The transcriptome profiling of multi-cell types by the droplet based full-length single-cell transcript sequencing
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE233170 | GEO | 2024/01/01
REPOSITORIES: GEO
Similar Datasets
Project description:Smart-seq3xpress was carefully optimized and >1,000 conditions were evaluated. This data submission is organized in 15 datasets that each contain fastq files, unmapped bam files, read count tables, UMI count tables and a barcode annotation file. The barcode_annotation.txt files contain the exact factors/variables tested. Below a short description of each set of experiments: K562_lowvolume: Evaluation of scaling volumes of Smart-seq3 (indicated volume refers to total volume in PCR), whether overlay was used and if cDNA was bead-cleaned or diluted prior to tagmentation. Cell input was K562 cells. The columns \\"treatment\\", \\"volume\\" and \\"VL\\" indicate the experimental parameters. HEK_lowvolume: Evaluation of scaling volumes of Smart-seq3 (indicated volume refers to total volume in PCR), whether overlay was used and if cDNA was bead-cleaned or diluted prior to tagmentation. Cell input was HEK293FT cells. The columns \\"treatment\\", \\"volume\\" and \\"VL\\" indicate the experimental parameters. overlays: Evaluation of the effect of various overlays when generating HEK293FT libraries in 1 uL total volume. The column \\"condition\\" indicates the applied overlay. tagmentations: Evaluation of input cDNA vs Tn5 amount during tagmentation. Purified cDNA from one 384-well plate was used as input into various conditions of tagmentations. The experiments contain evaluation of cDNA amount with fixed Tn5 amount or varying Tn5 amount while keeping the default volume (2 uL) of the tagmentation reaction or scaling the reaction volume. The column \\"condition\\" contains a string indicating reaction volume, cDNA input and Tn5 ATM enzyme amount. If no volume is indicated, reaction was performed in 2 uL. HomeTn5: Evaluation of tagmentation using in-house produced Tn5 enzyme (Picelli et al., 2015) when tagmenting cDNA generated from HEK293FT cells in 1 uL total volume. The column \\"Tn5concentration\\" indicates the Tn5 reaction concentration at 2 uL reaction volume. cycles_cleanups: Optimization of Smart-seq3xpress (column \\"experiment\\" shows \\"direct_tag\\") in regards to clean-ups after cDNA synthesis (column \\"condition\\": noclean, Exo+FastAP, ExoSAP) and dilution volume (9 or 19 uL); PCR cycle numbers (column \\"pcr_input\\") and ATM Tn5 enzyme amount (column \\"ATM\\"). Cell input was HEK293FT cells. PreAmp_Polymerase: Evaluation of various PCR polymerases during initial cDNA amplification. The polymerases are indicated in column \\"polymerase\\". We also evaluated several TSO concentrations (concentration in RT is given) and fwd/rev PCR primers (concentration given in PCR reaction). Cell input was HEK293FT cells. TDE1: Large optimization of tagmentation conditions using the TDE1 Tn5 enzyme. We varied reactions by changing PCR polymerase (KAPA / SeqAmp), PCR extension time and the number of PCR cycles during cDNA amplification. During tagmentation, we varied the amount of TDE1 enzyme, the amount of DMF in the tagmentation reaction buffer and the presence of Tween-20 in the final post-tagmentation PCR. Cell input was HEK293FT cells. TSOs_RT_v1-7: Large scale evaluation of conditions relating to RT and PCR, with a focus on new template-switching oligo (TSO) designs. In total, >20,000 cells and >500 conditions are contained in these datasets. The barcode annotation file contains precise information on the reaction conditions of Lysis, RT, PCR as well as utilized TSO designs. Data was generated from HEK293FT cells and hPBMC (Lonza).
