Evidence map›Paper›PMID 33903756›Full record

ArticleNature protocols2021

Chromatin tracing and multiplexed imaging of nucleome architectures (MINA) and RNAs in single mammalian cells and tissue.

Miao Liu, Bing Yang, Mengwei Hu, Jonathan S D Radda, Yanbo Chen, Shengyan Jin, Yubao Cheng, Siyuan Wang

Abstract read
In one paragraph

Article in Nature protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Review
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  11. The Biological Function of Genome Organization.International journal of molecular sciences · 2025
    Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Article
  19. Reconstructing human-specific regulatory functions in model systems.Current opinion in genetics & development · 2024
    Review
  20. Article
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

8 authors.

Miao LiuDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA.
Bing YangDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-9355-2538
Mengwei HuDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA.
Jonathan S D RaddaDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-2242-9604
Yanbo ChenDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA.
Shengyan JinDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA.
Yubao ChengDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA.
Siyuan WangDepartment of Genetics, Yale University School of Medicine, New Haven, CT, USA. siyuan.wang@yale.edu.ORCID http://orcid.org/0000-0001-6550-4064

Funding

Yale Liver CenterP30DK034989 · NIDDK · YALE UNIVERSITY · PI YASUKO IWAKIRI · 1986 to 2026
$31.1M
PREDOCTORAL TRAINING PROGRAM IN GENETICST32GM007499 · NIGMS · YALE UNIVERSITY · PI CARLSON, JOHN R, REINKE, VALERIE J · 1985 to 2022
$13.9M
Genome Architecture in Human Germinal Center B Cell Development, Malignancy, and Somatic HypermutationU01CA260701 · NCI · YALE UNIVERSITY · PI SCHATZ, DAVID G., WANG, SIYUAN · 2020 to 2024
$3.1M
Building the 3D genomic regulatomeDP2GM137414 · NIGMS · YALE UNIVERSITY · PI WANG, SIYUAN · 2019 to 2019
$2.5M
Integrative single-cell spatial genomic, transcriptomic, and epigenetic imaging in mammalian tissueR01HG011245 · NHGRI · YALE UNIVERSITY · PI WANG, SIYUAN · 2020 to 2023
$2.1M
Multiplexed imaging of chromatin folding and RNA profiles in cancerR33CA251037 · NCI · YALE UNIVERSITY · PI MUZUMDAR, MANDAR DEEPAK, WANG, SIYUAN · 2020 to 2020
$1.2M
NCI NIH HHS R33 CA251037NCI NIH HHS U01 CA260701NHGRI NIH HHS R01 HG011245NIDDK NIH HHS P30 DK034989NIGMS NIH HHS DP2 GM137414NIGMS NIH HHS T32 GM007499
6 · The paper itself

Abstract

The genome is hierarchically organized into several 3D architectures, including chromatin loops, domains, compartments and regions associated with nuclear lamina and nucleoli. Changes in these architectures have been associated with normal development, aging and a wide range of diseases. Despite its critical importance, understanding how the genome is spatially organized in single cells, how organization varies in different cell types in mammalian tissue and how organization affects gene expression remains a major challenge. Previous approaches have been limited by a lack of capacity to directly trace chromatin folding in 3D and to simultaneously measure genomic organization in relation to other nuclear components and gene expression in the same single cells. We have developed an image-based 3D genomics technique termed 'chromatin tracing', which enables direct 3D tracing of chromatin folding along individual chromosomes in single cells. More recently, we also developed multiplexed imaging of nucleome architectures (MINA), which enables simultaneous measurements of multiscale chromatin folding, associations of genomic regions with nuclear lamina and nucleoli and copy numbers of numerous RNA species in the same single cells in mammalian tissue. Here, we provide detailed protocols for chromatin tracing in cell lines and MINA in mammalian tissue, which take 3-4 d for experimental work and 2-3 d for data analysis. We expect these developments to be broadly applicable and to affect many lines of research on 3D genomics by depicting multiscale genomic architectures associated with gene expression, in different types of cells and tissue undergoing different biological processes.

Indexed as

Molecular ImagingAnimalsCell LineChromatinGene Expression ProfilingHumansRNASingle-Cell AnalysisChromatinRNA

Identifiers

PMID33903756
PMCPMC9007104

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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.