Genome-scale analysis of interactions between genetic perturbations and natural variation

• Published in: Nature communications Vol. 15; no. 1; p. 4234
• Main Authors: Hale, Joseph J., Matsui, Takeshi, Goldstein, Ilan, Mullis, Martin N., Roy, Kevin R., Ville, Christopher Ne, Miller, Darach, Wang, Charley, Reynolds, Trevor, Steinmetz, Lars M., Levy, Sasha F., Ehrenreich, Ian M.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 18-05-2024; Nature Publishing Group; Nature Portfolio
• Subjects: 49/47; 631/208/207; 631/208/480; 631/208/737; BASIC BIOLOGICAL SCIENCES; Combinatorial analysis; CRISPR-Cas Systems; DNA Barcoding, Taxonomic; DNA sequencing; Epistasis; Epistasis, Genetic; Gene sequencing; Genes; Genetic crosses; Genetic diversity; Genetic Fitness; Genetic Variation; Genome, Fungal; Genomes; Humanities and Social Sciences; multidisciplinary; Perturbation; Phenotype; Saccharomyces cerevisiae - genetics; Science; Science (multidisciplinary); Yeast; Yeasts
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-48626-1

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual’s response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.
Here the authors investigate the interactions between genetic perturbations and segregating loci on a genome scale in yeast using barcoded CRISPRi. Strains’ responses to perturbations are shaped by perturbation-locus interactions that cannot be measured by examining perturbations or natural variation alone.