Functional Genetic Variants Revealed by Massively Parallel Precise Genome Editing

Publication date: Available online 20 September 2018Source: CellAuthor(s): Eilon Sharon, Shi-An A. Chen, Neil M. Khosla, Justin D. Smith, Jonathan K. Pritchard, Hunter B. FraserSummaryA 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.Graphical Abstract

Source: Cell - September 21, 2018 Category: Cytology Source Type: research