Computational approaches for protein functional analysis using CRISPR screens

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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.