Di-Methyl-Histone H3 (Lys4) Antibody

What is Di-Methyl-Histone H3 (Lys4) and why is it significant in epigenetic research?

Di-Methyl-Histone H3 (Lys4), commonly abbreviated as H3K4me2, refers to histone H3 that has been di-methylated specifically at the lysine 4 position. This post-translational modification is a critical epigenetic mark that plays a significant role in chromatin structure and gene expression regulation. H3K4me2 is particularly important because it is predominantly found in coding regions of active genes and correlates with transcriptional activity . This distinguishes it from other histone modifications that may be more concentrated at promoters or enhancers.

The significance of H3K4me2 lies in its function coordinating the recruitment of chromatin modifying enzymes containing methyl-lysine binding modules such as chromodomains (HP1, PRC1), PHD fingers (BPTF, ING2), tudor domains (53BP1), and WD-40 domains (WDR5) . These protein interactions form part of the complex "histone code" that regulates gene accessibility and expression, making H3K4me2 antibodies essential tools for researchers studying transcriptional regulation and chromatin biology.

What applications can Di-Methyl-Histone H3 (Lys4) Antibody be used for in research settings?

Di-Methyl-Histone H3 (Lys4) Antibody is a versatile research tool that can be applied in multiple experimental contexts:

These applications enable researchers to investigate H3K4me2 from multiple perspectives, from broad genomic distribution patterns to specific protein interactions . The antibody is particularly valuable for ChIP experiments, which allow identification of genomic regions associated with this histone modification. In ChIP-seq applications, researchers can generate genome-wide maps of H3K4me2 distribution, providing insights into gene regulation on a global scale .

How specific are Di-Methyl-Histone H3 (Lys4) antibodies and how is specificity validated?

The specificity of Di-Methyl-Histone H3 (Lys4) antibodies is crucial for experimental reliability and varies between products. High-quality antibodies demonstrate excellent discrimination between H3K4me2 and other histone modifications.

According to specificity analyses, certain monoclonal antibodies like the Di-Methyl-Histone H3 (Lys4) (C64G9) Rabbit mAb show minimal cross-reactivity with related modifications. This antibody may exhibit weak cross-reactivity with H3K4me1 but does not cross-react with non-methylated H3K4 or H3K4me3 . Additionally, it shows no significant cross-reactivity with other methylated residues including H3K9, H3K27, H3K36, or H4K20 .

Rigorous validation methods include:

• Peptide array analysis: Using modified histone peptide arrays to quantify binding specificity across numerous histone modifications . The specificity factor is calculated as the ratio of signal intensity between H3K4me2-containing peptides versus other modifications.

• Dot blot analysis: Testing at 1:1,000 dilution against various histone peptides to confirm specific detection of H3K4me2 without cross-reactivity .

• ChIP validation: Using qPCR with primers for known positive control regions (active genes like GAPDH, PABPC1) and negative control regions (inactive satellite repeats like SAT2 and SATα) .

Figure 1 in source demonstrates how specificity analysis comparing two anti-H3K4me2 antibodies reveals significant differences in their performance, underlining the importance of validation before experimental use.

What species reactivity can be expected from Di-Methyl-Histone H3 (Lys4) Antibodies?

Di-Methyl-Histone H3 (Lys4) Antibodies typically demonstrate reactivity with multiple species due to the high conservation of histone H3 sequences across evolutionary lineages. Based on the product information, the following species reactivity is commonly observed:

The consistent cross-species reactivity stems from the fact that "the antigen sequence used to produce this antibody shares 100% sequence homology with the species listed" . This conservation of the H3K4 region makes these antibodies versatile tools for comparative studies across different model organisms.

For researchers working with other species not explicitly listed, it's important to note that additional species may potentially react based on sequence homology, but manufacturers typically do not guarantee reactivity unless specifically tested. When working with unconventional model organisms, sequence alignment of the immunogen region with your species of interest can provide insight into potential reactivity .

What are the recommended dilutions and experimental conditions for various applications?

