Scalable genetic screening for regulatory circuits using compressed Perturb-seq.

Area of Science:

• Genomics
• Immunology
• Bioinformatics

Background:

• Pooled CRISPR screens with single-cell RNA sequencing (Perturb-seq) are vital for functional genomics.
• Current Perturb-seq methods face limitations in scale due to cost and complexity.

Purpose of the Study:

• To develop a cost-effective and scalable Perturb-seq method.
• To enhance the ability to study genetic interactions and immune responses.

Main Methods:

• Modified Perturb-seq using algorithms for random, low-dimensional observations.
• Developed Compressed Perturb-seq to measure multiple perturbations per cell or cells per droplet.
• Utilized computational decompression leveraging sparse regulatory circuit structures.

Main Results:

• Compressed Perturb-seq achieved comparable accuracy to conventional Perturb-seq with a tenfold cost reduction.
• Demonstrated increased power for learning genetic interactions in immune response pathways.
• Identified known and novel regulators of immune responses to bacterial lipopolysaccharide.
• Uncovered evolutionarily constrained genes with targets enriched for immune disease heritability, including those missed by GWAS.

Conclusions:

• Compressed Perturb-seq offers a scalable and cost-efficient framework for functional genomics.
• The method provides new insights into immune response regulation and genetic architecture of immune diseases.
• Enables higher-throughput interrogation of gene function and interactions.