Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations.

Area of Science:

• Functional Genomics
• Computational Biology
• Immunology

Background:

• Pooled CRISPR screens with single-cell RNA-seq (Perturb-seq) are vital for functional genomics but face scalability challenges due to cost and complexity.
• Existing methods limit the scope of large-scale genetic perturbation studies, hindering comprehensive understanding of complex biological systems like immune responses.

Approach:

• Introduced compressed Perturb-seq, an algorithmic reimagining of Perturb-seq using random, low-dimensional observations.
• Developed a computational decompression method leveraging sparse regulatory circuit structures to analyze measurements of multiple perturbations per cell or multiple cells per droplet.
• Applied compressed Perturb-seq to study 598 genes involved in the immune response to bacterial lipopolysaccharide.

Key Points:

• Compressed Perturb-seq achieves comparable accuracy to conventional Perturb-seq at 4 to 20-fold reduced cost.
• The new method offers enhanced power for discovering genetic interactions.
• Identified known and novel immune response regulators and evolutionarily constrained genes linked to immune disease heritability.

Conclusions:

• Compressed Perturb-seq provides a scalable and cost-effective framework for high-throughput functional genomics.
• The approach uncovers genetic regulators and disease-associated genes missed by current genome-wide association studies (GWAS) and trans-eQTL studies.
• This framework enables unprecedented scales of interrogation for Perturb-seq, advancing functional genomics research.