), grant ERC-2011-AdG-294653-RNA-MAPS from the European Community financial support under the FP7 (https://erc.europa.eu/) and grant R01MH101814 by the National Human Genome Research Institute of the National Institutes of Health (https://www.genome.gov/), to RG. Ramón y Cajal RYC-2011-08851 and Plan Nacional BIO2011-27220, both from the Spanish Ministry of Science (http://www.mineco.gob.es/portal/site/mineco/idi), to RJ. We also acknowledge support of the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’, SEV-2012-0208 (http://www.mineco.gob.es/portal/site/mineco/idi). We also acknowledge the support of the CERCA Programme / Generalitat de Catalunya (http://web.gencat.cat/ca/temes/tecnologia/). This research was partly supported by the NCCR RNA & Disease funded by the Swiss National Science Foundation (http://www.nccr-rna-and-disease.ch/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
FREE PDF GRATIS: PLoS Computational Biology