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Human DNMT3A (UniProt Q9Y6K1): Functional-Annotation Research Report

Executive summary

DNMT3A is the correctly identified human protein for the supplied UniProt accession Q9Y6K1: DNA (cytosine-5)-methyltransferase 3A, encoded by DNMT3A. The literature consistently describes the same human multidomain enzyme, with PWWP and ADD chromatin-reader domains and a C-terminal C5 DNA-methyltransferase domain; no ambiguous or conflicting gene identity was encountered. The accession-to-protein mapping is taken from the supplied UniProt record, while human nomenclature and domain architecture are independently corroborated by structural and clinical literature and by the approved human gene record ENSG00000119772. (OpenTargets Search: -DNMT3A, chen2024structuralbasisfor pages 1-2, zebrauskiene2024aorticdiseaseand pages 1-2)

DNMT3A is principally a nuclear, chromatin-associated, de novo DNA methyltransferase. It transfers a methyl group from S-adenosyl-L-methionine (SAM/AdoMet) to carbon 5 of cytosine, generating 5-methylcytosine and S-adenosyl-L-homocysteine. Its principal physiological targets are CpG dinucleotides in chromosomal DNA, although DNMT3A also contributes to non-CpG methylation—especially CpA—in selected cell types. Its genomic specificity is not determined by DNA sequence alone: multiple chromatin-reading modules recognize histone states and the nucleosome surface, thereby coupling DNA methylation to histone signaling. (wapenaar2023thenterminalregion pages 1-4, schmelmer2026targetingdnmt3aregulatory pages 9-15, chen2024structuralbasisfor pages 1-2)

The most important 2024 advance was a substantially more resolved model of DNMT3A1 recruitment to nucleosomes. Independent cryo-EM and cellular studies showed that its isoform-specific ubiquitin-dependent recruitment region, or UDR, binds H2AK119ub1, nucleosomal DNA, and the H2A–H2B acidic patch. This complements PWWP recognition of H3K36me2/3 and ADD recognition of H3K4me0, establishing DNMT3A as a multivalent chromatin sensor rather than a freely diffusing enzyme with simple CpG specificity. (chen2024structuralbasisfor pages 1-2, gretarsson2024cancerassociateddnahypermethylation pages 1-2, wapenaar2024thenterminalregion pages 1-3)

Evidence summary

Table: Concise evidence map for human DNMT3A Q9Y6K1, covering molecular function, chromatin targeting, localization, disease associations, quantitative findings, and therapeutic status. The accession is treated as user-provided because the gathered literature did not independently verify it.

1. Identity verification and nomenclature

The requested symbol is not ambiguous in this context. DNMT3A is the approved human symbol for DNA methyltransferase 3 alpha, and the supplied UniProt entry identifies Q9Y6K1 as the human DNA (cytosine-5)-methyltransferase 3A. Current studies use DNMT3A for the same vertebrate de novo methyltransferase and distinguish it clearly from DNMT3B, the maintenance enzyme DNMT1, and catalytically inactive DNMT3L. Open Targets likewise maps DNMT3A to human gene ENSG00000119772 and reports strong genetic and disease associations with AML, other myeloid neoplasms, and Tatton–Brown–Rahman syndrome. (OpenTargets Search: -DNMT3A, chen2024structuralbasisfor pages 1-2)

The supplied InterPro annotations align with the literature. DNMT3A contains a PWWP chromatin-reader domain, an ATRX–DNMT3–DNMT3L-type zinc-binding ADD domain, and a C-terminal class-I-like SAM-binding C5-cytosine methyltransferase domain containing the active site, SAM pocket, DNA-binding loops, and target-recognition region. DNMT3A1 also contains an N-terminal UDR that is absent from DNMT3A2. (wapenaar2023thenterminalregion pages 62-64, wapenaar2024thenterminalregion pages 1-3, zebrauskiene2024aorticdiseaseand pages 1-2)

2. Primary molecular function and reaction

DNMT3A catalyzes:

SAM + DNA cytosine → S-adenosyl-L-homocysteine + DNA 5-methylcytosine.

