Di-methyl-Histone H3(K27) Monoclonal Antibody

What is H3K27me2 and how does it differ from other H3K27 modifications?

H3K27me2 (di-methyl lysine 27 on histone H3) is a specific post-translational modification of histone H3, where two methyl groups are added to the lysine residue at position 27. This modification differs fundamentally from H3K27me3 (tri-methylation) and H3K27ac (acetylation) in both its enzymatic regulation and biological function. H3K27me2 is part of the "histone code" that regulates DNA accessibility to cellular machinery, playing a central role in transcription regulation, DNA repair, replication, and chromosomal stability .

When studying these modifications, it's important to note that H3K27 acetylation (H3K27ac) levels typically rise when methylation is reduced, as the acetyltransferases compete with methyltransferases like PRC2 for the same lysine residue . Unlike tri-methylation (H3K27me3), which is strongly associated with gene silencing, di-methylation can have more context-dependent functions, often serving as an intermediate state in the modification process.

Which enzymes are responsible for establishing and removing H3K27me2 marks?

The sequential addition of methyl groups (from mono- to di- to tri-methylation) is catalyzed by the same enzyme complex, but with different efficiencies and regulatory mechanisms. Demethylases that remove these marks include the KDM6 family enzymes, which show specificity for different methylation states. Understanding the balance between these enzymes is crucial for interpreting experimental results when studying chromatin regulation.

How do I determine whether to study H3K27me2 versus H3K27me3 or H3K27ac in my research project?

This decision should be based on your specific biological question. Consider studying H3K27me2:

• When investigating intermediate states of gene regulation

• When examining transitions between active and repressed chromatin

• When analysis of H3K27me3 shows incomplete correlation with transcriptional repression

H3K27me3 is more appropriate for studying stable gene silencing and Polycomb-mediated repression, while H3K27ac is ideal for identifying active enhancers and promoters . Research has shown that these modifications can exist in dynamic equilibrium, with H3K27ac rising when PRC2 function is compromised .

A comprehensive approach would involve analyzing multiple modifications simultaneously to understand their interrelationships. For example, deletion of EED leads to dramatic loss of H3K27me1/2/3 and destabilization of EZH2, while H3K27ac levels increase, suggesting competitive regulation of the same lysine residue .

Which techniques can I use to detect and quantify H3K27me2 in my samples?

Several validated techniques are available for detecting H3K27me2:

For Western Blotting, use 1 μg/mL of antibody concentration with appropriate controls . For ChIP applications, 2μg of antibody with 25μg of chromatin yields reliable results for real-time PCR quantification . Immunohistochemistry typically requires heat-mediated antigen retrieval with sodium citrate buffer (pH6) for optimal results . The specificity of your antibody should be validated through peptide competition assays to ensure it doesn't cross-react with other histone modifications .

How do I design a ChIP experiment to study H3K27me2 distribution across the genome?

A well-designed ChIP experiment for H3K27me2 should include:

• Proper cell fixation (typically 10 minutes with formaldehyde)

• Optimized chromatin fragmentation (200-500bp fragments)

• Immunoprecipitation with 2μg of validated H3K27me2-specific antibody

• Appropriate controls:

  • Input chromatin (non-immunoprecipitated)

  • IgG control (non-specific antibody)

  • Beads-only control

• qPCR validation of enrichment at known target regions

For genomic distribution analysis, ChIP-sequencing is recommended. Analyze the data focusing on peak distribution patterns relative to gene features (promoters, gene bodies, enhancers). Compare H3K27me2 distribution with other histone marks like H3K27me3 and H3K27ac to gain comprehensive insights into chromatin state dynamics .

For primer design in qPCR validation, target the first kilobase of the transcribed region for maximal detection sensitivity . Consider using both active and inactive loci as controls, employing different approaches (Taqman for active/inactive loci, Sybr green for heterochromatic regions) .

What are the key considerations for ensuring antibody specificity in H3K27me2 detection?

