Introducing Omni-C™

Omni-C™ is a sequence-independent endonuclease-based Dovetail™ proximity-ligation protocol, which aims to address the limitations of RE-based Hi-C approaches. By employing an endonuclease, Omni-C™ increases the genomic coverage of a proximity-ligation assay, therefore expanding the efficiency of each sequencing run by covering more of the genome and reducing biases imposed by RE site density. As such, Omni-C™ generates libraries where more of the genome is included in analyses and thereby making the data more versatile and unbiased by RE sites.

Technology

Endonuclease-based molecular biology

The Omni-C™ process starts with endogenous chromatin fixed in place (cross-linked) by formaldehyde. After cross-linking, an endonuclease digests the chromatin in situ. The digested chromatin is released from the cell to generate a lysate, which is subjected to end-polishing, and followed by the ligation of a 28-mer biotinylated oligonucleotide bridge and intra-aggregate ligation. After cross link reversal and DNA purification, libraries are generated by a streptavidin enrichment step on the biotinylated bridge, resulting in an Illumina ready Omni-C™ library.

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Process

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Omni-C™ Kit

The Omni-C™ 8-reaction kit generates sequence-independent endonuclease-based Hi-C libraries that provide more uniform coverage across the genome. The Omni-C™ assay is a 2-day workflow – Day 1 for Sample Prep & Proximity Ligation and Day 2 for Library Generation – resulting in an Illumina-ready library. To ensure reaction efficiency, Omni-C™ has three molecular biology-based quality control checks that are predictive of library quality. Omni-C™ is currently validated on mammalian cells and tissues, and work is in progress to confirm a broader range of sample types. Accompanying the Omni-C™ assay is an open-source library QC tool to assess the library quality. In summary, the Omni-C™ workflow generates Hi-C-libraries with uniform coverage that can be easily integrated with open-source analysis tools.

  • Prepare & Crosslink Sample (1-1.5 hrs) *optional stopping 🛑point
  • In situ Nuclease Digestion (30 min)
  • Quantify & Select Lysate (2 hrs) *optional stopping 🛑point
  • Bind Chromatin to Chromatin Capture Beads (20 min)
  • End Polishing (1 hr)
  • Bridget Ligation (30 min)
  • Intra-Aggregate Ligation (1 hr)
  • Crosslink Reversal (1 hr)
  • DNA Purification & Size Selection (30 min) *optional stopping 🛑point
  • End Repair (1.25 hrs)
  • Adapter Ligation (45 min)
  • DNA Purification (30 min) *optional stopping 🛑point
  • Ligation Capture (45 min)
  • Index PCR (30 min)
  • DNA Purification & Size Selection (30 min) *optional stopping 🛑point
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Quality

Built-in QC steps allow users to determine library quality before sequencing. The Chromatin Digestion Index (CDI) quantitatively predicts the complexity (in unique molecules per 300 million read pairs sequenced) and the expected proportion of long-range cis reads in situ for each reaction. Omni-C™ generated libraries with high complexity and long-range information, regardless of sample type.

CDI is Predictive of Library Quality

Validation of Sample Input Types

SampleInput
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Cells and tissues from human and mice were used as inputs to validate Omni-C™. All libraries were sequenced to 20-40 million read pairs (2×150 bp) and processed through the Dovetail Genomics Omni-C™ QC pipeline.
Shown in the figure to the left, long-range cis read pairs were plotted as a percent of total cis reads in the library, and complexity was plotted as percent of unique molecules projected per 300 million read pairs.

Flexibility

Omni-C™ is designed to be a flexible assay, with a workflow that allows for a wide range of starting amounts. The normal workflow calls for 1 million cells or 50 mg of tissue, but the low input protocol can take as little starting material as 100 thousand cells or 5 mg of tissue and still yield highly complex libraries. Omni-C™ is also a dynamic assay that enables researchers to perform target enrichments, such as hybrid capture, thereby reducing sequence burden and increasing resolution around sites of interest.

Low Input Options

Omni-C™ libraries were generated from cell and muscle inputs from both human and mice. The resulting libraries were sequenced to 20-40 million read pairs (2×150 bp) and assessed on the Omni-C™ QC pipeline.

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Coverage

The endonuclease-based Omni-C™ provides superior coverage across the genome. Omni-C™ data exhibit a narrow per base coverage histogram when compared to other RE-based Hi-C, suggesting the entire genome is being sequenced at the same frequency. Typical Hi-C approaches miss a significant portion of the genome, leading to wider histograms and portions of the genome with no coverage at all.

