From the gene expression of single cells, algorithms can not only reconstruct their place of origin in the tissue, but also read functional details. This is reported by the teams around Kai Schmidt-Ott and Nikolaus Rajewsky in the specialist journal "JASN" using the example of the kidney.
In order to find out exactly what happens when in a specific cell, scientists look at its transcriptome – the entirety of all genes that are transcribed at a specific point in time and transcribed into RNA. With the help of single-cell RNA sequencing, the expression profiles of many thousands of cells can now be analyzed in parallel. But to do this, they have to be detached from the cell structure. The information about where a cell was previously located in the tissue is lost.
However, this can be reconstructed bioinformatically on the basis of gene expression. “We wanted to know whether algorithms can be used to obtain functional information from the single-cell sequencing in addition to reconstructing the spatial arrangement. For example, about the environmental conditions of kidney cells," says Dr. Christian Hinze from the Molecular and Translational Kidney Research group at the Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) and from the Charité - Universitätsmedizin Berlin. He is the lead author of the study, which has now been published in the Journal of the American Society of Nephrology (JASN).
Christian Hinze et al. (2020) Kidney Single-cell Transcriptomes Predict Spatial Corticomedullary Gene Expression and Tissue Osmolality Gradients. JASN, DOI: 10.1681/ASN.2020070930
Back to Overview