Abstract: 

Precise spatiotemporal control of gene regulation is fundamental to normal biological processes and the development of disease. Therefore, detection of gene regulatory interactions is a critical component of understanding the biology of gene regulatory elements. Proximity ligation assays coupled with NGS provide a means to measure chromatin interactions within the nucleus. For example, Hi-C measures the frequency of genomic interactions at a genome-wide scale, and has become a mainstream technology for detecting genome structures ranging from genomic compartments, TADs, to chromatin loops, collectively undercovering a structural framework for gene regulation. Despite this utility, HiC is a genome-wide sequencing assay with relatively increased costs for high resolution analyses (>600M reads). Furthermore, HiC doesn’t directly enrich for gene regulatory interactions, such as those between promoters and enhancers. To address this and build upon our existing Arima-HiC kit platform, we have developed Arima-HiChIP. Arima-HiChIP integrates our Arima-HiC technology with ChIP-seq, thereby enriching for gene regulatory interactions associated with active regulatory elements. The optimized Arima-HiChIP workflow begins with ~2 million cells, and can be completed in 3 days.

Our Arima-HiChIP workflow is currently designed for integration with Covaris truChIP chromatin shearing kit and focused-ultrasonicators for chromatin shearing. We have optimized the Arima-HiChIP workflow for high resolution analysis of gene regulatory interactions associated with histone modifications, such as H3K27ac or H3K4me3, with reduced sequencing requirements (<200M reads). We have also built-in QC assays for the HiC portion of the workflow, chromatin shearing efficiency, ChIP enrichment, and library complexity. On the bioinformatics side, we have validated two open-source HiChIP analysis pipelines, MAPS and FitHiChIP. From extensive analyses of public and internal HiChIP datasets, we propose a new standardized framework and
metrics for analytical QC of HiChIP data. We aim to expand our Arima-HiChIP technology towards optimized protocols for analysis of transcription factors and low input samples.

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Covaris
www.covaris.com
info@covaris.com
Arima Genomics
www.arimagenomics.com