InquiryCells occupy a wide range of phenotypes and morphologies that meet the functional requirements of each of their tissues and ecological niches, helping researchers understand cellular diversity by classifying cells into different types that carry specific molecular signatures and allowing the management of large amounts of non-simplifiable and complex cellular information through classification.
How we identify novel cell types
CD Genomics can use spatial genomics techniques to identify molecules and cells in context and to localize individual biomolecules to define different cell types and locations. Importantly, this highly multiplexed analysis can be done directly in the tissue microenvironment, providing high-resolution mapping of expression profiles directly within the tissue, preserving the spatial context of cells in the sample. This spatial multimodal approach can be used to explore the nuclear organization and cellular states in different biological systems to identify new cell types.
Figure 1. Single-cell RNA-sequencing analyses to study liver pathophysiology. (Antonio S., et al., 2020)
The transcriptome-level analysis provided by CD Genomics allows unbiased identification of cell classes and their spatial organization in tissues, helping researchers to better understand the parameters that distinguish cells, including the relationships between cell state, function, and identity, so that cell subtypes and classes can be depicted at a higher resolution. As a result, researchers can use the technical services we provide to characterize cell identity and status in a wide range of biological and biomedical fields covering neuroscience, developmental biology, oncology, immunology, and more.
How researchers can use our services
- Characterize intercellular interactions and their effect on gene expression.
- Determine the location of a given cell in the spatial context and therefore determine the type of a cell.
- Enhance understanding of complex cellular processes in living cells as a bridge between genotype and phenotype.
- Identify adjacent ligand-receptor pairs and understand intercellular communication and signaling.
- Mapping genomic organization and nuclear structure and analyzing cell trajectories.
Why choose us
- Allows unbiased classification of cells based on gene expression patterns.
- Allows identification of new cell types and subtypes without a priori knowledge.
- Allows the study of rare cell types, cell state and subtype heterogeneity, disease-specific cell types, and intercellular interactions by ligand-receptor analysis.
- Allows discrimination of context-specific transcripts while preserving tissue and cellular structure.
- Does not require a trade-off between cell number and data quality.
Reference
- 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.
