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The UCSC Genome Browser (https://genome.ucsc.edu) is a graphical viewer for exploring genome annotations. For almost two decades, the Browser has provided visualization tools for genetics and molecular biology and continues to add new data and features. This year, we added a new tool that lets users interactively arrange existing graphing tracks into new groups. Other software additions include new formats for chromosome interactions, a ChIP-Seq peak display for track hubs and improved support for HGVS. On the annotation side, we have added gnomAD, TCGA expression, RefSeq Functional elements, GTEx eQTLs, CRISPR Guides, SNPpedia and created a 30-way primate alignment on the human genome. Nine assemblies now have RefSeq-mapped gene models.

The UCSC Genome Browser (https://genome.ucsc.edu) is a graphical viewer for exploring genome annotations. For almost two decades, the Browser has provided visualization tools for genetics and molecular biology and continues to add new data and features. This year, we added a new tool that lets users interactively arrange existing graphing tracks into new groups. Other software additions include new formats for chromosome interactions, a ChIP-Seq peak display for track hubs and improved support for HGVS. On the annotation side, we have added gnomAD, TCGA expression, RefSeq Functional elements, GTEx eQTLs, CRISPR Guides, SNPpedia and created a 30-way primate alignment on the human genome. Nine assemblies now have RefSeq-mapped gene models.

BackgroundThe success of the CRISPR/Cas9 genome editing technique depends on the choice of the guide RNA sequence, which is facilitated by various websites. Despite the importance and popularity of these algorithms, it is unclear to which extent their predictions are in agreement with actual measurements.ResultsWe conduct the first independent evaluation of CRISPR/Cas9 predictions. To this end, we collect data from eight SpCas9 off-target studies and compare them with the sites predicted by popular algorithms. We identify problems in one implementation but found that sequence-based off-target predictions are very reliable, identifying most off-targets with mutation rates superior to 0.1 %, while the number of false positives can be largely reduced with a cutoff on the off-target score. We also evaluate on-target efficiency prediction algorithms against available datasets. The correlation between the predictions and the guide activity varied considerably, especially for zebrafish. Together with novel data from our labs, we find that the optimal on-target efficiency prediction model strongly depends on whether the guide RNA is expressed from a U6 promoter or transcribed in vitro. We further demonstrate that the best predictions can significantly reduce the time spent on guide screening.ConclusionsTo make these guidelines easily accessible to anyone planning a CRISPR genome editing experiment, we built a new website ( http://crispor.org ) that predicts off-targets and helps select and clone efficient guide sequences for more than 120 genomes using different Cas9 proteins and the eight efficiency scoring systems evaluated here.

The CRISPR-Cas revolution is taking place in virtually all fields of life sciences. Harnessing DNA cleavage with the CRISPR-Cas9 system of Streptococcus pyogenes has proven to be extraordinarily simple and efficient, relying only on the design of a synthetic single guide RNA (sgRNA) and its co-expression with Cas9. Here, we review the progress in the design of sgRNA from the original dual RNA guide for S. pyogenes and Staphylococcus aureus Cas9 (SpCas9 and SaCas9). New assays for genome-wide identification of off-targets have provided important insights into the issue of cleavage specificity in vivo. At the same time, the on-target activity of thousands of guides has been determined. These data have led to numerous online tools that facilitate the selection of guide RNAs in target sequences. It appears that for most basic research applications, cleavage activity can be maximized and off-targets minimized by carefully choosing guide RNAs based on computational predictions. Moreover, recent studies of Cas proteins have further improved the flexibility and precision of the CRISPR-Cas toolkit for genome editing. Inspired by the crystal structure of the complex of sgRNA-SpCas9 bound to target DNA, several variants of SpCas9 have recently been engineered, either with novel protospacer adjacent motifs (PAMs) or with drastically reduced off-targets. Novel Cas9 and Cas9-like proteins called Cpf1 have also been characterized from other bacteria and will benefit from the insights obtained from SpCas9. Genome editing with CRISPR-Cas9 may also progress with better understanding and control of cellular DNA repair pathways activated after Cas9-induced DNA cleavage.

Genome Browser in a Box (GBiB) is a small virtual machine version of the popular University of California Santa Cruz (UCSC) Genome Browser that can be run on a researcher's own computer. Once GBiB is installed, a standard web browser is used to access the virtual server and add personal data files from the local hard disk. Annotation data are loaded on demand through the Internet from UCSC or can be downloaded to the local computer for faster access. Availability and Implementation: Software downloads and installation instructions are freely available for non-commercial use at https://genome-store.ucsc.edu/. GBiB requires the installation of open-source software VirtualBox, available for all major operating systems, and the UCSC Genome Browser, which is open source and free for non-commercial use. Commercial use of GBiB and the Genome Browser requires a license (http://genome.ucsc.edu/license/).genome@soe.ucsc.edu.

Genome Browser in a Box (GBiB) is a small virtual machine version of the popular University of California Santa Cruz (UCSC) Genome Browser that can be run on a researcher's own computer. Once GBiB is installed, a standard web browser is used to access the virtual server and add personal data files from the local hard disk. Annotation data are loaded on demand through the Internet from UCSC or can be downloaded to the local computer for faster access. Availability and Implementation: Software downloads and installation instructions are freely available for non-commercial use at https://genome-store.ucsc.edu/. GBiB requires the installation of open-source software VirtualBox, available for all major operating systems, and the UCSC Genome Browser, which is open source and free for non-commercial use. Commercial use of GBiB and the Genome Browser requires a license (http://genome.ucsc.edu/license/).genome@soe.ucsc.edu.