New Technique for Cheaper, More Efficient Single Cell Sequencing

Single-cell sequencing has shown a lot of promise in identifying genetic differences between cells in a given tissue sample. It is particularly useful for understanding heterogeneity and evolution in resected tumors, and is increasingly used for improving precision medicine approaches. Unfortunately, conventional methods are cost-prohibitive, thus they restrict the cell numbers that can be assessed and are therefore not widely used. A new technique, dubbed SCI-seq (single-cell combinatorial indexed sequencing), developed at the Oregon Health & Science University (OHSU) was used to generate libraries for samples much larger than possible with previous technologies (by about two orders of magnitude), and at a fraction of the price.

Each point in this illustration is a single cell genome sequenced from a pancreatic tumor. The four different colors represent non-cancer cells (green) and three different genetically distinct cancer cell types present within the same tumor. (OHSU)

One application of single-cell sequencing is for the detection of copy-number variations (CNVs), the number of times a given gene segment is repeated in a cell. CNV plays a role in generating diversity in a species, but is also observed within adjacent tissues and many CNVs are associated with cancers. SCI-seq allows for efficient detection of CNVs by combining two methods of barcoding a cell before sequencing. The nuclei of cells from a given sample are isolated and targeted with transposases (enzymes to insert DNA) for the addition of the first barcode. This is followed by a second step that uses PCR to add a second barcode, optimizing the number of nuclei to reduce uncertainty and duplications in barcoded identities.

By using this two-tier strategy, the research team was able to precisely interrogate CNVs from large samples, applying this technique to the analysis of cultured cells and primate brain tissue samples. They went on to demonstrate its use for analyzing the heterogeneity of a human pancreatic tumor sample, observing populations delineating healthy tissues and three distinct tumor clusters. Single-cell interrogations of tumor heterogeneity of this type reveal key mutations shared across the tumor, as well as the prevalence of other druggable targets, uncovering potential drug combinations that offer the best chances at complete elimination. The authors of this study have expressed an interest in collaborating with colleagues at OHSU to bring this technique to the clinic and impact patients’ lives.

Article from Nature Methods: Sequencing thousands of single-cell genomes with combinatorial indexing…

Via OHSU: New genome-mapping technique opens new avenues for precision medicine…