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Dirks, R. A. M.

Publications and source records attributed to Dirks, R. A. M..

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A plug and play microfluidic platform for standardized sensitive low-input Chromatin Immunoprecipitation

Epigenetic profiling by ChIP-Seq has become a powerful tool for genome-wide identification of regulatory elements, for defining transcriptional regulatory networks and for screening for biomarkers. However, the ChIP-Seq protocol for low-input samples is laborious, time-consuming and suffers from experimental variation, resulting in poor reproducibility and low throughput. Although prototypic microfluidic ChIP-Seq platforms have been developed, these are poorly transferable as they require sophisticated custom-made equipment and in-depth microfluidic and ChIP expertise, while lacking parallelisation. To enable standardized, automated ChIP-Seq profiling of low-input samples, we constructed PDMS-based plates containing microfluidic Integrated Fluidic Circuits capable of performing 24 sensitive ChIP reactions within 30 minutes hands-on time. These disposable plates can conveniently be loaded into a widely available controller for pneumatics and thermocycling, making the ChIP-Seq procedure Plug and Play (PnP). We demonstrate high-quality ChIP-seq on hundreds to few thousands of cells for multiple widely-profiled post-translational histone modifications, together allowing genome-wide identification of regulatory elements. As proof of principle, we managed to generate high-quality epigenetic profiles of rare totipotent subpopulations of mESCs using our platform. In light of the ready-to-go ChIP plates and the automated workflow, we named our procedure PnP-ChIP-Seq. PnP-ChIP-Seq allows non-expert labs worldwide to conveniently run robust, standardized ChIP-Seq, while its high-throughput, consistency and sensitivity paves the way towards large-scale profiling of precious sample types such as rare subpopulations of cells or biopsies. Reviewer link to dataAll sequencing data has been submitted to the NCBI GEO database. Reviewer link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=klwnocicrpaxrkv&acc=GSE120673

genetics