A robust and sensitive assay for simultaneous measurement of transcriptome, chromatin accessibility, and cis-regulatory chromatin contacts

Unmet Need

Cis-regulatory elements (cREs) of the genome are non-coding regions that play essential roles in regulating gene expression in development and disease. Importantly, these regions are characterized by the presence of “open” chromatin and can be probed with a variety of existing sequencing technologies (ATAC-Seq, DNase-Seq, FAIRE-Seq). Additionally, chromosome conformation capture (3C) technologies can be used to understand high-order chromatin organization. However, to map long-range cis-regulatory interactions, deep sequencing is required. This insight is essential to study how long-range cRE interactions contribute to development and human disease but is currently extremely cost- and reagent-intensive. Thus, there is an urgent need for more robust, sensitive, and cost-efficient methods to map cis-regulatory chromatin organization using reduced sample input.

Technology

Duke inventors have developed a robust and sensitive method to simultaneously characterize chromatin accessibility and analyze the transcriptome with low sample input requirements. This is intended to be utilized in academic, clinical, and industry settings for the advancement of genomic and precision medicine. Specifically, HiCAR (High-throughput Chromosome conformation capture on Accessible DNA with mRNA-seq co-assay) is a multi-omics approach for unbiased mapping of high-order chromatin conformations, accessibility, and long-range interactions, and simultaneous characterization of the transcriptome from the same cellular starting material. This assay is significantly more effective and efficient than currently available alternatives and has demonstrated success in mouse and human cells.

Advantages

  • Outperforms other state-of-the-art technologies: HiChIP and PLAC-seq
  • Does not rely on antibody pulldown
  • Requires 50-fold less cells than HiChIP and PLAC-seq and 1000-fold less than trac-looping
  • Yields cleaner, more comprehensive datasets
  • More reliably captures long-range chromatin interactions
  • Lower cost than other methods
  • Can use frozen or crosslinked cells