The reaction modifies carbon 5 of the cytosine pyrimidine ring without changing the DNA sequence. In the canonical C5-DNA-methyltransferase mechanism, the target cytosine is flipped from the duplex into the catalytic pocket; an active-site cysteine attacks the cytosine ring, enabling transfer of the SAM methyl group, followed by elimination and restoration of aromaticity. (wapenaar2023thenterminalregion pages 1-4, schmelmer2026targetingdnmt3aregulatory pages 9-15)

DNMT3A is conventionally termed a de novo methyltransferase because it can methylate previously unmethylated DNA rather than requiring a hemimethylated CpG template. This contrasts with DNMT1’s strong specialization for copying methylation after replication. The distinction is not absolute in living cells: DNMT3A remains expressed after development and contributes to adult methylation homeostasis, while de novo and maintenance enzymes can cooperate. (wapenaar2023thenterminalregion pages 1-4, wapenaar2024thenterminalregion pages 1-3)

Substrate specificity

The dominant physiological substrate is double-stranded nuclear DNA in chromatin, particularly cytosines in CpG dinucleotides. The isolated catalytic domain can perform CpG-specific methylation, but nucleosomes, linker geometry, histone modifications, oligomerization, and accessory factors strongly influence which CpGs are reached in vivo. DNMT3A can also methylate non-CpG sites, especially CpA, in embryonic, germ-cell, and neuronal contexts; therefore, describing the enzyme as absolutely CpG-specific would be incorrect. (chen2024structuralbasisfor pages 1-2, wapenaar2024thenterminalregion pages 1-3)

More than 80% of genomic CpGs are methylated overall, but that statistic represents the combined methylation system and should not be interpreted as the fraction methylated directly by DNMT3A. CpG islands at active promoters commonly remain unmethylated despite high CpG density, demonstrating that CpG availability alone is insufficient for recruitment. (wapenaar2024thenterminalregion pages 1-3)

3. Structure, assembly, and regulation

Catalytic assembly

DNMT3A forms homodimers, homotetramers, and higher-order oligomers. It can also assemble with catalytically inactive DNMT3L in a DNMT3L–DNMT3A–DNMT3A–DNMT3L heterotetramer, or with catalytically inactive DNMT3B3. These accessory proteins stabilize productive assemblies and stimulate methylation without themselves supplying the active catalytic center. (schmelmer2026targetingdnmt3aregulatory pages 9-15, gretarsson2024cancerassociateddnahypermethylation pages 1-2, zebrauskiene2024aorticdiseaseand pages 1-2)

Oligomerization is functionally important rather than merely structural. The R882 interface is a major AML mutation hotspot; substitutions at this site perturb DNA engagement and normal assembly, producing marked loss of activity and, in heterozygous cells, dominant-negative behavior toward wild-type subunits. The exact balance among impaired DNA binding, altered oligomerization, and catalytic defects depends on the variant and experimental system. (liddo2024theimplicationsof pages 2-4, liddo2024theimplicationsof pages 1-2, liddo2024theimplicationsof pages 4-5)

ADD domain: H3K4 methylation sensor and allosteric switch

The ADD domain recognizes the unmodified histone H3 amino terminus, particularly H3K4me0. In the absence of an appropriate H3 tail, the ADD domain can occupy and inhibit the catalytic region. H3K4me0 binding drives a conformational reorganization that relieves this autoinhibition. Conversely, H3K4 methylation—especially the active-promoter mark H3K4me3—opposes this interaction and helps protect active promoters from de novo methylation. (schmelmer2026targetingdnmt3aregulatory pages 9-15, dupas2026dnmt3aincancer pages 2-3, zebrauskiene2024aorticdiseaseand pages 1-2)

This model has in-vivo support. A 2024 mouse germ-cell study found that loss-of-function substitutions in either the DNMT3A or DNMT3L ADD domain moderately reduced global CG methylation; combined disruption produced a much stronger loss, particularly in oocytes, and aberrant non-CG methylation at thousands of regions. Thus, ADD–H3K4me0 recognition helps determine both methylation quantity and placement. DOI: https://doi.org/10.1038/s41467-024-47699-2. (schmelmer2026targetingdnmt3aregulatory pages 91-93, schmelmer2026targetingdnmt3aregulatory pages 84-86)

PWWP domain: H3K36 methylation reader

The PWWP domain recognizes H3K36me2 and H3K36me3 and also interacts with DNA. This directs DNMT3A toward H3K36-methylated intergenic regions, promoter-proximal regions, and gene bodies. H3K36me2 is particularly associated with DNMT3A recruitment and can stimulate methylation on nucleosome substrates. Pathogenic PWWP variants can redirect DNMT3A and cause abnormal methylation rather than simply producing uniform loss of function. (chen2024structuralbasisfor pages 1-2, gretarsson2024cancerassociateddnahypermethylation pages 1-2, wapenaar2024thenterminalregion pages 1-3)

DNMT3A1 UDR: H2AK119ub1 and Polycomb-linked recruitment

Three complementary 2024 studies sharpened understanding of the DNMT3A1-specific N terminus. Chen et al. resolved a 3.26-Å cryo-EM structure in which two UDR molecules bind one H2AK119ub1 nucleosome. The UDR contacts ubiquitin, nucleosomal DNA, the H2A–H2B acidic patch, and a groove formed by H2A and H3. Its affinity was 16.6 nM for an H2AK119ub1 nucleosome versus 197 nM for an unmodified nucleosome—approximately a 12-fold preference. The work was accepted July 12, 2024; DOI: https://doi.org/10.1038/s41467-024-50526-3. (chen2024structuralbasisfor pages 1-2)

