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Enhlink infers distal and context-specific enhancer-promoter linkages.

ABSTRACT: Enhlink is a computational tool for scATAC-seq data analysis, facilitating precise interrogation of enhancer function at the single-cell level. It employs an ensemble approach incorporating technical and biological covariates to infer condition-specific regulatory DNA linkages. Enhlink can integrate multi-omic data for enhanced specificity, when available. Evaluation with simulated and real data, including multi-omic datasets from the mouse striatum and novel promoter capture Hi-C data, demonstrate that Enhlink outperfoms alternative methods. Coupled with eQTL analysis, it identified a putative super-enhancer in striatal neurons. Overall, Enhlink offers accuracy, power, and potential for revealing novel biological insights in gene regulation.

SUBMITTER: Poirion OB

PROVIDER: S-EPMC11368035 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature

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Enhlink infers distal and context-specific enhancer-promoter linkages.

Poirion Olivier B OB Zuo Wulin W Spruce Catrina C Baker Candice N CN Daigle Sandra L SL Olson Ashley A Skelly Daniel A DA Chesler Elissa J EJ Baker Christopher L CL White Brian S BS

Genome biology 20240902 1

Enhlink is a computational tool for scATAC-seq data analysis, facilitating precise interrogation of enhancer function at the single-cell level. It employs an ensemble approach incorporating technical and biological covariates to infer condition-specific regulatory DNA linkages. Enhlink can integrate multi-omic data for enhanced specificity, when available. Evaluation with simulated and real data, including multi-omic datasets from the mouse striatum and novel promoter capture Hi-C data, demonstr ...[more]

PMID: 39223609

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Enhlink infers distal and context-specific enhancer-promoter linkages.

Project description:Enhancers play a crucial role in regulating gene expression and their functional status can be queried with cell type precision using using single-cell (sc)ATAC-seq. To facilitate analysis of such data, we developed Enhlink, a novel computational approach that leverages single-cell signals to infer linkages between regulatory DNA sequences, such as enhancers and promoters. Enhlink uses an ensemble strategy that integrates cell-level technical covariates to control for batch effects and biological covariates to infer robust condition-specific links and their associated p-values. It can integrate simultaneous gene expression and chromatin accessibility measurements of individual cells profiled by multi-omic experiments for increased specificity. We evaluated Enhlink using simulated and real scATAC-seq data, including those paired with physical enhancer-promoter links enumerated by promoter capture Hi-C and with multi-omic scATAC-/RNA-seq data we generated from the mouse striatum. These examples demonstrated that our method outperforms popular alternative strategies. In conjunction with eQTL analysis, Enhlink revealed a putative super-enhancer regulating key cell type-specific markers of striatal neurons. Taken together, our analyses demonstrate that Enhlink is accurate, powerful, and provides features that can lead to novel biological insights.

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