Single-cell transcriptomics approaches allow the analysis of gene expression heterogeneity in individual cells to study cell fate determination mechanisms. Dissociating tissues into individual cells allows for high-throughput genomic measurements, but spatial information about cells is often lost, and spatial histology technologies are advancing the study of tissue and cellular communication at an unprecedented scale.
How we provide cell-to-cell communication analysis services
CD Genomics leverages computational tools to obtain spatial information at the cell cluster level through data preparation, communication network construction, and result validation, combined with scRNA-seq data to identify spatial domains with coherent gene expression in spatial imaging (e.g., in situ hybridization). This allows intercellular communication quantification by inferring intercellular communication from scRNA-seq data, allowing researchers to better infer communication between cells located at different locations in intact tissues.
General process
Figure 1. General procedures of cell-cell communication studies using scRNA-seq techniques. (Shao X., et al., 2020)
- Perform pre-processing such as dissection of samples (human, mouse).
- The prepared samples are subjected to scRNA-seq analysis to obtain single-cell transcriptome data in preparation for the construction of intercellular communication networks.
- In combination with statistical analysis, cell-gene matrices generated by the scRNA-seq protocol and cell-cell linkage matrices generated from cell-cell communication networks were integrated to study cell-cell communication at single-cell resolution.
- Validation is performed for inferred cell-cell communication.
We do better
- Mapping between scRNA-seq data and spatial data
- Infer spatial distances between individual cells
- Quantitatively compare spatial gene expression patterns
- Reconstruct spatial cell-cell communication
- Estimate the spatial extent of specific types of intercellular signaling
- Identify gene pairs that may regulate each other between cells
Practical applications
With CD Genomics' scRNA-seq data-based cell-cell communication analysis services, researchers can elucidate physiological processes such as embryogenesis, homeostasis, and organogenesis, understand the pathogenesis and progression of diseases such as cancer, liver disease, and inflammation, or study the underlying mechanisms of pharmacology and drug resistance, which may provide insights into new therapeutic strategies and targets.
Reference
- Shao X., et al., (2020). "New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data." Protein & Cell, 11: 866-880.