Dissecting quantitative trait nucleotides with saturation genome editing
收藏NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1067405
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资源简介:
Genome editing technologies have the potential to uncover the genetic basis of complex traits and disease risk by enabling the systematic engineering and phenotypic characterization of variants at the genome scale. However, there has yet to be a system with sufficient efficiency, fidelity, and throughput to comprehensively identify causal variants. Here we explored the ability of CRISPR systems using homology-directed repair (HDR) with donor templates to install natural variants genome-wide in budding yeast. We benchmarked and optimized several approaches for enhancing HDR, including single-stranded donor production by bacterial retrons, donor DNA recruitment to target sites, and in vivo donor plasmid assembly. We uncovered unique advantages of each system that we engineered into a single superior system termed MAGESTIC 3.0. We used MAGESTIC 3.0 to dissect causal variants residing in 112 genomic regions impacting 32 different growth phenotypes, revealing an enrichment for missense variants and loci with multiple causal variants.
创建时间:
2024-01-22