Gretarsson et al. showed that this is a bidentate cellular recruitment mechanism: DNMT3A1 recognition of both H2AK119ub and the acidic patch is required for effective engagement with Polycomb-marked chromatin. Experimentally redirecting DNMT3A1 to Polycomb targets recreated a cancer-associated promoter-CpG-island hypermethylation signature and blocked transcriptional activation during differentiation; disrupting the acidic-patch interaction rescued the phenotype. Published August 28, 2024; DOI: https://doi.org/10.1126/sciadv.adp0975. (gretarsson2024cancerassociateddnahypermethylation pages 1-2)

Wapenaar et al. confirmed these interactions using full-length DNMT3A1–DNMT3L and emphasized a key mechanistic distinction: H2AK119ub increases recruitment but does not itself stimulate methyltransferase activity in the way H3K36me2 does. The authors interpret DNMT3A targeting as multivalent avidity across histone marks, DNA, and the nucleosome surface. Published online November 11, 2024; DOI: https://doi.org/10.1038/s44319-024-00306-3. (wapenaar2024thenterminalregion pages 1-3)

Collectively, these studies support an expert model in which binding and catalysis are separable. A chromatin mark may concentrate DNMT3A without activating its catalytic center; productive methylation requires compatible DNA accessibility, histone context, ADD activation, and enzyme assembly. (chen2024structuralbasisfor pages 1-2, gretarsson2024cancerassociateddnahypermethylation pages 1-2, wapenaar2024thenterminalregion pages 1-3)

4. Isoforms and cellular localization

Human DNMT3A has at least two principal protein isoforms. DNMT3A1 is full length and contains the approximately 223-residue N-terminal extension with the UDR. It is broadly and stably expressed in somatic cells and is the predominant postnatal isoform. DNMT3A2 uses an alternative promoter, lacks this N-terminal segment, and is prominent in embryonic stem cells, early development, and germ cells, although expression persists in selected adult tissues and cancers. (chen2024structuralbasisfor pages 1-2, wapenaar2024thenterminalregion pages 1-3)

Both isoforms carry out their principal function in the nucleus on chromatin. DNMT3A1 has been reported as exclusively nuclear and enriched in transcriptionally inactive heterochromatin, whereas DNMT3A2 has a more diffuse nuclear pattern associated with transcriptionally active euchromatin. This distribution is consistent with DNMT3A1’s N-terminal recognition of H2AK119ub-marked facultative heterochromatin and with broader differences in developmental expression. (chen2024structuralbasisfor pages 1-2)

DNMT3A should therefore be annotated as a nuclear/chromatin enzyme, not as a secreted, membrane, or cytosolic protein. Its subnuclear distribution is dynamic and depends on isoform, cell type, interacting proteins, histone modifications, and disease-associated variants. (chen2024structuralbasisfor pages 1-2, wapenaar2024thenterminalregion pages 1-3)

5. Biological pathways and precise physiological roles

DNMT3A operates at the interface of the DNA-methylation, histone-modification, Polycomb, differentiation, and genomic-imprinting pathways. Its direct biochemical output is 5mC deposition; downstream consequences arise because methylated DNA can alter transcription-factor binding, recruit methyl-CpG readers, reinforce repressive chromatin, and stabilize cell-type-specific regulatory states. (wapenaar2023thenterminalregion pages 1-4, gretarsson2024cancerassociateddnahypermethylation pages 1-2)

During embryogenesis and germ-cell development, DNMT3A establishes new methylation patterns, including methylation needed for genomic imprints. DNMT3L is especially important in germ cells, where it stimulates DNMT3A and helps couple H3-tail state to DNA methylation. Genetic disruption of Dnmt3a causes severe postnatal developmental failure in mice, supporting a nonredundant role despite partial overlap with DNMT3B. (dupas2026dnmt3aincancer pages 2-3, liddo2024theimplicationsof pages 4-5)

In adult hematopoietic stem cells, DNMT3A limits excessive self-renewal and supports orderly differentiation. Loss-of-function variants confer a competitive stem-cell advantage, permitting long-lived mutant clones that can precede overt leukemia by years. The mutation is therefore often an initiating or “founder” lesion rather than a late consequence of transformation. (liddo2024theimplicationsof pages 4-5, dunn2024clonalhematopoiesisand pages 1-2, kawashima2024landscapeofbiallelic pages 1-2)

