Evidence map›Paper›PMID 27826357›Full record

ArticleEpigenetics & chromatin2016

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

Michele Busby, Catherine Xue, Catherine Li, Yossi Farjoun, Elizabeth Gienger, Ido Yofe, Adrianne Gladden, Charles B Epstein, Evan M Cornett, Scott B Rothbart and 2 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in Epigenetics & chromatin, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Michele BusbyBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Catherine XueBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Catherine LiBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Yossi FarjounBroad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Elizabeth GiengerBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Ido YofeBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA ; Department of Immunology, Weizmann Institute, 76100 Rehovot, Israel.
Adrianne GladdenBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Charles B EpsteinBroad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Evan M CornettCenter for Epigenetics, Van Andel Research Institute, Grand Rapids, MI 49503 USA.
Scott B RothbartCenter for Epigenetics, Van Andel Research Institute, Grand Rapids, MI 49503 USA.
Chad NusbaumBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA.
Alon GorenBroad Technology Labs, Broad Institute of MIT and Harvard, Cambridge, MA 02142 USA ; Department of Medicine, University of California San Diego, La Jolla, CA 92093 USA.ORCID 0000-0001-5669-9357
Broad Institute · USVan Andel Institute · US

Funding

Mechanisms Regulating DNA Methylation Maintenance in ChromatinR00CA181343 · NCI · VAN ANDEL RESEARCH INSTITUTE · PI ROTHBART, SCOTT · 2015 to 2017
$746k
NCI NIH HHS R00 CA181343
6 · The paper itself

Abstract

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.

Indexed as

AnimalsAntibodiesAntibodies, MonoclonalChromatin ImmunoprecipitationDNAHistonesHumansK562 CellsMiceMouse Embryonic Stem CellsPeptide MappingProtein Processing, Post-TranslationalSequence Analysis, DNAAntibodiesAntibodies, MonoclonalDNAHistonesAntibodiesChIP-seqMethodsMonoclonalPolyclonal

Identifiers

PMID27826357
PMCPMC5097419
OpenAlexW2952789913

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.