Highly Combinatorial Genetic Interaction Analysis Reveals a Multi-Drug Transporter Influence Network.
Cell Syst
; 10(1): 25-38.e10, 2020 01 22.
Article
em En
| MEDLINE
| ID: mdl-31668799
ABSTRACT
Many traits are complex, depending non-additively on variant combinations. Even in model systems, such as the yeast S. cerevisiae, carrying out the high-order variant-combination testing needed to dissect complex traits remains a daunting challenge. Here, we describe "X-gene" genetic analysis (XGA), a strategy for engineering and profiling highly combinatorial gene perturbations. We demonstrate XGA on yeast ABC transporters by engineering 5,353 strains, each deleted for a random subset of 16 transporters, and profiling each strain's resistance to 16 compounds. XGA yielded 85,648 genotype-to-resistance observations, revealing high-order genetic interactions for 13 of the 16 transporters studied. Neural networks yielded intuitive functional models and guided exploration of fluconazole resistance, which was influenced non-additively by five genes. Together, our results showed that highly combinatorial genetic perturbation can functionally dissect complex traits, supporting pursuit of analogous strategies in human cells and other model systems.
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Base de dados:
MEDLINE
Assunto principal:
Proteínas de Membrana Transportadoras
/
Transporte Biológico
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article