Scalable variant-to-function screens using prime editing perturb-seq
- 1Relation Therapeutics
Abstract
Linking genetic variants to their functional consequences at scale remains a major challenge in human genetics. Perturb-seq is limited in the variants it can install, while prime editing has largely been restricted to simpler mechanistic readouts. Here, we introduce prime editing perturb-seq (PEP-seq), which links programmed mutations to transcriptomic states. We designed 2,164 prime editing guides targeting common expression quantitative trait loci (eQTLs), premature termination codons, and position-matched synonymous controls, generating 749,110 time-resolved single-cell transcriptomes. PEP-seq precisely detected nonsense-mediated decay, while probe-based junction measurements suggested depletion of mature RNAs. For eQTLs, a locus-size-corrected specificity metric showed that the intended target was frequently the most affected transcript within a 1 Mb window, with effects also associated with open chromatin near the edit site. These results establish PEP-seq as a scalable platform for direct, endogenous variant-to-function mapping.
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BibTeX
@misc{jonghe2026scalable,
title = {{Scalable variant-to-function screens using prime editing perturb-seq}},
author = {J. De Jonghe and M. Armas Reyes and C. Jamieson and J. B. Christensen and J. W. Opzoomer and J. P. Taylor-King},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.28.762453},
url = {https://www.biorxiv.org/content/10.64898/2026.10.28.762453v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Scalable variant-to-function screens using prime editing perturb-seq
AU - J. De Jonghe
AU - M. Armas Reyes
AU - C. Jamieson
AU - J. B. Christensen
AU - J. W. Opzoomer
AU - J. P. Taylor-King
PY - 2026
DA - 2026/10/28
PB - bioRxiv
DO - 10.64898/2026.10.28.762453
UR - https://www.biorxiv.org/content/10.64898/2026.10.28.762453v1
AB - Linking genetic variants to their functional consequences at scale remains a major challenge in human genetics. Perturb-seq is limited in the variants it can install, while prime editing has largely been restricted to simpler mechanistic readouts. Here, we introduce prime editing perturb-seq (PEP-seq), which links programmed mutations to transcriptomic states. We designed 2,164 prime editing guides targeting common expression quantitative trait loci (eQTLs), premature termination codons, and position-matched synonymous controls, generating 749,110 time-resolved single-cell transcriptomes. PEP-seq precisely detected nonsense-mediated decay, while probe-based junction measurements suggested depletion of mature RNAs. For eQTLs, a locus-size-corrected specificity metric showed that the intended target was frequently the most affected transcript within a 1 Mb window, with effects also associated with open chromatin near the edit site. These results establish PEP-seq as a scalable platform for direct, endogenous variant-to-function mapping.
ER -