Optimal use of tandem biotin and V5 tags in ChIP assays

Background  

Chromatin immunoprecipitation (ChIP) assays coupled to genome arrays (Chip-on-chip) or massive parallel sequencing (ChIP-seq) lead to the genome wide identification of binding sites of chromatin associated proteins. However, the highly variable quality of antibodies and the availability of epitopes in crosslinked chromatin can compromise genomic ChIP outcomes. Epitope tags have often been used as more reliable alternatives. In addition, we have employed protein in vivo biotinylation tagging as a very high affinity alternative to antibodies. In this paper we describe the optimization of biotinylation tagging for ChIP and its coupling to a known epitope tag in providing a reliable and efficient alternative to antibodies.     

Immunostaining of modified histones defines high-level features of the human metaphase epigenome

Background  

Immunolabeling of metaphase chromosome spreads can map components of the human epigenome at the single cell level. Previously, there has been no systematic attempt to explore the potential of this approach for epigenomic mapping and thereby to complement approaches based on chromatin immunoprecipitation (ChIP) and sequencing technologies.     

ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data

Background  

Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standard technologies for genome-wide identification of DNA-binding protein target sites. A number of algorithms have been developed in parallel that allow identification of binding sites from ChIP-seq or ChIP-chip datasets and subsequent visualization in the University of California Santa Cruz (UCSC) Genome Browser as custom annotation tracks. However, summarizing these tracks can be a daunting task, particularly if there are a large number of binding sites or the binding sites are distributed widely across the genome.     

Immediate chromatin immunoprecipitation and on-bead quantitative PCR analysis: a versatile and rapid ChIP procedure

Genome-wide chromatin immunoprecipitation (ChIP) studies have brought significant insight into the genomic localization of chromatin-associated proteins and histone modifications. The large amount of data generated by these analyses, however, require approaches that enable rapid validation and analysis of biological relevance. Furthermore, there are still protein and modification targets that are difficult to detect using standard ChIP methods. To address these issues, we developed an immediate chromatin immunoprecipitation procedure which we call ZipChip. ZipChip significantly reduces the time and increases sensitivity allowing for rapid screening of multiple loci. Here we describe how ZipChIP enables detection of histone modifications (H3K4 mono- and trimethylation) and two yeast histone demethylases, Jhd2 and Rph1, which were previously difficult to detect using standard methods. Furthermore, we demonstrate the versatility of ZipChIP by analyzing the enrichment of the histone deacetylase Sir2 at heterochromatin in yeast and enrichment of the chromatin remodeler, PICKLE, at euchromatin in Arabidopsis thaliana.     

An effective approach for identification of <Emphasis Type="Italic">in vivo</Emphasis> protein-DNA binding sites from paired-end ChIP-Seq data

Background  

ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with high-throughput massively parallel sequencing, is increasingly being used for identification of protein-DNA interactions in vivo in the genome. However, to maximize the effectiveness of data analysis of such sequences requires the development of new algorithms that are able to accurately predict DNA-protein binding sites.     

Chromatin Immunoprecipitation (ChIP) using Drosophila tissue

Epigenetics remains a rapidly developing field that studies how the chromatin state contributes to differential gene expression in distinct cell types at different developmental stages. Epigenetic regulation contributes to a broad spectrum of biological processes, including cellular differentiation during embryonic development and homeostasis in adulthood. A critical strategy in epigenetic studies is to examine how various histone modifications and chromatin factors regulate gene expression. To address this, Chromatin Immunoprecipitation (ChIP) is used widely to obtain a snapshot of the association of particular factors with DNA in the cells of interest.ChIP technique commonly uses cultured cells as starting material, which can be obtained in abundance and homogeneity to generate reproducible data. However, there are several caveats: First, the environment to grow cells in Petri dish is different from that in vivo, thus may not reflect the endogenous chromatin state of cells in a living organism. Second, not all types of cells can be cultured ex vivo. There are only a limited number of cell lines, from which people can obtain enough material for ChIP assay.Here we describe a method to do ChIP experiment using Drosophila tissues. The starting material is dissected tissue from a living animal, thus can accurately reflect the endogenous chromatin state. The adaptability of this method with many different types of tissue will allow researchers to address a lot more biologically relevant questions regarding epigenetic regulation in vivo^{1, 2}. Combining this method with high-throughput sequencing (ChIP-seq) will further allow researchers to obtain an epigenomic landscape.     

Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas

Background  

Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets.     

CATCHprofiles: clustering and alignment tool for ChIP profiles

Chromatin Immuno Precipitation (ChIP) profiling detects in vivo protein-DNA binding, and has revealed a large combinatorial complexity in the binding of chromatin associated proteins and their post-translational modifications. To fully explore the spatial and combinatorial patterns in ChIP-profiling data and detect potentially meaningful patterns, the areas of enrichment must be aligned and clustered, which is an algorithmically and computationally challenging task. We have developed CATCHprofiles, a novel tool for exhaustive pattern detection in ChIP profiling data. CATCHprofiles is built upon a computationally efficient implementation for the exhaustive alignment and hierarchical clustering of ChIP profiling data. The tool features a graphical interface for examination and browsing of the clustering results. CATCHprofiles requires no prior knowledge about functional sites, detects known binding patterns "ab initio", and enables the detection of new patterns from ChIP data at a high resolution, exemplified by the detection of asymmetric histone and histone modification patterns around H2A.Z-enriched sites. CATCHprofiles' capability for exhaustive analysis combined with its ease-of-use makes it an invaluable tool for explorative research based on ChIP profiling data. CATCHprofiles and the CATCH algorithm run on all platforms and is available for free through the CATCH website: http://catch.cmbi.ru.nl/. User support is available by subscribing to the mailing list catch-users@bioinformatics.org.     

A cell behavior screen: identification,sorting, and enrichment of cells based on motility

Background  

Identifying and isolating cells with specific behavioral characteristics will facilitate the understanding of the molecular basis regulating these behaviors. Although many approaches exist to characterize cell motility, retrieving cells of specific motility following analysis remains challenging.