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

Lorenzo Boninsegna; Asli Yildirim; Guido Polles; Yuxiang Zhan; Sofia A Quinodoz; Elizabeth H Finn; Mitchell Guttman; Xianghong Jasmine Zhou; Frank Alber

doi:10.1038/s41592-022-01527-x

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

Nat Methods. 2022 Aug;19(8):938-949. doi: 10.1038/s41592-022-01527-x. Epub 2022 Jul 11.

Authors

Lorenzo Boninsegna^{1

2}, Asli Yildirim^{1

2}, Guido Polles^{1

2

3}, Yuxiang Zhan^{1

2

3}, Sofia A Quinodoz⁴, Elizabeth H Finn⁵, Mitchell Guttman⁴, Xianghong Jasmine Zhou^{1

6}, Frank Alber^{7

8

9}

Affiliations

¹ Institute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA.
² Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
³ Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
⁴ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
⁵ National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
⁶ Department of Pathology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁷ Institute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA. falber@g.ucla.edu.
⁸ Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA. falber@g.ucla.edu.
⁹ Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. falber@g.ucla.edu.

Abstract

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.

Publication types

Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Cell Nucleus
Chromatin* / genetics
Chromosomes* / genetics
Genome

Substances

Chromatin

Abstract

Publication types

MeSH terms

Substances

Grants and funding