CoChat
Sign Up
Cited by 119Genomics and Chromatin DynamicsChromatin Remodeling and CancerChromosomal and Genetic Variations

The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.

Dynamics of the 4D genome during in vivo lineage specification and differentiation

Open access
Oudelaar, A. Marieke, Beagrie, Robert A., Gosden, Matthew, de Ornellas, Sara, Georgiades, Emily, Kerry, Jon, Hidalgo, Daniel, Carrelha, Joana, Shivalingam, Arun, El-Sagheer, Afaf H., Telenius, Jelena M., Brown, Tom, Buckle, Veronica J., Socolovsky, Merav, Higgs, Douglas R., Hughes, Jim R.·2020·Nature Communications
DOI 10.1038/s41467-020-16598-7PMC PMC7264236

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Mammalian gene expression patterns are controlled by regulatory elements, which interact within topologically associating domains (TADs). The relationship between activation of regulatory elements, formation of structural chromatin interactions and gene expression during development is unclear. Here, we present Tiled-C, a low-input chromosome conformation capture (3C) technique. We use this approach to study chromatin architecture at high spatial and temporal resolution through in vivo mouse erythroid differentiation. Integrated analysis of chromatin accessibility and single-cell expression data shows that regulatory elements gradually become accessible within pre-existing TADs during early differentiation. This is followed by structural re-organization within the TAD and formation of specific contacts between enhancers and promoters. Our high-resolution data show that these enhancer-promoter interactions are not established prior to gene expression, but formed gradually during differentiation, concomitant with progressive upregulation of gene activity. Together, these results provide new insight into the close, interdependent relationship between chromatin architecture and gene regulation during development.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-020-16598-7

