Smart-Seq2

Smart-Seq2

Method Category: Transcriptome > RNA Low-Level Detection

Description: For Smart-Seq2, single cells are lysed in a buffer that contains free dNTPs and oligo(dT)-tailed oligonucleotides with a universal 5'-anchor sequence. RT is performed, which adds 2–5 untemplated nucleotides to the cDNA 3′ end. A template-switching oligo (TSO) is added, carrying 2 riboguanosines and a modified guanosine to produce a LNA as the last base at the 3′ end. After the first-strand reaction, the cDNA is amplified using a limited number of cycles. Next, tagmentation is used to construct sequencing libraries quickly and efficiently from the amplified cDNA.

Pros:

• As little as 50 pg of starting material can be used
• mRNA sequence does not have to be known
• Improved coverage across transcripts
• High level of mappable reads

Cons:

• Not strand-specific
• No early multiplexing¹
• Transcript length bias, with inefficient transcription of reads over 4 Kb²
• Preferential amplification of high-abundance transcripts
• Purification step may lead to loss of material
• Could be subject to strand-invasion bias³

• Smart-Seq2: Picelli S., Bjorklund A. K., Faridani O. R., Sagasser S., Winberg G., et al. (2013) Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10: 1096-1098
• Smart-Seq2: Picelli S., Faridani O. R., Björklund Å. K., Winberg G., Sagasser S., et al. (2014) Full-length RNA-Seq from single cells using Smart-seq2. Nat. Protocols 9: 171-181
• 1. Shapiro E., Biezuner T. and Linnarsson S. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat Rev Genet. 2013;14:618-630
• 2. Bhargava V., Head S. R., Ordoukhanian P., Mercola M. and Subramaniam S. Technical variations in low-input RNA-seq methodologies. Sci Rep. 2014;4:3678
• 3. Tang D. T., Plessy C., Salimullah M., et al. Suppression of artifacts and barcode bias in high-throughput transcriptome analyses utilizing template switching. Nucleic Acids Res. 2013;41:e44

Related Publications

1. Macaulay I. C., Haerty W., Kumar P., Li Y. I., Hu T. X., et al. (2015) G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat Methods 12: 519-522
2. Moignard V., Woodhouse S., Haghverdi L., Lilly A. J., Tanaka Y., et al. (2015) Decoding the regulatory network of early blood development from single-cell gene expression measurements. Nat Biotechnol 33: 269-276
3. Swiech L., Heidenreich M., Banerjee A., Habib N., Li Y., et al. (2015) In vivo interrogation of gene function in the mammalian brain using CRISPR-Cas9. Nat Biotechnol 33: 102-106
4. Deng Q., Ramskold D., Reinius B. and Sandberg R. (2014) Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 343: 193-196
5. Picelli S., Faridani O. R., Bjorklund A. K., Winberg G., Sagasser S., et al. (2014) Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 9: 171-181