Sequencing Small-RNA transcriptome of individual cells
Omid R. Faridani1,6,*, Ilgar Abdullayev1,2,6, Michael Hagemann-Jensen1,3, John P. Schell4, Fredrik Lanner4,5 and Rickard Sandberg1,2,*
1Ludwig Institute for Cancer Research, Stockholm, Sweden; 2Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden; 3Respiratory Medicine Unit, Department of Medicine, Solna & Center for Molecular Medicine, Stockholm, Sweden; 4Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden; 5Division of Obstetrics and Gynecology, Karolinska University Hospital, Stockholm, Sweden
6These authors contributed equally
Small RNAs have been extensively studied and several small RNA classes have been identified. Current small RNA methods are limited to large number of cells. Here, we developed a novel method for sequencing small RNAs from individual cells and used it to profile naïve and primed human embryonic stem cells and cancer cells. Removing unwanted adaptor dimer ligations and blocking highly abundant rRNAs using masking oligo allowed us to reduce the input levels down to single cells and allowed us skip the common size-selection step, which makes this method automation friendly. Furthermore, by introducing a variant of unique molecular identifiers we were able to count small RNA molecules. We developed a computational pipeline to analyze data from potentially diverse classes of RNAs. As a result, the method captured mature and precursor RNAs of several classes including microRNAs, snoRNAs, tRNAs with their distinct length characteristics. In particular, single-cell micoRNA profiling stratified cell types robustly, indicating that single-cell small-RNA sequencing can be used to decode complex heterogeneous tissues. We envision that this method will open up for a wave of studies that will determine the small RNA landscape across rare cell types in vivo.
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