PDF(Pubmed)
Abstract：
Genome editing technologies have the potential to transform our understanding of how genetic variation gives rise to complex traits through the systematic engineering and phenotypic characterization of genetic variants. However, there has yet to be a system with sufficient efficiency, fidelity, and throughput to comprehensively identify causal variants at the genome scale. Here we explored the ability of templated CRISPR editing systems to install natural variants genome-wide in budding yeast. We optimized several approaches to enhance homology-directed repair (HDR) with donor DNA templates, including donor recruitment to target sites, single-stranded donor production by bacterial retrons, and in vivo plasmid assembly. We uncovered unique advantages of each system that we integrated into a single superior system named MAGESTIC 3.0. We used MAGESTIC 3.0 to dissect causal variants residing in 112 quantitative trait loci across 32 environmental conditions, revealing an enrichment for missense variants and loci with multiple causal variants. MAGESTIC 3.0 will facilitate the functional analysis of the genome at single-nucleotide resolution and provides a roadmap for improving template-based genome editing systems in other organisms.
摘要：
基因组编辑技术有可能改变我们对遗传变异如何通过遗传变异的系统工程和表型表征引起复杂性状的理解。然而,还没有一个足够高效的系统，保真度，和通量，以在基因组尺度上全面识别因果变异。在这里，我们探索了模板化CRISPR编辑系统在出芽酵母中全基因组安装天然变体的能力。我们优化了几种使用供体DNA模板增强同源定向修复（HDR）的方法，包括向目标地点招募捐助者，通过细菌反射产生单链供体，和体内质粒组装。我们发现了每个系统的独特优势，我们将其集成到名为MAGESTIC3.0的单个高级系统中。我们使用MAGESTIC3.0来剖析在32个环境条件下存在于112个数量性状基因座中的因果变异，揭示了错义变体和具有多个因果变体的基因座的富集。MAGESTIC3.0将促进以单核苷酸分辨率对基因组进行功能分析，并为改进其他生物体中基于模板的基因组编辑系统提供路线图。
