Immune Cell - Methods summary

Summary

The Immune Cell section contains single cell information on genome-wide RNA expression profiles of human protein-coding genes covering various B- and T-cells, monocytes, granulocytes and dendritic cells. The transcriptomics analysis covers 18 cell types isolated with cell sorting.

Key publication

Uhlen M et al. (2019) “A genome-wide transcriptomic analysis of protein-coding genes in human blood cells” Science 366 (6472): aax9198

What can you learn from the Immune Cell section?

Learn about:

• if a gene is enriched in a particular immune cell type (specificity)
• genes with a similar expression profile across the immune cells (expression cluster)
• the catalogue of genes elevated in each of the immune cell types

How has the data been generated?

A quantitative expression analysis of 18 canonical immune cell populations has been performed from human blood separated by flow cytometric sorting. Whole blood was collected from six healthy individuals, and 18 immune cell types were separated by flow cytometric sorting, as outlined in the figure.

How has the data been analyzed?

We used flow cytometric sorting to allow whole genome transcriptome analysis of the major blood cell types from human blood (see figure). The transcriptomics data was normalized by applying two different strategies with the main objective to allow (i) within-sample comparisons and (ii) between-sample comparisons, respectively.

What is presented in the section?

The RNA expression levels were determined for all protein-coding genes (n = 20090) across the 18 immune cell populations and the results are presented on the gene summary page of the Immune Cell section as shown in the figure. The results from the similar efforts by Schmiedel et al (2018) and Monaco et al (2019) are also displayed.

How has the classification of all protein-coding genes been done?

A genome-wide classification of the protein-coding genes with regard to tissue and cell distribution as well as specificity has been performed using between-sample normalized data. The results can serve as a reference for researchers interested in spatial expression profiles of human immune cells in relation to the body-wide profiles in all major tissues and organs. The genes were classified according to specificity into (i) tissue-enriched genes with at least fourfold higher expression levels in one tissue type as compared with any other analysed tissue; (ii) group-enriched genes with enriched expression in a small number of tissues (2 to 5); and (iii) tissue-enhanced genes with only moderately elevated expression. In addition, all genes were classified according to distribution in which each gene is scored according to the presence (expression levels higher than a cut-off) in the immune cells.

The immune cell enriched and group enriched genes are displayed in the interactive plot below in which clicking on the red and orange circles results in gene lists for the correspondingl enriched and group enriched genes, respectively.

Finally, a new classification has been introduced in which genes are clustered based on similarity in expression across the immune cells. The results are presented as an interactive UMAP plot in which mouse-over displays general information for the clusters and the clicking on a cluster will display more information and plots regarding that specific cluster, as well as, a clickable list of all clusters.