InquiryOrgan systems are composed of different cellular subpopulations whose spatial location in a given tissue is closely related to their function. Understanding the biological functions, networks, and interactions of the different cell types that regulate organ and disease development requires cellular information and spatial context. Traditional RNA sequencing experiments provide quantitative information at the expression level, but spatial information is lost. In contrast, spatial transcriptomics (ST) technologies enable the precise localization of gene expression events to specific locations in biological tissues.
We offer a gene expression solution with a spatial-omics context
The integration of spatial and temporal information with single-cell gene expression data is critical for identifying key differences between cell types and for detailed analysis of developing tissues. CD Genomics selectively combines the power of different technologies (ST, scRNA-seq, ISS, smFISH) to reveal the integrated transcriptional landscape of a sample's cell type and maps cell type-specific gene expression to specific anatomical structural domains to comprehensively characterize spatio-temporal differences in gene expression during specific physiological and pathogenic processes with single-cell resolution.
Compared to conventional transcriptome analysis results using bulk sequencing or scRNA-seq, CD Genomics can now capture high-resolution spatial heterogeneity and retain rich spatial information about unbiased gene expression in cells and tissues in ST results. This allows our customers to explore global spatial transcriptional patterns in tissues and selectively target key genes with spatially heterogeneous expression patterns that lead to cell-type differences.
General processes
By placing tissue sections on slides containing oligonucleotide arrays containing positional barcodes, CD Genomics can generate high-quality cDNA libraries containing precise positional information for RNA sequencing. By capturing RNA at its natural tissue location and barcoding it, our customers can visualize and quantify gene expression in situ.
Figure 1. A molecular approach to analyze spatial cardiac gene expression patterns and cellular heterogeneity. (Asp M., et al., 2019)
We do it better
- Identify unique gene expression profiles corresponding to different tissue sections.
- Elucidate the spatial distribution of different cell types in tissue samples and the heterogeneity of their spatial domains.
- Explore the developmental processes of other organisms for which little information is available.
- Retain rich spatial information about cellular and tissue unbiased gene expression.
- Perform spatio-temporal analysis of gene expression at single-cell resolution.
- Analyze gene expression patterns and cellular heterogeneity.
Practical applications
Figure 2. Adding spatial information to transcriptomes: integration of single-cell and spatial transcriptomics data. (Longo S. K., et al., 2021)
CD Genomics' integration of scRNA-seq and spatial transcriptomics data increases our clients' understanding of the role of specific cell subpopulations and their interactions in development, homeostasis, and disease, and the heterogeneity of gene expression and spatial organization in the tissue samples obtained helps our clients identify potential pathogenesis of the disease.
References
- Asp M., et al., (2019). "A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart." Cell, 179(9): 1647-1660.e19.
- Longo S. K., et al., (2021). "Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics." Nature Reviews Genetics, 22: 627-644.
