Single-cell and spatial omics techniques enable complex biological systems to be studied at a resolution beyond that of conventional sequencing of whole tissues or cell populations. Instead of providing an averaged result for the entire sample, they enable analysis of individual cells or nuclei, identification of differences between them, and determination of their locations and relationships within the tissue.
These methods are used in areas including developmental biology, oncology, immunology, neuroscience, plant biology, tissue regeneration research and the analysis of cellular responses to environmental factors, treatment or other experimental conditions.
10x Genomics RNA-seq
Single-cell RNA-seq, i.e. RNA sequencing of individual cells, enables gene expression to be analysed separately for each cell or nucleus. In the 10x Genomics workflow, biological material is partitioned using a microfluidic system, and RNA molecules are assigned unique barcodes that link sequencing reads to their cell of origin.
10x Genomics ATAC-seq
Single-cell ATAC-seq enables analysis of chromatin accessibility in individual nuclei. The method identifies genomic regions with open chromatin that may be involved in regulating gene activity. The 10x Genomics technology enables chromatin accessibility profiles to be analysed simultaneously in thousands of nuclei from a single sample.
Spatial Transcriptomics
Spatial transcriptomics enables gene expression analysis while preserving information about the spatial location of the measured signal within tissue. Unlike conventional RNA-seq and most single-cell RNA-seq methods, the sample is not analysed solely as a suspension of isolated cells. Gene expression results can be overlaid on a microscopic image of a tissue section, linking molecular data with tissue structure and morphology.
Analytical resolution depends on the technology used and may range from regions containing several cells to individual cells and, for selected platforms, subcellular localisation of the signal.
Which technique should you choose?
The appropriate method depends primarily on the research question:
These techniques can be used independently or integrated within a single project. Combining transcriptomic, epigenomic and spatial data enables comprehensive characterisation of cell types, their functional states, gene regulatory mechanisms and the organisation of the biological system under study.
To obtain pricing for the available services, we recommend completing the project specification form and/or reading the article on service pricing.