Optimal dilutions and experimental conditions vary by application and should be empirically determined for each experimental system. Based on manufacturer recommendations, the following serve as starting points:

For ChIP experiments, successful protocols have used approximately 5 μg of antibody with 20 μL Protein A/G beads and chromatin from 5×10^6 crosslinked HeLa cells . When performing ChIP-seq, at least twelve million mapped reads are typically required for comprehensive genome coverage .

These dilutions should be considered starting points that may require optimization based on sample type, detection method, and desired signal-to-noise ratio. Preliminary titration experiments are recommended when establishing new protocols or working with different experimental systems.

How can researchers validate the specificity of a Di-Methyl-Histone H3 (Lys4) Antibody for their experimental system?

Comprehensive validation of antibody specificity is essential for ensuring reliable experimental outcomes, particularly for chromatin studies. For Di-Methyl-Histone H3 (Lys4) Antibody, a multi-faceted validation approach should include:

• Peptide Array Analysis:

  • Utilize commercial modified histone peptide arrays containing various histone modifications

  • Calculate specificity factors as the ratio of signal intensity between spots containing H3K4me2 versus non-H3K4me2 spots

  • High-quality antibodies show specificity factors >20 for the target modification

• Dot Blot Validation:

  • Test antibody binding against synthetic peptides with different modifications (H3K4me1, H3K4me2, H3K4me3, unmodified H3K4)

  • A 1:1,000 dilution should specifically detect the H3K4me2-modified peptide with minimal cross-reactivity

  • Include potential cross-reacting modifications based on sequence similarity

• Western Blot Validation:

  • Verify single-band detection at approximately 17 kDa (histone H3's molecular weight)

  • Perform peptide competition assays to confirm binding specificity

  • Compare signal between wild-type cells and those with altered H3K4 methylation (if available)

• ChIP-qPCR Validation:

  • Conduct ChIP using established positive control regions (active gene promoters)

  • Include negative control regions (inactive heterochromatin)

  • Calculate fold enrichment compared to non-specific IgG control

  • Successful validation shows 10-20 fold enrichment at positive control regions

  • Test with chromatin from 1×10^6 cell equivalents using 4 μg of antibody

• Sequential ChIP:

  • Perform ChIP with anti-H3K4me2 followed by re-ChIP with antibodies against other modifications

  • This confirms whether the antibody selectively enriches for the intended modification

Comparing the antibody's performance against published datasets or previously validated antibodies provides further confirmation of specificity. As demonstrated in source , antibodies from different suppliers can show significant variation in specificity despite targeting the same modification.

What are the best practices for optimizing ChIP-seq experiments with Di-Methyl-Histone H3 (Lys4) Antibody?

Successful ChIP-seq experiments with Di-Methyl-Histone H3 (Lys4) Antibody require careful optimization at multiple experimental stages:

• Chromatin Preparation:

  • Crosslink with 1% formaldehyde for 10 minutes at room temperature

  • Sonicate to generate fragments primarily between 200-500 bp

  • Verify sonication efficiency by agarose gel electrophoresis

  • For H3K4me2, prepare chromatin from 5×10^6 cells per immunoprecipitation

  • Include protease inhibitors throughout sample preparation

• Immunoprecipitation:

  • Use 5 μg antibody per ChIP for 5×10^6 cells

  • Include 20 μL Protein A/G magnetic beads per reaction

  • Incubate antibody-chromatin mixture overnight at 4°C with rotation

  • Implement stringent washing (low salt, high salt, LiCl, and TE buffers)

  • Elute and reverse crosslinks at 65°C overnight

• Library Preparation:

  • Purify DNA using magnetic beads for consistent size selection

  • Prepare libraries with Illumina-compatible adapters

  • Include unique barcodes for multiplexing

  • Size-select to remove adapter dimers and fragments outside 150-300 bp range

• Sequencing Considerations:

  • Aim for minimum twelve million mapped reads per sample

  • Consider paired-end sequencing for improved mapping accuracy

  • Include input chromatin control sequenced to similar depth

• Data Analysis Pipeline:

  • Use TagDust for tag removal to clean sequencing artifacts

  • Map reads with Bowtie or similar alignment software

  • Call peaks using MACS or equivalent peak-calling algorithm

  • Visualize in genome browsers (UCSC, IGV)

