# Towards Robust Multiplex Genome Engineering Beyond CRISPR-Cas9 > **NIH NIH R35** · STANFORD UNIVERSITY · 2021 · $393,625 ## Abstract Supplement Application Abstract Towards Robust Multiplex Genome Engineering Beyond CRISPR-Cas9 Recent genome-wide association studies on Alzheimer’s Diseases (AD) and related dementias have provided a rich resource of AD risk genes and variants. While this bounty of information is poised to transform neurodegeneration research, we need tools to identify and validate their functions. Genome engineering tools such as CRISPR-Cas9 are valuable for such validation, allowing precise editing of AD-related genomic variants. However, current genetic engineering approaches are limited in efficiency, scalability, and have unwanted editing errors that could confound validation experiments. Moreover, we need tools with robust activities in challenging neuroscience models, beyond editing a few cell lines. Hence, building on our existing NHGRI-funded work, we will use innovative genome technologies for studying AD and related dementias, in collaboration with experts at the Stanford Alzheimer's Disease Research Center (ADRC). Firstly, we will use computational simulation with experimentation to develop precision tools to edit human risk variants in AD models. We will leverage and further develop our novel CRISPR enzymes and RNA-to-DNA editing tools that we recently established based on work from the parent award (JACS. 2019). Secondly, we are developing error- free gene-editors via mining metagenomic recombination enzymes. These error-free gene-editors are capable of engineering up to multi-kilobase sequences in human stem cells and neurons (Wang et al., under review). We will use this accurate gene-editing methods to engineer large AD risk alleles in neurodegeneration models, and, working with expert collaborators, demonstrate in vivo editing. Thirdly, we are developing Turbo-seq, a single-cell perturb-seq platform leveraging machine-learning algorithms and our multi-target CRISPR screen tool for AD studies (Hughes et al., submitted). We will apply Turbo-seq to simultaneously engineer single and multiple AD-associated variants in relevant disease models, with an initial focus on APOE alleles and related protective (or causal) variants. We will determine the functional consequences when genetically engineering these AD variants compared with healthy controls, integrating single-cell profiling of RNAs and proteins. Our multi-target, scalable CRISPR tools will significantly accelerate functional study of neurodegeneration variants when considering the large number of candidates, existing and from our collaborators’ work with the Stanford Extreme Phenotypes in AD (StEP AD) cohort, and help identify potential interactions between risk alleles. Overall, our plan is to build a gene-editing and single-cell toolkit, with an accompanying data- analysis pipeline for neurodegeneration research, thereby expanding the parent award’s tool-building and resource-sharing efforts into this new focus with the supplement. ## Key facts - **NIH application ID:** 10287896 - **Project number:** 3R35HG011316-02S1 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** Le Cong - **Activity code:** R35 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $393,625 - **Award type:** 3 - **Project period:** 2020-09-01 → 2025-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10287896 ## Citation > US National Institutes of Health, RePORTER application 10287896, Towards Robust Multiplex Genome Engineering Beyond CRISPR-Cas9 (3R35HG011316-02S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10287896. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*