Evidence map›Paper›PMID 35817938›Full record

ArticleNature methods2022

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

Abstract read
In one paragraph

Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lorenzo BoninsegnaInstitute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0003-4529-3567
Asli YildirimInstitute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA.
Guido PollesInstitute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA.
Yuxiang ZhanInstitute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA.
Sofia A QuinodozDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
Elizabeth H FinnNational Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Mitchell GuttmanDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID http://orcid.org/0000-0003-4748-9352
Xianghong Jasmine ZhouInstitute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA.
Frank AlberInstitute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA, USA. falber@g.ucla.edu.ORCID http://orcid.org/0000-0003-1981-8390

Funding

Multiscale Analyses of 4D Nucleome Structure and Function by Comprehensive Multimodal Data IntegrationUM1HG011593 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI ALBER, FRANK, BELMONT, ANDREW STEVEN · 2020 to 2024
$10.4M
Mapping the 3D Genome LandscapeU54DK107981 · NIDDK · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHEN, LIN · 2015 to 2019
$4.2M
NHGRI NIH HHS UM1 HG011593NIDDK NIH HHS U54 DK107981
6 · The paper itself

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.

Indexed as

ChromatinChromosomesCell NucleusGenomeChromatin

Identifiers

PMID35817938
PMCPMC9349046

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.