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An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila

Wolfe, Jareth C and Mikheeva, Liudmila A and Hagras, Hani and Zabet, Nicolae Radu (2021) 'An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila.' Genome Biology, 22 (1). 308-. ISSN 1474-7596

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Abstract

Background Enhancers are non-coding regions of the genome that control the activity of target genes. Recent efforts to identify active enhancers experimentally and in silico have proven effective. While these tools can predict the locations of enhancers with a high degree of accuracy, the mechanisms underpinning the activity of enhancers are often unclear. Results Using machine learning (ML) and a rule-based explainable artificial intelligence (XAI) model, we demonstrate that we can predict the location of known enhancers in Drosophila with a high degree of accuracy. Most importantly, we use the rules of the XAI model to provide insight into the underlying combinatorial histone modifications code of enhancers. In addition, we identified a large set of putative enhancers that display the same epigenetic signature as enhancers identified experimentally. These putative enhancers are enriched in nascent transcription, divergent transcription and have 3D contacts with promoters of transcribed genes. However, they display only intermediary enrichment of mediator and cohesin complexes compared to previously characterised active enhancers. We also found that 10–15% of the predicted enhancers display similar characteristics to super enhancers observed in other species. Conclusions Here, we applied an explainable AI model to predict enhancers with high accuracy. Most importantly, we identified that different combinations of epigenetic marks characterise different groups of enhancers. Finally, we discovered a large set of putative enhancers which display similar characteristics with previously characterised active enhancers.

Item Type: Article
Uncontrolled Keywords: Enhancers; Histone modifications; Explainable Artificial Intelligence; Gene regulation; Drosophila
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Faculty of Science and Health > Life Sciences, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 08 Nov 2021 15:47
Last Modified: 15 Jan 2022 01:39
URI: http://repository.essex.ac.uk/id/eprint/31461

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