Single-cell and Spatial Transcriptomics: All the cool kids are doing it

They're freaking cool!

The transcriptome is the study of all of the ribonucleic acid (RNA) produced within a cell.

It differs from the genome in a couple of important ways:

1) The transcriptome is made up of RNA messages, and the genome is made up of DNA

2) RNA is the template for making proteins, the genome is the template for making RNA

3) Each cell has the same genome but a different transcriptome

4) Each tissue (many cells working together) has a variety of transcriptomes that enable a function ie organ tissue

But for a very long time, our evaluation of transcriptomes were limited to surveying large populations of cells from ground up tissues or looking at whole blood.

We even have two consortiums dedicated to better understanding transcriptomes. One is the ENCODE Project or the ENCyclopedia Of Dna Elements and the other is the Genotype-Tissue Expression (GTEx) Project. Both projects have generated datasets that try to figure out how a single genome ends up creating the cellular diversity we see in all of our tissues by looking at regulatory elements in the DNA, protein associations with chromatin, epigenetic signatures, expression levels of RNA, and quantifying protein levels.

But, the initial datasets for ENCODE were based on sequencing homogenized tissues. This is a bit like trying to hang a picture with a sledgehammer when you don't have a tack hammer handy.

Thankfully, we can do more refined analyses now using single cell and spatial transcriptomics!

Single cell: This method was popularized academically as Drop-seq. It uses bead linked oil emulsions to capture transcripts from single cells for sequencing. Basically, a bead (or in the case of 10x Genomics' version, a hydrogel) covered in polyT capture sequences is combined in an oil droplet with a single cell. The oil droplet contains reagents that break open the cell and the polyT sequence hybridizes with the polyA sequence on the RNA transcripts. These sequences can be linked back to their original cells and grouped together because the capture sequence includes a cell barcode and a unique molecular identifier (UMI) sequence.

Spatial: The newest kid on the block which uses tissue samples as the input but instead of homogenizing these into single cells, they're treated more like a pathology slide. There are a couple of approaches here with companies using capture array technology, in-situ sequencing, multiplex FISH, or UV microdissection of selected regions of a tissue slide for capture and/or sequencing. They have the added benefit of being able to spatially profile protein locations using fluorescent antibodies; so not only can you use these systems to visualize where the RNAs are expressed in tissues but also the degree to which they create proteins. Which is super cool but also ends up producing some really beautiful images!