SliceIt

SliceIt enables genome-wide CRISPR/Cas9 targeting of protein–RNA interaction sites to functionally dissect RNA-binding proteins (RBPs) and their RNA targets across coding and noncoding genomic regions.

Key Features:

• In silico sgRNA library: Approximately 4.8 million unique single guide RNAs (sgRNAs) are provided, targeting over 100 RBPs with an estimated 2–8 sgRNAs per RBP binding site.
• eCLIP-derived targeting: sgRNA designs are based on eCLIP experiments from ENCODE performed in HepG2 and K562 cell lines to map RBP binding sites.
• Coverage of coding and noncoding regions: Designed sgRNAs target both coding and noncoding genomic regions containing RBP binding sites.
• Integrated functional genomics data: Binding sites are annotated with exon expression levels across 53 human tissues, SNP prevalence, and GWAS hit associations.
• Experimental validation: Design utility was validated by targeting RBP binding sites in the Lipt1 gene in HepG2 cells, where CRISPR/Cas9 perturbations produced altered proximal exon expression measured by qPCR.
• Scalability for screens: Resource supports design of both low- and high-throughput CRISPR/Cas9 screening strategies focused on RBP binding sites.

Scientific Applications:

• Functional dissection of RBPs: Enable targeted perturbation of RBP binding sites to determine RBP roles and target RNA functions.
• Genome-wide CRISPR/Cas9 screens: Support design and implementation of large-scale screens that probe protein–RNA interaction networks.
• Disease and phenotype association studies: Facilitate investigation of phenotypic or disease associations of RBP binding sites using integrated SNP and GWAS data alongside tissue expression.
• Post-transcriptional regulation analysis: Allow probing of the global impact of protein–RNA interactions across cell types to study post-transcriptional regulatory mechanisms.

Methodology:

sgRNAs were designed in silico from ENCODE eCLIP-derived RBP binding sites in HepG2 and K562 to generate ~4.8 million guides (~2–8 per site), with indexing and search implemented using Elasticsearch.