Cas13 Guide Design Resource
This resource provides optimized guide RNAs to target protein-coding transcripts in the human transcriptome. To use the tool, you will first need to find the Ensembl transcript ID for the transcript isoform to target and then paste this transcript ID into the Cas13 guide designer. These two steps are performed using the tabs in the navigation bar.
Here are the steps to use the design tool:
Click on the Lookup transcript button in the navigator bar. Typing in a gene name will retrieve a list of all associated Ensembl transcript isoforms for that gene along with expression data for each isoform in different human cell lines.
Copy the Ensembl transcript ID of the desired transcript.
Click on the Design guide RNAs button in the navigation bar.
Paste the Ensembl transcript ID into search box in the upper left side and click the submit button.
After lookup, you can browse individual guide RNAs and download a graphical representation of guide RNAs or a table with all guide RNAs that target the transcript.
To predict guide RNA scores for custom target RNA, please use our
Cas13 guide design software.
Questions, comments or feedback? Please do not hesitate to get in touch with us here.
This online resource for the prediction Cas13d guides for protein coding transcripts integrates guide RNA design rules from this manuscript:
Hans-Hermann Wessels*, Alejandro Méndez-Mancilla*, Xinyi Guo, Mateusz Legut, Zharko Daniloski, Neville E. Sanjana
* These authors contributed equally
This resource currently features:
GENCODE v19 (GRCh37)
annotation allowing us to integrate gene expression information from the
Cancer Cell Line Encyclopedia (CCLE).
Please retrieve transcript isoform expression information directly from the CCLE repository if you don't find your cell line represented.
- Selection of perfect matching guides for all protein coding genes, separted by transcript and mRNA sub-annotation categories (5'UTR, CDS, 3'UTR).
- Integration of Cancer Cell Line Encyclopedia (CCLE) gene expression data for the selection by cell type specific expression level.
- 12.2019: v0.3 model update with improved prediction accuracy. The model is now trained on four tiling screen data sets.
- 09.2019: v0.2 improved data structure to allow real-time start up. Adding improved visualizations and data download.
- 07.2019: v0.1 goes online