Dataset Information

A quality control system for profiles obtained by ChIP sequencing.

ABSTRACT: The absence of a quality control (QC) system is a major weakness for the comparative analysis of genome-wide profiles generated by next-generation sequencing (NGS). This concerns particularly genome binding/occupancy profiling assays like chromatin immunoprecipitation (ChIP-seq) but also related enrichment-based studies like methylated DNA immunoprecipitation/methylated DNA binding domain sequencing, global run on sequencing or RNA-seq. Importantly, QC assessment may significantly improve multidimensional comparisons that have great promise for extracting information from combinatorial analyses of the global profiles established for chromatin modifications, the bindings of epigenetic and chromatin-modifying enzymes/machineries, RNA polymerases and transcription factors and total, nascent or ribosome-bound RNAs. Here we present an approach that associates global and local QC indicators to ChIP-seq data sets as well as to a variety of enrichment-based studies by NGS. This QC system was used to certify >5600 publicly available data sets, hosted in a database for data mining and comparative QC analyses.

SUBMITTER: Mendoza-Parra MA

PROVIDER: S-EPMC3834836 | biostudies-other | 2013 Nov

REPOSITORIES: biostudies-other

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A quality control system for profiles obtained by ChIP sequencing.

Mendoza-Parra Marco-Antonio MA Van Gool Wouter W Mohamed Saleem Mohamed Ashick MA Ceschin Danilo Guillermo DG Gronemeyer Hinrich H

Nucleic acids research 20130914 21

The absence of a quality control (QC) system is a major weakness for the comparative analysis of genome-wide profiles generated by next-generation sequencing (NGS). This concerns particularly genome binding/occupancy profiling assays like chromatin immunoprecipitation (ChIP-seq) but also related enrichment-based studies like methylated DNA immunoprecipitation/methylated DNA binding domain sequencing, global run on sequencing or RNA-seq. Importantly, QC assessment may significantly improve multid ...[more]

PMID: 24038469

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Project description:The advent of next-generation sequencing has significantly facilitated characterization of the oral microbiome. Despite great efforts in streamlining the processes of sequencing and data curation, upstream steps required for amplicon library generation could still influence 16S rRNA gene-based microbial profiles. Among upstream processes, DNA extraction is a critical step that could represent a great source of bias. Accounting for bias introduced by extraction procedures is important when comparing studies that use different methods. Identifying the method that best portrays communities is also desirable. Accordingly, the aim of this study was to evaluate bias introduced by different DNA extraction procedures on oral microbiome profiles. Four DNA extraction methods were tested on mock communities consisting of seven representative oral bacteria. Additionally, supragingival plaque samples were collected from seven individuals and divided equally to test two commonly used DNA extraction procedures. Amplicon libraries of the 16S rRNA gene were generated and sequenced via 454-pyrosequencing. Evaluation of mock communities revealed that DNA yield and bacterial species representation varied with DNA extraction methods. Despite producing the lowest yield of DNA, a method that included bead beating was the only protocol capable of detecting all seven species in the mock community. Comparison of the performance of two commonly used methods (crude lysis and a chemical/enzymatic lysis+column-based DNA isolation) on plaque samples showed no effect of extraction protocols on taxa prevalence but global community structure and relative abundance of individual taxa were affected. At the phylum level, the latter method improved the recovery of Actinobacteria, Bacteroidetes, and Spirochaetes over crude lysis. DNA extraction distorts microbial profiles in simulated and clinical oral samples, reinforcing the importance of careful selection of a DNA extraction protocol to improve species recovery and facilitate data comparison across oral microbiology studies.

Dataset Information

A quality control system for profiles obtained by ChIP sequencing.

Publications

A quality control system for profiles obtained by ChIP sequencing.

Similar Datasets

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