Cited by 217Epigenetics and DNA MethylationGenomics and Chromatin DynamicsBone Metabolism and Diseases

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PU.1 target genes undergo Tet2-coupled demethylation and DNMT3b-mediated methylation in monocyte-to-osteoclast differentiation

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de la Rica, Lorenzo, Rodríguez-Ubreva, Javier, García, Mireia, Islam, Abul BMMK, Urquiza, José M, Hernando, Henar, Christensen, Jesper, Helin, Kristian, Gómez-Vaquero, Carmen, Ballestar, Esteban·2013·Genome Biology

Abstract

Background: DNA methylation is a key epigenetic mechanism for driving and stabilizing cell-fate decisions. Local deposition and removal of DNA methylation are tightly coupled with transcription factor binding, although the relationship varies with the specific differentiation process. Conversion of monocytes to osteoclasts is a unique terminal differentiation process within the hematopoietic system. This differentiation model is relevant to autoimmune disease and cancer, and there is abundant knowledge on the sets of transcription factors involved. Results: Here we focused on DNA methylation changes during osteoclastogenesis. Hypermethylation and hypomethylation changes took place in several thousand genes, including all relevant osteoclast differentiation and function categories. Hypomethylation occurred in association with changes in 5-hydroxymethylcytosine, a proposed intermediate toward demethylation. Transcription factor binding motif analysis revealed an over-representation of PU.1, NF-κB, and AP-1 (Jun/Fos) binding motifs in genes undergoing DNA methylation changes. Among these, only PU.1 motifs were significantly enriched in both hypermethylated and hypomethylated genes; ChIP-seq data analysis confirmed its association to both gene sets. Moreover, PU.1 interacts with both DNMT3b and TET2, suggesting its participation in driving hypermethylation and hydroxymethylation-mediated hypomethylation. Consistent with this, siRNA-mediated PU.1 knockdown in primary monocytes impaired the acquisition of DNA methylation and expression changes, and reduced the association of TET2 and DNMT3b at PU.1 targets during osteoclast differentiation. Conclusions: The work described here identifies key changes in DNA methylation during monocyte-to-osteoclast differentiation and reveals novel roles for PU.1 in this process.

Overview

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TL;DR

In matched human monocyte-to-osteoclast differentiation samples, DNA methylation is extensively remodeled, with thousands of genes gaining or losing methylation. PU.1 binds both hypo- and hypermethylated targets and recruits TET2 or DNMT3b, and PU.1 knockdown impairs these methylation and expression changes.

Key findings

  • In three matched CD14+ monocyte/osteoclast pairs, 3,515 genes (8,028 CpGs) were differentially methylated (FC ≥2 or ≤0.5; FDR ≤0.05): 1,895 hypomethylated genes (3,597 CpGs) and 2,054 hypermethylated genes (4,429 CpGs).
  • Hypomethylation occurred early (about 60% of the range by days 0–4), without replication (BrdU-positive cells <9.8% between days 1 and 4; 5azadC treatment had no significant effect on osteoclastogenesis), and was associated with 5hmC changes at genes such as ACP5 and TM4SF19.
  • Motif analysis found PU.1 enrichment in both directions: 15% of hypomethylated genes had PU.1/ETS motifs (PU.1 alone 9%) and 15% of hypermethylated genes had PU.1 motifs; ChIP-seq showed PU.1 peaks within 500 bp of 10.7% of promoter hypomethylated CpGs and 25.1% of promoter hypermethylated CpGs.
  • PU.1 co-immunoprecipitated with DNMT3b and TET2; siRNA PU.1 knockdown (~60%) impaired acquisition of DNA methylation and expression changes at PU.1 targets and reduced TET2 and DNMT3b association at those promoters.