Antibody specificity is critical for accurate H3K27me2 detection. Key considerations include:

• Validation through peptide competition assays to confirm the antibody doesn't recognize:

  • H3K27me1 or H3K27me3

  • Modifications at other lysine residues (e.g., H3K4me2, H3K9me2)

• Positive and negative controls in every experiment:

  • Positive: Samples known to have H3K27me2 (e.g., calf thymus histone)

  • Negative: Samples with competing peptide blocking

• Cross-validation using multiple techniques (e.g., IF, WB, ChIP) to confirm consistent results

• Species validation for cross-species experiments, as antibody performance may vary

The antibody ab24684 has been validated to not recognize H3K27 mono- or tri-methylation, nor methylation at H3K4 or H3K9 positions . Proper validation ensures your experimental results specifically reflect H3K27me2 rather than other histone modifications, which is essential for accurate biological interpretation.

Why might I observe inconsistent H3K27me2 signals in my Western blot experiments?

Inconsistent H3K27me2 signals can result from several factors:

• Sample preparation issues:

  • Incomplete histone extraction

  • Histone degradation during preparation

  • Variable protein loading

• Antibody-related problems:

  • Insufficient antibody concentration (try 1 μg/mL as a starting point)

  • Batch-to-batch variability with polyclonal antibodies

  • Non-specific binding

• Technical considerations:

  • Insufficient blocking

  • Inadequate washing steps

  • Exposure time variations (optimal around 5s for standard samples)

• Biological variables:

  • Cell cycle stage (histone modifications fluctuate)

  • Treatment effects on global histone modification levels

To troubleshoot, compare your observed band size (typically ~17 kDa) with the predicted size (~15 kDa) . Include peptide competition controls to confirm specificity, and consider using recombinant histones as positive controls. Standardize your protein extraction protocol, focusing on nuclear extraction methods optimized for histone proteins.

How do I interpret ChIP-seq data when H3K27me2 and H3K27me3 patterns overlap?

Interpreting overlapping H3K27me2 and H3K27me3 patterns requires careful analysis and consideration of several factors:

• Biological significance:

  • Overlapping regions may represent transition states between different repressive domains

  • Some genes may be regulated by both modifications with distinct functions

  • Consider developmental timing or cellular context

• Technical considerations:

  • Antibody cross-reactivity (validate with peptide competition assays)

  • Sequencing depth and normalization methods

  • Peak calling algorithm parameters

• Analysis strategies:

  • Compare peak intensities rather than just presence/absence

  • Examine correlation with transcriptional data

  • Analyze co-occurrence with other histone marks

Research has shown that deletion of PRC2 components affects H3K27me2 and H3K27me3 to different degrees, with H3K27me3 typically showing more dramatic changes . This suggests distinct regulatory mechanisms despite overlap. Consider analyzing regions with exclusively H3K27me2 or H3K27me3 to identify unique functions of each modification.

What factors affect the cross-reactivity of H3K27me2 antibodies with other histone modifications?

Several factors influence antibody cross-reactivity:

• Antibody production method:

  • Monoclonal vs. polyclonal (monoclonals generally offer higher specificity)

  • Immunogen design (peptide length and flanking sequences)

  • Host species and purification methods

• Epitope similarity:

  • Chemical similarity between di- and tri-methylation

  • Sequence context around K27 resembling other methylated lysines

  • Post-translational modifications on adjacent residues affecting recognition

• Experimental conditions:

  • Antibody concentration (higher concentrations may increase cross-reactivity)

  • Stringency of washing buffers

  • Incubation time and temperature

Quality antibodies like ab24684 undergo rigorous testing to ensure they don't recognize other methylation states at K27 or methylation at other sites like K4 or K9 . Always perform peptide competition assays to validate specificity in your experimental conditions. Consider using orthogonal methods (such as mass spectrometry) for critical experiments requiring absolute specificity confirmation.

How do mutations in EZH2 affect H3K27me2 distribution and what are the implications for interpreting ChIP data?

Mutations in EZH2 have profound effects on H3K27 methylation patterns:

• Loss-of-function mutations:

  • Reduce H3K27me2/me3 levels with variable severity

  • Lead to compensatory upregulation of EZH1 activity

  • Result in increased H3K27ac at former PRC2 targets

• Gain-of-function mutations (common in lymphomas):

  • May alter the ratio of H3K27me2 to H3K27me3

  • Can create aberrant distribution patterns

  • Often show enhanced repression of PRC2 target genes

When interpreting ChIP data from cells with EZH2 mutations, consider:

• Comparing H3K27me2, H3K27me3, and H3K27ac distributions simultaneously

• Analyzing effects on gene expression at affected loci

• Examining changes in other PRC2 components (e.g., EED stability)

Research has shown that deletion of EZH2 leads to pronounced reduction in H3K27me3 and milder drops in H3K27me2, indicating that EZH1 partially compensates for loss of its more active paralog . This differential effect on methylation states must be considered when analyzing ChIP data from EZH2-mutant samples.