In neurons, DNMT3A and the activity-inducible DNMT3A2 isoform contribute to postnatal methylation and activity-dependent gene regulation. Interaction between DNMT3A’s ADD domain and MECP2 can regulate DNMT3A activity and subnuclear localization; the MECP2 interaction overlaps the histone-H3 binding surface, suggesting competitive control. Protein Science, 2023; DOI: https://doi.org/10.1002/pro.4542. (wapenaar2023thenterminalregion pages 1-4)

6. Disease mechanisms and recent quantitative evidence

Clonal hematopoiesis

Clonal hematopoiesis is expansion of a hematopoietic stem-cell clone carrying a fitness-conferring mutation. CHIP conventionally denotes a clone with variant allele fraction of at least 2%, corresponding to roughly 4% of nucleated blood cells for a heterozygous variant. Standard-depth sequencing detects CHIP in approximately 10–20% of people older than 70, while highly sensitive methods detect much smaller clones in nearly everyone by ages 50–60. DNMT3A is among the most frequent driver genes. (dunn2024clonalhematopoiesisand pages 1-2)

The clinical interpretation must be variant-specific. DNMT3A-mutant CH is not equivalent to AML and usually remains subclinical, but it raises the probability of later myeloid neoplasia. Risk is shaped by clone size, mutation site—particularly R882—co-mutations, blood-count abnormalities, and expansion dynamics. A 2024 JCI review emphasizes that current research is moving from binary CHIP detection toward multivariable risk prediction and interception programs. Published October 2024; DOI: https://doi.org/10.1172/JCI180065. (dunn2024clonalhematopoiesisand pages 1-2)

AML, MDS, and related myeloid neoplasms

DNMT3A mutations occur in approximately 20–25% of de novo AML and about 10% of MDS; broader AML series commonly report 20–30%. R882 substitutions constitute the dominant hotspot and were estimated at approximately two-thirds of DNMT3A-mutant AML in one 2024 review. These variants are associated with abnormal methylation, impaired differentiation, treatment resistance in some settings, and adverse outcomes, although prognosis depends heavily on co-mutations and treatment. (OpenTargets Search: -DNMT3A, liddo2024theimplicationsof pages 1-2, kawashima2024landscapeofbiallelic pages 1-2)

A 2024 Cleveland Clinic study analyzed 5,603 consecutive myeloid neoplasms and found DNMT3A mutations in 533 patients (9.5%); 45 of 533 (8.4%) had multiple DNMT3A hits. Multiple hits were associated with IDH2 mutations—24.4% versus 9.6%, odds ratio 3.03, P=0.005—and ETV6 mutations—6.7% versus 1.4%, odds ratio 4.91, P=0.044. (kawashima2024landscapeofbiallelic pages 1-2)

Among treated AML patients, inferred biallelic DNMT3A impairment was associated with 5.6% two-year overall survival, versus 47.6% for monoallelic DNMT3A-mutant AML, P=0.002. Biallelic impairment remained independently adverse, hazard ratio 2.65, P=0.001. In longitudinal analysis, 9 of 12 biallelic clones—75%—persisted or expanded at relapse or transformation, supporting their early origin and strong leukemogenic potential. Published September 2024; DOI: https://doi.org/10.1186/s13045-024-01607-9. (kawashima2024landscapeofbiallelic pages 1-2)

Germline DNMT3A disorders

Heterozygous, usually de novo loss-of-function variants cause Tatton–Brown–Rahman syndrome (TBRS), also called DNMT3A-overgrowth syndrome. Core findings are generalized overgrowth, intellectual disability, and characteristic facial features. In a 2024 French series of 24 affected individuals—including 17 novel variants—intellectual disability occurred in 100%, characteristic facial features in 96%, and overgrowth in 87%. Approximately 100 individuals with de novo germline variants had been described before that cohort. Published June 2024; DOI: https://doi.org/10.1136/jmg-2024-110031. (thomas2024expandingthegenetic pages 1-5)

A 2024 family study expanded possible cardiovascular manifestations. Three adults carrying a familial Ser775Tyr variant in the methyltransferase domain had variable combinations of aortic dilation, mitral regurgitation, ventricular dilation, and arrhythmia. Because this is a single family, it establishes a surveillance signal rather than a population risk estimate; the authors recommended assessment for aortic and valvular disease in congenital DNMT3A cases. DOI: https://doi.org/10.1186/s13148-024-01686-y. (zebrauskiene2024aorticdiseaseand pages 1-2)

Domain-specific gain- or change-of-function variants can produce phenotypes distinct from classic TBRS, including Heyn–Sproul–Jackson syndrome and microcephalic dwarfism. PWWP-domain disruption may redistribute DNMT3A away from H3K36-methylated chromatin, producing ectopic hypermethylation rather than simple global hypomethylation. This distinction is important for variant interpretation. (chen2024structuralbasisfor pages 1-2, gretarsson2024cancerassociateddnahypermethylation pages 1-2)

