大规模并行精确基因组编辑揭示的功能遗传变异
Functional Genetic Variants Revealed by Massively Parallel Precise Genome Editing.
机构信息
Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
Department of Biology, Stanford University, Stanford, CA 94305, USA.
出版信息
Cell. 2018 Oct 4;175(2):544-557.e16. doi: 10.1016/j.cell.2018.08.057. Epub 2018 Sep 20.
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.
在遗传学中，一个主要的挑战是识别驱动自然表型变异的遗传变异。然而，目前的遗传图谱绘制方法的分辨率有限。为了解决这一挑战，我们开发了一种基于 CRISPR-Cas9 的高通量基因组编辑方法，该方法可以在单个实验中引入数千种特定的遗传变异。这使我们能够研究酵母中 16006 种自然遗传变异的适应度后果。我们在葡萄糖培养基中鉴定出 572 个具有显著适应度差异的变异；这些变异高度富集在启动子中，特别是在转录因子结合位点，而只有 19.2%的变异影响氨基酸序列。引人注目的是，附近的变异几乎总是有利于同一亲本的等位基因，这表明谱系特异性选择通常是由多个聚集的变异驱动的。总之，我们的基因组编辑方法以单碱基分辨率揭示了适应度变化的遗传结构，并且可以适应测量任何细胞存活或可分选标记筛选中全基因组遗传变异的影响。
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