Next-generation Functional Genetic Screening of Un-screenable Traits

项目摘要/摘要 随着DNA测序的快速发展，我们现在有了一个近乎完整的人类基因组，相当 全面的生殖系和体细胞变异目录，以及丰富的功能基因组注释 元素。该领域的下一个挑战是获得遗传变异和 在细胞和生物水平上的基因组元素。基因组编辑技术，特别是 CRISPR/Cas9系统，使基因组能够快速和精确地修改，并将这些连接到 功能结果。然而，目前所有的高通量筛选方法都依赖于能够 与细胞存活、细胞成像、荧光细胞分选或亲和力增强相结合。基因变异 有更微妙的表型后果，这可能代表大多数人，不服从这样的 屏幕。此外，通过对单个细胞系的体外分析，筛选自然遗传变异 培养条件的吞吐量也是有限的，可能会错过取决于具体情况的功能差异 生理环境。在这个项目中，我们寻求开发下一代功能性基因筛查 方法，可以克服这些当前的限制。利用诱导多能干细胞分化作为一种 样例模型系统，我们将开发和演示我们的集成实验和计算 实现编码和非编码基因组的全面和整体功能筛选的方法学 元素。我们预计我们的平台将极大地加速基因变体的功能注释，包括 许多未知意义的变种，横跨各种正常和疾病的细胞类型和组织。

Project Summary/Abstract With the rapid advances in DNA sequencing, we now have a near-complete human genome, a fairly comprehensive catalog of germline and somatic variants, as well as rich annotations of functional genomic elements. The next challenge in the field is to obtain a complete functional annotation of genetic variants and genomic elements at the cellular and organismal levels. Genome editing technology, in particularly the CRISPR/Cas9 system, has allowed rapid and precise modifications of the genome and connecting of these to functional outcomes. However, all current high-throughput screening approaches rely on phenotypes that can be coupled to cell survival, cell imaging, fluorescent cell sorting, or affinity enrichments. Genetic variants that have more subtle phenotypic consequences, which might represent the majority, are not amenable to such screens. Furthermore, screening of natural genetic variation via assaying of individual cell lines under in vitro culture conditions also has limited throughput and might miss functional differences that depend on specific physiological contexts. In this project we seek to develop a next-generation functional genetic screening method that can overcome these current limitations. Utilizing induced pluripotent stem cell differentiation as an exemplar model system, we will develop and demonstrate our integrated experimental and computational methodology to enable comprehensive and en masse functional screening of coding and non-coding genomic elements. We expect our platform will greatly accelerate the functional annotation of genetic variants, including many variants of unknown significance, across various normal and diseased cell types and tissues.