7. Current applications and real-world implementation

Molecular diagnosis and risk stratification

DNMT3A is routinely included on clinical NGS panels for AML, MDS, unexplained cytopenias, and other myeloid neoplasms. Reporting generally includes the precise variant, variant allele fraction, R882 status, and relevant co-mutations. In AML, these data contribute to clonal reconstruction, prognosis, and longitudinal disease assessment, although DNMT3A can persist in preleukemic clones during remission and must not automatically be interpreted as residual leukemia. (dunn2024clonalhematopoiesisand pages 1-2, kawashima2024landscapeofbiallelic pages 1-2)

For suspected TBRS, germline sequencing establishes the molecular diagnosis; genome-wide methylation signatures can provide orthogonal support for pathogenicity, especially for missense variants or variants of uncertain significance. Cardiovascular and hematologic surveillance is increasingly considered where indicated by the patient’s variant and phenotype, but evidence-based schedules remain limited by cohort size. (thomas2024expandingthegenetic pages 1-5, zebrauskiene2024aorticdiseaseand pages 1-2)

Therapeutic use

No selective, clinically approved DNMT3A-directed inhibitor or activator was identified in the gathered evidence. Azacitidine and decitabine are approved hypomethylating nucleoside analogues used in AML and MDS, but they inhibit the DNA-methyltransferase system broadly and should not be called DNMT3A-specific therapies. Their clinical activity does not prove that direct inhibition of DNMT3A is beneficial, particularly because many AML-associated DNMT3A mutations already reduce normal enzyme function. (OpenTargets Search: -DNMT3A, liddo2024theimplicationsof pages 2-4, liddo2024theimplicationsof pages 4-5)

This creates a central therapeutic challenge: wild-type DNMT3A may need preservation, whereas mutant clones may require restoration of normal methylation, disruption of dominant-negative assembly, elimination of mutant stem cells, or targeting of downstream dependencies. The newly defined ADD, PWWP, UDR, acidic-patch, and oligomerization interfaces are plausible drug-discovery sites, but selective modulation remains preclinical. (schmelmer2026targetingdnmt3aregulatory pages 91-93, chen2024structuralbasisfor pages 1-2, gretarsson2024cancerassociateddnahypermethylation pages 1-2)

The most mature real-world use of DNMT3A information is therefore diagnostic and prognostic, not direct pharmacologic targeting. CHIP clinics and research programs increasingly use DNMT3A findings for surveillance and cardiovascular/myeloid risk assessment, but routine population screening and preventive treatment are not yet established standards. (dunn2024clonalhematopoiesisand pages 1-2)

8. Evidence appraisal and expert interpretation

The highest-confidence annotation is that DNMT3A is a nuclear, chromatin-directed SAM-dependent cytosine-C5 methyltransferase. Reaction chemistry, catalytic-domain structure, de novo CpG activity, and PWWP/ADD architecture are supported by convergent biochemical, structural, and genetic evidence. (schmelmer2026targetingdnmt3aregulatory pages 9-15, chen2024structuralbasisfor pages 1-2, zebrauskiene2024aorticdiseaseand pages 1-2)

A current mechanistic synthesis is that DNMT3A specificity is multilayered:

1. The catalytic domain recognizes and methylates accessible DNA cytosines.
2. Oligomerization determines catalytic efficiency and spacing.
3. ADD binding to H3K4me0 relieves autoinhibition.
4. PWWP recognition of H3K36me2/3 promotes regional recruitment.
5. The DNMT3A1-specific UDR recognizes H2AK119ub and the nucleosome acidic patch.
6. DNMT3L or DNMT3B3 stabilizes and stimulates selected complexes.
7. Cell type, isoform expression, nucleosome positioning, and competing chromatin proteins determine the final methylation pattern. (schmelmer2026targetingdnmt3aregulatory pages 9-15, chen2024structuralbasisfor pages 1-2, gretarsson2024cancerassociateddnahypermethylation pages 1-2, wapenaar2024thenterminalregion pages 1-3)

The strongest recent conceptual advance is the separation of recruitment from activation. H2AK119ub can markedly enhance DNMT3A1 binding yet fail to stimulate catalytic activity, whereas H3K36me2 can support both recruitment and methylation. This explains why simple colocalization between DNMT3A and a chromatin mark does not necessarily predict DNA hypermethylation. (chen2024structuralbasisfor pages 1-2, wapenaar2024thenterminalregion pages 1-3)

Disease interpretation must likewise avoid a universal “loss-of-function” model. TBRS commonly reflects haploinsufficiency or impaired activity; AML R882 variants often behave dominantly; and PWWP variants can redistribute methylation and cause locus-specific gains. Variant position, zygosity, isoform, and chromatin context are therefore essential to functional annotation and clinical interpretation. (chen2024structuralbasisfor pages 1-2, thomas2024expandingthegenetic pages 1-5, kawashima2024landscapeofbiallelic pages 1-2)