Methods

  • Primary human CD14+ monocytes from buffy coats were differentiated to osteoclasts with M-CSF and RANKL for 21 days; three matched monocyte/osteoclast pairs were profiled.
  • Genome-wide DNA methylation used Illumina HumanMethylation450 arrays, with differential methylation by paired limma (FC ≥2 or ≤0.5; P<0.01; FDR<0.05), validated by bisulfite pyrosequencing; expression data came from ArrayExpress E-MEXP-2019.
  • Mechanistic assays included TRANSFAC/STORM motif analysis, PU.1 ChIP-seq (GSE31621), ChIP, immunoprecipitation, siRNA knockdown, 5hmC detection, BrdU, and 5azadC treatment.

Limitations

  • Stated: PU.1 knockdown only partially impaired DNA methylation/expression changes and only partially reduced TET2/DNMT3b binding, indicating additional transcription factors participate; TM7SF4 showed no effect, possibly because it demethylates before PU.1 knockdown is effective.
  • Stated: the detailed mechanisms coupling 5mC hydroxylation and demethylation remain debated, and the study did not address whether PU.1 interactions involve different subpopulations or post-translational modifications.
  • Evident: array analyses used three matched pairs, and some ChIP experiments are described as three biological triplicates but only one experiment is shown; TRANSFAC predictions had limited overlap with ChIP-seq (20.6% hypomethylated, 46.9% hypermethylated), which the authors note reveals weakness in predictive motif searches.

