Ludwig Institute for Cancer Research, Stockholm, Sweden.
Nat Methods. 2013 Nov;10(11):1096-8. doi: 10.1038/nmeth.2639. Epub 2013 Sep 22.
Single-cell gene expression analyses hold promise for characterizing cellular heterogeneity, but current methods compromise on either the coverage, the sensitivity or the throughput. Here, 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. Smart-seq2 transcriptome libraries have improved detection, coverage, bias and accuracy compared to Smart-seq libraries and are generated with off-the-shelf reagents at lower cost.
单细胞基因表达分析有望用于描述细胞异质性,但目前的方法在覆盖度、灵敏度或通量方面存在妥协。在这里,我们引入了 Smart-seq2,通过改进逆转录、模板转换和预扩增来提高从单个细胞生成的 cDNA 文库的产量和长度。与 Smart-seq 文库相比,Smart-seq2 转录组文库具有更好的检测、覆盖度、偏差和准确性,并且可以使用现成的试剂以更低的成本生成。