As a scientist, you might have come across single-cell sequencing before. But what is it exactly? In this post, we provide you with a brief explanation.
Single-cell sequencing refers to the sequencing of individual cells to obtain genomic, transcriptomic, or multi-omics information at single-cell level.
The data you generate with this technology has a much higher resolution than conventional bulk sequencing methods and can reveal details that you would otherwise miss.
The smoothie analogy
A simple way to look at this is to use a smoothie as an analogy. If you take a sip from a smoothie, you’ll taste a combination of all the ingredients.
You might be able to guess that the smoothie contains oranges, apples and a bit of strawberry. But you might miss the blueberries and mango that were also used. And it gets even more difficult when you try to determine the ratio’s between the different fruits that were used for the smoothy.
You need a different, more advanced, method than just your taste to exactly determine what the ingredients of your smoothy are. When you compare this to conventional bulk RNA sequencing, the analogy is clear. With bulk RNA sequencing, you generate information on the transcriptome of thousands to millions of cells at once. This means that the expression you measure is the average of all the cells combined.
If you want to study the transcriptome at the level of single cells, you need a more advanced method. You need single-cell sequencing.
Single-cell RNA sequencing provides you with gene expression data at the level of individual, single cells. This allows you to precisely determine the different cell types and subtypes in your sample. Compared to the average gene expression profile obtained with bulk RNA sequencing, single-cell RNA sequencing gives you a high-resolution view of your sample – down to the individual cell.