2022-05-16 | E-MTAB-11467 | biostudies-arrayexpress
Project description:<p>We developed a novel microfluidic platform to automatically barcode genomic DNA from individual cancer cells. Using this approach, we sequenced acute myeloid leukemia (AML) tumors targeting up to 62 loci relevant for the disease from thousands of cells. We predict that our platform will enable analysis of heterogeneity in AML and improve stratification and therapy selection.</p>
| phs001627 | dbGaP
Project description:Single-cell transcriptomics methods have become very popular to study the cellular composition of organs and tissues and characterize the expression profiles of the individual cells that compose them. The main critical step for single-cell transcriptomics methods is sample preparation. Several methods have been developed to preserve cells after sample dissociation to uncouple sample handling from library preparation. Yet, the suitability of these methods depends on the types of cells to be processed. In this project, we perform a systematic comparison of preservation methods for droplet-based single-cell RNA-seq (scRNA-seq) on human neural progenitor cell populations derived from induced pluripotent stem cells (iPSCs) and highlight their strengths and weaknesses. We compared the cellular composition and expression profile of single-cell suspensions from fresh NPCs with that of NPCs preserved with Dimethyl Sulfoxide (DMSO), Methanol, vivoPHIX and Acetil-methanol (ACME). Our results show that while DMSO provides the highest cell quality in terms of RNA molecules and genes detected per cell. Yet, it strongly affects the cellular composition and the expression profile of the resulting datasets. In contrast, methanol fixed samples display a cellular composition like that of fresh samples while providing a good cell quality and smaller expression biases. Taken together, our results show that methanol fixation is the method of choice for performing droplet-based single-cell transcriptomics experiments on neural cell populations.
2023-05-15 | GSE209947 | GEO
Project description:These datasets are test datasets of sample-multiplexed scRNA-seq, consisting of cDNA (transcriptome) and sample barcode read files: Three-sample multiplexing experiment (JS009) is a MULTI-seq dataset containing mesenchyme embryonic hind limb bud cells, embryonic stem (ES) cells, and NIH3T3 cells. Each cell sample was labelled with a distinct MULTI-seq barcode. The barcode sequences were, CATAGAGC, TCCTCGAA, and GTGTACCT for the limb bud mesenchyme cells, the ES cells, and the NIH3T3 cells, respectively. Two-sample multiplexing experiment (JS010) is a CellPlex detaset, containing ES cells and NIH3T3 cells. Each cell sample was labelled with the 3'CellPlex Kit (10X Genomics). NIH3T3 cells and ES cells were labelled with CMO301 and CMO302, respectively.
2024-01-09 | E-MTAB-13181 | biostudies-arrayexpress
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.
2017-05-03 | GSE89164 | GEO
Project description:Recently, RNA sequencing has achieved single cell resolution, but what is limiting is an effective way to routinely isolate and process large numbers of individual cells for in-depth sequencing, and to do so quantitatively. We have developed a droplet-microfluidic approach for parallel barcoding thousands of individual cells for subsequent RNA profiling by next-generation sequencing. This high-throughput method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. Using this technique, we analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after LIF withdrawal. The reproducibility and low noise of this high-throughput single cell data allowed us to deconstruct cell populations and infer gene expression relationships. A total of 8 single cell data sets are submitted: 3 for mouse embryonic stem (ES) cells (1 biological replicate, 2 technical replicates); 3 samples following LIF withdrawal (days 2,4, 7); one pure RNA data set (from human lymphoblast K562 cells); and one sample of single K562 cells.
2015-05-20 | E-GEOD-65525 | biostudies-arrayexpress
Project description:A widespread assumption for single-cell analyses specifies that one cell’s nucleic acids are predominantly captured by one oligonucleotide barcode. However, we show that ~13-21% of cell barcodes from the 10x Chromium scATAC-seq assay may have been derived from a droplet with more than one oligonucleotide sequence, which we call “barcode multiplets”. We demonstrate that barcode multiplets can be derived from at least two different sources. First, we confirm that approximately 4% of droplets from the 10x platform may contain multiple beads. Additionally, we find that approximately 5% of beads may contain detectable levels of multiple oligonucleotide barcodes. We show that this artifact can confound single-cell analyses, including the interpretation of clonal diversity and proliferation of intra-tumor lymphocytes. Overall, our work provides a conceptual and computational framework to identify and assess the impacts of barcode multiplets in single-cell data.
2020-01-07 | GSE143197 | GEO
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.
2024-04-14 | GSE215901 | GEO
Project description:Analysis of histone modifications at single-cell resolution can provide insights into the cellular heterogeneity in activity states of regulatory elements. However, current methods are hindered by lengthy procedures and insufficient sensitivity. Here we present Droplet Paired-Tag, a microfluidic cell barcoding-based method for fast and robust joint analysis of histone modifications and gene expression from single cells. We applied Droplet Paired-Tag to mouse brain and demonstrated its utility in accurately identifying active or repressive regulatory elements, and resolving the dynamic interactions between candidate regulatory elements and putative target genes.
2023-06-29 | GSE224560 | GEO