Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Profiling of transcription factor binding events by chromatin immunoprecipitation sequencing (ChIP-seq).

ABSTRACT: In multi-cellular organisms, gene expression is orchestrated by thousands of transcription factors (TF). Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a robust tool to investigate gene expression because this technique profiles in vivo protein-DNA interaction at a genome-wide scale. Eight years after the first ChIP-seq paper, there are limited reports of ChIP-seq experiments in plants, especially for sequence-specific DNA binding TFs This lag greatly prevents our understanding of transcriptional regulation in an entire kingdom. In order to bridge the technical gap, we describe a ChIP-seq procedure that we have successfully applied to dozens of sequence-specific DNA binding TFs. The basic protocol includes procedures to isolate nuclei, sonicate chromatin, immunoprecipitate TF-DNA complex, and recover ChIP-enriched DNA fragments. The support protocol also describes practices to optimize library preparation by a gel-free DNA size selection. Lastly, examples are given to optimize library amplification using real-time PCR.

SUBMITTER: Song L

PROVIDER: S-EPMC5544034 | biostudies-other | 2016

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Generation of high quality chromatin immunoprecipitation DNA template for high-throughput sequencing (ChIP-seq).

Project description:ChIP-sequencing (ChIP-seq) methods directly offer whole-genome coverage, where combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing can be utilized to identify the repertoire of mammalian DNA sequences bound by transcription factors in vivo. "Next-generation" genome sequencing technologies provide 1-2 orders of magnitude increase in the amount of sequence that can be cost-effectively generated over older technologies thus allowing for ChIP-seq methods to directly provide whole-genome coverage for effective profiling of mammalian protein-DNA interactions. For successful ChIP-seq approaches, one must generate high quality ChIP DNA template to obtain the best sequencing outcomes. The description is based around experience with the protein product of the gene most strongly implicated in the pathogenesis of type 2 diabetes, namely the transcription factor transcription factor 7-like 2 (TCF7L2). This factor has also been implicated in various cancers. Outlined is how to generate high quality ChIP DNA template derived from the colorectal carcinoma cell line, HCT116, in order to build a high-resolution map through sequencing to determine the genes bound by TCF7L2, giving further insight in to its key role in the pathogenesis of complex traits.

| S-EPMC3665311 | biostudies-other

Chromatin analyses of Zymoseptoria tritici: Methods for chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq).

Project description:The presence or absence of specific transcription factors, chromatin remodeling machineries, chromatin modification enzymes, post-translational histone modifications and histone variants all play crucial roles in the regulation of pathogenicity genes. Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) provides an important tool to study genome-wide protein-DNA interactions to help understand gene regulation in the context of native chromatin. ChIP-seq is a convenient in vivo technique to identify, map and characterize occupancy of specific DNA fragments with proteins against which specific antibodies exist or which can be epitope-tagged in vivo. We optimized existing ChIP protocols for use in the wheat pathogen Zymoseptoria tritici and closely related sister species. Here, we provide a detailed method, underscoring which aspects of the technique are organism-specific. Library preparation for Illumina sequencing is described, as this is currently the most widely used ChIP-seq method. One approach for the analysis and visualization of representative sequence is described; improved tools for these analyses are constantly being developed. Using ChIP-seq with antibodies against H3K4me2, which is considered a mark for euchromatin or H3K9me3 and H3K27me3, which are considered marks for heterochromatin, the overall distribution of euchromatin and heterochromatin in the genome of Z. tritici can be determined. Our ChIP-seq protocol was also successfully applied to Z. tritici strains with high levels of melanization or aberrant colony morphology, and to different species of the genus (Z. ardabiliae and Z. pseudotritici), suggesting that our technique is robust. The methods described here provide a powerful framework to study new aspects of chromatin biology and gene regulation in this prominent wheat pathogen.

| S-EPMC4620941 | biostudies-literature

Identifying differential transcription factor binding in ChIP-seq.

