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Cited by 48Genomics and Chromatin DynamicsChromatin Remodeling and CancerGenetic Associations and Epidemiology

Interpretation of allele-specific chromatin accessibility using cell state–aware deep learning

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Atak, Zeynep Kalender, Taskiran, Ibrahim Ihsan, Demeulemeester, Jonas, Flerin, Christopher, Mauduit, David, Minnoye, Liesbeth, Hulselmans, Gert, Christiaens, Valerie +3 more·2021·Genome Research
DOI 10.1101/gr.260851.120PMC PMC8168584

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Abstract

Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or a cancer genome, to identify those that impact cis -regulatory function, remains a major challenge. Interpretation of noncoding genome variation benefits from explainable artificial intelligence to predict and interpret the impact of a mutation on gene regulation. Here we generate phased whole genomes with matched chromatin accessibility, histone modifications, and gene expression for 10 melanoma cell lines. We find that training a specialized deep learning model, called DeepMEL2, on melanoma chromatin accessibility data can capture the various regulatory programs of the melanocytic and mesenchymal-like melanoma cell states. This model outperforms motif-based variant scoring, as well as more generic deep learning models. We detect hundreds to thousands of allele-specific chromatin accessibility variants (ASCAVs) in each melanoma genome, of which 15%–20% can be explained by gains or losses of transcription factor binding sites. A considerable fraction of ASCAVs are caused by changes in AP-1 binding, as confirmed by matched ChIP-seq data to identify allele-specific binding of JUN and FOSL1. Finally, by augmenting the DeepMEL2 model with ChIP-seq data for GABPA, the TERT promoter mutation, as well as additional ETS motif gains, can be identified with high confidence. In conclusion, we present a new integrative genomics approach and a deep learning model to identify and interpret functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.

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  • CNN-based enhancer modeling has recently gained traction due to its capacity for interpretation of enhancer grammar.

    “CNN-based enhancer modeling has recently gained traction, due to their capacity for the interpretation of enhancer grammar 12,19,20,74”

    From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [74]

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Cited by

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Authors
Atak, Z. K., Taskiran, I. I., Demeulemeester, J., Flerin, C., Mauduit, D., Minnoye, L., Hulselmans, G., Christiaens, V., Ghanem, G.-E., Wouters, J., & Aerts, S.
Affiliations
  • VIB-KU Leuven Center for Brain & Disease Research (BE)
  • The Francis Crick Institute (GB)
  • Université Libre de Bruxelles (BE)
Corresponding author
Aerts, Stein
ORCID
Venue
Genome Research
Publisher
Cold Spring Harbor Laboratory
Published
2021-04-08
Volume
31
Issue
6
Pages
1082-1096
ISSN
  • 1088-9051 (ISSN-L)
  • 1549-5469
DOI
10.1101/gr.260851.120
PMC
PMC8168584
OpenAlex
W3146159774
Cited by
48
References
13
Citations by year
2026: 8 · 2025: 7 · 2024: 5 · 2023: 9 · 2022: 14 · 2021: 5
Type
posted content
Language
en
Open access
Licence
other-oa
Locations
  • Genome Research (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Lirias (KU Leuven) (submittedVersion, other-oa)
  • Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
Funders
  • European Research Council (724226_cis-CONTROL)
  • KU Leuven (C14/18/092)
  • Foundation Against Cancer (2016-070)
  • Fonds Wetenschappelijk Onderzoek (1S03317N, 12J6916N)
  • Kom op tegen Kanker
  • Flemish Cancer Society
  • Stichting tegen Kanker
  • Vlaams Supercomputer Center
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
melanoma, explainable AI, enhancer mutations, transcription factor binding sites, c-Jun, FOSL1, GABPA, TERT promoter mutation, histone modifications, gene expression, allelic imbalance
MeSH terms
Deep Learning, Alleles, Artificial Intelligence, Chromatin, Promoter Regions, Genetic

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