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. 2020 Jun 22;3:321. doi: 10.1038/s42003-020-1014-1

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© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — a The analyzed genomes. On the left, the green part of the cylinder shows complete genomes containing CRISPR arrays with no identifiable protospacers, and the blue part shows complete genomes containing spacers with identifiable protospacers. The schematic on the right shows a genome with CRISPR arrays, one of which contains a virus-targeting spacer. b Distributions of the number of spacers per array for arrays containing protospacers with detectable matches (blue) and arrays lacking such protospacers (red). c The computational pipeline for spacer analysis. The workflow includes the generation of mock spacers, k-mer generation, and search for k-mer matches in spacers. The underlying data are available at ftp://ftp.ncbi.nih.gov/pub/wolf/_suppl/spacers2020/.