  • Compare H3K4me2 profile with gene expression data

• Quality Control Metrics:

  • Calculate enrichment at positive control regions vs. IgG

  • Assess fragment size distribution post-sequencing

  • Calculate fraction of reads in peaks (FRiP) score

  • Evaluate reproducibility between biological replicates

A successfully optimized protocol should yield a characteristic H3K4me2 profile with enrichment primarily in gene bodies of actively transcribed genes , distinguishing it from H3K4me3 (promoter-focused) and H3K4me1 (enhancer-associated) profiles.

How does the genomic distribution of Di-Methyl-Histone H3 (Lys4) differ from other histone modifications?

Di-Methyl-Histone H3 (Lys4) exhibits a distinctive genomic distribution pattern that differentiates it from other histone modifications:

• Comparison with other H3K4 methylation states:

  • H3K4me1 (monomethylation) predominantly marks enhancers and regions flanking active promoters

  • H3K4me2 (dimethylation) is distinctively enriched in coding regions of active genes

  • H3K4me3 (trimethylation) is highly concentrated at active promoters and transcription start sites

• Contrast with repressive modifications:

  • H3K9me2/3 and H3K27me3 mark inactive heterochromatin regions and silenced genes

  • H3K4me2 shows inverse correlation with these repressive marks

  • Bivalent domains with both H3K4me3 and H3K27me3 mark poised developmental genes, whereas active genes typically show H3K4me2 in gene bodies without repressive marks

• Relationship with transcriptional activity:

  • H3K4me2 shows strong positive correlation with transcriptional activity in gene bodies

  • The modification typically follows a pattern where H3K4me3 marks promoters and transitions to H3K4me2 in coding regions

  • H3K36me3, another active gene mark, is often found alongside H3K4me2 but tends to be more enriched toward 3' regions

ChIP analyses consistently demonstrate that H3K4me2 antibodies enrich for active genes like GAPDH, PABPC1, and cFOS, but not for inactive regions like satellite repeats . This pattern provides a reliable signature for identifying transcriptionally active regions through genome-wide profiling.

The distinct distribution pattern of H3K4me2 makes it particularly valuable for epigenomic studies aimed at distinguishing between different functional states of chromatin and identifying actively transcribed gene bodies beyond promoter regions.

What is the significance of Di-Methyl-Histone H3 (Lys4) in coding regions of active genes?

The presence of Di-Methyl-Histone H3 (Lys4) in coding regions of active genes has profound implications for our understanding of chromatin regulation and transcription:

• Correlation with Transcriptional Activity:

  • Research demonstrates that H3K4me2 enrichment in coding regions significantly correlates with active transcription

  • This pattern differs from many other active histone marks that are primarily concentrated at promoters

  • The presence of H3K4me2 in gene bodies provides a more comprehensive marker of genes that are being actively transcribed, not just those poised for activation

• Molecular Function in Transcription:

  • H3K4me2 facilitates recruitment of chromatin remodeling complexes that maintain open chromatin structure

  • The modification may serve as a bookmark of recently transcribed regions

  • It potentially functions in transcriptional elongation processes rather than just initiation

  • H3K4me2 coordinates recruitment of proteins containing methyl-lysine binding modules , which can further modify the chromatin environment

• Dynamic Regulation:

  • H3K4me2 in coding regions represents an intermediate methylation state

  • It can be further methylated to H3K4me3 or demethylated to H3K4me1

  • The discovery of histone demethylases like LSD1, JMJD1, and JHDM1 demonstrates that this is a reversible epigenetic mark

  • This dynamic nature allows for responsive regulation of gene expression

• Functional Significance:

  • May prevent inappropriate silencing of active genes during cell division

  • Could play roles in co-transcriptional processes like RNA processing or splicing

  • Provides a mechanism to distinguish actively transcribed genes from those that are only temporarily or sporadically expressed

In ChIP experiments, researchers routinely use housekeeping genes like GAPDH and PABPC1 as positive controls for H3K4me2 enrichment , leveraging the reliable presence of this mark in constitutively expressed genes across many cell types.

