PROJECT SUMMARY Large-scale pooled CRISPR screens have proven to be a powerful approach to identify genes that affect cell state and behavior. Notwithstanding the countless genetic associations discovered with proliferation and drug resistance pathways using viability or marker-based enrichment screens, there is tremendous potential for pooled screens to go further by incorporating high complexity readouts like gene expression profiles. The cancer community is already acting on this opportunity to access new pathways and immediately gain mechanistic information about the nature of screening hits by interpreting the impact of perturbations on expression profiles. However, pooled gene expression screens are underutilized and not routinely applied for large (eg. genome- wide) screens for a simple reason - the cost of processing so many cells for single-cell gene expression readout and carrying out the massive amount of sequence data generation required is too high. Here, we propose to solve this problem with a method we call Stitch-seq, an ultra-high-throughput droplet-based overlap PCR method that enables readout of the expression levels of a target gene panel in the pooled screening context. Stitch-seq is low-cost because it does not require specialized barcoded reagents like beads and operates as a massively parallel single-cell emulsion Rt-PCR that physically links CRISPR guide RNA sequences to the targeted mRNA sequences by overlap extension. In the proposed work, we will characterize the quantitative performance of the Stitch-seq reaction in detail, and demonstrate the technical and cost performance of Stitch-seq in targeted and genome-wide screens. Stitch-seq will address the significant throughput limitations associated with existing pooled CRISPR expression screening modalities by providing a facile, low-cost, and ultra-high-throughput method to physically link perturbations to gene sets of interest across a range of perturbation modalities including all manner of CRISPR perturbations (knock-out, CRISPRi, CRISPRoff, CRISPRa, base editing, prime editing, etc.) and beyond.