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Registry

Crossref · 10.1186/gb-2013-14-9-r99

Cites

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Figures

Figure 1 High-throughput methylation comparison between monocytes (MOs) and derived osteoclasts (OCs). (A) Heatmap including the data for three paired samples of MOs (MO D1, D2, D3) and their derived OCs (OC D1, D2, D3) harvested on day 21. The heatmap includes all CpG-containing probes displaying significant methylation changes (8,028 in total with FC ≥2 or FC ≤0.5; P ≤0.01 and FDR ≤0.05) (Additional file 2). Scale shown at the bottom, whereby beta values (that is, the ratio of the methylated probe intensity to the overall intensity, where overall intensity is the sum of methylated and unmethylated probe intensities) ranging from 0 (unmethylated, blue) to 1 (completely methylated, red). (B) Scatterplot showing the mean methylation profile of three matching MO/OC pairs. Genes with significant differences (FC >2, FDR <0.05) in averaged results from the three pairs of samples are highlighted in red (hypermethylated) or blue (hypomethylated). (C) Distribution of differentially methylated CpGs among genomic regions (promoter, gene bodies, 3′UTR, and intergenic) in different subsets of CpGs (hypomethylated, hypermethylated). (D) Gene ontology enrichment analysis of hypomethylated and hypermethylated CpGs showing the most important categories. (E) Technical validation of the array data by bisulfite pyrosequencing of modified DNA. BS pyrosequencing of three representative hypomethylated genes (ACP5, CTSK, and TM7SF4) and one hypermethylated gene (CX3CR1) from the array data are shown. A representation showing the excellent correlation between array data (beta values) and pyrosequencing data (% methylation) including the data for the four genes (right panel). (F) Cluster analysis of contiguous differentially methylated regions (<500 bp). Two examples of regions with more than nine consecutive CpGs differentially methylated are shown. (G) Analysis of methylation levels in repetitive elements (Sat2, D4Z4, NBL2) and ribosomal RNA genes (18S and 28S regions) as obtained from bisulfite sequencing analysis.
Figure 1 High-throughput methylation comparison between monocytes (MOs) and derived osteoclasts (OCs). (A) Heatmap including the data for three paired samples of MOs (MO D1, D2, D3) and their derived OCs (OC D1, D2, D3) harvested on day 21. The heatmap includes all CpG-containing probes displaying significant methylation changes (8,028 in total with FC ≥2 or FC ≤0.5; P ≤0.01 and FDR ≤0.05) (Additional file 2). Scale shown at the bottom, whereby beta values (that is, the ratio of the methylated probe intensity to the overall intensity, where overall intensity is the sum of methylated and unmethylated probe intensities) ranging from 0 (unmethylated, blue) to 1 (completely methylated, red). (B) Scatterplot showing the mean methylation profile of three matching MO/OC pairs. Genes with significant differences (FC >2, FDR <0.05) in averaged results from the three pairs of samples are highlighted in red (hypermethylated) or blue (hypomethylated). (C) Distribution of differentially methylated CpGs among genomic regions (promoter, gene bodies, 3′UTR, and intergenic) in different subsets of CpGs (hypomethylated, hypermethylated). (D) Gene ontology enrichment analysis of hypomethylated and hypermethylated CpGs showing the most important categories. (E) Technical validation of the array data by bisulfite pyrosequencing of modified DNA. BS pyrosequencing of three representative hypomethylated genes (ACP5, CTSK, and TM7SF4) and one hypermethylated gene (CX3CR1) from the array data are shown. A representation showing the excellent correlation between array data (beta values) and pyrosequencing data (% methylation) including the data for the four genes (right panel). (F) Cluster analysis of contiguous differentially methylated regions (<500 bp). Two examples of regions with more than nine consecutive CpGs differentially methylated are shown. (G) Analysis of methylation levels in repetitive elements (Sat2, D4Z4, NBL2) and ribosomal RNA genes (18S and 28S regions) as obtained from bisulfite sequencing analysis.CC BY · PubMed Central
