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Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification.

ABSTRACT: We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from 'AAA' to 'DDD') to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody. We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBC ( www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label "ChIP-seq grade".

SUBMITTER: Mendoza-Parra MA

PROVIDER: S-EPMC4893979 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification.

Mendoza-Parra Marco-Antonio MA Saravaki Vincent V Cholley Pierre-Etienne PE Blum Matthias M Billoré Benjamin B Gronemeyer Hinrich H

F1000Research 20160112

We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the origin ...[more]

PMID: 27335635

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Project description:We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from âAAAâ to âDDDâ) to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody. We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBA (www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label âChIP-seq gradeâ. The NGS-QC team has setup a certification procedure for Antibodies dedicated to ChIP-seq applications based on (1)a highly reproducible pipeline for performing ChIP-seq assays including the use of an automated liquid handling platform (TECAN EVO75) for ChIP and sequencing library preparation steps and (2) the use of the NGS-QC Generator tool for providing a ChIP-seq quality grade and to evaluate other parameters like the Optimal sequencing depth, the degree of reproducibility among biological replicates and the comparison of the quality grades of the certified antibody with datasets retrieved in the public domain. This quality certification structure makes possible to assign a measured Quality Stamp to ChIP-seq grade Antibodies.

Project description:BACKGROUND:Cell-specific gene expression is controlled by epigenetic modifications and transcription factor binding. While genome-wide maps for these protein-DNA interactions have become widely available, quantitative comparison of the resulting ChIP-Seq data sets remains challenging. Current approaches to detect differentially bound or modified regions are mainly borrowed from RNA-Seq data analysis, thus focusing on total counts of fragments mapped to a region, ignoring any information encoded in the shape of the peaks. RESULTS:Here, we present MMDiff, a robust, broadly applicable method for detecting differences between sequence count data sets. Based on quantifying shape changes in signal profiles, it overcomes challenges imposed by the highly structured nature of the data and the paucity of replicates.We first use a simulated data set to compare the performance of MMDiff with results obtained by four alternative methods. We demonstrate that MMDiff excels when peak profiles change between samples. We next use MMDiff to re-analyse a recent data set of the histone modification H3K4me3 elucidating the establishment of this prominent epigenomic marker. Our empirical analysis shows that the method yields reproducible results across experiments, and is able to detect functional important changes in histone modifications. To further explore the broader applicability of MMDiff, we apply it to two ENCODE data sets: one investigating the histone modification H3K27ac and one measuring the genome-wide binding of the transcription factor CTCF. In both cases, MMDiff proves to be complementary to count-based methods. In addition, we can show that MMDiff is capable of directly detecting changes of homotypic binding events at neighbouring binding sites. MMDiff is readily available as a Bioconductor package. CONCLUSIONS:Our results demonstrate that higher order features of ChIP-Seq peaks carry relevant and often complementary information to total counts, and hence are important in assessing differential histone modifications and transcription factor binding. We have developed a new computational method, MMDiff, that is capable of exploring these features and therefore closes an existing gap in the analysis of ChIP-Seq data sets.

Dataset Information

Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification.

Publications

Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification.

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