The DOI matches its Crossref record; 86 of the 87 references it cites were found in a registry or an index, and 1 are not checked yet.
DNA methylation disruption reshapes the hematopoietic differentiation landscape
Open accessAbstract
Mutations in genes involved in DNA methylation (DNAme; for example, TET2 and DNMT3A) are frequently observed in hematological malignancies 1-3 and clonal hematopoiesis 4,5. Applying single-cell sequencing to murine hematopoietic stem and progenitor cells, we observed that these mutations disrupt hematopoietic differentiation, causing opposite shifts in the frequencies of erythroid versus myelomonocytic progenitors following Tet2 or Dnmt3a loss. Notably, these shifts trace back to transcriptional priming skews in uncommitted hematopoietic stem cells. To reconcile genome-wide DNAme changes with specific erythroid versus myelomonocytic skews, we provide evidence in support of differential sensitivity of transcription factors due to biases in CpG enrichment in their binding motif. Single-cell transcriptomes with targeted genotyping showed similar skews in transcriptional priming of DNMT3A-mutated human clonal hematopoiesis bone marrow progenitors. These data show that DNAme shapes the topography of hematopoietic differentiation, and support a model in which genome-wide methylation changes are transduced to differentiation skews through biases in CpG enrichment of the transcription factor binding motif.
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.
Integrity signals
Registry
Cites
Statistics
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.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, analysis of DNA methylation and gene expression patterns in mouse (15,17) and human (17,18) systems have yet to identify a unifying molecular mechanism to explain the increased fitness of these mutant HSCs.”
From Txnip Enhances Fitness of Dnmt3a -Mutant Hematopoietic Stem Cells via p21 (2022) · cites this paper as [17]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“yet focal methylation alterations appear physiologically relevant (17,18,37,41).”
From Txnip Enhances Fitness of Dnmt3a -Mutant Hematopoietic Stem Cells via p21 (2022) · cites this paper as [17]
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
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S. L., Jagodnik, K. M., Lachmann, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw377 · Cited by 10,799
Generalized linear mixed models: a practical guide for ecology and evolution
Bolker, B. M., Brooks, M. E., Clark, C. J., Geange, S. W., Poulsen, J. R., Stevens, M. H. H., & White, J.-S. S. (2009) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2008.10.008 · Cited by 8,910
DNA methylation patterns and epigenetic memory
Bird, A. (2002) · Genes & Development · doi:10.1101/gad.947102 · Cited by 7,124
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110
Scenic: single-cell regulatory network inference and clustering.
Aibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.-C., Geurts, P., Aerts, J., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4463 · Cited by 6,520
Mutational heterogeneity in cancer and the search for new cancer-associated genes
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., Carter, S. L., Stewart, C., Mermel, C. H., Roberts, S. A., et al. (2013) · Nature · doi:10.1038/nature12213 · Cited by 5,461
Self-citation
Cited by
Sorted by citations
Items 201–236 of 236
ASXL1 Directs Neutrophilic Differentiation via Modulation of MYC and RNA Polymerase IIPreprint
Braun, T. P., Estabrook, J., Darmusey, L., Coleman, D. J., Schonrock, Z., Smith, B. M., Taherinasab, A., Enright, T., Coblentz, C., Yashar, W. M., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.14.295295
Investigating the Role of ZNF384 Rearrangements in Acute Leukemia
Dickerson, K. M. (2021) · doi:10.21007/etd.cghs.2021.0528
Biran, A., Yin, S., Kretzmer, H., ten Hacken, E., Parvin, S., Lucas, F. M., Uduman, M., Gutierrez, C., Dangle, N. J., Billington, L., et al. (2023) · doi:10.1158/0008-5472.c.6513540.v1
Data from ZNF384 Fusion Oncoproteins Drive Lineage Aberrancy in Acute Leukemia
Dickerson, K. M., Qu, C., Gao, Q., Iacobucci, I., Gu, Z., Yoshihara, H., Backhaus, E. A., Chang, Y., Janke, L. J., Xu, B., et al. (2023) · doi:10.1158/2643-3230.c.6550713.v1
Chen, S., Vedula, R. S., Cuevas-Navarro, A., Lü, B., Hogg, S. J., Wang, E., Benbarche, S., Knorr, K. L. B., Kim, W. J., Stanley, R. F., et al. (2023) · doi:10.1158/2159-8290.c.6549783
Self-citationEpigenetic Code for Cell Fate During Development and Disease in Human
Uzuner, S. Ç. (2023) · Eurasian Journal of Medicine and Oncology · doi:10.14744/ejmo.2023.42324
Cell of origin epigenetic priming determines susceptibility to Tet2 mutationPreprint
Schiroli, G., Kartha, V. K., Duarte, F. M., Kristiansen, T. A., Mayerhofer, C., Shrestha, R., Earl, A., Hu, Y., Tay, T., Rhee, C., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.04.556230
The clones have STRACK: Tracing responses to leukemic mutations
Papapetrou, E. P. (2025) · Cell stem cell · doi:10.1016/j.stem.2025.03.001