Figure 2 Dynamics of DNA methylation and its relationship with expression changes. (A) Heatmap showing expression levels on 0, 5, and 20 days for genes displaying significant methylation and expression changes (4,753 in total with FC ≥2 or FC ≤0.5; P ≤0.01 and FDR ≤0.05) (Additional file 7). (B) catterplots showing the relationship between the log2-transformed FC in expression and the log2-transformed FC in DNA methylation. Sixty-two percent of the hypomethylated genes are overexpressed (in blue); 55% of the hypermethylated genes are repressed (in red). (C) Correlation between methylation and expression data (slope from the linear regression between DNA methylation differences versus expression differences) for all differentially methylated genes organized by genomic location (first exon, TSS, 5′UTR, gene body, 3′UTR). (D) DNA methylation and expression dynamics of selected loci during monocyte-to-osteoclast differentiation. Methylation percentage determined by bisulfite pyrosequencing. Quantitative RT-PCR data relative to RPL38. DNA methylation and expression data are represented with a black line and a red line, respectively. (E) BrdU assay showing the percentage of replicating cells at different times. From days 1 to 4, only 9.46% of cells divide. (F) Effects of 5azadC treatment (50 nM, 500 nM) on osteoclastogenesis monitoring ACP5, CTSK, and CX3CR1 levels and TRAP staining over time. (G) Workflow for testing the presence of 5 hydroxymethylcytosine in hypomethylated genes. DNA was treated with a 5hmC-specific glucosyltransferase. Cytosines bearing a 5-hydroxymethyl are protected against MspI digestion, and the surrounding region can be amplified by qPCR. When no 5hmC is present, glucose is not transferred to C, DNA is cleaved at CCGG sites, and there is less qPCR amplification. Several controls are used to set the 0% and 100% content of 5hmC. (H) 5hmC content in several of the CpGs that are rapidly demethylated after RANKL and M-CSF stimulation of OC precursors.
Figure 2 Dynamics of DNA methylation and its relationship with expression changes. (A) Heatmap showing expression levels on 0, 5, and 20 days for genes displaying significant methylation and expression changes (4,753 in total with FC ≥2 or FC ≤0.5; P ≤0.01 and FDR ≤0.05) (Additional file 7). (B) catterplots showing the relationship between the log2-transformed FC in expression and the log2-transformed FC in DNA methylation. Sixty-two percent of the hypomethylated genes are overexpressed (in blue); 55% of the hypermethylated genes are repressed (in red). (C) Correlation between methylation and expression data (slope from the linear regression between DNA methylation differences versus expression differences) for all differentially methylated genes organized by genomic location (first exon, TSS, 5′UTR, gene body, 3′UTR). (D) DNA methylation and expression dynamics of selected loci during monocyte-to-osteoclast differentiation. Methylation percentage determined by bisulfite pyrosequencing. Quantitative RT-PCR data relative to RPL38. DNA methylation and expression data are represented with a black line and a red line, respectively. (E) BrdU assay showing the percentage of replicating cells at different times. From days 1 to 4, only 9.46% of cells divide. (F) Effects of 5azadC treatment (50 nM, 500 nM) on osteoclastogenesis monitoring ACP5, CTSK, and CX3CR1 levels and TRAP staining over time. (G) Workflow for testing the presence of 5 hydroxymethylcytosine in hypomethylated genes. DNA was treated with a 5hmC-specific glucosyltransferase. Cytosines bearing a 5-hydroxymethyl are protected against MspI digestion, and the surrounding region can be amplified by qPCR. When no 5hmC is present, glucose is not transferred to C, DNA is cleaved at CCGG sites, and there is less qPCR amplification. Several controls are used to set the 0% and 100% content of 5hmC. (H) 5hmC content in several of the CpGs that are rapidly demethylated after RANKL and M-CSF stimulation of OC precursors.CC BY · PubMed Central
Figure 3 Association of transcription factors with DNA methylation changes during moncoyte to OC differentiation. (A) Significant enrichment of predicted TF (TRANSFAC motif) in hypo-/hypermethylated CpG sites regions. A 500-bp window centered around the hypo-/hypermethylated CpG sites was tested. The name of the transcription factor binding motif, the P value and the TF family are provided. Below we show three of the motifs that have a higher representation in this analysis. (B) Diagrams showing the percentage of hypo-/hypermethylated CpGs with AP-1, NF-kB, and PU.1 binding sites relative to the total number of hypo-/hypermethylated CpGs. (C) Quantitative ChIP assays showing the binding of three selected transcription factors (p65 NF-kB subunit, Fos, and PU.1 to target genes selected by the presence of the putative binding motifs according to the TRANSFAC analysis). Samples were analyzed at 0 and 2 days after RANKL/M-CSF stimulation. We used Sat2 repeats and the TRDR1 MyoD1 promoter as negative control sequences.
