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Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-ce...

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Autores principales: Boninsegna, Lorenzo, Yildirim, Asli, Polles, Guido, Zhan, Yuxiang, Quinodoz, Sofia A., Finn, Elizabeth H., Guttman, Mitchell, Zhou, Xianghong Jasmine, Alber, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9349046/
https://www.ncbi.nlm.nih.gov/pubmed/35817938
http://dx.doi.org/10.1038/s41592-022-01527-x
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author Boninsegna, Lorenzo
Yildirim, Asli
Polles, Guido
Zhan, Yuxiang
Quinodoz, Sofia A.
Finn, Elizabeth H.
Guttman, Mitchell
Zhou, Xianghong Jasmine
Alber, Frank
author_facet Boninsegna, Lorenzo
Yildirim, Asli
Polles, Guido
Zhan, Yuxiang
Quinodoz, Sofia A.
Finn, Elizabeth H.
Guttman, Mitchell
Zhou, Xianghong Jasmine
Alber, Frank
author_sort Boninsegna, Lorenzo
collection PubMed
description A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency (‘rare’) interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package.
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spelling pubmed-93490462022-08-05 Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations Boninsegna, Lorenzo Yildirim, Asli Polles, Guido Zhan, Yuxiang Quinodoz, Sofia A. Finn, Elizabeth H. Guttman, Mitchell Zhou, Xianghong Jasmine Alber, Frank Nat Methods Article A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency (‘rare’) interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package. Nature Publishing Group US 2022-07-11 2022 /pmc/articles/PMC9349046/ /pubmed/35817938 http://dx.doi.org/10.1038/s41592-022-01527-x Text en © The Author(s) 2022 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
Boninsegna, Lorenzo
Yildirim, Asli
Polles, Guido
Zhan, Yuxiang
Quinodoz, Sofia A.
Finn, Elizabeth H.
Guttman, Mitchell
Zhou, Xianghong Jasmine
Alber, Frank
Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations
title Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations
title_full Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations
title_fullStr Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations
title_full_unstemmed Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations
title_short Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations
title_sort integrative genome modeling platform reveals essentiality of rare contact events in 3d genome organizations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9349046/
https://www.ncbi.nlm.nih.gov/pubmed/35817938
http://dx.doi.org/10.1038/s41592-022-01527-x
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