Conclusion

Human DNMT3A/Q9Y6K1 is a multidomain de novo DNA methyltransferase whose catalytic substrate is chromosomal DNA and whose methyl donor is SAM. It functions primarily in the nucleus, where the PWWP, ADD, and DNMT3A1-specific UDR modules integrate H3K36 methylation, H3K4 methylation state, H2AK119 ubiquitylation, DNA, and the nucleosome surface. Through this multivalent system, DNMT3A establishes and remodels methylation patterns during development, imprinting, differentiation, hematopoiesis, and postnatal tissue function. (wapenaar2023thenterminalregion pages 1-4, chen2024structuralbasisfor pages 1-2, wapenaar2024thenterminalregion pages 1-3)

The most consequential clinical applications are germline and somatic variant diagnosis, AML and CHIP risk stratification, and molecular surveillance. DNMT3A is a major disease gene, but there is currently no validated selective DNMT3A therapy; broad hypomethylating drugs act on the methyltransferase system rather than specifically correcting DNMT3A dysfunction. Recent 2024 structural studies now provide a stronger foundation for variant interpretation and for future selective targeting of chromatin-recruitment and oligomerization interfaces. (OpenTargets Search: -DNMT3A, chen2024structuralbasisfor pages 1-2, gretarsson2024cancerassociateddnahypermethylation pages 1-2, kawashima2024landscapeofbiallelic pages 1-2)

References

1. (OpenTargets Search: -DNMT3A): Open Targets Query (-DNMT3A, 8 results). Buniello, A. et al. (2025). Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery. Nucleic Acids Research.

2. (chen2024structuralbasisfor pages 1-2): Xinyi Chen, Yiran Guo, Ting Zhao, Jiuwei Lu, Jian Fang, Yinsheng Wang, Gang Greg Wang, and Jikui Song. Structural basis for the h2ak119ub1-specific dnmt3a-nucleosome interaction. Nature Communications, Jul 2024. URL: https://doi.org/10.1038/s41467-024-50526-3, doi:10.1038/s41467-024-50526-3. This article has 32 citations and is from a highest quality peer-reviewed journal.

3. (zebrauskiene2024aorticdiseaseand pages 1-2): Dovile Zebrauskiene, Egle Sadauskiene, Justas Dapkunas, Visvaldas Kairys, Joris Balciunas, Aleksandras Konovalovas, Ruta Masiuliene, Gunda Petraityte, Nomeda Valeviciene, Mindaugas Mataciunas, Jurate Barysiene, Violeta Mikstiene, Migle Tomkuviene, and Egle Preiksaitiene. Aortic disease and cardiomyopathy in patients with a novel dnmt3a gene variant causing tatton-brown–rahman syndrome. Clinical Epigenetics, Jun 2024. URL: https://doi.org/10.1186/s13148-024-01686-y, doi:10.1186/s13148-024-01686-y. This article has 3 citations and is from a peer-reviewed journal.

4. (wapenaar2023thenterminalregion pages 1-4): Hannah Wapenaar, Gillian Clifford, Willow Rolls, Hayden Burdett, Yujie Zhang, Gauri Deák, Juan Zou, Mark R. D. Taylor, Jacquie Mills, James A. Watson, Dhananjay Kumar, Alakta Das, Devisree Valsakumar, Janice Bramham, Philipp Voigt, and Marcus D. Wilson. The n-terminal region of dnmt3a combines multiple chromatin reading motifs to guide recruitment. bioRxiv, Oct 2023. URL: https://doi.org/10.1101/2023.10.29.564595, doi:10.1101/2023.10.29.564595. This article has 2 citations.

5. (schmelmer2026targetingdnmt3aregulatory pages 9-15): BMF Schmelmer. Targeting dnmt3a regulatory interactions for selective epigenetic inhibition. Unknown journal, 2026.

6. (gretarsson2024cancerassociateddnahypermethylation pages 1-2): Kristjan H. Gretarsson, Stephen Abini-Agbomson, Susan L. Gloor, Daniel N. Weinberg, Jamie L. McCuiston, Vishnu Udayakumar Sunitha Kumary, Allison R. Hickman, Varun Sahu, Rachel Lee, Xinjing Xu, Natalie Lipieta, Samuel Flashner, Oluwatobi A. Adeleke, Irina K. Popova, Hailey F. Taylor, Kelsey Noll, Carolina Lin Windham, Danielle N. Maryanski, Bryan J. Venters, Hiroshi Nakagawa, Michael-Christopher Keogh, Karim-Jean Armache, and Chao Lu. Cancer-associated dna hypermethylation of polycomb targets requires dnmt3a dual recognition of histone h2ak119 ubiquitination and the nucleosome acidic patch. Science Advances, Aug 2024. URL: https://doi.org/10.1126/sciadv.adp0975, doi:10.1126/sciadv.adp0975. This article has 31 citations and is from a highest quality peer-reviewed journal.

