ChIP-on-chip

[2] If histones are subject of interest, it is believed that the distribution of modifications and their localizations may offer new insights into the mechanisms of regulation.

One of the long-term goals ChIP-on-chip was designed for is to establish a catalogue of (selected) organisms that lists all protein-DNA interactions under various physiological conditions.

The early versions of microarrays were designed to detect RNAs from expressed genomic regions (open reading frames aka ORFs).

Although such arrays are perfectly suited to study gene expression profiles, they have limited importance in ChIP experiments since most "interesting" proteins with respect to this technique bind in intergenic regions.

[3] Array size: The first microarrays used for ChIP-on-Chip contained about 13,000 spotted DNA segments representing all ORFs and intergenic regions from the yeast genome.

Just to name one example, Affymetrix offers a set of seven arrays with about 90 million probes, spanning the complete non-repetitive part of the human genome with about 35bp spacing.

The most important elements are, among others, hybridization ovens, chip scanners, and software packages for subsequent numerical analysis of the raw data.

The antibodies may be attached to a solid surface, may have a magnetic bead, or some other physical property that allows separation of cross-linked complexes and unbound fragments.

Finally, the fragments are poured over the surface of the DNA microarray, which is spotted with short, single-stranded sequences that cover the genomic portion of interest.

Problems arise throughout this portion of the workflow, ranging from the initial chip read-out, to suitable methods to subtract background noise, and finally to appropriate algorithms that normalize the data and make it available for subsequent statistical analysis, which then hopefully lead to a better understanding of the biological question that the experiment seeks to address.

These methods generally differ in how low-intensity signals are handled, how much background noise is accepted, and which trait for the data is emphasized during the computation.

As mentioned previously, the statistical analysis of the huge amount of data generated from arrays is a challenge and normalization procedures should aim to minimize artifacts and determine what is really biologically significant.

ChIP-on-chip requires highly specific antibodies that must recognize its epitope in free solution and also under fixed conditions.

Companies that provide ChIP-grade antibodies include Abcam, Cell Signaling Technology, Santa Cruz, and Upstate.

To overcome the problem of specificity, the protein of interest can be fused to a tag like FLAG or HA that are recognized by antibodies.

The ChIP-on-chip technique using all of the ORFs of the genome (that nevertheless remains incomplete, missing intergenic regions) was then applied successfully in three papers published in 2000 and 2001.

In 2002, Richard Young's group[10] determined the genome-wide positions of 106 transcription factors using a c-Myc tagging system in yeast.

[11] This study was followed several months later in a collaboration between the Young lab with the laboratory of Brian Dynlacht which used the ChIP-on-chip technique to show for the first time that E2F targets encode components of the DNA damage checkpoint and repair pathways, as well as factors involved in chromatin assembly/condensation, chromosome segregation, and the mitotic spindle checkpoint[12] Other applications for ChIP-on-chip include DNA replication, recombination, and chromatin structure.

Thus, many studies in mammalian cells have focused on select promoter regions that are predicted to bind transcription factors and have not analyzed the entire genome.

In the future, as ChIP-on-chip arrays become more and more advanced, high resolution whole genome maps of DNA-binding proteins and chromatin components for mammals will be analyzed in more detail.

CUT&RUN sequencing uses antibody recognition with targeted enzymatic cleavage to address some technical limitations of ChIP.