Agilent Launches Microarrays for ChIP-on-Chip Analysis

Agilent Technologies Inc. has announced the availability of oligo array-based ChIP-on-chip (chromatin immunoprecipitation on a chip) microarrays with a sixfold increase in density over previous offerings.

The higher density microarrays complement the platform’s sensitivity and reproducibility, letting researchers conduct genomic tiling experiments.

These microarrays are available in two formats: one microarray per slide with 244,000 features or four microarrays per slide each with 44,000 features.

"Researchers recognize that having more features per array increases efficiency because they use fewer slides," said Kevin Meldrum, Agilent director of Genomics Marketing.

"They also acknowledge that more features do not necessarily mean more accurate measurements."

"Tiling experiments require optimized probe design to detect a binding event with ChIP-on-chip. Our arrays deliver the density, flexibility and sensitivity that these investigators demand."

Common applications include characterization of transcription, DNA replication and DNA repair events; mapping of chromatin modifications such as DNA methylation; determination of modalities and interactions between therapeutic compounds and target genes; and validation of gene expression data.

"This technique is being rapidly adopted worldwide," said Rini Saxena, Agilent product manager.

"ChIP-on-chip provides biological insights that have not been previously identified by solely using gene expression."

"Our investigations are currently focused on the ETS gene family as a model system, and the issue of transcription factor specificity is central to the control of cell growth and differentiation as well as the misregulation of these processes during oncogenesis," said Dr. Barbara Graves, chairman of the Department of Oncological Sciences at the Huntsman Cancer Institute.

"Agilent’s ChIP-on-chip platform enables us to investigate binding events on a global scale."

"The 4-array format lets researchers run four samples on a single slide, significantly reducing the total cost of experiment," Saxena added.

"For example, researchers in the yeast community will be able to study four different conditions against four whole genomes by simply using one slide."