Scalable variant-to-function screens using prime editing perturb-seq

De Jonghe, J.; Armas Reyes, M.; Jamieson, C.; Christensen, J. B.; Opzoomer, J. W.; Taylor-King, J. P.

doi:10.64898/2026.10.28.762453

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bioRxiv · 10.64898/2026.10.28.762453

Scalable variant-to-function screens using prime editing perturb-seq

De Jonghe, J.·Armas Reyes, M.·Jamieson, C.·Christensen, J. B.·Opzoomer, J. W.·Taylor-King, J. P.

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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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De Jonghe, J., Armas Reyes, M., Jamieson, C., Christensen, J. B., Opzoomer, J. W., Taylor-King, J. P.. 2026-10-28. Scalable variant-to-function screens using prime editing perturb-seq. https://doi.org/10.64898/2026.10.28.762453

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