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Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line

Non-coding regulatory elements such as enhancers are key in controlling the cell-type specificity and spatio-temporal expression of genes. To drive stable and precise gene transcription robust to genetic variation and environmental stress, genes are often targeted by multiple enhancers with redundan...

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Autores principales: Ziyani, Chaymae, Delaneau, Olivier, Ribeiro, Diogo M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10219981/
https://www.ncbi.nlm.nih.gov/pubmed/37237005
http://dx.doi.org/10.1038/s42003-023-04954-4
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author Ziyani, Chaymae
Delaneau, Olivier
Ribeiro, Diogo M.
author_facet Ziyani, Chaymae
Delaneau, Olivier
Ribeiro, Diogo M.
author_sort Ziyani, Chaymae
collection PubMed
description Non-coding regulatory elements such as enhancers are key in controlling the cell-type specificity and spatio-temporal expression of genes. To drive stable and precise gene transcription robust to genetic variation and environmental stress, genes are often targeted by multiple enhancers with redundant action. However, it is unknown whether enhancers targeting the same gene display simultaneous activity or whether some enhancer combinations are more often co-active than others. Here, we take advantage of recent developments in single cell technology that permit assessing chromatin status (scATAC-seq) and gene expression (scRNA-seq) in the same single cells to correlate gene expression to the activity of multiple enhancers. Measuring activity patterns across 24,844 human lymphoblastoid single cells, we find that the majority of enhancers associated with the same gene display significant correlation in their chromatin profiles. For 6944 expressed genes associated with enhancers, we predict 89,885 significant enhancer-enhancer associations between nearby enhancers. We find that associated enhancers share similar transcription factor binding profiles and that gene essentiality is linked with higher enhancer co-activity. We provide a set of predicted enhancer-enhancer associations based on correlation derived from a single cell line, which can be further investigated for functional relevance.
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spelling pubmed-102199812023-05-28 Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line Ziyani, Chaymae Delaneau, Olivier Ribeiro, Diogo M. Commun Biol Article Non-coding regulatory elements such as enhancers are key in controlling the cell-type specificity and spatio-temporal expression of genes. To drive stable and precise gene transcription robust to genetic variation and environmental stress, genes are often targeted by multiple enhancers with redundant action. However, it is unknown whether enhancers targeting the same gene display simultaneous activity or whether some enhancer combinations are more often co-active than others. Here, we take advantage of recent developments in single cell technology that permit assessing chromatin status (scATAC-seq) and gene expression (scRNA-seq) in the same single cells to correlate gene expression to the activity of multiple enhancers. Measuring activity patterns across 24,844 human lymphoblastoid single cells, we find that the majority of enhancers associated with the same gene display significant correlation in their chromatin profiles. For 6944 expressed genes associated with enhancers, we predict 89,885 significant enhancer-enhancer associations between nearby enhancers. We find that associated enhancers share similar transcription factor binding profiles and that gene essentiality is linked with higher enhancer co-activity. We provide a set of predicted enhancer-enhancer associations based on correlation derived from a single cell line, which can be further investigated for functional relevance. Nature Publishing Group UK 2023-05-26 /pmc/articles/PMC10219981/ /pubmed/37237005 http://dx.doi.org/10.1038/s42003-023-04954-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ziyani, Chaymae
Delaneau, Olivier
Ribeiro, Diogo M.
Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line
title Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line
title_full Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line
title_fullStr Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line
title_full_unstemmed Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line
title_short Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line
title_sort multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10219981/
https://www.ncbi.nlm.nih.gov/pubmed/37237005
http://dx.doi.org/10.1038/s42003-023-04954-4
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