Figure 3 Association of transcription factors with DNA methylation changes during moncoyte to OC differentiation. (A) Significant enrichment of predicted TF (TRANSFAC motif) in hypo-/hypermethylated CpG sites regions. A 500-bp window centered around the hypo-/hypermethylated CpG sites was tested. The name of the transcription factor binding motif, the P value and the TF family are provided. Below we show three of the motifs that have a higher representation in this analysis. (B) Diagrams showing the percentage of hypo-/hypermethylated CpGs with AP-1, NF-kB, and PU.1 binding sites relative to the total number of hypo-/hypermethylated CpGs. (C) Quantitative ChIP assays showing the binding of three selected transcription factors (p65 NF-kB subunit, Fos, and PU.1 to target genes selected by the presence of the putative binding motifs according to the TRANSFAC analysis). Samples were analyzed at 0 and 2 days after RANKL/M-CSF stimulation. We used Sat2 repeats and the TRDR1 MyoD1 promoter as negative control sequences.CC BY · PubMed Central
Figure 4 Interactions between PU.1 and DNTM3b and TET2 and association with promoters undergoing DNA methylation changes. (A) Quantitative RT-PCR analysis for CTSK, PU.1, p65 NF-kB, TET1, TET2, and DNMT3B during osteoclastogenesis. (B) Western blot for the same factors indicated above. (C) Immunoprecipitation experiment of p65 and PU.1 with DNMT3B and TET2 at 0, 2, and 4 days after RANKL and M-CSF stimulation. IgG used as a negative control. Reciprocal immunoprecipitation experiments in the bottom panel. (D) Quantitative ChIP assays showing PU.1, TET2, and DNMT3b binding to hypomethylated genes (ACP5, TM7SF4, TM4SF19) and hypermethylated genes (CX3CR1, NR4A2), all direct PU.1 targets, and a negative control (MYOD1 promoter) without PU.1 target sites. The experiment was performed with three biological triplicates but only one experiment is shown. T-student test comparing binding of each antibody between 0 days vs. 2 days was performed: * corresponds to P value <0.05; ** means P value <0.01; *** means P value <0.001. (E) Examples showing PU.1 binding (from ChIPseq data, GSE31621) to the region neighboring hypo- and hypermethylated CpGs. The PU.1 binding motif location is presented as a horizontal blue dot and the CpG displaying differential methylation (Illumina probe) between MO and OC is marked with a red bar. (F) Analysis of ChIPseq analysis for PU.1 and comparison to TRANSFAC predictions. Top panel: proportion of the CpG-containing probes displaying DNA methylation changes that have peaks for PU.1 binding in the same 500-bp window. Diagrams are separated in the hypo- and hypermethylated sets and in promoter and distal regions (gene bodies, 3′UTR, and intergenic regions). Bottom panel, Venn diagrams showing the overlap of PU.1 targets from ChIPseq data (GEO accession number: GSE31621) in MOs and TRANSFAC prediction for PU.1, both using a window of 500 pb centered by the CpG displaying significant methylation changes.
Figure 4 Interactions between PU.1 and DNTM3b and TET2 and association with promoters undergoing DNA methylation changes. (A) Quantitative RT-PCR analysis for CTSK, PU.1, p65 NF-kB, TET1, TET2, and DNMT3B during osteoclastogenesis. (B) Western blot for the same factors indicated above. (C) Immunoprecipitation experiment of p65 and PU.1 with DNMT3B and TET2 at 0, 2, and 4 days after RANKL and M-CSF stimulation. IgG used as a negative control. Reciprocal immunoprecipitation experiments in the bottom panel. (D) Quantitative ChIP assays showing PU.1, TET2, and DNMT3b binding to hypomethylated genes (ACP5, TM7SF4, TM4SF19) and hypermethylated genes (CX3CR1, NR4A2), all direct PU.1 targets, and a negative control (MYOD1 promoter) without PU.1 target sites. The experiment was performed with three biological triplicates but only one experiment is shown. T-student test comparing binding of each antibody between 0 days vs. 2 days was performed: * corresponds to P value <0.05; ** means P value <0.01; *** means P value <0.001. (E) Examples showing PU.1 binding (from ChIPseq data, GSE31621) to the region neighboring hypo- and hypermethylated CpGs. The PU.1 binding motif location is presented as a horizontal blue dot and the CpG displaying differential methylation (Illumina probe) between MO and OC is marked with a red bar. (F) Analysis of ChIPseq analysis for PU.1 and comparison to TRANSFAC predictions. Top panel: proportion of the CpG-containing probes displaying DNA methylation changes that have peaks for PU.1 binding in the same 500-bp window. Diagrams are separated in the hypo- and hypermethylated sets and in promoter and distal regions (gene bodies, 3′UTR, and intergenic regions). Bottom panel, Venn diagrams showing the overlap of PU.1 targets from ChIPseq data (GEO accession number: GSE31621) in MOs and TRANSFAC prediction for PU.1, both using a window of 500 pb centered by the CpG displaying significant methylation changes.CC BY · PubMed Central
