MASC-seq – Massive and parallel expression profiling using microarrayed single-cell sequencing

Single-cell transcriptome analysis overcomes problems inherently associated with averaging gene expression measurements in bulk analysis. However, single-cell analysis is currently challenging in terms of cost, throughput and robustness. Here, researchers from the KTH Royal Institute of Technology present a method enabling massive microarray-based barcoding of expression patterns in single cells, termed MASC-seq. This technology enables both imaging and high-throughput single-cell analysis, characterizing thousands of single-cell transcriptomes per day at a low cost (0.13 USD/cell), which is two orders of magnitude less than commercially available systems. This novel approach provides data in a rapid and simple way. Therefore, MASC-seq has the potential to accelerate the study of subtle clonal dynamics and help provide critical insights into disease development and other biological processes.


“We found that CLL cells do not consist of a single cell type, but of a number of sub-clones that exhibit entirely different gene expression,” says Joakim Lundeberg, a professor of Gene Technology at KTH in Stockholm and director of the SciLifeLab genomics platform.

Typically, RNA sequencing will provide information about what RNA molecules are present in a biological sample, but not where or in which cells they are active.

“With this new, highly cost-effective technology, we can now get a whole new view of this complexity within the blood cancer sample. Molecular resolution of single cells is likely to become a more widely-used therapy option,” he says.

Lundeberg says the method provides analysis of all mRNA molecules in individual cells by binding a location tag to the molecules.

Individual cells are sorted on a specially-made glass surface and using analysis of RNA molecules with next-generation sequencing, one can tell which genes are active. The spatial information on the glass surface tells which cell a specific RNA molecule is to be found in.

The researchers have also developed an open, available software ( ) which combines images of individual cells with information from the sequencing, that is, which genes are expressed and at what level.

“With the new method, and the software, we can study thousands of cells in a day,” he says.

Vickovic S, Ståhl PL, Salmén F, Giatrellis S, Westholm JO, Mollbrink A, Navarro JF, Custodio J, Bienko M, Sutton LA, Rosenquist R, Frisén J, Lundeberg J. (2016) Massive and parallel expression profiling using microarrayed single-cell sequencing. Nature Comm [Epub ahead of print]. [article]

Source – KTH Royal Institute of Technology

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