Spatial-scERA: a method for reconstructing spatial single-cell enhancer activity in multicellular organisms

Enhancers play an essential role in developmental processes by regulating the spatiotemporal expression of genes. Characterizing their spatiotemporal activity remains however an important challenge. Here we introduce a novel in vivo/in silico method for spatial single-cell enhancer-reporter assays (spatial-scERA) designed to reconstruct the spatial activity of candidate enhancer regions in parallel in multicellular organisms. Spatial-scERA integrates parallel reporter assays with single-cell RNA sequencing and spatial reconstruction using optimal transport, to map cell-type-specific enhancer activity at the single-cell level on a 3D virtual sample. We evaluated spatial-scERA in Drosophila embryos using 25 candidate enhancers, and validated the robustness of our reconstructions by comparing them to in situ hybridization. Remarkably, spatial-scERA faithfully reconstructed the spatial activity of these enhancers, even when the reporter construct was expressed in as few as 10 cells. Our results demonstrate the importance of integrating transcriptomic and spatial data for accurately predicting enhancer activity patterns in complex multicellular samples and linking enhancers to their potential target genes. Overall, spatial-scERA provides a scalable approach to map the spatial activity of enhancers at single-cell resolution without the need for imaging or a priori knowledge of embryology and can be applied to any multicellular organism amenable to transgenesis.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-07-19
DOI
https://doi.org/10.1093/nar/gkaf684
Citations
1
Primary Topic
14-3-3 protein interactions
Type
article
Field-Weighted Citation Impact
0.81

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article

Spatial-scERA: a method for reconstructing spatial single-cell enhancer activity in multicellular organisms

Damien Lajoignie, Sergio Sarnataro, Yad Ghavi-Helm, Hélène Tarayre et al.
1 citations
Nucleic Acids Research
14-3-3 protein interactions
0.81
article

Spatial-scERA: a method for reconstructing spatial single-cell enhancer activity in multicellular organisms

Damien Lajoignie, Sergio Sarnataro, Yad Ghavi-Helm, Hélène Tarayre, José João Mendes, Séverine Vincent, Paul Villoutreix, Isabelle Stévant, Baptiste Alberti
article en
1 citations

Abstract

Enhancers play an essential role in developmental processes by regulating the spatiotemporal expression of genes. Characterizing their spatiotemporal activity remains however an important challenge. Here we introduce a novel in vivo/in silico method for spatial single-cell enhancer-reporter assays (spatial-scERA) designed to reconstruct the spatial activity of candidate enhancer regions in parallel in multicellular organisms. Spatial-scERA integrates parallel reporter assays with single-cell RNA sequencing and spatial reconstruction using optimal transport, to map cell-type-specific enhancer activity at the single-cell level on a 3D virtual sample. We evaluated spatial-scERA in Drosophila embryos using 25 candidate enhancers, and validated the robustness of our reconstructions by comparing them to in situ hybridization. Remarkably, spatial-scERA faithfully reconstructed the spatial activity of these enhancers, even when the reporter construct was expressed in as few as 10 cells. Our results demonstrate the importance of integrating transcriptomic and spatial data for accurately predicting enhancer activity patterns in complex multicellular samples and linking enhancers to their potential target genes. Overall, spatial-scERA provides a scalable approach to map the spatial activity of enhancers at single-cell resolution without the need for imaging or a priori knowledge of embryology and can be applied to any multicellular organism amenable to transgenesis.

Nucleic Acids ResearchVol. 53(14)
Université Claude Bernard Lyon 1 (FR), Institut de Génomique Fonctionnelle de Lyon (FR), Living Systems (United States) (US)
Equipex, Agence Nationale de la Recherche, Fondation pour la Recherche Médicale
Openalex Percentile: Top 26%
14-3-3 protein interactions
0.81
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