7. (wapenaar2024thenterminalregion pages 1-3): Hannah Wapenaar, Gillian Clifford, Willow Rolls, Moira Pasquier, Hayden Burdett, Yujie Zhang, Gauri Deák, Juan Zou, Christos Spanos, Mark R D Taylor, Jacquie Mills, James A Watson, Dhananjay Kumar, Richard Clark, Alakta Das, Devisree Valsakumar, Janice Bramham, Philipp Voigt, Duncan Sproul, and Marcus D Wilson. The n-terminal region of dnmt3a engages the nucleosome surface to aid chromatin recruitment. EMBO Reports, 25:5743-5779, Nov 2024. URL: https://doi.org/10.1038/s44319-024-00306-3, doi:10.1038/s44319-024-00306-3. This article has 21 citations and is from a highest quality peer-reviewed journal.

8. (liddo2024theimplicationsof pages 4-5): Kaela J. Di Liddo. The implications of dnmt mutations and the prognostic and therapeutic relevance of dnmtis in aml: a literature review. Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal, 8:1-9, Nov 2024. URL: https://doi.org/10.26685/urncst.697, doi:10.26685/urncst.697. This article has 2 citations.

9. (liddo2024theimplicationsof pages 1-2): Kaela J. Di Liddo. The implications of dnmt mutations and the prognostic and therapeutic relevance of dnmtis in aml: a literature review. Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal, 8:1-9, Nov 2024. URL: https://doi.org/10.26685/urncst.697, doi:10.26685/urncst.697. This article has 2 citations.

10. (kawashima2024landscapeofbiallelic pages 1-2): Naomi Kawashima, Yasuo Kubota, Carlos Bravo-Perez, Luca Guarnera, Nakisha D. Williams, Arda Durmaz, Michaela Witt, Arooj Ahmed, Carmelo Gurnari, Jaroslaw P. Maciejewski, and Valeria Visconte. Landscape of biallelic dnmt3a mutant myeloid neoplasms. Journal of Hematology & Oncology, Sep 2024. URL: https://doi.org/10.1186/s13045-024-01607-9, doi:10.1186/s13045-024-01607-9. This article has 8 citations and is from a domain leading peer-reviewed journal.

11. (dunn2024clonalhematopoiesisand pages 1-2): William G. Dunn, Matthew A. McLoughlin, and George S. Vassiliou. Clonal hematopoiesis and hematological malignancy. The Journal of Clinical Investigation, Oct 2024. URL: https://doi.org/10.1172/jci180065, doi:10.1172/jci180065. This article has 73 citations.

12. (thomas2024expandingthegenetic pages 1-5): Hortense Thomas, Tom Alix, Émeline Renard, Mathilde Renaud, Justine Wourms, Stéphane Zuily, Bruno Leheup, David Geneviève, Natacha Dreumont, Emmanuelle Schmitt, Myriam Bronner, Marc Muller, Marion Divoux, Marion Wandzel, Jean-Marie Ravel, Mylène Dexheimer, Aurélie Becker, Virginie Roth, Marjolaine Willems, Christine Coubes, Gaëlle Vieville, Françoise Devillard, Élise Schaefer, Sarah Baer, Amélie Piton, Bénédicte Gérard, Marie Vincent, Mathilde Nizon, Benjamin Cogné, Lyse Ruaud, Nathalie Couque, Audrey Putoux, Patrick Edery, Gaëtan Lesca, Nicolas Chatron, Marianne Till, Laurence Faivre, Frédéric Tran-Mau-Them, Jean-Luc Alessandri, Marine Lebrun, Chloé Quélin, Sylvie Odent, Christèle Dubourg, Véronique David, Marie Faoucher, Cyril Mignot, Boris Keren, Élise Pisan, Alexandra Afenjar, Sophie Julia, Éric Bieth, Guillaume Banneau, Alice Goldenberg, Thomas Husson, Dominique Campion, François Lecoquierre, Gaël Nicolas, Camille Charbonnier, Anne De Saint Martin, Sophie Naudion, Manon Degoutin, Sophie Rondeau, Caroline Michot, Valérie Cormier-Daire, Abderrahim Oussalah, Carine Pourié, Laëtitia Lambert, and Céline Bonnet. Expanding the genetic and clinical spectrum of tatton-brown-rahman syndrome in a series of 24 french patients. Journal of Medical Genetics, 61:878-885, Jun 2024. URL: https://doi.org/10.1136/jmg-2024-110031, doi:10.1136/jmg-2024-110031. This article has 6 citations and is from a domain leading peer-reviewed journal.

