Development of compact transcriptional effectors using high-throughput measurements in diverse contexts

Transcriptional effectors are protein domains known to activate or repress gene expression, however, a systematic understanding of which effector domains regulate transcription robustly across genomic, cell-type, and DNA-binding domain (DBD) contexts is lacking. Here, we develop dCas9-mediated high-throughput recruitment (HT-recruit), a pooled screening method for quantifying effector function at endogenous target genes, and test effector function for a library containing 5,092 nuclear protein Pfam domains across varied contexts. We also map context dependencies of effectors drawn from unannotated protein regions using a larger library containing 114,288 sequences tiling chromatin regulators and transcription factors. We find that many effectors depend on target and DBD contexts, such as HLH domains that can act as either activators or repressors. To enable efficient perturbations, we select context-robust domains, including ZNF705 KRAB, that improve CRISPRi tools to silence promoters and enhancers. We engineer a compact human activator NFZ by combining several domains, which enables efficient CRISPRa with better viral delivery, and inducible control of CAR T-cells. Together, this effector-by-context functional map reveals context-dependence across human effectors and guides effector selection for manipulating transcription.