Project description:Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed “single-cell combinatorial fluidic indexing” (scifi). The scifi-RNA-seq assay combines one-step combinatorial pre-indexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Pre-indexing allows us to load multiple cells per droplet and bioinformatically demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and it provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared to multi-round combinatorial indexing, scifi-RNA-seq provides an easier, faster, and more efficient workflow. In contrast to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets.
Project description:Single-cell RNA sequencing in principle offers unique opportunities to improve the efficacy of contemporary T-cell based immunotherapy against cancer. The use of high-quality single-cell data will aid our incomplete understanding of molecular programs determining the differentiation and functional heterogeneity of cytotoxic T lymphocytes (CTLs) allowing for optimal therapeutic design. So far a major obstacle to high depth single-cell analysis of CTLs is the minute amount of RNA available leading to low capturing efficacy. To overcome this we tailor a droplet-based approach for high-throughput analysis (tDrop-seq) and a plate-based method for high-performance in-depth CTL analysis (tSCRB-seq). The latter gives on average a 15-fold higher number of captured transcripts per gene compared to droplet-based technologies. The improved dynamic range of gene detection gives tSCRB-seq an edge in resolution sensitive downstream applications such as graded high confidence gene expression measurements and cluster characterization. We demonstrate the power of tSCRB-seq by revealing the subpopulation-specific expression of co-inhibitory and co-stimulatory receptor targets of key importance for immunotherapy.
Project description:We performed a high-throughput mapping of the 5’ end transcriptome of the pAA plasmid of the clinical Escherichia coli O104:H4 (E. coli O104:H4) isolate LB226692. We employed differential RNA-sequencing (dRNA-seq), a terminator exonuclease (TEX)-based RNA-seq approach allowing for the discrimination of primary and processed transcripts. This method has proven to be a powerful tool for the mapping of transcription start sites (TSS) and detection of non-coding RNAs (ncRNAs) in bacteria. We catalogued pAA-associated TSS and processing sites on a plasmid-wide scale and performed a detailed analysis of the primary transcriptome focusing on pAA virulence gene expression.
Project description:To generate a gene expression atlas of early adrenogonadal development, we performed single-cell transcriptome profiling using a high throughput droplet-based system (10X Genomics).
Project description:A bead supsension and a solution of ERCC spike-ins at a concentration of ~100,000 molecules per droplet was used in Drop-Seq, a novel technology for high-throughput single cell mRNAseq An estimated 84 beads were selected for amplification.
Project description:We performed a high-throughput droplet-based single-cell RNA sequencing experiment on a sensitive MCL cell line model (REC-1) treated with ibrutinib over time using the 10x Genomics platform. Two biological replicates were generated of an untreated control, 6 h, and 48 h ibrutinib-treated cells.
