Charactering the impacts of regulatory epistasis with high-throughput precision genome editing.

通过高通量精准基因组编辑来表征监管上位性的影响。

• 批准号: 10247472
• 负责人: Katya Mack
• 金额: $ 6.64万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10247472
• 关键词: Address; Affect; Alleles; Automobile Driving; Biological Assay; Biology; CRISPR/Cas technology; Complex; DNA; Disease; Elements; Evolution; Gene Expression; Genes; Genetic; Genetic Epistasis; Genetic Variation; Genotype; Individual; Measures; Methods; Modeling; Mutation; Natural Selections; Nature; Noise; Nucleic Acid Regulatory Sequences; Outcome; Output; Pattern; Phenotype; Prevalence; Property; Psychological reinforcement; Quantitative Reverse Transcriptase PCR; Quantitative Trait Loci; Regulation; Regulatory Element; Research Design; Role; Saccharomyces cerevisiae; Scanning; Shapes; Surveys; System; Testing; Translating; Variant; Work; Yeasts; base; combinatorial; fitness; genetic variant; genome editing; genome-wide; human disease; in vivo; innovation; promoter; trait

PROJECT SUMMARY Connecting genotype to phenotype remains a major challenge. Our inability to predict the fitness effects of individual mutations, particularly when the effects of mutations are non-additive, have made it difficult to connect genetic variation to phenotypes and disease traits. Changes in gene expression are thought to frequently underlie phenotypic variation. However, how mutations within regulatory regions act to dictate changes in gene expression is still not well understood. In particular, the role of additive versus non-additive (epistatic) interactions between genetic variants within regulatory regions remains largely unexplored. The proposed work will use an innovation in the CRISPR/Cas9 system (“CRISPEY”) to investigate the role of epistasis in regulatory variation and evolution. CRISPEY greatly increases the efficiency of traditional precision editing by generating a large number of potential donor DNAs in vivo using a bacterial retron element. In preliminary analyses, this method shows ~100% efficiency of precision editing with no off-target edits. The first CRISPEY scan assayed the fitness affects of 16,000 natural genetic variants differing between two strains of Saccharomyces cerevisiae (RM and BY). Strikingly, it was found that the effects of proximal promoter variants nearly always favored the same parental strain’s alleles. Reinforcement between variants in a cluster is not expected under neutral evolution, and provides evidence of widespread lineage-specific selection acting on promoter variants. Following this discovery, we will ask whether these proximal promoter variants affect fitness additively or epistatically by creating combinatorial edits of variants in each cluster. First, we will characterize general properties of regulatory epistasis. We will generate all possible combinations of 305 clusters of promoter variants (n=5,392). The fitness of each combinatorial edit will be compared to that of the predicted fitness based on individual variants to assess the extent, magnitude, and prevalence of different kinds of epistasis. Second, we ask how natural selection shapes epistasis within regulatory regions by comparing patterns observed in clusters of natural variants to a set of control variants. Next, we will ask how epistasis constrains paths available for adaptive evolution of cis-regulation by assaying all possible paths between the full BY and RM genotypes. Finally, we will ask whether epistasis for fitness results from epistasis for gene expression levels. We will use qRT-PCR to quantify gene expression levels under different combinatorial edits to assess the extent and magnitude of gene expression epistasis between natural variants. This will be the first study to conduct a genome-wide survey of epistasis between natural variants within regulatory regions. This work is critical to understanding how genetic variation translates to phenotypic variation, which is relevant for understanding the genetic basis of human disease.

项目概要 将基因型与表型联系起来仍然是一个重大挑战。我们无法预测健身效果 个体突变，特别是当突变的影响是非累加性的时，使得很难 将遗传变异与表型和疾病特征联系起来。基因表达的变化被认为 通常是表型变异的基础。然而，监管区域内的突变如何发挥作用来决定 基因表达的变化仍不清楚。特别是添加剂与非添加剂的作用 调控区域内遗传变异之间的（上位）相互作用在很大程度上仍未被探索。 拟议的工作将利用 CRISPR/Cas9 系统（“CRISPEY”）的创新来研究 监管变异和进化中的上位性。 CRISPEY大幅提升传统精密效率 通过使用细菌逆转录子元件在体内生成大量潜在的供体 DNA 进行编辑。在 初步分析，该方法显示精确编辑效率约为 100%，没有脱靶编辑。第一个 CRISPEY 扫描分析了两种菌株之间 16,000 个不同的自然遗传变异对健康的影响 酿酒酵母（RM 和 BY）。引人注目的是，发现近端启动子变异的影响 几乎总是偏爱同一亲本品系的等位基因。簇中变体之间的强化不是 预期在中性进化下，并提供了广泛的谱系特异性选择作用的证据 启动子变体。根据这一发现，我们将询问这些近端启动子变异是否会影响适应性 通过在每个簇中创建变体的组合编辑来进行加性或上位性编辑。首先，我们将表征 调节上位性的一般特性。我们将生成 305 个簇的所有可能组合 启动子变体（n=5,392）。每个组合编辑的适合度将与预测的适合度进行比较 基于个体变异的适应性来评估不同种类的变异的程度、程度和普遍性 上位性。其次，我们通过比较自然选择如何在监管区域内塑造上位性 在自然变体簇中观察到的模式到一组对照变体。接下来我们要问上位如何 通过分析顺式调节之间所有可能的路径来限制可用于顺式调节的适应性进化的路径 完整的 BY 和 RM 基因型。最后，我们会问适应性的上位是否是基因上位的结果 表达水平。我们将使用 qRT-PCR 来量化不同组合编辑下的基因表达水平 评估自然变异之间基因表达上位性的程度和程度。这将是第一个 研究对监管区域内自然变异之间的上位性进行全基因组调查。这 这项工作对于理解遗传变异如何转化为表型变异至关重要，这与 了解人类疾病的遗传基础。