Size no longer matters

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Science Translational Medicine  16 Nov 2016:
Vol. 8, Issue 365, pp. 365ec185
DOI: 10.1126/scitranslmed.aal0073

Recent advances in single-cell genomic profiling have transformed our ability to characterize cell types and states and also uncover salient molecular pathways and biomarkers. Yet, most single-cell transcriptomic methods only capture long poly-adenylated RNAs, such as mRNAs, and overlook small ones, such as microRNAs, whose expression can inform cellular phenotype and dysfunction.

To address this, Faridani and co-workers developed an experimental and computational method for measuring and quantifying the genome-wide expression of small RNAs in single cells. In their approach, single-cell small RNA-seq libraries were prepared by ligating adaptors to both ends of each RNA before reverse transcription and amplification. To curb unwanted ribosomal RNA and adaptor dimer contamination, the authors incorporated masking oligonucleotides and enzymatic digestion, respectively; to facilitate accurate quantification, they utilized adaptors with unique molecular identifiers. Applying their technique to single naïve and primed human embryonic stem cells, HEK cells, and glioblastoma cell lines, the authors demonstrated unbiased capture of thousands of small RNAs, including microRNAs, transfer RNAs (tRNAs), and small nucleolar RNAs (snoRNAs). Serial dilution assays showed that their method is sensitive and representative in terms of its sampling. Overall, the amassed data suggest that the abundance of single-cell small RNAs, such as microRNAs, can effectively distinguish distinct cell types and may be powerful biomarkers for basic and applied research.

Although improvements in capture efficiency and scale are needed, as is a deeper examination of the discerning power of small RNAs for detecting subtle differences between cell types and states, Faridani et al. have established a precedent. Based on the authors’ work, it is straightforward to envision workflows that couple long and short RNA profiling in single cells to help address outstanding fundamental scientific questions—for example, how cellular mRNA expression is controlled post-transcriptionally. Their method could also be used to identify biomarkers for tracking instances of cellular dysfunction like cancer, addressing outstanding clinical needs.

Omid R. Faridani et al., Single-cell sequencing of the small-RNA transcriptome. Nat. Biotechnol. 10.1038/nbt.3701 (2016). [Abstract]

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