It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. The VU team developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. Dr Linas Mažutis and his colleagues analysed mouseembryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed the researchers to deconstruct cell populations and infer gene expression relationships.
Dr Linas Mažutis admitted in his comment to the publishers, – "The result of our long lasting efforts is an excellent example of a teamwork and our reported technology has already been taken over for further development and application by several research groups. I assume we would not achieve such results if working separately. We are pleased indeed that this technology has already been recognized in the level of a single-cell transcriptomics and genomics."
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