Fu, M. P., Edwards, K., Navarro‐Delgado, E. I., Merrill, S. M., Kitaba, N. T., Konwar, C., Mandhane, P. J., Simons, E., Subbarao, P., Moraes, T. J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.22.649907
Swann, J. W., Fung, J. H., Chen, Z., Olson, O. C., Collins, A., Lhakhang, T. W., Proven, M. A., Zhang, R., Rabadán, R., & Passegue, E. A. (2026) · Cell stem cell · doi:10.1016/j.stem.2026.05.007
Differences between in vivo and ex vivo models drive divergent perturbation outcomesPreprint
Geetha, A. R. S. J., del Valle, C., Esser‐Skala, W., Lara‐Astiaso, D., & Fortelny, N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.02.673692
DNA methylation as a new frontier in treating fear-related disorders: A need for careful evaluation
Huang, X., Chen, D., Wang, Y., Zhang, Y., Ntim, M., Ge, Y., & Wang, B. (2025) · World Journal of Psychiatry · doi:10.5498/wjp.v15.i11.110581
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962412
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962454
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962430
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962421
Cheng, G., Wu, J., Ji, M., Hu, W., Wu, C., & Jiang, J. (2023) · Figshare · doi:10.6084/m9.figshare.24089380
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962442
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962451
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962433
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962418
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962406
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962445
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962409
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962448
Mei, Y., Liu, Y., Liu, W., Chen, M., Liu, X., Wang, S., Mou, J., Xing, H., Tang, K., Tian, Z., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26962427
Cypris, O., Franzen, J., Frobel, J., Glück, P., Kuo, C.-C., Schmitz, S., Nüchtern, S., Zenke, M., & Wagner, W. (2022) · Figshare · doi:10.6084/m9.figshare.20081040
Song, J., Wang, F., Xie, Y., Luo, X., Tao, H., Fan, R., Zhou, Y., Wu, J., Huang, T., Zhao, H., et al. (2026) · Cell Death and Differentiation · doi:10.1038/s41418-026-01715-8
Critical and different roles of DNA methylation in male germ cell development
Dura, M. (2021) · theses.fr (ABES) · doi:10.70675/a86104ccz3d42z4526za2bczff2519550eda
Deciphering the role of DNA methylation in early cellular transitions
Schulz, M. (2022) · theses.fr (ABES) · doi:10.70675/7612d87bz4c9ez49e6z87d4zb159d5924480
TET2: a critical regulatory hub with broad therapeutic implications across human diseases
Tang, J., Wang, R., Long, L., Ma, W., Han, X., & Fu, H. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1802805
Liu, X., Liu, J., Feng, L., Xu, D., Wei, X., & Tong, D. (2026) · Cell Biochemistry and Function · doi:10.1002/cbf.70287
Li, Y., Luo, K., Xia, K., Liu, J., Zhao, Z., Cai, Z., & Dong, G. (2026) · Disease Models & Mechanisms · doi:10.1242/dmm.052484
Metadata
- Authors
- Izzo, F., Lee, S. C., Poran, A., Chaligne, R., Gaiti, F., Gross, B., Murali, R. R., Deochand, S. D., Ang, C., Jones, P. W., Nam, A. S., Kim, K.-T., Kothen-Hill, S., Schulman, R. C., Ki, M., Lhoumaud, P., Skok, J. A., Viny, A. D., Levine, R. L., Kenigsberg, E., Abdel-Wahab, O., & Landau, D. A.
- Affiliations
- New York Genome Center (US)
- Memorial Sloan Kettering Cancer Center (US)
- Weill Cornell Medicine (US)
- NYU Langone Health (US)
- Icahn School of Medicine at Mount Sinai (US)
- Corresponding author
- Landau, Dan A.
- ORCID
- Venue
- Nature Genetics
- Published
- 2020-03-23
- Volume
- 52
- Issue
- 4
- Pages
- 378-387
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC7216752
- OpenAlex
- W3012899267
- Cited by
- 236
- References
- 86
- Citations by year
- 2026: 16 · 2025: 25 · 2024: 46 · 2023: 42 · 2022: 45 · 2021: 38 · 2020: 24
- FWCI
- 23.53
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Burroughs Wellcome Fund
- Pershing Square Foundation
- Foundation for the National Institutes of Health (DP2-CA239065)
- EIF | Stand Up To Cancer (SU2C-AACR-IRG-0616)
- American Society of Hematology
- Marie Skłodowska-Curie
- National Cancer Center
- U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI R00 CA218896, K08 CA215317)
- U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (1R35GM122515)
- Damon Runyon Cancer Research Foundation (DRG 117-15)
- Edward P. Evans Foundation
- Leukemia and Lymphoma Society
- U.S. Department of Health & Human Services | National Institutes of Health (P30 CA008748)
- Topics
- Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Hematology › Hematopoietic Stem Cell Transplantation
- Keywords
- DNA methylation, hematopoietic differentiation, TET2, DNMT3A, clonal hematopoiesis, hematologic malignancies, hematopoietic stem cells, erythroid progenitor cells, transcriptional priming, transcription factor binding motifs, single-cell transcriptomics, targeted genotyping
- MeSH terms
- Animals, Cell Differentiation, DNA (Cytosine-5-)-Methyltransferases, DNA-Binding Proteins, Hematopoiesis, Hematopoietic Stem Cells, Humans, Male, Mice, Transgenic, Mutation, Transcription, Genetic, DNA Methylation, Mice, Transcriptome
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