Project description:ChIP seq is a widely used assay to measure genome-wide protein binding. The decrease in costs associated with sequencing has led to a rise in the number of studies that investigate protein binding across treatment conditions or cell lines. In addition to the identification of binding sites, new studies evaluate the variation in protein binding between conditions. A number of approaches to study differential transcription factor binding have recently been developed. Several of these methods build upon established methods from RNA-seq to quantify differences in read counts. We compare how these new approaches perform on different data sets from the ENCODE project to illustrate the impact of data processing pipelines under different study designs. The performance of normalization methods for differential ChIP-seq depends strongly on the variation in total amount of protein bound between conditions, with total read count outperforming effective library size, or variants thereof, when a large variation in binding was studied. Use of input subtraction to correct for non-specific binding showed a relatively modest impact on the number of differential peaks found and the fold change accuracy to biological validation, however a larger impact might be expected for samples with more extreme copy number variations between them. Still, it did identify a small subset of novel differential regions while excluding some differential peaks in regions with high background signal. These results highlight proper scaling for between-sample data normalization as critical for differential transcription factor binding analysis and suggest bioinformaticians need to know about the variation in level of total protein binding between conditions to select the best analysis method. At the same time, validation using fold-change estimates from qRT-PCR suggests there is still room for further method improvement.

| S-EPMC4413818 | biostudies-literature

Characterization of the Escherichia coli σ(S) core regulon by Chromatin Immunoprecipitation-sequencing (ChIP-seq) analysis.

Project description:In bacteria, selective promoter recognition by RNA polymerase is achieved by its association with σ factors, accessory subunits able to direct RNA polymerase "core enzyme" (E) to different promoter sequences. Using Chromatin Immunoprecipitation-sequencing (ChIP-seq), we searched for promoters bound by the σ(S)-associated RNA polymerase form (Eσ(S)) during transition from exponential to stationary phase. We identified 63 binding sites for Eσ(S) overlapping known or putative promoters, often located upstream of genes (encoding either ORFs or non-coding RNAs) showing at least some degree of dependence on the σ(S)-encoding rpoS gene. Eσ(S) binding did not always correlate with an increase in transcription level, suggesting that, at some σ(S)-dependent promoters, Eσ(S) might remain poised in a pre-initiation state upon binding. A large fraction of Eσ(S)-binding sites corresponded to promoters recognized by RNA polymerase associated with σ(70) or other σ factors, suggesting a considerable overlap in promoter recognition between different forms of RNA polymerase. In particular, Eσ(S) appears to contribute significantly to transcription of genes encoding proteins involved in LPS biosynthesis and in cell surface composition. Finally, our results highlight a direct role of Eσ(S) in the regulation of non coding RNAs, such as OmrA/B, RyeA/B and SibC.

| S-EPMC4447067 | biostudies-literature

Fully automated high-throughput chromatin immunoprecipitation for ChIP-seq: identifying ChIP-quality p300 monoclonal antibodies.

Project description:Chromatin immunoprecipitation coupled with DNA sequencing (ChIP-seq) is the major contemporary method for mapping in vivo protein-DNA interactions in the genome. It identifies sites of transcription factor, cofactor and RNA polymerase occupancy, as well as the distribution of histone marks. Consortia such as the ENCyclopedia Of DNA Elements (ENCODE) have produced large datasets using manual protocols. However, future measurements of hundreds of additional factors in many cell types and physiological states call for higher throughput and consistency afforded by automation. Such automation advances, when provided by multiuser facilities, could also improve the quality and efficiency of individual small-scale projects. The immunoprecipitation process has become rate-limiting, and is a source of substantial variability when performed manually. Here we report a fully automated robotic ChIP (R-ChIP) pipeline that allows up to 96 reactions. A second bottleneck is the dearth of renewable ChIP-validated immune reagents, which do not yet exist for most mammalian transcription factors. We used R-ChIP to screen new mouse monoclonal antibodies raised against p300, a histone acetylase, well-known as a marker of active enhancers, for which ChIP-competent monoclonal reagents have been lacking. We identified, validated for ChIP-seq, and made publicly available a monoclonal reagent called ENCITp300-1.

| S-EPMC4053718 | biostudies-literature

Optimized ChIP-seq method facilitates transcription factor profiling in human tumors.

Project description:Chromatin immunoprecipitation (ChIP)-seq analyses of transcription factors in clinical specimens are challenging due to the technical limitations and low quantities of starting material, often resulting in low enrichments and poor signal-to-noise ratio. Here, we present an optimized protocol for transcription factor ChIP-seq analyses in human tissue, yielding an ?100% success rate for all transcription factors analyzed. As proof of concept and to illustrate general applicability of the approach, human tissue from the breast, prostate, and endometrial cancers were analyzed. In addition to standard formaldehyde fixation, disuccinimidyl glutarate was included in the procedure, greatly increasing data quality. To illustrate the sensitivity of the optimized protocol, we provide high-quality ChIP-seq data for three independent factors (AR, FOXA1, and H3K27ac) from a single core needle prostate cancer biopsy specimen. In summary, double-cross-linking strongly improved transcription factor ChIP-seq quality on human tumor samples, further facilitating and enhancing translational research on limited amounts of tissue.

| S-EPMC6311467 | biostudies-literature

AHT-ChIP-seq: a completely automated robotic protocol for high-throughput chromatin immunoprecipitation.