Cites

61 of 61 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Tiled-C generates deep all vs all 3C data at regions of interest. a Comparison of Tiled-C and Hi-C contact matrices at 2 kb resolution in mouse ES cells. Contact frequencies represent normalized, unique interactions in three and four replicates for Tiled-C and Hi-C data, respectively. Coordinates (mm9): chr11:29,902,000–33,228,000. b Tiled-C contact matrices of ~3.3 Mb spanning the mouse α-globin locus in primary mature erythroid cells (top) and ES cells (bottom) at 2 kb resolution. Contact frequencies represent normalized, unique interactions in three replicates. Gene annotation (α-globin genes highlighted in red), open chromatin (ATAC), and CTCF occupancy are shown below the matrices. Coordinates (mm9): chr11:29,902,000–33,228,000. c Tiled-C contact matrices of ~3.4 Mb spanning the mouse Sox2 locus in primary mature erythroid cells (top) and ES cells (bottom) at 5 kb resolution. Contact frequencies represent normalized, unique interactions in four replicates. Gene annotation (Sox2 gene highlighted in red), open chromatin (ATAC), and CTCF occupancy are shown below the matrices. Coordinates (mm9): chr3:33,200,000–36,565,000.
Fig. 1 Tiled-C generates deep all vs all 3C data at regions of interest. a Comparison of Tiled-C and Hi-C contact matrices at 2 kb resolution in mouse ES cells. Contact frequencies represent normalized, unique interactions in three and four replicates for Tiled-C and Hi-C data, respectively. Coordinates (mm9): chr11:29,902,000–33,228,000. b Tiled-C contact matrices of ~3.3 Mb spanning the mouse α-globin locus in primary mature erythroid cells (top) and ES cells (bottom) at 2 kb resolution. Contact frequencies represent normalized, unique interactions in three replicates. Gene annotation (α-globin genes highlighted in red), open chromatin (ATAC), and CTCF occupancy are shown below the matrices. Coordinates (mm9): chr11:29,902,000–33,228,000. c Tiled-C contact matrices of ~3.4 Mb spanning the mouse Sox2 locus in primary mature erythroid cells (top) and ES cells (bottom) at 5 kb resolution. Contact frequencies represent normalized, unique interactions in four replicates. Gene annotation (Sox2 gene highlighted in red), open chromatin (ATAC), and CTCF occupancy are shown below the matrices. Coordinates (mm9): chr3:33,200,000–36,565,000.CC BY · PubMed Central
Fig. 2 Tiled-C generates high-resolution contact matrices from small numbers of cells. Tiled-C contact matrices of ~3.3 Mb spanning the mouse α-globin locus at 5 kb resolution, generated from small aliquots of primary mature erythroid cells. Contact frequencies represent normalized, unique interactions in three replicates. TADs are indicated below each matrix with a black bar. Gene annotation (α-globin genes highlighted in red), open chromatin (ATAC), and CTCF occupancy are shown below the matrices. Coordinates (mm9): chr11:29,900,000–33,230,000.
Fig. 2 Tiled-C generates high-resolution contact matrices from small numbers of cells. Tiled-C contact matrices of ~3.3 Mb spanning the mouse α-globin locus at 5 kb resolution, generated from small aliquots of primary mature erythroid cells. Contact frequencies represent normalized, unique interactions in three replicates. TADs are indicated below each matrix with a black bar. Gene annotation (α-globin genes highlighted in red), open chromatin (ATAC), and CTCF occupancy are shown below the matrices. Coordinates (mm9): chr11:29,900,000–33,230,000.CC BY · PubMed Central
Fig. 3 Expression of α-globin is gradually upregulated during in vivo erythroid differentiation. a Scheme of erythroid differentiation showing the various populations analyzed. b Example FACS plot showing the gating strategy used to isolate erythroid progenitors from mouse fetal liver. c Expression (in counts per million) of α-globin transcripts in each population as determined by single-cell RNA-seq. Mean expression for each population is given at the top of each bar. d Representative RNA-FISH images showing detection of nascent α-globin transcripts in sorted early erythroid progenitors. Scale bar is 3 μM for each image. e RNA-FISH quantification, showing the mean ± s.d. of n = 3 independent experiments (except for brain and “no primary” negative controls, which have n = 2). P-values were calculated by two-tailed paired t-tests (S0-low vs S0-medium P = 0.041, S0-low vs S1 P = 0.002). Source data are provided as a Source Data file.
Fig. 3 Expression of α-globin is gradually upregulated during in vivo erythroid differentiation. a Scheme of erythroid differentiation showing the various populations analyzed. b Example FACS plot showing the gating strategy used to isolate erythroid progenitors from mouse fetal liver. c Expression (in counts per million) of α-globin transcripts in each population as determined by single-cell RNA-seq. Mean expression for each population is given at the top of each bar. d Representative RNA-FISH images showing detection of nascent α-globin transcripts in sorted early erythroid progenitors. Scale bar is 3 μM for each image. e RNA-FISH quantification, showing the mean ± s.d. of n = 3 independent experiments (except for brain and “no primary” negative controls, which have n = 2). P-values were calculated by two-tailed paired t-tests (S0-low vs S0-medium P = 0.041, S0-low vs S1 P = 0.002). Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 4 Upregulation of α-globin expression correlates with increased chromatin accessibility and enhancer-promoter interactions. Tiled-C contact matrices of 500 kb spanning the mouse α-globin locus in sequential stages of in vivo erythroid differentiation at 2 kb resolution. Contact frequencies represent normalized, unique interactions in two replicates. The black and gray bar below each matrix represent the pre-existing TAD (chr11:32,080,000-32,245,000) and erythroid-specific sub-TAD (chr11:32,136,000-32,202,000), respectively. Matched open chromatin (ATAC) profiles are shown underneath the matrices and represent normalized data from 3 S0-low, S0-medium, and S1 replicates and 2 S2 and S3 replicates. The ATAC profiles are shown at different scales to highlight changes in accessibility in early stages of differentiation. Gene annotation (α-globin genes highlighted in red), open chromatin (ATAC; α-globin enhancers highlighted in red), and CTCF occupancy in mature mouse erythroblast cells are shown at the top. Coordinates (mm9): chr11:31,900,000–32,400,000.
Fig. 4 Upregulation of α-globin expression correlates with increased chromatin accessibility and enhancer-promoter interactions. Tiled-C contact matrices of 500 kb spanning the mouse α-globin locus in sequential stages of in vivo erythroid differentiation at 2 kb resolution. Contact frequencies represent normalized, unique interactions in two replicates. The black and gray bar below each matrix represent the pre-existing TAD (chr11:32,080,000-32,245,000) and erythroid-specific sub-TAD (chr11:32,136,000-32,202,000), respectively. Matched open chromatin (ATAC) profiles are shown underneath the matrices and represent normalized data from 3 S0-low, S0-medium, and S1 replicates and 2 S2 and S3 replicates. The ATAC profiles are shown at different scales to highlight changes in accessibility in early stages of differentiation. Gene annotation (α-globin genes highlighted in red), open chromatin (ATAC; α-globin enhancers highlighted in red), and CTCF occupancy in mature mouse erythroblast cells are shown at the top. Coordinates (mm9): chr11:31,900,000–32,400,000.CC BY · PubMed Central
Fig. 5 Enhancer-promoter interactions are formed progressively during erythroid differentiation and correlate with upregulation of gene expression. Quantification of enhancer-promoter interactions and gene expression during in vivo erythroid differentiation at six erythroid gene loci. Contact frequencies (black circles; left Y-axis) represent unique interactions normalized for the total number of contacts in the matrix. Expression counts (gray squares; right Y-axis) represent mean expression in counts per million (CPM) for each population as determined by single-cell RNA-seq. Expression of α-globin, Slc25a37 and Tal1, is upregulated early in differentiation, concomitant with increased enhancer-promoter interactions. Cd47 is expressed in hematopoietic stem cells and further upregulated later in erythroid differentiation when enhancer-promoter interactions are strengthened. Cpeb4 and Btg2 become robustly expressed in the S1 stage and are further upregulated as enhancer-promoter interactions increase later in differentiation.
Fig. 5 Enhancer-promoter interactions are formed progressively during erythroid differentiation and correlate with upregulation of gene expression. Quantification of enhancer-promoter interactions and gene expression during in vivo erythroid differentiation at six erythroid gene loci. Contact frequencies (black circles; left Y-axis) represent unique interactions normalized for the total number of contacts in the matrix. Expression counts (gray squares; right Y-axis) represent mean expression in counts per million (CPM) for each population as determined by single-cell RNA-seq. Expression of α-globin, Slc25a37 and Tal1, is upregulated early in differentiation, concomitant with increased enhancer-promoter interactions. Cd47 is expressed in hematopoietic stem cells and further upregulated later in erythroid differentiation when enhancer-promoter interactions are strengthened. Cpeb4 and Btg2 become robustly expressed in the S1 stage and are further upregulated as enhancer-promoter interactions increase later in differentiation.CC BY · PubMed Central
Fig. 6 Graphical Summary. Based on our findings, we propose a model in which TADs are established very early in differentiation. During lineage commitment, tissue-specific open chromatin sites are established within these domains. This is followed by the formation of smaller sub-domains within TADs, in which enhancers and promoters form interactions. Through differentiation, accessibility and specific interactions between enhancers and promoters are gradually increased, concomitant with upregulation of gene expression.
Fig. 6 Graphical Summary. Based on our findings, we propose a model in which TADs are established very early in differentiation. During lineage commitment, tissue-specific open chromatin sites are established within these domains. This is followed by the formation of smaller sub-domains within TADs, in which enhancers and promoters form interactions. Through differentiation, accessibility and specific interactions between enhancers and promoters are gradually increased, concomitant with upregulation of gene expression.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Sorted by citations