How can researchers troubleshoot weak or non-specific signals when using Di-Methyl-Histone H3 (Lys4) Antibody?

When encountering signal issues with Di-Methyl-Histone H3 (Lys4) Antibody, a systematic troubleshooting approach is essential:

• Addressing Weak Signals:

  a) Antibody-Related Factors:

  • Increase antibody concentration (e.g., from 1:1000 to 1:500 for Western blotting)

  • For ChIP applications, increase from 4 μL to 5-10 μL per immunoprecipitation

  • Verify antibody storage conditions and expiration date

  • Consider testing alternative antibody lots or suppliers

  b) Sample Preparation:

  • Ensure complete nuclear extraction for histone proteins

  • Verify histone integrity by Coomassie staining or total H3 detection

  • For ChIP, check chromatin sonication efficiency (200-500 bp fragments)

  • Include protease and phosphatase inhibitors to prevent degradation

  c) Detection Methods:

  • Implement more sensitive detection systems (e.g., highly sensitive ECL)

  • For immunofluorescence, use signal amplification systems

  • Optimize imaging parameters (exposure time, gain settings)

  • For ChIP-qPCR, design primers for regions with known high enrichment

• Resolving Non-specific Signals:

  a) Blocking Optimization:

  • Test different blocking agents (BSA, non-fat milk, serum)

  • Extend blocking time to reduce background

  • Add 0.1-0.3% Triton X-100 to reduce hydrophobic interactions

  • For Western blots, use 5% BSA rather than milk for blocking

  b) Washing Conditions:

  • Implement more stringent washing (higher salt, additional detergent)

  • Increase number and duration of washing steps

  • For ChIP, include high-stringency LiCl wash steps

  c) Antibody Specificity Verification:

  • Perform peptide competition assays to confirm binding specificity

  • Compare with specificity analysis data from peptide arrays

  • Test a pre-cleared antibody preparation

• Application-Specific Solutions:

  a) For Western Blotting:

  • Add 0.1% SDS to transfer buffer to improve histone transfer

  • Use PVDF membranes instead of nitrocellulose for better protein retention

  • Include a positive control sample (e.g., HeLa cell extract)

  • Optimize gel percentage (15-18%) for better resolution of histones

  b) For ChIP Applications:

  • Ensure proper crosslinking (1% formaldehyde, 10 minutes)

  • Optimize antibody:chromatin ratio

  • Include spike-in controls for normalization

  • Compare enrichment to properly validated positive controls

  c) For Immunofluorescence:

  • Test different fixation methods (4% PFA vs. methanol)

  • Include antigen retrieval steps for formalin-fixed samples

  • Optimize permeabilization conditions

  • Use mounting media with anti-fade properties

Properly optimized experiments should yield signal-to-noise ratios of 10-20 fold enrichment over IgG control at positive control genomic regions when performing ChIP with anti-H3K4me2 .

What strategies exist for distinguishing between the functions of H3K4me1, H3K4me2, and H3K4me3 in chromatin biology?

Distinguishing between the three methylation states of H3K4 requires sophisticated experimental approaches that can reveal their distinct functions:

• Comparative Genomic Profiling:

  • Perform parallel ChIP-seq with highly specific antibodies for each methylation state

  • Compare genome-wide distribution patterns:

    • H3K4me1: Primarily enhancers and regions flanking promoters

    • H3K4me2: Coding regions of active genes

    • H3K4me3: Concentrated at promoters and transcription start sites

  • Correlate these patterns with RNA-seq data to link modifications with transcriptional output

  • Analyze transition zones between different methylation states

• Sequential ChIP (Re-ChIP):

  • First immunoprecipitate with one H3K4 methylation antibody

  • Re-immunoprecipitate the enriched material with antibodies against other modifications

  • This identifies genomic regions containing combinations of modifications

  • Reveals hierarchy and potential interplay between different methylation states

• Enzyme Perturbation Studies:

  • Target methyltransferases with different specificities:

    • SET1A/SET1B (primarily catalyze H3K4me3)

