Analysis of long and short enhancers in melanoma cell states
- KU Leuven, Belgium
Abstract
Understanding how enhancers drive cell type specificity and efficiently identifying them is essential for the development of innovative therapeutic strategies. In melanoma, the melanocytic (MEL) and the mesenchymal-like (MES) states present themselves with different responses to therapy, making the identification of specific enhancers highly relevant. Using massively parallel reporter assays (MPRA) in a panel of patient-derived melanoma lines (MM lines), we set to identify and decipher melanoma enhancers by first focusing on regions with state specific H3K27 acetylation close to differentially expressed genes. An in-depth evaluation of those regions was then pursued by investigating the activity of overlapping ATAC-seq peaks along with a full tiling of the acetylated regions with 190 bp sequences. Activity was observed in more than 60% of the selected regions and we were able to precisely locate the active enhancers within ATAC-seq peaks. Comparison of sequence content with activity, using the deep learning model DeepMEL2, revealed that AP-1 alone is responsible for the MES enhancer activity. In contrast, SOX10 and MITF both influence MEL enhancer function with SOX10 being required to achieve high levels of activity. Overall, our MPRAs shed light on the relationship between long and short sequences in terms of their sequence content, enhancer activity, and specificity across melanoma cell states.
Data availability
Sequencing data have been deposited in GEO under accession codes GSE180879.Enhancer activity tables for each library is provided as source data.Scripts used for enhancer - barcode assignment, read processing and activity measurement and analysis are provided in the Scripts directory.
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Analysis of long and short enhancers in melanoma cell statesNCBI Gene Expression Omnibus, GSE180879.
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TFAP2A ChIP-seq in human primary melanocytesNCBI Gene Expression Omnibus, GSE67555.
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Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state.NCBI Gene Expression Omnibus, GSE60666.
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cisTopic: cis-regulatory topic modelling on single-cell ATAC-seq dataNCBI Gene Expression Omnibus, GSE114557.
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Cross-species analysis of melanoma enhancer logic using deep learningNCBI Gene Expression Omnibus, GSE142238.
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Single-cell analysis of gene expression variation and phenotype switching in melanomaNCBI Gene Expression Omnibus, GSE134432.
Article and author information
Author details
Jonas Demeulemeester
Funding
H2020 European Research Council (724226_cis-CONTROL)
- Stein Aerts
KU Leuven (C14/18/092)
- Stein Aerts
Fonds Wetenschappelijk Onderzoek (1S03317N)
- Liesbeth Minnoye
Fonds Wetenschappelijk Onderzoek (12J6916N)
- Jonas Demeulemeester
Kom op tegen Kanker
- Jasper Wouters
H2020 European Research Council (724226_cis-CONTROL)
- David Mauduit
H2020 European Research Council (724226_cis-CONTROL)
- Valerie Christiaens
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Jian Xu, University of Texas Southwestern Medical Center, United States
Publication history
- Received: June 28, 2021
- Preprint posted: July 27, 2021 (view preprint)
- Accepted: December 6, 2021
- Accepted Manuscript published: December 7, 2021 (version 1)
- Version of Record published: December 21, 2021 (version 2)
Copyright
© 2021, Mauduit et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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