Project description:ChIP-seq is an established manually-performed method for identifying DNA-protein interactions genome-wide. Here, we describe a protocol for automated high-throughput (AHT) ChIP-seq. To demonstrate the quality of data obtained using AHT-ChIP-seq, we applied it to five proteins in mouse livers using a single 96-well plate, demonstrating an extremely high degree of qualitative and quantitative reproducibility among biological and technical replicates. We estimated the optimum and minimum recommended cell numbers required to perform AHT-ChIP-seq by running an additional plate using HepG2 and MCF7 cells. With this protocol, commercially available robotics can perform four hundred experiments in five days.

| S-EPMC4053851 | biostudies-literature

Pinpointing transcription factor binding sites from ChIP-seq data with SeqSite.

Project description:BackgroundChromatin immunoprecipitation combined with the next-generation DNA sequencing technologies (ChIP-seq) becomes a key approach for detecting genome-wide sets of genomic sites bound by proteins, such as transcription factors (TFs). Several methods and open-source tools have been developed to analyze ChIP-seq data. However, most of them are designed for detecting TF binding regions instead of accurately locating transcription factor binding sites (TFBSs). It is still challenging to pinpoint TFBSs directly from ChIP-seq data, especially in regions with closely spaced binding events.ResultsWith the aim to pinpoint TFBSs at a high resolution, we propose a novel method named SeqSite, implementing a two-step strategy: detecting tag-enriched regions first and pinpointing binding sites in the detected regions. The second step is done by modeling the tag density profile, locating TFBSs on each strand with a least-squares model fitting strategy, and merging the detections from the two strands. Experiments on simulation data show that SeqSite can locate most of the binding sites more than 40-bp from each other. Applications on three human TF ChIP-seq datasets demonstrate the advantage of SeqSite for its higher resolution in pinpointing binding sites compared with existing methods.ConclusionsWe have developed a computational tool named SeqSite, which can pinpoint both closely spaced and isolated binding sites, and consequently improves the resolution of TFBS detection from ChIP-seq data.

| S-EPMC3287483 | biostudies-literature

Optimized detection of transcription factor-binding sites in ChIP-seq experiments.

Project description:We developed a computational procedure for optimizing the binding site detections in a given ChIP-seq experiment by maximizing their reproducibility under bootstrap sampling. We demonstrate how the procedure can improve the detection accuracies beyond those obtained with the default settings of popular peak calling software, or inform the user whether the peak detection results are compromised, circumventing the need for arbitrary re-iterative peak calling under varying parameter settings. The generic, open-source implementation is easily extendable to accommodate additional features and to promote its widespread application in future ChIP-seq studies. The peakROTS R-package and user guide are freely available at http://www.nic.funet.fi/pub/sci/molbio/peakROTS.

| S-EPMC3245948 | biostudies-literature

Important biological information uncovered in previously unaligned reads from chromatin immunoprecipitation experiments (ChIP-Seq).

Project description:Establishing the architecture of gene regulatory networks (GRNs) relies on chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) methods that provide genome-wide transcription factor binding sites (TFBSs). ChIP-Seq furnishes millions of short reads that, after alignment, describe the genome-wide binding sites of a particular TF. However, in all organisms investigated an average of 40% of reads fail to align to the corresponding genome, with some datasets having as much as 80% of reads failing to align. We describe here the provenance of previously unaligned reads in ChIP-Seq experiments from animals and plants. We show that a substantial portion corresponds to sequences of bacterial and metazoan origin, irrespective of the ChIP-Seq chromatin source. Unforeseen was the finding that 30%-40% of unaligned reads were actually alignable. To validate these observations, we investigated the characteristics of the previously unaligned reads corresponding to TAL1, a human TF involved in lineage specification of hemopoietic cells. We show that, while unmapped ChIP-Seq read datasets contain foreign DNA sequences, additional TFBSs can be identified from the previously unaligned ChIP-Seq reads. Our results indicate that the re-evaluation of previously unaligned reads from ChIP-Seq experiments will significantly contribute to TF target identification and determination of emerging properties of GRNs.

| S-EPMC4345404 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data