Scalable, quantitative, single-cell CRISPR screens

可扩展、定量、单细胞 CRISPR 筛选

基本信息

项目摘要

PROJECT SUMMARY Numerous large sequencing initiatives have produced catalogs of human genetic diversity. A major obstacle in using these data to better understand health and disease is the vast scale of the human genome: for example, there are ~22,000 protein coding genes, millions of candidate regulatory elements, and tens of millions of common variants. This challenge has motivated the development of increasingly refined functional genomics tools that enable many distinct hypotheses to be tested in parallel. For example, CRISPR screening libraries enable every gene in the genome to be systematically knocked out, activated, or knocked down, providing a means of testing how connect genes to phenotype. Though highly successful, these approaches are in one sense rather wasteful: quantification usually amounts to counting the representation of the sgRNAs mediating the perturbations by sequencing, meaning thousands of cells per gene are often used in practice to ensure statistical power. This simple constraint means that screens are often conducted in only a handful of conditions, limits applications to precious cell types such as patient samples, and makes scaling to larger problems difficult. Here we leverage the explosion of recent innovation that has accompanied the popularization of single-cell RNA sequencing to revisit the task of conducting CRISPR screens. We propose Quantitative Reporter Sequencing (QRS), a highly scalable and highly quantitative approach for connecting CRISPR-mediated genetic perturbations to their effects on an engineered phenotypic reporter in pooled format. Using a simple library prep protocol that requires no special instruments, QRS enables CRISPR screens with single-cell resolution and absolute quantification of phenotype. Each cell therefore serves as an independent replicate measurement, reducing cell input requirements and enabling the measurement of distributions of phenotype for each perturbation rather than average effects. Through applications we demonstrate how this approach can be used to conduct highly sensitive screens for weak effects in precious cell types, to efficiently quantify genetic interactions (i.e. emergent effects of perturbing multiple genes simultaneously), and to guide the search for drivers of incompletely penetrant phenotypes. This platform will extend CRISPR-mediated functional genomics to contexts and cell types that are currently intractable and enable experiments that are “beyond genome-scale.”
项目摘要 许多大型测序计划已经产生了人类遗传多样性的目录。的主要障碍 使用这些数据来更好地了解健康和疾病是人类基因组的巨大规模:例如, 大约有22,000个蛋白质编码基因,数百万个候选调控元件,以及数千万个 常见变体这一挑战促使功能基因组学的发展日益完善 工具,使许多不同的假设进行测试并行。例如,CRISPR筛选文库 使基因组中的每一个基因都能被系统地敲除、激活或敲低, 测试基因与表现型之间联系的方法。虽然非常成功,但这些方法是一个 有意义的,而不是浪费:定量通常相当于计数的代表性的sgRNA介导的 测序的干扰,意味着每个基因数千个细胞,在实践中经常被用来确保 统计力量这个简单的限制意味着筛选通常只在少数几个国家进行, 条件下,限制应用于珍贵的细胞类型,如患者样本,并使规模更大, 困难的问题。在这里,我们利用了最近的创新爆炸,伴随着 单细胞RNA测序的普及,以重新审视进行CRISPR筛选的任务。我们提出 定量报告基因测序(QRS),一种高度可扩展和高度定量的方法, CRISPR介导的遗传扰动对合并形式的工程化表型报告基因的影响。 使用简单的库准备协议,不需要特殊的仪器,QRS使CRISPR屏幕, 单细胞分辨率和表型的绝对定量。因此,每个细胞都是独立的 重复测量,减少电池输入要求,并能够测量 表型的每一个扰动,而不是平均效果。通过应用程序,我们演示了如何 这种方法可以用于在珍贵的细胞类型中进行高灵敏度的筛选,以有效地 量化遗传相互作用(即同时干扰多个基因的紧急影响),并指导 寻找不完全渗透表型的驱动因素。该平台将扩展CRISPR介导的 功能基因组学的背景和细胞类型,目前是棘手的,并使实验, “超越基因组规模”

项目成果

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Thomas Maxwell Norman其他文献

Thomas Maxwell Norman的其他文献

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{{ truncateString('Thomas Maxwell Norman', 18)}}的其他基金

Scalable, quantitative, single-cell CRISPR screens
可扩展、定量、单细胞 CRISPR 筛选
  • 批准号:
    10675047
  • 财政年份:
    2022
  • 资助金额:
    $ 26.55万
  • 项目类别:
Predictive engineering of cellular transcriptional state
细胞转录状态的预测工程
  • 批准号:
    10001677
  • 财政年份:
    2020
  • 资助金额:
    $ 26.55万
  • 项目类别:

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