New and Improved Method for Analyzing Single-Cell Gene Expression
Scientists from the Ludwig Institute for Cancer Research and the Karolinska Institutet report the development of an improved method for analyzing the genes expressed within a single cell. They say their finding (“Smart-seq2 for sensitive full-length transcriptome profiling in single cells”), published this week in Nature Methods, will be relevant for everything from basic research to future cancer diagnostics.
“We introduce Smart-seq2 with improved reverse transcription, template switching, and preamplification to increase both yield and length of cDNA libraries generated from individual cells,” wrote the investigators in the journal article.
According to Richard Sandberg, Ph.D., senior author, there are cells in tumors and in healthy tissues that are not present in sufficient numbers to permit analysis using anything but single-cell methods.
“This method allows us to identify rare and important subpopulations of cells in all sorts of tissues. We can also use it to tease apart, more rigorously than ever before, how the expression of unique suites of genes transform cells from one state to another as, say, an embryo develops into an organism or a tumor becomes metastatic,” he said.
Traditional approaches, which depend on the collective analysis of gene expression in millions of cells at once, tend to obscure biologically significant differences in the genes expressed by specialized cells within a particular kind of tissue. Single-cell analysis of gene expression overcomes this limitation. The leading method for such analysis (Smart-seq) was developed in 2012 by Illumina, together with Dr. Sandberg’s laboratory.
To develop the new technique, named Smart-seq2, Dr. Sandberg's team conducted more than 450 experiments to improve upon their initial method. The new procedure consistently captures three to four times as many RNA molecules, which often translates into 2,000 more genes per cell than current methods allow, explained Dr. Sandberg. This, he said, will permit researchers to conduct a more granular analysis of how subtle differences between single nucleotide polymorphisms in different people contribute to differences in biology and disease.
The new method is likely to be of great value to cancer research, he continued. Identifying rare subpopulations of cells in tumors and understanding their role in the survival and progression of cancers can provide invaluable information for the development of diagnostics and targeted therapies.
A study recently published by Ludwig researchers described, for example, how certain subpopulations of cells in melanomas can be pushed into a drug-susceptible state and then destroyed by chemotherapy. More such strategies might be devised as researchers get a better handle on the cellular species found in different types of tumors, and the patterns of gene expression that define them.