    • ASH1L (associated with H3K4me2)

    • MLL family enzymes (varying specificities)

  • Target demethylases like KDM5 family members

  • Analyze resulting changes in histone modification patterns and gene expression

  • Infer specific functions from differential effects

• Protein Interaction Studies:

  • Identify proteins that specifically recognize each methylation state

  • Use modified histone peptide pull-downs with mass spectrometry

  • Characterize how different "reader" proteins translate each modification into functional outcomes

  • Examples: BPTF recognizes H3K4me3, while other PHD finger proteins may prefer H3K4me2

• Developmental and Differentiation Models:

  • Profile changes in all three methylation states during cell differentiation

  • Correlate with developmental gene expression programs

  • Identify temporal relationships between different methylation states

  • Determine which genes transition between different methylation patterns

• CRISPR-Based Epigenome Editing:

  • Use catalytically inactive Cas9 (dCas9) fused to specific methyltransferases

  • Target individual genomic loci to alter specific methylation states

  • Measure effects on transcription, chromatin accessibility, and other epigenetic marks

  • This approach provides direct evidence for causality rather than correlation

When selecting antibodies for these comparative studies, researchers should choose validated products with minimal cross-reactivity between methylation states. For example, the Di-Methyl-Histone H3 (Lys4) (C64G9) Rabbit mAb shows minimal cross-reactivity with H3K4me3, making it suitable for distinguishing these modifications .

How do researchers integrate Di-Methyl-Histone H3 (Lys4) ChIP-seq data with other genomic datasets?

Integrative analysis of Di-Methyl-Histone H3 (Lys4) ChIP-seq data with complementary genomic datasets provides comprehensive insights into chromatin regulation and gene expression:

• Integration with Transcriptomic Data:

  • Correlate H3K4me2 enrichment patterns with RNA-seq or microarray expression data

  • Calculate gene-body H3K4me2 signals and compare with transcript levels

  • Analyze genes with discordant H3K4me2/expression patterns to identify additional regulatory mechanisms

  • This integration confirms the correlation between H3K4me2 in coding regions and active transcription

• Multi-Modification Epigenomic Analysis:

  • Compare H3K4me2 profiles with other histone modifications (H3K4me1/3, H3K27ac, H3K36me3)

  • Identify chromatin states through combinatorial modification patterns

  • Use tools like ChromHMM or Segway for systematic chromatin state definition

  • Create comprehensive epigenomic maps distinguishing promoters, enhancers, and transcribed regions

• Transcription Factor Binding Integration:

  • Overlay H3K4me2 patterns with transcription factor ChIP-seq data

  • Identify factors that preferentially bind regions with H3K4me2 enrichment

  • Analyze how H3K4me2 might facilitate or result from transcription factor binding

  • Integrate with chromatin accessibility data (DNase-seq, ATAC-seq)

• Computational Analysis Approaches:

  • Implement peak calling using specialized tools like MACS

  • Utilize differential binding analysis to compare conditions

  • Perform gene ontology enrichment for genes with high H3K4me2

  • Generate heatmaps and metaplots centered on genomic features

  • Develop custom visualization in genome browsers from BigWig and BED files

• Three-Dimensional Chromatin Structure:

  • Integrate H3K4me2 ChIP-seq with chromatin conformation data (Hi-C, ChIA-PET)

  • Analyze relationship between H3K4me2 and topological domains

  • Investigate whether H3K4me2-marked regions interact across genomic distances

• Disease-Relevant Integration:

  • Compare H3K4me2 patterns between normal and disease states

  • Integrate with disease-associated genetic variants (GWAS)

  • Identify altered H3K4me2 patterns at disease-relevant loci

  • Correlate with DNA methylation data to study epigenetic cross-talk

For effective integration, researchers should ensure consistent experimental conditions across datasets. ChIP-seq experiments should include input controls and generate sufficient coverage (minimum twelve million mapped reads) to enable robust comparative analyses.

When visualizing integrated data, specialized browsers like UCSC or IGV allow simultaneous display of multiple tracks, facilitating the identification of relationships between H3K4me2 distribution and other genomic features .