Project description:High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in several of the reaction steps of Quartz-Seq2 allow us to effectively convert initial reads to UMI counts (at a rate of 30%–50%). To demonstrate the power of Quartz-Seq2, we analyzed transcriptomes from a cell population of in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of sequence reads. Preprint: http://www.biorxiv.org/content/early/2017/07/21/159384
Project description:We report novel single-cell RNA-Seq, called Quartz-Seq. Quartz-Seq was simplified method compared with previous methods based on poly-A tailing reaction. RNA-seq by illumina TruSeq, KAPA library preparation kit, single-cell Quartz-Seq and single-cell Smart-Seq by illumina HiSeq 2000/1000
Project description:We developed SCAN-seq2, a high-throughput and highly sensitive single-cell RNA sequencing method based on the TGS platform. Our study demonstrated that SCAN-seq2 improves upon the previous method, SCAN-seq, in terms of sensitivity and throughput. By using reference-guided assembly of single-cell data, we were able to identify thousands of novel full-length RNA isoforms, including cell type-specific expression patterns of pseudogenes. We also accurately determined V(D)J rearrangement events in T and B cells. Lastly, we found that treatment of HepG2 and Hela cells with the spliceosome inhibitor Isoginkgetin (IGG) resulted in a subpopulation of cells with distinct apoptosis features. Our study provides a promising new tool for single-cell transcriptome research. The source code for SCAN-seq2 data analysis pipelines is available at https://github.com/liuzhenyu-yyy/SCAN-seq2 .
Project description:We report novel single-cell RNA-Seq, called Quartz-Seq. Quartz-Seq was simplified method compared with previous methods based on poly-A tailing reaction.
Project description:Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artificial reads, enhanced throughput, and increased library complexity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large scale single-cell epigenomic studies.
Project description:Chromatin profiling in single cells has been extremely challenging and almost exclusively limited to histone proteins. In cases where single cell methods have shown promise, many require highly specialized equipment or cell type specific protocols and are relatively low throughput. Here, we combine the advantages of tagmentation, linear amplification and combinatorial indexing to produce a high throughput single cell DNA binding site mapping method that is simple, inexpensive and capable of multiplexing several independent samples per experiment. Targeted Insertion of Promoters (TIP-seq) uses Tn5 fused to protein A to insert a T7 RNA polymerase promoter adjacent to a chromatin protein of interest. Linear amplification of flanking DNA with T7 polymerase prior to sequencing library preparation provides ~10-fold higher unique reads per single cell compared to other methods. We apply TIP-seq to map histone modifications, RNA Polymerase II (RNAPII) and transcription factor CTCF binding sites in single human and mouse cells.
