Functional genetic variants revealed by massively parallel precise genome editing

• Eilon Sharon ^[1] ; Shi-An A. Chen ^[1] ; Neil M. Khosla ^[1]
  1. [1] Stanford University

     Stanford University

     Estados Unidos

     
• Localización: Cell, ISSN 0092-8674, Vol. 175, Nº. 2, 2018, págs. 544-557
• Idioma: inglés
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• Resumen

  • A major challenge in genetics is to identify genetic variants driving natural phenotypic variation. However, current methods of genetic mapping have limited resolution. To address this challenge, we developed a CRISPR-Cas9-based high-throughput genome editing approach that can introduce thousands of specific genetic variants in a single experiment. This enabled us to study the fitness consequences of 16,006 natural genetic variants in yeast. We identified 572 variants with significant fitness differences in glucose media; these are highly enriched in promoters, particularly in transcription factor binding sites, while only 19.2% affect amino acid sequences. Strikingly, nearby variants nearly always favor the same parent’s alleles, suggesting that lineage-specific selection is often driven by multiple clustered variants. In sum, our genome editing approach reveals the genetic architecture of fitness variation at single-base resolution and could be adapted to measure the effects of genome-wide genetic variation in any screen for cell survival or cell-sortable markers.