Improved discovery of genetic interactions using CRISPRiSeq across multiple environments

Area of Science:

• Systems Biology
• Genetics
• Molecular Biology

Background:

• Large-scale genetic interaction (GI) screens in yeast are crucial for understanding molecular systems biology and gene function.
• Most existing GI data is limited to a single environmental condition due to high costs and long experiment times.
• A significant portion of genetic interactions may be condition-specific, remaining undiscovered.

Purpose of the Study:

• To develop a high-throughput method for assaying genetic interactions across multiple growth conditions.
• To investigate the prevalence and impact of condition-specific genetic interactions.
• To enhance the functional classification of genes using conditional GI data.

Main Methods:

• Developed a pooled-growth CRISPR interference (CRISPRi)-based sequencing assay for genetic interactions (CRISPRiSeq).
• Assayed approximately 17,000 strains, covering about 7700 pairwise interactions, across five different growth conditions.
• Utilized sequencing to measure strain fitness and infer genetic interactions.

Main Results:

• The CRISPRiSeq assay significantly increased throughput, enabling multi-condition GI screening.
• The number of detected GIs increased nearly threefold when including additional conditions compared to rich media alone.
• Condition-specific GIs were found to be prevalent, improving the power to functionally classify genes.
• New links were identified between the Ras pathway, the COG complex, and a gene of unknown function during respiratory growth.

Conclusions:

• Conditional genetic interaction screens have substantial potential for advancing our understanding of cellular genetic networks.
• CRISPRiSeq provides a powerful tool for comprehensive, multi-condition GI analysis.
• Discovering condition-specific GIs is essential for a complete picture of gene function and biological systems.