The transcriptome profiling of multi-cell types by the droplet based full-length single-cell transcript sequencing
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ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE233170 | GEO | 2024/01/01
REPOSITORIES: GEO
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Project description:To establish an ultra-high-throughput single cell chromatin accessibility profiling method that is cost-effective and widely accessible, we built on sci-ATAC-seq (Cusanovich, D. A. et al. Science. 2015; Amini, S. et al. Nature Genetics. 2014) and SPLIT-seq (Rosenberg, A. B. et al. Science. 2018) to design SPATAC-seq, which in situ label chromatin fragment in the same single cell through combinatorial barcoding. Briefly, in SPATAC-seq, (1) fixed nuclei are transposed in 48 different wells by 48 unique Tn5 transposase, which containing barcoded adaptors and 5'-phosphorylation; (2) the nuclei from all wells are collected and redistributed into second and third 48-well plate in turn, where the next two rounds of indexing are achieved through into either end of the custom transposome, which result in the generation of more than 110,000 (48^3) unique barcode combinations. (3) the nuclei are pooled, split into sublibraries and lysed, and the DNA was amplified by polymerase chain reaction (PCR), which introduce illumina sequencing barcodes and complete libraries construction. (4) After sequencing, fastq files were demultiplexed according to the same four-barcode combinations. For profiling more cells in one sublibrary, we can increase the number of barcode combinations by increase the number of indexing of each round to 96, which can produce about 1 million combinations. To assess the fidelity of SPATAC-seq, we performed a species-mixing experiment with cultured human (K562) and mouse (Hepa) cells. Here, we tagged mixed permeabilized nuclei with only 8 barcoded transposome. In round 4, we generated eight sublibraries with different cell-recovery targets, which can be used to evaluating the stability of this method and the correlation between real doublet rates and theoretical value.
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Project description:Background: Recent developments in droplet-based microfluidics allow the transcriptional profiling of thousands of individual cells, in a quantitative, highly parallel and cost-effective way. A critical, often limiting step is the preparation of cells in an unperturbed state, not compromised by stress or ageing. Another challenge are rare cells that need to be collected over several days, or samples prepared at different times or locations. Results: Here, we used chemical fixation to overcome these problems. Methanol fixation allowed us to stabilize and preserve dissociated cells for weeks. By using mixtures of fixed human and mouse cells, we showed that individual transcriptomes could be confidently assigned to one of the two species. Single-cell gene expression from live and fixed samples correlated well with bulk mRNA-seq data. We then applied methanol fixation to transcriptionally profile primary single cells from dissociated complex tissues. Low RNA content cells from Drosophila embryos, as well as mouse hindbrain and cerebellum cells sorted by FACS, were successfully analysed after fixation, storage and single-cell droplet RNA-seq. We were able to identify diverse cell populations, including neuronal subtypes. As an additional resource, we provide 'dropbead', an R package for exploratory data analysis, visualization and filtering of Drop-seq data. Conclusions: We expect that the availability of a simple cell fixation method will open up many new opportunities in diverse biological contexts to analyse transcriptional dynamics at single cell resolution.
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