Uneven coverage is also reflected in the pile-up of reads at RE sites, whereas Omni-C™ libraries show no enrichment of reads at RE sites. As such, Omni-C™ data capture single-nucleotide information in a manner that is independent of RE site proximity. When viewing Omni-C™ data in IGV, it is clear where RE-based Hi-C falls short in coverage and missed SNPs. The improved coverage that is inherent to Omni-C™ enables a more holistic view of the genome in down-stream analyses, which could include SNP calling and phasing.

Contact Map Resolution at a Fixed Sequencing Depth

Omni-C™ libraries were generated from cell and muscle inputs from both human and mice. The resulting libraries were sequenced to 20-40 million read pairs (2×150 bp) and assessed on the Omni-C™ QC pipeline.

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SequencingDepthResolution

Coverage Analysis

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Deeply sequenced Omni-C™ (1 billion read pairs) libraries were compared to RE-based Hi-C libraries for coverage. (A) Per base coverage, in Kbps. Coverage at RE sites, GATC (B) and GANTC (C) are plotted as the average of the absolute value both upstream and downstream of RE sites. (D) IVG view of coverage across a 14 Kbp window. Colored vertical lines indicate single nucleotide polymorphisms.

Topology

In addition to uniform coverage, Omni-C™ delivers on conformation. In the first figure below, Omni-C™ libraries from GM12878 cells were sequenced to 1.77 billion read pairs and loops were called using HiCCUPs. The resulting loops were then compared to loops found by Rao et al. (2014) after sequencing GM12878 cells to 4.9 billion read pairs.

Contact matrices generated from Omni-C™ libraries present a more complete view of genome conformation compared to RE-based Hi-C libraries. Areas with low coverage result in blank vectors due to normalization, as seen in the Hi-C matrices, whereas Omni-C™’s uniformity generates a much more complete contact matrix at these sites. Below, we highlight three regions where Omni-C™ reveals topological features interrupted in RE-based Hi-C.

Loop Detection

Loop calling with Omni-C™ data from GM12878 via HiCCUPS detected 14,552 chromatin loops with 5062 overlapping with Rao et al., 2014, despite 3-fold less sequencing. Overlapping loop calls between Omni-C™ and Rao et al., are similar in number to other such comparisons.

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Omni-C™ Libraries Generate More Complete Contact Matrices

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Blank bands in the contact matrix occur in regions where coverage is too low, causing the contacts to be normalized with a zero value in the denominator during contact matrix balancing. Here, we present several examples in which these results could cause confounding interpretations from RE-based Hi-C data, and the subsequent improvements to these matrices by Omni-C™.
(Top left) Chr5 at a cancer susceptibility locus that is often over-expressed in lung cancer. (Top middle) An ~5Mbp region in Chr9 that encompasses the TRAF2 gene, which plays a key role in apoptotic signaling. (Top right) Chr17, containing a suspected oncogene, FASN, which is often over-expressed in breast cancer. (Bottom left and right) Zoomed in sections of Chr5 that encompass TERT- vital to telomere maintenance and often over-expressed in lung cancers- at 4kbp and 1kbp resolutions, respectively.
The blue boxes below these comparisons denote 3kbp regions devoid of RE sites, and the black and red arrows are gene tracks.

Scaffolding

A staple application of proximity ligation data is scaffolding contigs for genome assembly. The ability of Hi-C data to scaffold correctly depends on the RE site density captured within each assembled contig. The analysis on scaffolding a human genome shows RE-dependent Hi-C scaffolding misses contigs that Omni-C™ can include. Omni-C™ is RE agnostic, allowing it to scaffold contigs more efficiently than Hi-C data, where RE frequency per contig is low. RE frequency increases RE-based Hi-C and Omni-C™ scaffolds at similar rates, which is expected as RE-based Hi-C is an efficient means of scaffolding high-quality input assemblies.

Omni-C™ is More Efficient at Scaffolding Contigs with Low RE Site Density

The human genome, HG38, was cut into contigs of random size and libraries were made on both Omni-C™ and RE-based Hi-C. The contigs were scaffolded using HiRise™ and then binned into groups by the number of RE sites per contig. Scaffolding efficiency was determined by normalizing the number of contigs scaffolded by the total number of contigs in each RE site group.

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Omni-C™ Award Program

Project Proposal Guidelines

Dovetail Genomics is excited to put the Omni-C™ kit into the hands of the community through the Omni-C™ Award Program.  Through September 30, 2019, we are welcoming submissions for projects that will benefit from the superior uniformity of coverage Omni-C™ delivers.

Approved proposals will receive matching funds in the form of a 50% discount off the list price for the Omni-C™ kits required within scope the project.

Have questions about Omni-C™ or any of our other products and services? Contact us to discover more about how our breakthrough technology and how it can help achieve your research goals.

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