Spatial Omics Solutions for Liver Disease

Spatial Omics Solutions for Liver Disease

Globally, liver health has been an unmet medical need. Although it is a vital organ, people may not realize that liver health is critical. Chronic liver disease has become a major global health problem, with an estimated global prevalence of 2.5% and 2 million deaths worldwide each year from chronic liver disease. However, it can be reversed if diagnosed early and properly monitored and treated.

How we enable spatial omics for liver disease research

CD Genomics' spatial-omics-based technology service performs scRNA-seq on tissue sections using spatially organized RNA capture probes for spatially resolved RNA sequencing, paired cell sequencing. Where required, we use a combination of scRNA-seq technologies. For example, we may use a micro drop-based system and Smart-seq2 as a way to create synergy and increase the likelihood of capturing rare cell types and low-abundance transcripts.

We offer solutions that match the RNA profile of hepatocytes to their location in the tissue, helping our clients to study transcriptional activity at the spatial level. Paves the way for the discovery of previously unknown cell types and subtypes in normal and diseased livers. Facilitates the study of rare cells (e.g. hepatic progenitor cells) and the functional role of non-parenchymal cells in chronic liver disease.

General technical protocol flow

Model of in situ spatial transcriptomics.Figure 1. Model of in situ spatial transcriptomics. (Antonio S., et al., 2020)

  • Selection of specific cell populations from heterogeneous tissues. Includes tissue dissociation and single-cell isolation.
  • Protocols for reverse transcription using Smart-seq2 and amplification by PCR. These protocols involve capturing RNA poly(A) tails and inserting random unique molecular identifiers and pre-specified cellular barcodes into cDNAs. Cell barcodes and molecular identifiers are present in each cDNA, so we can pool cDNAs from different cells for amplification and sequencing steps. Cell barcodes are used to infer cell origin and to quantify gene expression by counting and normalizing molecular identifiers for each cell.
  • Discovery, identification, and study of rare cell types, cell subtypes, liver disease-specific cell types, and cell-cell interactions.

Technical features

A variety of technologies are available and our scientists will select the appropriate technology or combination of technologies based on the client's study design and desired endpoint (e.g. study of rare hepatocyte types or analysis of low-expressed genes or splice variants). Smart-seq2 is the preferred choice when analyzing splicing, transcriptome annotation, or genome integration. High-throughput micro drop-based microfluidic technology allows for broader cellular coverage at shallower sequencing read depths.

Optional analysis options

  • Use sophisticated computational algorithms to infer spatial information from scRNA-seq data.
  • Use smRNA-FISH to assess the spatial distribution of signature genes in known partitions at high resolution.
  • Characterize multidirectional interactions between cells using single-cell data, multispectral ligand-receptor interaction analysis, and multiplex immunofluorescence.

Practical application areas

CD Genomics offers protocols that have been applied to study liver regeneration, the organization and function of hepatocytes and non-parenchymal cells, and to analyze the single-cell landscape of chronic liver disease and liver cancer. It can also be used to characterize the liver function and gene expression dynamics during liver disease, as well as to identify prognostic markers or features and to facilitate the discovery of new therapeutic targets.


  1. Antonio S., et al., (2020). "Single-cell genomics and spatial transcriptomics: Discovery of novel cell states and cellular interactions in liver physiology and disease biology." Journal of Hepatology, 73 (5): 1219-1230.
For research use only, not intended for any clinical use.

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