Abstract
Exonic enhancers (EEs) occupy an under-appreciated niche in gene regulation. By integrating transcription factor binding, chromatin accessibility, and high-throughput enhancer-reporter assays, we demonstrate that many protein-coding exons possess enhancer activity across species. These candidate EEs (cEEs) exhibit characteristic epigenomic signatures, form long-range interactions with gene promoters, and can be altered by both nonsynonymous and synonymous variants. CRISPR-mediated inactivation demonstrated the involvement of cEEs in the cis-regulation of host and distal gene expression. Through large-scale cancer genome analyses, we reveal that cEE mutations correlate with dysregulated target-gene expression and clinical outcomes, highlighting their potential relevance in disease. Evolutionary comparisons show that cEEs exhibit both strong sequence constraint and lineage-specific plasticity, suggesting that they serve ancient regulatory functions while also contributing to species divergence. Our findings expand the landscape of functional elements by establishing cEEs as a component of gene regulation, while revealing how coding regions can simultaneously fulfil both protein-coding and cis-regulatory roles.
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Data availability
Data supporting the findings of this study are available in a Zenodo repository (https://doi.org/10.5281/zenodo.17208730) organised by analysis block in accordance with the structure of the paper. All datasets used in this study are publicly available or have been deposited in appropriate repositories. Annotated coding exons and transcripts (human, mouse, fly, thale cress) were retrieved from UCSC and Ensembl, while FANTOM5, modENCODE, and Arabidopsis TSS data are detailed in the Methods. ChIP-seq data for exonic enhancers (ReMap2022), DNase-seq and ATAC-seq data (ENCODE, ChIP-Atlas, PlantRegMap), and STARR-seq catalogue (Supplementary Data 2 STARR-seq catalogues) were integrated to identify cEEs. G-quadruplex sequencing data (GSE110582) and the newly generated EE STARR-seq dataset (GEO accession GSE292804) were also incorporated. Cancer mutation data were obtained from the TCGA PanCanAtlas. Genomic interactions (promoter capture Hi-C), eQTLs (GTExv8), and ENCODE-rE2G mappings were used to define EE-gene relationships, while phyloP conservation scores (UCSC, PlantRegMap) and gene age classifications (Trigos etal.) further contextualised EE evolution. A genome Browser track hub containing all exonic enhancers identified in this study is available in the UCSC public hubs (https://genome.ucsc.edu/cgi-bin/hgHubConnect) and also public sessions (https://genome.ucsc.edu/cgi-bin/hgPublicSessions). Source Data are provided with this paper. Generated plasmids, reporter constructs, and CRISPRi guide sequences generated in this study are available from the corresponding author. Source data are provided with this paper.
Code availability
We deposited codes and bioinformatics environments in GitHub at (https://github.com/benoitballester/ExonEnhancer) and in Zenodo (https://doi.org/10.5281/zenodo.18255062). Both data and codes are publicly available for the replication of the whole study.
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Acknowledgements
The authors thank Robin Steinhaus for his assistance with fabian-tools and lifting the VCF query capacity. We also appreciate Science AAAS for granting permission to reproduce and modify the PanCanAtlas schema in Fig. 5c. This work was supported by a PhD Fellowship awarded to J.-C.M. from the French Ministry of Higher Education and Research (MESR), Institut National de la Santé et de la Recherche Médicale (INSERM), the Core Cluster of the Institut Français de Bioinformatique (IFB; ANR-11-INBS-0013), and by the Agence Nationale pour la Recherche (ANR; grant ANR-23-CE12-0008-01). A Marie Sklodowska-Curie Action postdoctoral fellowship (Eprom-101065610) supported A.V.O. We acknowledge the contribution of AniRA lentivectors production facility from the CELPHEDIA Infrastructure and SFR Biosciences (UAR3444/CNRS, US8/Inserm, ENS de Lyon, UCBL), especially Gisèle Froment, Aurélie Thibaut and Caroline Costa. We thank the Marseille-Luminy cell biology platform for managing cell culture and Nori Sadouni from HL BIOPROCESS (Marseille, France) for the STARR-seq preprocessing. The results presented here are based on data generated by the TCGA Research Network, the GTEx project, the ENCODE Consortium and its production laboratories, as well as independent laboratories that submitted raw ChIP-seq and other omics datasets to public repositories (GEO). We thank Andreas Zanzoni for a helpful discussion about protein disorder.
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B.B. conceived and supervised the project. J-C.M. developed computational methods, curated ATAC-seq, DNase I, and STARR-seq datasets, and performed data analysis. M.T. and F.G. carried out luciferase reporter assays. I.M. and M.T. conducted CRISPRi experiments. A.V.O. performed STARR-seq assays and selected and designed CRISPRi guides. S.S. supervised STARR-seq and CRISPRi experiments. J-C.M. and B.B. prepared the figures, and J-C.M., S.S., and B.B. wrote the manuscript with input from all authors.
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Mouren, JC., Torres, M., van Ouwerkerk, A. et al. Exonic enhancers are a widespread class of dual-function regulatory elements. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71220-6
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DOI: https://doi.org/10.1038/s41467-026-71220-6