What is the relationship between H3K27me2 and the oncohistone H3.3K27M in disease models?

The relationship between H3K27me2 and the oncohistone H3.3K27M is complex and biologically significant:

• Mechanism of action:

  • H3.3K27M mutation inhibits PRC2 activity globally

  • Causes decreases in both H3K27me2 and H3K27me3, though typically less severe than EZH2 knockout

  • Leads to compensatory increases in H3K27ac

• Disease relevance:

  • H3.3K27M mutations are driver events in diffuse midline gliomas

  • Create epigenetic landscapes distinct from other PRC2-deficient cancers

  • Result in aberrant activation of developmental programs

• Research implications:

  • When studying systems with H3.3K27M, analyze multiple histone marks simultaneously

  • Consider regional effects (some genomic regions maintain H3K27me2/me3)

  • Account for potential redistribution rather than simple loss of marks

Research has demonstrated that H3.3K27M expression produces clear decreases in H3K27me2/me3, but to a lesser extent than observed in EZH2-KO cells . This indicates a partial inhibition mechanism that may affect certain genomic regions differently than complete PRC2 loss.

How do I integrate H3K27me2 ChIP-seq data with other epigenomic datasets to understand chromatin state dynamics?

Integrating H3K27me2 data with other epigenomic datasets requires sophisticated analytical approaches:

• Multi-mark analysis strategies:

  • Create chromatin state models using tools like ChromHMM

  • Perform correlation analyses between different histone marks

  • Identify transition zones between active and repressive domains

• Key datasets to integrate:

  • Other histone marks (H3K27me3, H3K27ac, H3K4me3, H3K36me3)

  • Chromatin accessibility (ATAC-seq, DNase-seq)

  • Transcription factor binding (ChIP-seq)

  • Transcriptional activity (RNA-seq)

• Biological context considerations:

  • Cell type-specific patterns

  • Developmental time points

  • Response to perturbations (e.g., EZH2 inhibition)

Research has shown that alterations in PRC2 function affect multiple histone marks simultaneously, with H3K27ac increasing when H3K27me2/me3 decreases . This competitive relationship creates complex patterns that require integrated analysis for proper interpretation. When designing studies, consider collecting data on multiple marks from the same biological samples to facilitate direct comparisons.

What are the functional differences between genomic regions marked with H3K27me2 versus H3K27me3?

The functional distinctions between H3K27me2 and H3K27me3 marked regions are important for understanding chromatin regulation:

• Transcriptional repression strength:

  • H3K27me3: Associated with strong, stable gene silencing

  • H3K27me2: Often linked to moderate repression or poised states

• Genomic distribution patterns:

  • H3K27me3: Enriched at promoters of developmental genes

  • H3K27me2: More broadly distributed, often in gene bodies

• Protein interactions:

  • H3K27me3: Strongly recruits Polycomb Repressive Complex 1 (PRC1)

  • H3K27me2: Weaker PRC1 recruitment, different reader protein affinities

• Stability and dynamics:

  • H3K27me3: More stable, maintains long-term repression

  • H3K27me2: More dynamic, may represent transitional states

Research shows that loss of PRC2 components affects these marks to different degrees, with H3K27me3 typically showing more dramatic changes than H3K27me2 . This suggests distinct regulatory mechanisms and biological functions. When interpreting ChIP-seq data, consider both the presence of these marks and their relative enrichment levels to understand their functional implications.

How does the balance between H3K27me2, H3K27me3, and H3K27ac impact gene expression patterns?

The balance between these H3K27 modifications creates a sophisticated regulatory system:

• Competitive relationship:

  • H3K27 acetylation and methylation are mutually exclusive

  • Loss of PRC2 function leads to increased H3K27ac at former targets

  • These modifications compete for the same lysine residue

• Expression outcomes:

  • H3K27ac: Strongly associated with active transcription

  • H3K27me3: Correlated with repressed genes

  • H3K27me2: Variable correlation with expression, context-dependent

• Regulatory dynamics:

  • Transitioning from me3→me2→me1→ac typically correlates with increasing expression

  • Rapid changes in one modification can affect the others

Research demonstrates that mutations affecting PRC2 function (EED deletion, EZH2 knockout, or H3.3K27M expression) all lead to increased H3K27ac levels, confirming the competitive relationship between these modifications . When analyzing gene expression data, consider the relative levels of these marks rather than simply their presence or absence.