Figure 5 PU.1 has a direct role in leading DNA methylation changes at their targets. (A) Scheme depicting the two regions of the SPI1 gene (PU.1) (exon 2 and 3′UTR) targeted by the two siRNAs used in this study. (B) Effects of siRNA experiments on PU.1 levels at 1, 2, 4, and 6 days as analyzed by qRT-pCR. (C) Effects of siRNA experiments on PU.1 levels at 1, 2, 4, and 6 days as analyzed by western blot (D) Effects of PU.1 downregulation on expression and methylation of PU.1-target genes that become demethylated (ACP5, CTSK), genes that become hypermethylated (CX3CR1, NR4A2) and non-pU.1 target genes, PLA2G4E, which becomes also overexpressed and demethylated, and FSCN3, which is hypermethylated and does not undergo loss of methylation during osteoclastogenesis. (E) ChIP assays showing the effects of PU.1 downregulation in its recruitment, together with TET2 and DNMT3b binding to the same genes. Data were obtained at 0, 2, and 6 days after M-CSF /RANL stimulation. To simplify the representation negative control assays with IgG for each time point have been substracted to the experiments with each antibody. We have used the MYOD1 promoter as a negative control (data without substracting the background is presented in Additional file 10). The experiment was performed with three biological triplicates but only one experiment is shown. Error bars correspond to technical replicates. Some of them are smaller than the data point icon. T-student test was performed: * corresponds to P value <0.05; ** means P value <0.01; *** means P value <0.001.
Figure 5 PU.1 has a direct role in leading DNA methylation changes at their targets. (A) Scheme depicting the two regions of the SPI1 gene (PU.1) (exon 2 and 3′UTR) targeted by the two siRNAs used in this study. (B) Effects of siRNA experiments on PU.1 levels at 1, 2, 4, and 6 days as analyzed by qRT-pCR. (C) Effects of siRNA experiments on PU.1 levels at 1, 2, 4, and 6 days as analyzed by western blot (D) Effects of PU.1 downregulation on expression and methylation of PU.1-target genes that become demethylated (ACP5, CTSK), genes that become hypermethylated (CX3CR1, NR4A2) and non-pU.1 target genes, PLA2G4E, which becomes also overexpressed and demethylated, and FSCN3, which is hypermethylated and does not undergo loss of methylation during osteoclastogenesis. (E) ChIP assays showing the effects of PU.1 downregulation in its recruitment, together with TET2 and DNMT3b binding to the same genes. Data were obtained at 0, 2, and 6 days after M-CSF /RANL stimulation. To simplify the representation negative control assays with IgG for each time point have been substracted to the experiments with each antibody. We have used the MYOD1 promoter as a negative control (data without substracting the background is presented in Additional file 10). The experiment was performed with three biological triplicates but only one experiment is shown. Error bars correspond to technical replicates. Some of them are smaller than the data point icon. T-student test was performed: * corresponds to P value <0.05; ** means P value <0.01; *** means P value <0.001.CC BY · PubMed Central
Figure 6 Model showing a simplified diagram proposing the recruitment of TET2 and DNMT3b by PU.1 to its target genes that become hypo- or hypermethylated, respectively, during osteoclastogenesis. Genes that become hypomethylated exchange PU.1-DNMT3b by PU.1-TET2 (although whether pre-existing subpopulations of these associations may exist or, alternatively, post-translational or another mechanisms may mediate exchange of TET2 and DNMT3b; this is not elucidated at present). TDG is likely to mediate conversion of 5hmC/5fmC/5caC to demethylated cytosine. Hypermethylated genes experience an increase in the binding of DNMT3b as differentiation to OCs is triggered.
Figure 6 Model showing a simplified diagram proposing the recruitment of TET2 and DNMT3b by PU.1 to its target genes that become hypo- or hypermethylated, respectively, during osteoclastogenesis. Genes that become hypomethylated exchange PU.1-DNMT3b by PU.1-TET2 (although whether pre-existing subpopulations of these associations may exist or, alternatively, post-translational or another mechanisms may mediate exchange of TET2 and DNMT3b; this is not elucidated at present). TDG is likely to mediate conversion of 5hmC/5fmC/5caC to demethylated cytosine. Hypermethylated genes experience an increase in the binding of DNMT3b as differentiation to OCs is triggered.CC BY · PubMed Central

