# Linking GWAS variants to function with single-cell pooled CRISPR screens

> **NIH NIH K99** · NEW YORK GENOME CENTER · 2024 · $17,600

## Abstract

PROJECT SUMMARY/ABSTRACT
Genome-wide association studies (GWAS) have identified thousands of common and rare genetic variants
associated with complex traits and common diseases. Most variants map to the 98% of the genome that is
noncoding, with their target genes or function largely unknown. This is the variant-to-function problem (V2F), and
solving it remains a major hurdle in human genetics research. To help solve V2F, I propose to develop modular
workflows combining GWAS variant prioritization methods and pooled single-cell CRISPR screens for target
gene identification. I have developed an integrative approach combining highly polygenic blood trait GWASs and
pooled single-cell CRISPR inhibition (CRISPRi) screens in a human erythroid progenitor cell model (K562), to
identify target genes: Systematic Targeting and Inhibition of Noncoding GWAS loci with single-cell sequencing
(STING-seq). STING-seq can functionally dissect multiple GWAS loci in a massively parallel fashion, identifying
target genes in cis as well as trans-regulatory networks. Here, I will develop STING-seq further and examine its
generalizability for other GWAS traits and their cell models. First, I will expand STING-seq with precise variant
insertion, developing base editing STING-seq (Bee-STING) for high-throughput measurements of GWAS variant
effects on target genes and regulatory networks. Second, I will develop modular workflows for GWAS variant
prioritization for STING-seq, targeting sets of variants with distinct selection criteria to increase STING-seq’s
target gene and regulatory network discovery rate. Third, I will focus STING-seq on new GWAS traits and cell
models to examine its generalizability, first piloting STING-seq for another highly polygenic complex trait, bone
mineral density, with a human osteoblast cell model (hFOB). In the long-term, these aims will help solve V2F for
human genetics research, as their continued development and application will improve our understanding of how
GWAS variants causally influence complex traits and common diseases. I have a comprehensive training plan
in place with my primary mentors, Dr. Neville Sanjana (genome engineering) and Dr. Tuuli Lappalainen (gene
regulation), my mentorship committee members, Dr. David Knowles (machine learning), Dr. Aravinda
Chakravarti (human genetics), Dr. Charles Farber (bone biology), and my collaborator Dr. Eugene Katsevich
(statistical methods). This plan will continue my training in dissecting GWAS variant function with multiple
computational and experimental approaches, along with additional training in grant writing, mentoring students,
teaching courses, and presenting at research conferences. The full mentorship committee will direct me to
pertinent literature, offer advice on my research program, and provide guidance as I navigate the academic job
market. The New York Genome Center is the ideal training location for me, given its cutting-edge facilities,
plentiful opportunities for career a...

## Key facts

- **NIH application ID:** 10789977
- **Project number:** 5K99HG012792-02
- **Recipient organization:** NEW YORK GENOME CENTER
- **Principal Investigator:** John Allan Morris
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $17,600
- **Award type:** 5
- **Project period:** 2023-02-16 → 2024-03-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10789977

## Citation

> US National Institutes of Health, RePORTER application 10789977, Linking GWAS variants to function with single-cell pooled CRISPR screens (5K99HG012792-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10789977. Licensed CC0.

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