8 research outputs found

    Systematic comparison of monoclonal versus polyclonal antibodies for mapping histone modifications by ChIP-seq.

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    BackgroundThe robustness of ChIP-seq datasets is highly dependent upon the antibodies used. Currently, polyclonal antibodies are the standard despite several limitations: They are non-renewable, vary in performance between lots and need to be validated with each new lot. In contrast, monoclonal antibody lots are renewable and provide consistent performance. To increase ChIP-seq standardization, we investigated whether monoclonal antibodies could replace polyclonal antibodies. We compared monoclonal antibodies that target five key histone modifications (H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3) to their polyclonal counterparts in both human and mouse cells.ResultsOverall performance was highly similar for four monoclonal/polyclonal pairs, including when we used two distinct lots of the same monoclonal antibody. In contrast, the binding patterns for H3K27ac differed substantially between polyclonal and monoclonal antibodies. However, this was most likely due to the distinct immunogen used rather than the clonality of the antibody.ConclusionsAltogether, we found that monoclonal antibodies as a class perform equivalently to polyclonal antibodies for the detection of histone post-translational modifications in both human and mouse. Accordingly, we recommend the use of monoclonal antibodies in ChIP-seq experiments

    Systematic comparison of monoclonal versus polyclonal antibodies for mapping histone modifications by ChIP-seq

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    BACKGROUND: The robustness of ChIP-seq datasets is highly dependent upon the antibodies used. Currently, polyclonal antibodies are the standard despite several limitations: They are non-renewable, vary in performance between lots and need to be validated with each new lot. In contrast, monoclonal antibody lots are renewable and provide consistent performance. To increase ChIP-seq standardization, we investigated whether monoclonal antibodies could replace polyclonal antibodies. We compared monoclonal antibodies that target five key histone modifications (H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3) to their polyclonal counterparts in both human and mouse cells. RESULTS: Overall performance was highly similar for four monoclonal/polyclonal pairs, including when we used two distinct lots of the same monoclonal antibody. In contrast, the binding patterns for H3K27ac differed substantially between polyclonal and monoclonal antibodies. However, this was most likely due to the distinct immunogen used rather than the clonality of the antibody. CONCLUSIONS: Altogether, we found that monoclonal antibodies as a class perform equivalently to polyclonal antibodies for the detection of histone post-translational modifications in both human and mouse. Accordingly, we recommend the use of monoclonal antibodies in ChIP-seq experiments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13072-016-0100-6) contains supplementary material, which is available to authorized users

    MOESM1 of Systematic comparison of monoclonal versus polyclonal antibodies for mapping histone modifications by ChIP-seq

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    Additional file 1: Figure S1. Reads aligning to annotated open and closed chromatin. Figure S2. Read coverage across the genome. Figure S3. Saturation curves. Figure S4. Mapping of peaks and reads to canonical chromatin regions. Figure S5. Correlation between monoclonal and polyclonal antibodies across the genome. Figure S6. Experimental quality control. Figure S7. Validation of the polyclonal antibody targeting H3K4me1 by peptide array
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