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  • Probably not a substantial claim. 21
  • It may state two separate claims as one. 31
  • The quote only partly states this claim. 1
51 of 51
  • The paper relies on this without support.

    PU.1 and NF-kB (p65) are representative examples of transcription factors involved in the acquisition of DNA methylation changes during osteoclastogenesis.

    “To investigate the potential role of the aforementioned transcription factors in the acquisition of DNA methylation changes we chose PU.1 and NF-kB (p65 subunit) as two representative examples.”
  • The paper relies on this without support.

    The Infinium HumanMethylation450 BeadChip interrogates >485,000 methylation sites per sample at single-nucleotide resolution, covering 99% of RefSeq genes, with an average of 17 CpG sites per gene region, and covers 96% of CpG islands plus additional coverage in CpG island shores and flanking regions.

    “This array allows interrogating >485,000 methylation sites per sample at single-nucleotide resolution, covering 99% of RefSeq genes, with an average of 17 CpG sites per gene region distributed across the promoter, 5′UTR, first exon, gene body and 3′UTR. It covers 96% of CpG islands, with additional coverage in CpG island shores and the regions flanking them.”
  • The authors state this as an assumption.

    Differentially methylated regions (DMRs) are more robust signals than differentially methylated probes (DMPs).

    “We considered that DMR are more robust signals than DMPs.”
  • The paper relies on this without support.

    In many cases, methylation changes are observed over a range of CpGs, which may be identified at shores close to transcription starting sites.

    “It has been shown that in many cases methylation changes are observed over a range of CpGs, which may be identified for instance at shores close to transcription starting sites.”
  • The paper relies on this without support.

    Under the conditions used to prepare monocytes for transfection, over 80% of the cells are monocytes.

    “Under these conditions over 80% are MOs.”
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Metadata

Authors
de la Rica, L., Rodríguez-Ubreva, J., García, M., Islam, A. B., Urquiza, J. M., Hernando, H., Christensen, J., Helin, K., Gómez-Vaquero, C., & Ballestar, E.
Affiliations
  • Bellvitge University Hospital (ES)
  • Institut d'Investigació Biomédica de Bellvitge (ES)
  • University of Copenhagen (DK)
Corresponding author
Ballestar, Esteban
Venue
Genome Biology
Published
2013-09-12
Volume
14
Issue
9
Pages
R99-R99
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
OpenAlex
W2123115454
Cited by
211
References
70
Citations by year
2026: 5 · 2025: 18 · 2024: 12 · 2023: 9 · 2022: 18 · 2021: 21 · 2020: 24 · 2019: 26 · 2018: 13 · 2017: 23 · 2016: 15 · 2015: 14 · 2014: 12 · 2013: 1
FWCI
6.23
Type
journal article
Language
en
Open access
Locations
  • Genome biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RECERCAT (Consorci de Serveis Universitaris de Catalunya) (publishedVersion, other-oa)
  • Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, cc-by)
  • Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by)
Funders
  • Fundación Ramón Areces
  • Ministerio de Ciencia e Innovación (2009SGR184, SAF2011-29635)
  • Agència de Gestió d'Ajuts Universitaris i de Recerca
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bone Metabolism and Diseases
Keywords
PU.1, TET2, DNMT3B, DNA methylation, 5-hydroxymethylcytosine, demethylation, osteoclastogenesis, monocyte differentiation, transcription factor binding motifs, epigenetic regulation, NF-κB, AP-1, transcription factor binding
MeSH terms
DNA Methyltransferase 3B, Proto-Oncogene Protein Spi-1, Binding Sites, Cell Differentiation, Cytosine, DNA (Cytosine-5-)-Methyltransferases, DNA-Binding Proteins, Humans, Monocytes, Osteoclasts, Protein Binding, Proto-Oncogene Proteins, Trans-Activators, NF-kappa B, Transcription Factor AP-1, CpG Islands, DNA Methylation, RNA, Small Interfering, Epigenesis, Genetic, 5-Methylcytosine, Dioxygenases, Protein Interaction Domains and Motifs

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