Taking off the Blinders- The Acceleration of Integrated Multi-omic Analysis

Joe Horsman on October 18, 2017

Typically our fields require us to specialize; geneticists profile DNA and RNA, flow cytometrists look at extracellular protein markers, and system biologists look at complex data from six different instruments. We often stay in our single-omic lane, only deviating when absolute necessity (or reviewer #2) requires us to step outside our comfort zone.

Our increased understanding of the interplay between genomics and proteomics and the value of functional analysis demands that we no longer specialize in a single technique, but rather deeply profile precious samples with integrated analysis of DNA, RNA, and protein. One acute illustration of the importance of multi-analyte analysis is the common discordance between RNA and protein expression, begging the question: “how do I know what to measure to best answer my biological question?”1

The solution lies in multi-omic analysis. This approach has been adopted in the field of systems biology but the myriad technology platforms utilized often make it unclear what changes are from true biological differences verses merely technical variation and complex data integration. Additionally, different platforms often require different sample input amounts or requirements and each platform comes with its own technical limitations.

Here we highlight a handful of recent publications and technologies working to solve the problems associated with multi-omic research, with a focus on analysis of cells in suspension:


Darmanis et. al. (2016)2 show a streamlined method utilizing qRT-PCR to obtain ~96 protein and RNA data points. This technique splits lysate from a single isolated cell to analyze both RNA and protein. Protein data is obtained using Proximity Extension Assay (PEA) which employs antibody pairs, similar to sandwich immuno-assays. These antibodies contain oligonucleotides, which when in proximity, can be amplified, producing cDNA reporters. These cDNA protein reporters are added to cDNA from reverse transcription of mRNA from the sample and the pooled sample is analyzed by qRT-PCR. This technology begins to move multi-omic data out of proteomic/genomic cores and into the hands of individual labs, enabling multiplexed RNA and protein analysis with qRT-PCR for mid-plex analysis.


Shahi et. al. (2017)3 pioneered a single cell proteomic technique utilizing unique oligonucleotide barcodes conjugated to antibodies. This Abseq protocol stains cells with oligo-tagged antibodies, followed by DNA sequencing of these oligo-tags to obtain protein expression data at single cell resolution. Each antibody must be tagged, validated, and tested by the lab before use to ensure the addition of the oligo does not change the antibody properties and that the antibodies perform well in multi-plex. Storckius et al. (2017)4 builds on this concept, combining these oligo-labeled antibodies with a RNA sequencing workflow in CITE-seq. The protein technology currently adds flow cytometry-like plex of ~13 proteins to the whole genome coverage of RNAseq with a turnaround time of up to two weeks. The resulting data is analogous to what is currently obtained by cell sorting and single cell sequencing, providing an integrated parallel solution to current flow cytometry based techniques. CITE-seq relies on current sequencing workflow and will require molecular biology and sequencing resources with adaptation of current workflows and reagents.

PLAYR (proximity ligation assay for RNA)

Attacking this multi-omics problem from a different direction, Frei et. al.5 utilize a modified rolling circle amplification to integrate RNA detection with the protein analytical workflows of flow and mass cytometry. The PLAYR technology is capable of analyzing up to 40 RNA and proteins from a single cell. Antibodies are used to detect protein as in standard cytometry methods, while RNA detection utilizes proximity ligation to measure individual transcripts. In this method, pairs of oligonucleotide probes hybridize to a single RNA target allowing DNA amplification of the probes and subsequent detection with separate, fluorescent or heavy metal tagged, oligonucleotides. This enables protein focused researchers to analyze RNA by modifying existing protein focused analytical techniques for lower plex analysis.

3D Biology™ Technology

The nCounter® Analysis System utilizes molecular barcode technology to measure a variety of nucleic acids, including mRNA and miRNA, without amplification. Building off these barcodes, 3D Biology Technology enables simultaneous analysis of up to 800 DNA, RNA, protein, and phospho-protein targets from the same sample, be it formalin fixed paraffin embedded (FFPE) tissue sections, cell or tissue lysates, or cells in suspension. Protein detection employs oligo-tagged antibodies designed to hybridize with the standard NanoString® molecular barcodes, while DNA SNV detection utilizes a modified probe design to identify SNV down to 5% mutant allele frequency. These assays enable researchers to run validated, multi-omic panels without significant development and troubleshooting efforts. 3D Biology Technology has been recently augmented with a novel workflow, 3D Flow™ Analysis, which integrates flow cytometry cell sorting and detection of 770 RNA and 30 proteins simultaneously from rare immune samples. This workflow provides a two-day turnaround time and requires no amplification or enzymes further expanding the questions that can be addressed from rare cell populations.

With technologies available like the ones highlighted above, the question cannot be, “should I look at multiple analytes?” but rather “what questions will deep molecular characterization of DNA, RNA, and protein and beyond enable me to address?”

Read more about 3D Biology Technology

FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.



1 Global quantification of mammalian gene expression control. Schwanhäusser B, et. al. Nature. 2011 May 19;473(7347):337-42. doi: 10.1038/ nature10098.

2 Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells. Darmanis, S. et al. Cell Reports, Volume 14 , Issue 2 , 380 – 389 (2016) DOI: 10.1016/j.celrep.2015.12.021

3 Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding. Shahi, P. et al. Scientific Reports 7, Article number: 44447 (2017) doi:10.1038/srep44447

4 Simultaneous epitope and transcriptome measurement in single cells. Stoeckius, M. et al. Nature Methods, (2017) doi:10.1038/nmeth.4380

5 Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Frei, AP. et al. Nature Methods, 13 269-275 (2017) doi:10.1038/nmeth.3742

Post by Joe Horsman