13. (liddo2024theimplicationsof pages 2-4): Kaela J. Di Liddo. The implications of dnmt mutations and the prognostic and therapeutic relevance of dnmtis in aml: a literature review. Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal, 8:1-9, Nov 2024. URL: https://doi.org/10.26685/urncst.697, doi:10.26685/urncst.697. This article has 2 citations.

14. (wapenaar2023thenterminalregion pages 62-64): Hannah Wapenaar, Gillian Clifford, Willow Rolls, Hayden Burdett, Yujie Zhang, Gauri Deák, Juan Zou, Mark R. D. Taylor, Jacquie Mills, James A. Watson, Dhananjay Kumar, Alakta Das, Devisree Valsakumar, Janice Bramham, Philipp Voigt, and Marcus D. Wilson. The n-terminal region of dnmt3a combines multiple chromatin reading motifs to guide recruitment. bioRxiv, Oct 2023. URL: https://doi.org/10.1101/2023.10.29.564595, doi:10.1101/2023.10.29.564595. This article has 2 citations.

15. (dupas2026dnmt3aincancer pages 2-3): Thomas Dupas, Enola Gautreau, Josianne Clavel, Noël J.-M. Raynal, and Serge McGraw. Dnmt3a in cancer: from epigenetic writer to oncogenic driver. Clinical Epigenetics, Apr 2026. URL: https://doi.org/10.1186/s13148-026-02127-8, doi:10.1186/s13148-026-02127-8. This article has 2 citations and is from a peer-reviewed journal.

16. (schmelmer2026targetingdnmt3aregulatory pages 91-93): BMF Schmelmer. Targeting dnmt3a regulatory interactions for selective epigenetic inhibition. Unknown journal, 2026.

17. (schmelmer2026targetingdnmt3aregulatory pages 84-86): BMF Schmelmer. Targeting dnmt3a regulatory interactions for selective epigenetic inhibition. Unknown journal, 2026.

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Citations

1. chen2024structuralbasisfor pages 1-2
2. kawashima2024landscapeofbiallelic pages 1-2
3. dunn2024clonalhematopoiesisand pages 1-2
4. thomas2024expandingthegenetic pages 1-5
5. zebrauskiene2024aorticdiseaseand pages 1-2
6. wapenaar2024thenterminalregion pages 1-3
7. gretarsson2024cancerassociateddnahypermethylation pages 1-2
8. wapenaar2023thenterminalregion pages 1-4
9. liddo2024theimplicationsof pages 4-5
10. liddo2024theimplicationsof pages 1-2
11. liddo2024theimplicationsof pages 2-4
12. wapenaar2023thenterminalregion pages 62-64
13. Nature Communications
14. EMBO Reports
15. Clinical Epigenetics
16. bioRxiv
17. Science Advances
18. Journal of Hematology & Oncology
19. URNCST Journal
20. Journal of Clinical Investigation
21. Journal of Medical Genetics
22. https://doi.org/10.1038/s41467-024-50526-3
23. https://doi.org/10.1038/s44319-024-00306-3
24. https://doi.org/10.1186/s13148-024-01686-y
25. https://doi.org/10.1101/2023.10.29.564595
26. https://doi.org/10.1126/sciadv.adp0975
27. https://doi.org/10.1038/s41467-024-47699-2
28. https://doi.org/10.1186/s13045-024-01607-9
29. https://doi.org/10.26685/urncst.697
30. https://doi.org/10.1172/JCI180065
31. https://doi.org/10.1136/jmg-2024-110031
32. https://doi.org/10.1038/s41467-024-47699-2.
33. https://doi.org/10.1038/s41467-024-50526-3.
34. https://doi.org/10.1126/sciadv.adp0975.
35. https://doi.org/10.1038/s44319-024-00306-3.
36. https://doi.org/10.1002/pro.4542.
37. https://doi.org/10.1172/JCI180065.
38. https://doi.org/10.1186/s13045-024-01607-9.
39. https://doi.org/10.1136/jmg-2024-110031.
40. https://doi.org/10.1186/s13148-024-01686-y.
41. https://doi.org/10.1038/s41467-024-50526-3,
42. https://doi.org/10.1186/s13148-024-01686-y,
43. https://doi.org/10.1101/2023.10.29.564595,
44. https://doi.org/10.1126/sciadv.adp0975,
45. https://doi.org/10.1038/s44319-024-00306-3,
46. https://doi.org/10.26685/urncst.697,
47. https://doi.org/10.1186/s13045-024-01607-9,
48. https://doi.org/10.1172/jci180065,
49. https://doi.org/10.1136/jmg-2024-110031,
50. https://doi.org/10.1186/s13148-026-02127-8,