Rewriting regulatory DNA to dissect and reprogram gene expression

Gabriella E Martyn; Michael T Montgomery; Hank Jones; Katherine Guo; Benjamin R Doughty; Johannes Linder; Deepa Bisht; Fan Xia; Xiangmeng S Cai; Ziwei Chen; Kelly Cochran; Kathryn A Lawrence; Glen Munson; Anusri Pampari; Charles P Fulco; Nidhi Sahni; David R Kelley; Eric S Lander; Anshul Kundaje; Jesse M Engreitz

doi:10.1016/j.cell.2025.03.034

Rewriting regulatory DNA to dissect and reprogram gene expression

Cell. 2025 Jun 12;188(12):3349-3366.e23. doi: 10.1016/j.cell.2025.03.034. Epub 2025 Apr 16.

Authors

Gabriella E Martyn¹, Michael T Montgomery¹, Hank Jones¹, Katherine Guo¹, Benjamin R Doughty², Johannes Linder³, Deepa Bisht⁴, Fan Xia¹, Xiangmeng S Cai⁵, Ziwei Chen⁶, Kelly Cochran⁶, Kathryn A Lawrence², Glen Munson⁷, Anusri Pampari⁶, Charles P Fulco⁸, Nidhi Sahni⁹, David R Kelley³, Eric S Lander¹⁰, Anshul Kundaje¹¹, Jesse M Engreitz¹²

Affiliations

¹ Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA.
² Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
³ Calico Life Sciences LLC, South San Francisco, CA 94080, USA.
⁴ Department of Genitourinary Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA.
⁵ Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
⁶ Department of Computer Science, Stanford University, Stanford, CA 94305, USA.
⁷ Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
⁸ Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
⁹ Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA; Quantitative and Computational Biosciences Program, Baylor College of Medicine, Houston, TX 77030, USA.
¹⁰ Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Biology, MIT, Cambridge, MA 02139, USA; Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.
¹¹ Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA.
¹² Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: engreitz@stanford.edu.

PMID: 40245860
PMCID: PMC12167154 (available on 2026-06-12)
DOI: 10.1016/j.cell.2025.03.034

Abstract

Regulatory DNA provides a platform for transcription factor binding to encode cell-type-specific patterns of gene expression. However, the effects and programmability of regulatory DNA sequences remain difficult to map or predict. Here, we develop variant effects from flow-sorting experiments with CRISPR targeting screens (Variant-EFFECTS) to introduce hundreds of designed edits to endogenous regulatory DNA and quantify their effects on gene expression. We systematically dissect and reprogram 3 regulatory elements for 2 genes in 2 cell types. These data reveal endogenous binding sites with effects specific to genomic context, transcription factor motifs with cell-type-specific activities, and limitations of computational models for predicting the effect sizes of variants. We identify small edits that can tune gene expression over a large dynamic range, suggesting new possibilities for prime-editing-based therapeutics targeting regulatory DNA. Variant-EFFECTS provides a generalizable tool to dissect regulatory DNA and to identify genome editing reagents that tune gene expression in an endogenous context.

Keywords: CRISPR; RNA FlowFISH; enhancers; gene regulation; high-throughput screening; non-coding variants; predictive models; prime editing; sequence design; transcription factors.

MeSH terms

Animals
Binding Sites
CRISPR-Cas Systems
Clustered Regularly Interspaced Short Palindromic Repeats
DNA* / genetics
DNA* / metabolism
Gene Editing* / methods
Gene Expression Regulation*
HEK293 Cells
Humans
Mice
Regulatory Sequences, Nucleic Acid* / genetics
Transcription Factors / metabolism

Substances

DNA
Transcription Factors

Abstract

MeSH terms

Substances

Grants and funding