How do I validate a histone PTM antibody?

Using highly specific antibodies will make a huge difference in the biological accuracy and quality of your results. EpiCypher is committed to offering the best histone PTM antibodies for your CUT&RUN studies, so you can be confident in your data. If we do not offer an antibody to your target of interest, contact us for recommendations or take the following steps to validate your own antibody.

  1. Obtain 3-5 antibodies (preferably monoclonal) to your PTM from various vendors. Make sure that the antibodies target distinct epitopes.
    • EpiCypher scientists have observed that antibodies good for immunofluorescence (IF) applications tend to produce good data in our CUTANA CUT&RUN assays. Although using IF-validated antibodies is NOT a guarantee for success, it may help guide CUT&RUN antibody selection for targets that lack validated reagents
  2. Perform CUT&RUN with all candidate antibodies. Additional controls and recommendations:
  3. Confirm positive and negative controls show expected sequencing results, including data from the SNAP-CUTANA K-MetStat Panel. The negative controls should have low, nonspecific recovery of nucleosomes from the K-MetStat Panel, while the positive control reaction should only recover spike-in nucleosomes carrying the target PTM (e.g. H3K4me3 with less than 20% cross-reactivity to off-targets). Positive controls should also generate robust peaks in expected genomic regions (i.e. sharp peaks at active transcription start sites for H3K4me3). See an expanded discussion and example data here.
  4. Examine sequencing data and compare the profiles from target antibodies as follows:
    • Lysine methylation PTMs: Antibodies should show <20% cross-reactivity using the SNAP-CUTANA K-MetStat Panel. Confirm that the genomic enrichment is consistent with the target PTM biology (e.g. broad vs narrow peak at functional elements) and shows high signal-to-noise.
    • For other PTMs: Compare results and select a specific antibody based on yields, expected target enrichment, and signal-to-noise in sequencing data.

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