Systematic identification of noncoding regulatory elements has, to date, mainly relied on large-scale reporter assays that do not reproduce endogenous conditions. We present two distinct CRISPR-Cas9 genetic screens to identify and characterize functional enhancers in their native context. Our strategy is to target Cas9 to transcription factor binding sites in enhancer regions. We identified several functional enhancer elements and characterized the role of two of them in mediating p53 (TP53) and ERα (ESR1) gene regulation. Moreover, we show that a genomic CRISPR-Cas9 tiling screen can precisely map functional domains within enhancer elements. Our approach expands the utility of CRISPR-Cas9 to elucidate the functions of the noncoding genome.

The CRISPR/Cas9 system provides a revolutionary genome editing tool for all areas of molecular biology. In long non-coding RNA (lncRNA) research, the Cas9 nuclease can delete lncRNA genes or introduce RNA-destabilizing elements into their locus. The nuclease-deficient dCas9 mutant retains its RNA-dependent DNA-binding activity and can modulate gene expression when fused to transcriptional repressor or activator domains. Here, we systematically analyze whether CRISPR approaches are suitable to target lncRNAs. Many lncRNAs are derived from bidirectional promoters or overlap with promoters or bodies of sense or antisense genes. In a genome-wide analysis, we find only 38% of 15929 lncRNA loci are safely amenable to CRISPR applications while almost two-thirds of lncRNA loci are at risk to inadvertently deregulate neighboring genes. CRISPR- but not siPOOL or Antisense Oligo (ASO)-mediated targeting of lncRNAs NOP14-AS1, LOC389641, MNX1-AS1 or HOTAIR also affects their respective neighboring genes. Frequently overlooked, the same restrictions may apply to mRNAs. For example, the tumor suppressor TP53 and its head-to-head neighbor WRAP53 are jointly affected by the same sgRNAs but not siPOOLs. Hence, despite the advantages of CRISPR/Cas9 to modulate expression bidirectionally and in cis, approaches based on ASOs or siPOOLs may be the better choice to target specifically the transcript from complex loci.