Analysis of long and short enhancers in melanoma cell states.

David Mauduit,Maxime De Waegeneer,Stein Aerts,Jonas Demeulemeester,Liesbeth Minnoye,Ibrahim Ihsan Taskiran,Valerie Christiaens,Gert Hulselmans,Jasper Wouters

doi:10.7554/elife.71735

David Mauduit, Maxime De Waegeneer + Show 7 more

Open Access

https://doi.org/10.7554/elife.71735

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Journal: eLife	Publication Date: Dec 7, 2021
Citations: 16	License type: CC BY 4.0

Affiliation: VIB-KU Leuven Center for Brain & Disease Research

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 (MPRAs) 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.

Highlights

Enhancers are crucial regulatory regions in the genome that control cell type-specific gene expression
We used only the H3K27ac peaks that are identified as active in the H3K27ac library or that are assigned as MEL- or MES-specific regulatory regions in our previously published cisTopic analysis of ATAC-seq data from 16 human melanoma cell lines (Bravo González-Blas et al, 2019)
Our results suggest that AP-1 is responsible for the activity of MES enhancers, agreeing with its predominance in allele-specific chromatin accessibility variants in melanoma (Atak et al, 2021)

Summary

Introduction

Enhancers are crucial regulatory regions in the genome that control cell type-specific gene expression. Such an approach requires prior knowledge of the cis-regulatory grammar in the studied cell types as only a small proportion of the TFBSs found in the genome are bound by the corresponding transcription factor (TF) (Yáñez-Cuna et al, 2012) Another strategy to identify candidate enhancers is to use active enhancer marks such as H3K27ac and chromatin accessibility (Gray et al, 2017; Minnoye et al., 2021; Rada-Iglesias et al, 2011). Limitations of sequence synthesis constrain one to choose either a large number of short sequences (e.g., thousands of sequences of 150-250 bp) or a small number of longer sequences (e.g., dozens of sequences of 500-1000 bp)(Inoue and Ahituv, 2015) This issue, combined with the difficulty of identifying putative enhancers, leads to a low rate of active enhancers in MPRAs. Here, we study enhancer location, specificity and regulatory grammar in melanoma, using a variety of MPRA strategies. We show that a melanoma deep learning model (DeepMEL2; Atak et al, 2021) trained on ATAC-seq data 73 pinpoints which TFBSs drive enhancer activity and specificity

Results

Discussion

Methods

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