Computational approaches for protein functional analysis using CRISPR screens

摘要 高通量生物技术的发展高度依赖于相关的计算方法， 系统优化和数据分析。另一方面，生物信息学方法的发展 需要深入了解生物系统和实验方案。远景目标 我们实验室的目标是开发可以与高通量无缝集成的计算方法 实验，以解决生物学问题，重点是转录和表观遗传调控。 了解蛋白质的功能是生物学的一个基本目标。CRISPR筛选的最新进展 技术已经使蛋白质的功能研究以高通量的方式，导致新的发现 超出了传统方法的能力。未来五年，我们的短期目标是发展 解决方案，以提高高通量CRISPR筛选用于蛋白质功能分析的利用率。实现 为此，我们提出三个研究课题： 1)预测CRSIPR筛选中改进的sgRNA文库设计的sgRNA敲除效应。这将 解决CRISPR筛选设计中的生物信息学需求; 2)使用CRISPR平铺-sgRNA筛选的蛋白质结构域分析。这将导致创新的解决方案， 蛋白质结构域和结构的研究。 3)从CRISPR筛选和组学数据推断转录调控网络。这会导致 开发新的方法来解决涉及蛋白质-蛋白质相互作用的开放性问题， 转录因子和表观遗传调节因子的调节。 总的来说，拟议的项目将有助于新的方法，以丰富蛋白质功能的工具箱 分析，并将提供新的见解转录和表观遗传调控领域。

Abstract The development of a high-throughput biotechnology highly relies on relevant computational methods for systematic optimization and data analysis. On the other hand, the development of bioinformatics methods requires in-depth understanding of the biological systems and the experimental protocols. The long-term goal of our lab is to develop computational methods that can be seamlessly integrated with high-throughput experiments to address biological questions, with a focus on transcriptional and epigenetic regulations. Understanding protein functions is a fundamental aim in biology. The recent advances of CRISPR screening techniques have enabled functional studies of proteins in a high-throughput manner, leading to novel discoveries beyond the capacity of traditional methods. During the next five years, our short-term goal is to develop solutions to boost the utilization of high-throughput CRISPR screens for protein functional analysis. To achieve this goal, we propose three research topics: 1) Prediction of sgRNA knockout effects for improved sgRNA library design in CRSIPR screens. This will address the bioinformatics needs in the design of CRISPR screens; 2) Protein domain analysis using CRISPR tiling-sgRNA screens. This will lead to innovative solutions for the studies of protein domain and structure. 3) Inference of transcriptional regulatory networks from CRISPR screen and -omic data. This will lead to the development of new methodology to address an open problem involving protein-protein interactions and regulations of transcription factors and epigenetic regulators. Collectively, the proposed project will contribute new methods to enrich the toolbox for protein functional analysis, and will provide novel insights into the fields of transcriptional and epigenetic regulations.