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Single-cell RNA-seq IDs Dozens of Mammalian Brain Cell Subtypes

NEW YORK (GenomeWeb) – In a study published online today in Science, Swedish researchers demonstrated the level of cell type resolution they could achieve using single-cell RNA sequencing on samples from two mouse brain regions.

"If you compare the brain to a fruit salad, you could say that previous methods were like running the fruit through a blender and seeing what color juice you got from different parts of the brain," co-senior author Sten Linnarsson, a molecular neurobiology researcher at the Karolinska Institute, said in a statement.

In contrast, he said, the current single-cell approach amounts to "taking pieces of the fruit salad, examining them one by one and then sorting them into piles to see how many different kinds of fruit it contains, what they're made up of and how they interrelate."

By sequencing more than 3,000 cells from somatosensory cortex and hippocampus sites in the brain, Linnarsson and his colleagues identified nearly four dozen different cell sub-classes, spanning all of the main cell types described in the regions previously, as well as new, more refined cell sub-types.

"[W]e have created a much more detailed map of the cells of the brain that describes each cell type in detail and shows which genes are active in it," Karolinska Institute researcher Jens Hjerling-Leffler, the study's other corresponding author, said in a statement. "This gives science a new tool for studying these cell types in disease models and helps us to understand better how brain cells respond to disease and injury."

In the past, researchers explained, cell features such as their location, appearance, electrochemical characteristics, physiological properties, and interactions have served as the basis for much of the cell type classification done in the brain and other parts of the nervous system.

But the team reasoned that it might learn more about cell types in the mammalian nervous system, through single-cell sequencing — an approach that's been used by other groups to assess cells from the lung, spleen, and embryonic brain.

Using a quantitative single-cell RNA-sequencing approach that Linnarsson and colleagues outlined in Nature Methods last year, the researchers sequenced transcriptomes from 3,005 individual cells from the mouse primary somatosensory cortex or hippocampal CA1 brain region.

After looking at the nature and quantity of the RNA transcripts present in the cells, the investigators used their computational clustering approach to group similar cells together, identifying nine main cell types.

A more detailed analysis of the cells revealed 47 sub-classes within each cell class, ranging from distinct neuron sub-types to new and known subsets of blood vessels, immune-related glial cells, and supportive cells known as oligodendrocytes.

Some cell type sub-classes appear to be specific to particular layers of the brain, researchers reported, while others were peppered throughout one or both of the brain regions.

Along with the transcriptional hints about the biology of each cell type, the sequence data also helped uncover molecular markers to distinguish between the varied brain cells. In the so-called S1 pyramidal neurons, for example, the team uncovered a characteristic long non-coding RNA called Gm11549. Other cell types consistently expressed particular transcription factors or protein-coding transcripts.

Together, the study's authors concluded, such findings "showcase the power of explorative single-cell RNA-seq, and point the way toward future whole-brain and even whole-organisms cell type discovery and characterization."