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Increasing the throughput of variant classification with multiplexed prime editing and single cell long-read technologies

Award Number: F31HG014981
ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: FELLOWSHIP/SCHOLARSHIP/STUDENT LOANS
PERIOD OF PERFORMANCE START DATE: 06/01/2026
PERIOD OF PERFORMANCE END DATE: 05/31/2028

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Increasing the throughput of variant classification with multiplexed prime editing and single cell long-read technologies - PROJECT SUMMARY In genetic medicine, variants of uncertain significance (VUS) have posed a significant challenge. These variants, identified through genetic testing, are alterations in one's DNA sequence that cannot be definitively classified as benign or pathogenic. Approximately 80% of missense variants in the ClinVar database are classified as VUS. In clinical care, a VUS result frequently prevents clinicians from providing definitive diagnoses, limits treatment options, and causes uncertainty for patients and their families. Resolving VUS is thus essential to improve patient care in genetic medicine. Multiplexed Assays of Variant Effect (MAVEs) offer a high-throughput solution to VUS resolution by assessing variant effect for thousands of variants in vitro simultaneously. However, there are two limitations to realizing the potential of MAVEs to resolve VUS at scale. First, it is challenging to introduce a comprehensive set of variants into cells at scale, and second, MAVEs have historically relied on a small set of function assays, such as proliferation or survival-based assays, limiting the number of genes that can be investigated. This proposal aims to address both of these limitations, using CHD2 as a model gene, but developing techniques that could be applied to hundreds of clinically relevant genes. We will first advance high-throughput endogenous genome editing through the development of a suite of computational and experimental tools for prime editing. While prime editing offers a precise and versatile approach, it is plagued by low editing efficiencies. To address these shortcomings, we will develop a computational pipeline to design prime editing guide RNA (pegRNA) libraries with high predicted editing efficiency, an optimized cell line for editing, and a FACS-based approach to enrich for edited cells. We expect that such tools will boost prime editing efficiency for multiplexed cell libraries and thereby increase the efficiency of MAVEs. We will also address the limited set of functional assays for MAVEs. Here we propose scAVER-seq: a widely applicable and scalable single-cell Assay of Variant Effect using RNA-sequencing. This technique will combine transcript capture and long-read technology in single cells to identify each cell’s introduced variant and link it to its corresponding transcriptome in a single-tube workflow. By using the transcriptome as a functional readout, we will revolutionize variant classification in disorders associated with robust transcriptional effects, such as those caused by pathogenic variants in regulators of gene expression. This approach could help resolve the over 500,000 VUS that exist in gene expression regulators, which comprise 31% of all VUS in ClinVar. By developing generalizable methods to characterize VUS, we aim to contribute to the NHGRI's mission of understanding the impact of genomic variation on human health and simultaneously help deliver answers to families facing genetic testing results reporting VUS.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $50,114 )
2026	2026	NORTHWESTERN UNIVERSITY	633 CLARK ST	EVANSTON	IL	60208	COOK	USA	Human Genome Research	001	1	4/28/2026	NEW	$0
2026	2026	NORTHWESTERN UNIVERSITY	633 CLARK ST	EVANSTON	IL	60208	COOK	USA	Human Genome Research	000	1	4/28/2026	NEW	$50,114
														Subtotal = $50,114

Grand Total All Awards = $50,114

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Increasing the throughput of variant classification with multiplexed prime editing and single cell long-read technologies

Award Number: F31HG014981

ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: FELLOWSHIP/SCHOLARSHIP/STUDENT LOANS

PERIOD OF PERFORMANCE START DATE: 06/01/2026

PERIOD OF PERFORMANCE END DATE: 05/31/2028

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