Project description:Barcode-based multiplexing methods can be used to increase throughput and reduce batch effects in large single-cell genomics studies. To evaluate methods for demultiplexing barcode-multiplexed data, we generated a dataset by labeling samples separately with barcode-tagged antibodies, mixing those samples, and progressively overloading a droplet-based scRNA-seq system.
Project description:Although classical single cell RNA analysis is a very powerful tool, it nevertheless has several drawbacks. To overcome these two disadvantages, the cell hashing technique seems interesting. In this work, we propose to test the feasibility and the reliability of the single cell hashing technique on primary AML cells. For this purpose, we compared the transcriptomic profile of AML cells analyzed by the classical single-cell RNA sequencing approach versus the cell hashing technique.
Project description:To verify the hypothesis that there are distinct subsets of cardiac fibroblasts, we performed single-cell RNA sequencing analysis of cardiac fibroblasts from pressure-overloaded ventricles.
Project description:Single cells from human colorectal cancer and normal adjacent colon of 16 patients were used for single-cell RNA-seq, TCR-seq, CITE-seq and Cell hashing. In brief, single cells were incubated for 3h with or without PMA/Ionomycin, and were treated with Cell hashing and CITE-seq antibodies to distinguish samples, stimulation/non-stimulation, and cell surface proteins. Sorted viable CD3+TCRαβ+ single cells were loaded into 10x genomics ChromiumTM controller to make nanoliter-scale droplets with uniquely barcoded 5’ gel beads called GEMs. After GEM-RT and the following some cDNA amplification steps, cDNAs derived from cellular mRNA were pooled for downstream processing and library preparation according to the manufacturer’s instructions. The 5’ transcript library was sequenced with Illumina Novaseq. The single cell TCR enriched library was sequenced with Illumina Miseq using 150 paired-end reads. HTO/ADTs from Cell hashing or CITE-seq were amplified using specific primers that append P5 and P7 sequences for illumina sequencing (Miseq or Nextseq). All fastq files were demultiplexed. Cell hashing and CITE-seq barcodes are available in attached text files. Fastq files from RNA-seq and TCR-seq can be processed through cellranger and vdjranger by 10xgenomics. The datasets include the data of independent experiments at May 29, June 16, June 23, and Aug 13, 2019. Details are available in Masuda et al., bioRxiv, 2020, The functional and phenotypic diversity of single T-cell infiltrates in human colorectal cancer as correlated with clinical outcome.
Project description:We performed single-cell RNA-seq analysis with CITE-seq and cell hashing of total viable aortic cells from Ldlr-/- mice fed a high fat diet for 13 weeks
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.