Functional Genetic Variants Revealed by Massively Parallel Precise Genome Editing

Cell. 2018 Oct 4;175(2):544-557.e16. doi: 10.1016/j.cell.2018.08.057. Epub 2018 Sep 20.

Abstract

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.

Keywords: CRISPR; Cas9; QTL; evolution; fitness; genetic variation; genome editing; yeast.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • CRISPR-Cas Systems
  • Chromosome Mapping
  • Clustered Regularly Interspaced Short Palindromic Repeats / genetics
  • Gene Editing / methods*
  • Genetic Variation / genetics
  • Genetic Vectors
  • Genome
  • High-Throughput Nucleotide Sequencing / methods*
  • Saccharomyces cerevisiae / genetics*
  • Yeasts / genetics