Smart-seq2 single-cell RNA-Seq modified method v1
Authors: J. Trombetta John , Gennert David , Lu Diana , Satija Rahul , K. Shalek Alex , Regev Aviv 
Published: June 2018

For the past several decades, due to technical limitations, the field of transcriptomics has focused on population‐level measurements that can mask significant differences between individual cells. With the advent of single‐cell RNA‐Seq, it is now possible to profile the responses of individual cells at unprecedented depth and thereby uncover, transcriptome‐wide, the heterogeneity that exists within these populations. This unit describes a method that merges several important technologies to produce, in high‐throughput, single‐cell RNA‐Seq libraries. Complementary DNA (cDNA) is made from full‐length mRNA transcripts using a reverse transcriptase that has terminal transferase activity. This, when combined with a second “template‐switch” primer, allows for cDNAs to be constructed that have two universal priming sequences. Following preamplification from these common sequences, Nextera XT is used to prepare a pool of 96 uniquely indexed samples ready for Illumina sequencing.Curr. Protoc. Mol. Biol. 107:4.22.1‐4.22.17. © 2014 by John Wiley & Sons, Inc. In single-cell RNA-Seq, small amounts of sample loss during a number of steps can lead to significant decreases in transcript detection sensitivity. A decrease in assay sensitivity results in data that is only accurate and reproducible for highly expressed genes, limiting the scope and confidence of gene expression analyses. Further complications in assay sensitivity arise from an uneven distribution of sequencing reads along a transcript; usually, in SMARTer, there is a bias towards more reads at the 3′ end of the transcript. Even coverage along a transcript improves the accuracy of analytical tools used to quantify gene expression and transcript isoform abundance. A method published by Picelli et al (Nature Methods, 2013) modified the traditional SMARTer protocol to address this by improving transcript detection, coverage, accuracy, yield, and cost. Following the same strategy as SMARTer library construction, Smart-seq2 uses several alternative reagents to generate whole-transcriptome full-length cDNA libraries. Avoiding small-volume, bead-based SPRI cleanups of each sample is an effective way of reducing loss and increasing assay sensitivity. Lysing single cells in a guanidine thiocyanate buffer necessitates SPRI cleanup due to the protein denaturing effects of the compound, which will affect downstream reactions, like reverse transcription. Multiple alternative lysis buffers exist that address this. The Ambion Single Cell Lysis buffer (Lifetechnologies, #4458235), often used for single-cell RT-PCR, only requires the addition of a stop solution to inactivate its lytic activity before subsequent reactions. A hypotonic lysis buffer with small amounts of RNase-inhibitor and surfactant, as described in Smart-seq2, is the preferred buffer due to the lack of a need for a post-lysis cleanup or the addition of a stop solution prior to reverse transcription. However, the optimal lysis strategy will depend on the experimental system being analyzed. Smart-seq2 takes additional steps to minimize sample loss during library construction. The reverse transcription is improved by the addition of betaine and additional magnesium chloride to the reaction mix and by the use of a template-switch oligonucleotide with one locked nucleic acid (LNA)riboguanosinebase. These improvements assist in the hybridization between the template-switch oligonucleotide and the cDNA product, thereby increasing the probability of successfully introducing a second PCR adapter onto the cDNA product (see Figure 1). A second key improvement was made in the preamplification PCR step, which can be heavily biased against either long transcripts or those containing regions with high G/C content. Picelli et al found that the preamplification PCR is improved by using the KAPA HiFi HotStart ReadyMix, which dramatically improved coverage and sensitivity, particularly for GC-rich transcripts.