Immune-mediated diseases arise from a dysregulated cellular immune response. Therefore, understanding gene function, regulation networks and cellular processes is necessary to identify new targets for disease modulation and control.
In this study we aim to build a transcriptional map of gene-effects on immune cells from lymphoid and myeloid lineages. Single-cell CRISPR screens have been used to map gene-effects on gene expression however, most screens use single-guide CRISPR systems and one modality resulting in relatively low editing efficiency and loss of statistical power.
We apply a recently described dual-guide system to tackle this problem1. This system uses two gRNAs (guide RNAs) targeting the same exon and separated by a tRNA (transfer RNA) into two 20nt gRNA spacers. Using this approach, we showed in CD4+ T cells an increase in editing efficiency from 50% to as much as 80% for the same target. This increased editing efficiency greatly improves the statistical power of the single-cell data, improving resolution such that cell-type specific DEGs may be detected with fewer cells than with a single-guide system.
We have validated our screening approach with a CRISPR knockout screen against 20 genes across three donors with single-cell readout and integration of the dual-guide system. scRNAseq showed strong on-target effects for 13/20 of targets and 12/20 targets had significant impacts on transcriptional profile, these hits included key immune regulation genes such as STAT3.
We also utilized CRISPR activation. Our data shows as much as 75% LRRC32 activation by DNA sequencing as well as flow cytometry and confirms strong upregulation of highly and lowly expressed genes at different timepoints of activation.
We have validated the scalability of our approach by carrying out in parallel CRISPR activation and knockout screens with single-cell readout targeting multiple immune genes map context specific gene network effects.