What are the implications of H3K27me2 redistribution in cancer and other diseases?

H3K27me2 redistribution has significant implications in disease contexts:

• Cancer-specific patterns:

  • EZH2 mutations in follicular lymphoma alter H3K27me2/me3 distribution

  • Changes in H3K27me2:H3K27me3 ratios may drive oncogenic gene expression

  • Redistribution rather than total loss may be more important in some contexts

• Developmental disorders:

  • Disrupted H3K27me2 patterns affect developmental gene regulation

  • May lead to inappropriate activation/repression of lineage-specific genes

  • Often disrupts cellular identity maintenance

• Therapeutic implications:

  • EZH2 inhibitors may differentially affect H3K27me2 vs. H3K27me3

  • Targeting enzymes that recognize specific methylation states

  • Potential for methylation state-specific interventions

Research has shown that the H3.3K27M oncohistone produces clear decreases in H3K27me2/3, but to a lesser extent than observed in EZH2-KO cells . This partial inhibition creates unique epigenetic landscapes that contribute to oncogenesis. When studying disease models, analyze H3K27me2 patterns in conjunction with other histone marks to understand the full regulatory landscape.

How can single-cell epigenomic approaches be applied to study H3K27me2 heterogeneity?

Single-cell approaches offer revolutionary insights into H3K27me2 biology:

• Available technologies:

  • Single-cell CUT&Tag/CUT&RUN for H3K27me2 profiling

  • scChIC-seq for histone modification analysis

  • Integrated single-cell multi-omics (combining with RNA-seq)

• Analytical considerations:

  • Data sparsity challenges unique to single-cell epigenomics

  • Need for specialized normalization and imputation methods

  • Integration with other single-cell modalities

• Biological applications:

  • Resolving cell-to-cell variability in H3K27me2 patterns

  • Identifying rare cell populations with unique epigenetic states

  • Tracking epigenetic changes during cellular differentiation or disease progression

When implementing these approaches, consider antibody specificity carefully, as cross-reactivity issues become more pronounced at the single-cell level . Validate findings with orthogonal bulk approaches and include appropriate controls. These techniques will increasingly enable researchers to connect H3K27me2 heterogeneity with functional outcomes at unprecedented resolution.

What are the advantages of using recombinant antibodies for H3K27me2 detection in long-term research projects?

Recombinant antibodies offer significant advantages for H3K27me2 research:

• Consistency benefits:

  • Elimination of batch-to-batch variability

  • Reproducible results across long-term studies

  • Standardization across research groups

• Technical advantages:

  • Defined specificity through engineered binding domains

  • Potential for custom modifications (tags, conjugates)

  • Often higher affinity and specificity than conventional antibodies

• Practical considerations:

  • Renewable source independent of animal immunization

  • Potential for improved performance in challenging applications

  • Consistent supply chain for extended projects

While the search results specifically mentioned recombinant formats for H3K27ac antibodies providing "unrivaled batch-batch consistency" , the same principles apply to H3K27me2 detection. For longitudinal studies where consistent detection is critical, recombinant antibodies provide significant advantages over traditional polyclonal antibodies that may vary between lots.

How might spatial epigenomics techniques advance our understanding of H3K27me2 function in tissue context?

Spatial epigenomics represents an emerging frontier for H3K27me2 research:

• Current technologies:

  • Imaging-based histone modification detection in tissue sections

  • Spatial-CUT&Tag for regional epigenomic profiling

  • Integration with spatial transcriptomics

• Research applications:

  • Mapping H3K27me2 distribution across tissue architecture

  • Correlating modification patterns with cellular niches

  • Understanding epigenetic heterogeneity in complex tissues

• Technical considerations:

  • Antibody performance in spatial contexts

  • Signal-to-noise optimization in tissue samples

  • Computational methods for spatial epigenetic data analysis

For optimal results in spatial techniques, validated antibodies with demonstrated performance in IHC/IF applications are essential . These approaches will increasingly enable researchers to understand how H3K27me2 patterns relate to tissue organization, cell-cell interactions, and microenvironmental influences that cannot be captured in conventional bulk or even single-cell approaches.