CAREER: Molecular mechanisms, algorithms and software for design and analysis of genome perturbation experiments

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Genome editing technology using CRISPR (which stands for Clustered Regularly Interspaced Short Palindromic Repeats) has transformed life sciences and is among the most influential inventions in modern biology. CRISPR can be used for guided edits of selected genomic targets. Multiple variants and extensions of CRISPR are actively being used by researchers for editing, knockout, activation and inhibition of genes and genomic elements for studying cell function and identification of important cellular regulators. Computational algorithms and software for experimental design are essential for continued successful use of the CRISPR technologies. However, fundamental molecular mechanisms and optimal parameters of efficient and targeted use of CRISPR technologies across entire genomes are not fully characterized. Limitations in current computational methods for design and analysis of CRISPR experiments include lack of complete unbiased genome-wide information about CRISPR off-targets across biological and experimental contexts, across cell types and across CRISPR variants; lack of specificity to genomes and genomic variants across individuals, cohorts and populations; and incomplete understanding of biases in results of CRISPR experiments caused by off-targets. These limitations present barriers for wider adoption of CRISPR technologies in life sciences and biomedicine. This project is devoted to overcoming these limitations and developing new computational methodology for design and analysis of CRISPR experiments. Fully integrated with this research plan, an educational and outreach program will be developed in order to involve undergraduate and high school students into open collaborative computational biology research. This work will substantially lower the bar for using CRISPR technologies across a wide range of applications and will inform the development of the next generation of such technologies. Implementation of this educational and outreach plan will make entering research careers in bioinformatics and computational biology substantially more accessible for the next generation of students, and will encourage wet lab biologists to obtain computational biology training and to productively collaborate with computational scientists.The goal of this project is to address major challenges in CRISPR low- and high-throughput experimental design and analysis via a combination of computational and experimental approaches. New high-throughput cell type-specific data on genome-wide CRISPR guide RNA on-target and off-target efficiency will be generated and then aggregated into new models of CRISPR efficiency and specificity. New algorithms and software will be developed for generalizable and customizable design, analysis and interpretation of CRISPR genome perturbation experiments across contexts, by incorporating results of the analysis of the newly generated experimental data. Integrated with this research, an educational and outreach program and a specially designed online platform will involve undergraduate and high school students into open collaborative computational biology research, with specific introductory set of research problems about design and analysis of CRISPR experiments. All the results from this project will be available at https://pritykinlab.github.io/This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.