See all 119

Related

See all

Metadata

Authors
Oudelaar, A. M., Beagrie, R. A., Gosden, M., de Ornellas, S., Georgiades, E., Kerry, J., Hidalgo, D., Carrelha, J., Shivalingam, A., El-Sagheer, A. H., Telenius, J. M., Brown, T., Buckle, V. J., Socolovsky, M., Higgs, D. R., & Hughes, J. R.
Affiliations
  • University of Oxford (GB)
  • University of Massachusetts Chan Medical School (US)
  • Suez University (EG)
Corresponding author
  • Higgs, Douglas R.
  • Hughes, Jim R.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2020-06-01
Volume
11
Issue
1
Pages
2722-2722
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-020-16598-7
PMC
PMC7264236
OpenAlex
W3030892594
Cited by
119
References
61
Citations by year
2026: 9 · 2025: 20 · 2024: 19 · 2023: 20 · 2022: 17 · 2021: 20 · 2020: 14
FWCI
5.76
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • The Journal of the American Medical Association (JAMA) Network (American Medical Association) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
Funders
  • RCUK | Medical Research Council
  • Wellcome Trust
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Chromosomal and Genetic Variations
Keywords
topologically associating domains, chromatin structure, enhancer-promoter interactions, erythroid differentiation, lineage specification, chromatin accessibility, chromosome conformation capture, regulatory elements, single-cell gene expression, mouse embryo
MeSH terms
Mouse Embryonic Stem Cells, Animals, Cell Differentiation, Cells, Cultured, Chromatin, Enhancer Elements, Genetic, Female, Hematopoietic Stem Cells, Mice, Inbred C57BL, Promoter Regions, Genetic, Stem Cells, Genome, Gene Expression Regulation, Developmental, Gene Expression Profiling, Chromosomes, Mammalian, Mice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review