Titrating gene expression using libraries of systematically attenuated CRISPR guide RNAs

Abstract

A lack of tools to precisely control gene expression has limited our ability to evaluate relationships between expression levels and phenotypes. Here, we describe an approach to titrate expression of human genes using CRISPR interference and series of single guide RNAs (sgRNAs) with systematically modulated activities. We used large-scale measurements across multiple cell models to characterize activities of sgRNAs containing mismatches to their target sites and derived rules governing mismatched sgRNA activity using deep learning. These rules enabled us to synthesize a compact sgRNA library to titrate expression of ~2,400 genes essential for robust cell growth and to construct an in silico sgRNA library spanning the human genome. Staging cells along a continuum of gene expression levels combined with single-cell RNA-seq readout revealed sharp transitions in cellular behaviors at gene-specific expression thresholds. Our work provides a general tool to control gene expression, with applications ranging from tuning biochemical pathways to identifying suppressors for diseases of dysregulated gene expression.

Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement

“…In contrast, association rates for effective sgRNAs were significantly faster than those of ineffective sgRNAs (p = 0.005, Wilcoxon Rank Sums test). This observation is consistent with recent CRISPRi data demonstrating that apparent association rates govern CRISPRi activity in human cells (26).…”

“…CRISPRi knockdown in human cells. Across 3,011 promoters with singly mismatched sgRNA series, we compared measured CRISPRi phenotypes both to our estimated DDGperturbation of productive binding and to activity predicted by a convolutional neural network (CNN) that incorporated additional features beyond the identity of the RNA-DNA mismatches (such as GC content and position relative to TSS) and was trained on this data set ( Figure 7E) (26). The mean spearman correlation with measured CRISPRi activity was 0.508 for DDGperturbation versus 0.667 for the CNN.…”

A kinetic model improves off-target predictions and reveals the physical basis of SpCas9 fidelity

“…CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats -CRISPR associated protein 9) is a ubiquitous tool in the biological sciences 1,2 with applications ranging from live-cell imaging 3 and gene knockdown/overexpression 4,5 , to genetic engineering 6,7 and gene therapy 8,9 . Streptococcus pyogenes (Sp) Cas9 is programmed with a ~100 nucleotide (nt) single-guide RNA (sgRNA) to target DNAs based on the level of complementarity to a 20 nt segment of the sgRNA 10 .…”

A multiplex CRISPR interference tool for virulence gene interrogation in an intracellular pathogen

“…DotO constructs provided a clear example of how gene silencing through placing spacers at ever distant positions within the array can lead to titrated effects to the biological system ( Figure 6D). Recent efforts have been made to tailor the degree of crRNAtargeting of a gene by creating numerous variations of the spacer sequence away from the perfect match (48,49). We imagine shifting the ideal spacer downward in the array would be a much simpler feat.…”